Jun 19 2025
How To Use Paid Search & Social Ads For Promoting Events via @sejournal, @LisaRocksSEM

Paid media offers one of the fastest ways to promote a business event and get the right people to take action.

Event campaigns are not just regular ads with a date added. They need a dedicated strategy, setup, budget, and audience targeting to succeed.

From webinars and product launches to open houses and local promotions, you’ll get better results by treating your event like a stand-alone campaign.

Here’s how to approach it with paid search and social ads that drive participation.

What Types Of Events Can Be Promoted?

Here are common examples of business events that can benefit from paid ad promotion:

  • Conferences (virtual or in-person).
  • Webinars.
  • Product launches.
  • Open houses.
  • Grand openings.
  • Sales or seasonal promotions.
  • Trade show participation or speaking engagements.
  • Local festivals or community events.
  • Pet adoption events.
  • Sports or sponsorship tie-ins.
  • Class registrations or training signups.

For an “event,” we generally look for a special, notable activity outside of normal business, with a limited time for engagement.

Considerations Before Campaign Setup

Use A Stand-Alone Campaign

Each event should have its own dedicated campaign. This gives you more control over:

  • Budget.
  • Targeting.
  • Messaging.
  • Conversion tracking.

Don’t try to squeeze event ads into your evergreen campaigns. Keep it separate so you can measure impact clearly.

Budget Separately

A separate budget prevents your main campaigns from losing momentum. Even a small spend focused on urgency and high-intent audiences can produce a strong ROI.

Incorporate Into Your Ad Copy

Add event details directly into your ad copy, such as headlines or descriptions in responsive search ads (RSAs), and use the pinning feature to lock critical details into place.

For higher control, create an entirely new custom ad built specifically around the event message.

Use promotion assets in Google Ads for sales-driven events that include a discount or monetary offer.

Double-check each platform’s documentation to confirm which features are available and how they are currently labeled.

screenshot of promotion extension in google adsScreenshot by author, June 2025

4 Tips To Design High-Performing Event Campaigns

After creating a new campaign for your event and allocating its budget, there are several other factors to consider when promoting events.

Tip 1: Get Straight To The Point

Event ads need clear details upfront:

  • Event name.
  • Date and time.
  • Location (or virtual link).
  • A CTA like “Register”, “Sign Up”, or “Save Your Seat.”

Use direct headlines and don’t leave room for interpretation. Test countdown timers (Google) in your ad copy to build urgency.

Check out Microsoft Ads, which has a great explanation on how the countdown feature works.

  • Example: “Only 3 Days Left to Register for the Free AI Workshop”

If you’re offering discounts or early-bird pricing, clearly state it in both the headline and description.

Below is the Google Ads example of setting this up in a headline and steps to implement.

screenshot of countdown timer steps in google adsScreenshot by author, May 2025

Tip 2: Be Strategic About Timing

The timeline for event promotion is mission-critical. Some events only require a few days of promotion, while others may need weeks or months of preparation.

Plan around three phases:

  • Pre-event hype: Build interest and drive signups.
  • During the event: Push for last-minute attendance or livestream engagement.
  • Post-event: Retarget attendees for future events or promote replays.

Also, confirm your ad platform’s scheduling limits. Google ends ads at 11:59 p.m. of the advertiser’s time zone. Some let you choose a specific time (in 24-hour format).

Tip 3: Location Targeting

The location targeting will be largely determined by the event’s real, physical location, but there are a few things to consider.

Depending on the density of the customer base, location targeting will vary for each advertiser. Match the event’s scale to your location settings:

For example:

  • Local: Use radius or city-level targeting around the physical location.
  • Regional: Layer metro areas or ZIP codes with high interest.
  • National or online: Prioritize geos with the highest engagement or ROI historically.

With national targeting, you may want to prioritize budget allocation to major metro areas. Another approach is to review your customer purchase data for trends in revenue or return on investment (ROI) by location.

Tip 4. Use Targeting Unique To The Event

Your existing keyword list or audience segments may not apply to an event. Build targeting around:

  • Specific event names or branded keywords, such as “Tech Expo 2025.”
  • Related topics or products featured at the event, such as boat models for the boat show.
  • Competitor brands or category searches.
  • Audience interests like “small business tools” or “data analytics training.”
  • Use customer lists on your preferred platform to reach similar audiences.

Bonus Tip: How To Leverage Events (Local Or Otherwise) Even If You Are Not Participating In Them

You don’t need to be directly involved in the event to benefit from event-driven ad traffic. You can also capitalize on events related to your business to gain extra exposure.

For example, if a local wedding expo is happening in your area, a florist or event planner can run campaigns targeting attendees who are searching for event services during the show.

This strategy works for:

  • Industry conferences.
  • Seasonal community events.
  • Awareness days or promotional months.

Set up a parallel campaign with relevant offers or content that aligns with the audience’s mindset during the event.

Final Thoughts

Event campaigns deserve more than a last-minute or a generic ad slot.

With a strategic approach, they can build brand awareness, generate leads, and leave a lasting impression.

By setting up a dedicated campaign, writing clear and timely messaging, and using specific targeting, you’re setting the stage for better results.

Even if you’re not hosting the event, there are still ways to show up and be seen.

Put your event in the spotlight. When you run it like a pro with paid media, the results speak for themselves.

More resources: 

Featured Image: PeopleImages.com – Yuri A/Shutterstock

Ecommerce MGMT 0 Comments
Jun 11 2025
Paid Media Reporting For Ecommerce: Navigating Attribution Across Paid

Global advertising expenditure has surpassed the $1 trillion mark for the first time.

Digital advertising continues to dominate this growth, with digital channels encompassing search and social media forecast to account for 72.9% of total ad revenue by the end of the year.

From a platform perspective, Google, Meta, Amazon, and Alibaba are expected to capture more than half of global ad revenues this year.

In-house and agency-side paid media teams are working harder than ever to grow ecommerce businesses efficiently, and the amount of data being used day-to-day (even hour-to-hour) is enormous.

With this growth and investment, something is clearly working, and given that brands can map new/returning audiences to their advertising funnel and serve ads across billions of auctions, it’s a lever that millions of businesses pull.

However, with budgets being split across channels (search, social, out-of-home, etc) and brands using CRM data, analytics platforms, third-party attribution tools, and more to define their “source of truth,” fragmentation begins to appear with reporting. Only 32% of executives feel they fully capitalize on their performance marketing data for this reason.

With data being spread across several sources, ad platforms having different attribution models, and the C-suite likely asking, “Which source of truth is correct?”, reporting paid media performance for ecommerce isn’t the most straightforward task.

This post digs into key performance indicators, platform attribution & modeling, business goals, and how to bring it all together for a holistic view of your advertising efficacy.

Key Performance Indicators (KPIs)

To begin navigating paid media reporting, it starts with the KPIs that each account optimizes towards and how this feeds into channel performance.

Each of these has purpose, benefits, limitations, and practical use cases that should be viewed through a lens of attribution unique to each platform.

Short-Term Performance

Return On Ad Spend (ROAS)

  • Definition: revenue/cost.

This metric measures the revenue generated for every dollar spent on advertising.

If your total ad cost was $1,000 and you drove $18,500 revenue, your ROAS would be 18.5.

  • Benefits: Direct measure of advertising efficiency and helps provide a snapshot of campaign profitability.
  • Limitations: Does not account for customer acquisition costs (CACs), margin, LTV, returns, shipping, etc.

Cost Per Acquisition (CPA)

  • Definition: cost/sales or leads.

This metric shows the average cost to generate a sale (or lead, depending on the goal, e.g., an ecommerce brand could be measuring using CPA to sign up new customers for an event).

For example, if your total ad cost was $5,000 and you drove 180 sales, your CPA would be $ 27.77.

  • Benefits: Easy to monitor over time and helps assess efficiency.
  • Limitations: Neglects revenue, customer acquisition cost, margin, LTV, etc., and treats all sales equally regardless of value.

Cost Of Sale (CoS)

  • Definition: total ad spend/revenue.

This metric measures what % of revenue is spent on advertising.

Say a brand spends $20,000 on Meta Ads and generates £100,000 in revenue, their resulting CoS would be 20%.

  • Benefits: Useful for margin-sensitive businesses and marketplaces where prices and/or Average Order Value (AOV) are volatile.
  • Limitations: Can mask unprofitable sales (in some scenarios) if margin, returns, shipping, etc., are not considered.

Mid-Term Efficiency

Customer Acquisition Cost (CAC)

  • Definition: total marketing costs spent on acquiring new customers/total number of new customers.
  • Detailed definition: total marketing costs spent on acquiring new customers + wages + software costs + agency/consultancy fees + overheads/total number of new customers.

This metric may reflect either marketing costs associated with driving new customer acquisition or a holistic view of all costs associated with acquiring new customers.

Let’s say a business has a CAC of $175 and an AOV of $58, they will need each new customer to repeat purchase ~3x to make acquisition profitable.

  • Benefits: Holistic view of acquisition cost, ideal for longer-term profitability analysis for paid media investment.
  • Limitations: Not always the most suitable for channel-specific reporting (think account structuring, audiences, etc.), and can be a lagging metric as it doesn’t reflect short-term changes in performance like ROAS or CPA would.

Marketing Efficiency Ratio (MER)

  • Definition: Sometimes referred to as blended ROAS, MER is calculated by dividing total revenue/total ad spend across all channels.

This metric shows how efficiently your total ad spend is converting into revenue, regardless of the channel.

Where MER is especially useful is when brands are active on multiple ad networks, all of which contribute in some way to the final sale, and where siloed platform attribution is inconsistent.

  • Benefits: Captures topline performance from a transactional perspective and simplifies multi-channel reporting.
  • Limitations: Neglects exactly where the sales and revenue came from and obscures channel efficiency, especially important for search, social, etc.

Long-Term Strategic

Customer Lifetime Value (CLV Or CLTV)

  • Definition: This metric estimates the total net revenue a customer brings over their relationship with a brand.

Used alongside CAC, this metric is essential for understanding the true value of both acquisition and retention, which is important for almost all ecommerce models, and especially important for brands looking to capitalize on repeat purchases and subscription-based models.

  • Benefits: Builds a foundation for tying performance marketing to long-term outcomes while helping give room to CAC targets across valuable customer segments.
  • Limitations: Takes a fair amount of work to get set up and maintain, in addition to requiring a clean cohort and repeat purchase data. Additionally, when brands introduce new products/services, it can be hard to forecast accurate CLV numbers, and it will take time.

So, which one should you be reporting on for your ecommerce brand?

Speaking from experience, there isn’t a right or wrong answer, nor is there a blueprint for which KPIs you should be reporting on.

Having a multifaceted approach will enable more informed decision making, combining short-, medium-, and long-term KPIs to form a holistic model for measuring performance that feeds into your reports.

However, even after choosing your KPIs, different attribution models across advertising platforms add another layer of complexity, as does the ever-evolving customer journey involving multiple touchpoints across devices, channels, etc.

The Ad Platforms

Each ad platform handles attribution and tracking differently.

Take Google Ads, for example, the default model is Data-Driven Attribution (DDA), and when using the Google Ads pixel, only paid channels receive credit.

Then, with a GA4 integration to Google Ads, both paid and organic are eligible to receive credit for sales.

Click-through windows, value, count, etc, can all be customised to provide a view of performance that feeds into your Google Ads campaigns.

Using the Google Ads pixel, say a user clicks a shopping ad, then a search ad, and then returns via organic to make the purchase, 40% of the credit could go to shopping, and 60% to the search ad.

With the GA4 integrated conversion, shopping could receive 30%, search 40%, and organic visit 30%, resulting in 70% of the value being attributed back to the campaigns in-platform.

Now, comparing this to Meta Ads, which uses a seven-day click and one-day view attribution window by default, when a user converts within this time frame, 100% of the credit will be attributed to Meta.

This is why the narrative for conversion tracking on Meta is one of overrepresentation, with brands seeing inflated revenue numbers vs. other channels, even more so with loose audience targeting, where campaign types such as ASC can serve assets to audiences who have already interacted with your brand.

Then, when you dig into third-party analytics, the comparisons between Google Ads, Meta Ads, Pinterest Ads, etc., are almost the complete opposite.

So, what should this data be used for, and how does it factor into the bigger picture?

In-platform metrics are best viewed as directional.

They help optimize within the walls of that specific platform to identify high-performing audiences, auctions, creatives, and placements, but they rarely reflect the true incremental value of paid media to your business.

The data in Google, Meta, Pinterest, etc. is a platform-specific lens on performance, and the goal shouldn’t be to pick one or ignore these metrics.

It should be to interpret these for what they are and how they play into the overarching strategy.

The Bigger Picture

KPIs such as ROAS and CPA offer immediate insights but provide a fragmented view of paid media performance.

To gain a comprehensive understanding, brands must combine medium- to long-term KPIs with broader modeling and tests that account for the multifaceted nature of performance marketing, while considering how complex customer journeys are in this day and age.

Marketing Mix Modeling (MMM)

Introduced in the 1950s, MMM is a statistical analysis that evaluates the effectiveness of marketing channels over time.

By analyzing historical data, MMM helps advertisers understand how different marketing activities contribute to sales and can guide budget allocation.

A 2024 Nielsen study found that 30% of global marketers cite MMM as their preferred method of measuring holistic ROI.

The very short version of how to get started with MMM includes:

  1. Collecting aggregated data (roughly speaking, at least two years of weekly data across all channels, mapped out with every possible variable (e.g., pricing, promotions, weather, social trends, etc.)
  2. Defining the dependent variable, which for ecommerce will be sales or revenue.
  3. Run regression modeling to isolate the contribution of each variable to sales (adjusting for overlaps, lags, etc.)
  4. Analyze, optimize, and report on the coefficients to understand the relative impact and ROI of your paid media activity as whole.

Unlike platform attribution, this doesn’t rely on user-level tracking, which is especially useful with privacy restrictions now and in the future.

From a tactical standpoint, your chosen KPIs will still lead campaign optimizations for your day-to-day management, but at a macro level, MMM will determine where to invest your budget and why.

Incrementality Testing

Instead of relying on attribution models, this uses controlled experiments to isolate the impact of your paid media campaigns on actual business outcomes.

This kind of testing aims to answer the question, “Would these sales have happened without the paid media investment?”.

This involves:

  1. Defining an objective or independent variable (e.g., sales, revenue, etc.)
  2. Creating test and control groups. This could be by audience or geography – one will be exposed to the campaigns and the other will not.
  3. Run the experiment while keeping all conditions equal across both groups.
  4. Compare the outcomes, analyze performance, and calculate the impact.

This isn’t one that’s run every week, but from a strategic point of view, these tests help to validate the actual performance of paid media and direct where and what spend should be allocated across ad platforms.

Operational Factors

These are equally as important (if not more) for ecommerce reporting and absolutely need to be considered when setting KPIs and beginning to think about modeling, testing, etc.

  • Product margin.
  • AOV variability.
  • Shipping costs.
  • Returns rates.
  • Repeat rates.
  • Discounting and promotions.
  • Cancelled and/or failed payments.
  • Stock availability.
  • Attribute availability (e.g., size, color, model).
  • Pixels and tracking.

Without considering these factors, brands will use inaccurate data from the get-go.

Think about the impact of buy now, pay later. Providers such as Klarna or Clearpay can lead to higher return rates, as bundle buying and impulsive purchases become more accessible.

Without considering operational factors, using this example and a basic in-platform ROAS, brands would be optimizing toward incorrect checkout data with higher AOV’s and no consideration of returns, restocking, etc.

Ultimately, building a true picture of paid media performance means stepping beyond the platform KPIs and metrics to consider all factors involved and how best to model the data to uncover not just “what” is happening, but “why” it is and how this impacts the wider business.

Bringing It All Together

No single tool or model tells the full story.

You’ll need to compare platform data, internal analytics, and external modeling to build a more reliable view of performance.

The first step is getting watertight KPIs nailed down that consider every possible operational factor so you know the platforms are being fed the correct data, and if you need to modify these based on platform nuances due to differing attribution models, do it.

Once these are nailed down, find a model that you trust and that will show you the holistic impact of your paid media spend on overall business performance.

You could explore the use of third-party attribution tools that aim to blend data together, but even with these, you’ll still require clear and accurate KPIs and reliable tracking.

Then, when it comes to the visual side of reporting, the world is your oyster.

Looker Studio, Tableau, and Datorama are among the long list of well-known platforms, and with most brands using three to four business intelligence tools and 67% of analysts relying on multiple dashboards, don’t stress if you can’t get everything under one lens.

When all of this is executed and made into a priority over the short-term ebbs and flows of paid media performance, this is the point where connecting media spend to profit begins.

More Resources:

Featured Image: Surasak_Ch/Shutterstock

Ecommerce MGMT 0 Comments
May 8 2025
Ultimate PPC Campaign Optimization: 6 New Ways To Easily Run Dozens Of PPC Campaigns For Different Sectors via @sejournal, @CallRail

Tip #1. Boost Relevance: Use Industry-Specific Conversion Signals To Customize Google Ads Messaging

Increasing clicks is as easy as increasing how relevant your ads are to your potential customers.

Sounds easy, but when you’re managing different brands, many industries, or multiple brick-and-mortar locations, it can quickly become difficult to understand exactly what each individual person needs.

What’s New That You Should Change & Try

Google Ads Responsive Search Ads and Assets (Structured Snippets) now allow faster VOC-driven testing.

Voice-of-customer (VOC) insights from tools like CallRail reveal what customers actually say before converting.

Now, you can use this real language to supercharge your ad messaging.

Is This Change Worth It?

Yes.

When you align your ad messaging with what your customers actually say, you boost ad relevance, increase clickthrough rates, and lower your cost per lead by matching real search intent.

You’ll see:

  • Higher relevance: This is crucial in paid advertising is critical because it directly impacts three major outcomes: cost, performance, and customer experience.
  • Lower Costs: Ad platforms like Google Ads reward high relevance with better quality scores, which can lower your cost per click (CPC) and help you win better ad placements without paying a premium.
  • Higher Engagement: When your ads match exactly what users are searching for or thinking about, you naturally boost clickthrough rates (CTR) because the ad feels more useful and timely.
  • Better Conversion Rates: Relevant ads lead to more qualified traffic, meaning users are more likely to take action once they land on your site, whether that’s calling, booking, or buying.
  • Improved Brand Trust: Ads that clearly resonate with real customer language and needs feel authentic, which strengthens brand credibility over time.

Which Industries Benefit Most From This PPC Engagement Boosting Technique?

  • Legal Services: Top keywords we’ve identified for you are [free consult] & [local attorney]
  • Home Services: [emergency repair] & [same-day service] are great seed keywords for this industry.
  • Medical/Dental: [accepts insurance] & [licensed doctor] are good starting points for PPC keyword lists.

Your industry not listed? See other industry insights here.

How did we discover those seed keywords?

By analyzing customer responses, transcripts, and chats for true language keywords that your customers are likely typing into search or ChatGPT.

How To Find Your Best PPC Conversion Signals

Effort Manual Method CallRail
Time Required High Low
Accuracy Depends on human analysis Automated and precise
Insights Available CTRs, keyword performance CTRs, keyword-level call tracking, automated trends
Effort Intensive Minimal

Manual Method For Finding PPC Conversion Signals

  • Analyze Campaign Data: Manually review metrics like click-through rates (CTR), conversion rates, and cost per conversion to evaluate performance.
  • Identify High-Performing Keywords: Manually analyze calls to find and optimize keywords driving the best results while excluding irrelevant terms.
  • Track User Behavior: Use tools like Google Analytics to observe user actions, such as pages visited or time on site, before converting.
  • Tie Conversions to Campaign Factors: Manually connect conversion data to specific ads, keywords, or timeframes for insights.
  • Challenges: Time-intensive, prone to human error, and limited in precision without advanced tools.

CallRail Method for Finding PPC Conversion Signals

  • Call Tracking: Easily and quickly track inbound calls back to specific ads, campaigns, or keywords to identify high-performing strategies.
  • Keyword-Level Attribution: Automatically pinpoint which keywords drive calls or form submissions without manual effort.
  • Automated Insights: Leverage AI-generated call transcripts, summaries, and data to detect patterns, trends, and high-performing campaigns effortlessly.
  • Integrations: Connect with platforms like Google Ads or HubSpot to centralize and streamline conversion tracking.
  • Key Benefits: Saves time, eliminates guesswork, provides precise and actionable insights to optimize PPC campaigns effectively.

The Manual Way:

  1. Spend hours manually analyzing call transcripts for high-intent phrases.
  2. Create tightly themed ad groups based on these phrases.
  3. Constantly refine keyword match types to match real search behavior (favor phrase match for accuracy).
  4. Use dynamic keyword insertion carefully to keep VOC language in ads.

Easy Way With CallRail: 

  1. Use CallRail’s free trial to extract VOC insights.
  2. Insert VOC themes into responsive search ad headlines and structured snippets.

Tip #2. Save Time: Automate Campaign Creation With Pre-Built Google Ads Templates & CRM Signals

Launching campaigns faster without sacrificing quality can transform how efficiently your agency operates.

Is This Change Worth It?

Absolutely.

When you automate campaign creation, your team gets more time back to focus on strategy instead of setup.

It means:

  • Faster launches.
  • Fewer errors.
  • Campaigns that are tailored more precisely to your clients’ real needs.

What’s New That You Should Change & Try

Google Ads Customer Match and Microsoft Ads Customer Match now enable direct CRM syncing to personalize campaigns automatically.

You can dynamically create or adjust campaigns based on real customer behavior without manual uploads.

Why Do This

Automating your campaign setup drastically reduces your manual workload, speeds up your time-to-market, and helps your team personalize campaigns at scale across locations or services.

Which Industries Benefit Most From This Time-Saving PPC Technique?

  • Franchise & Multi-Location Retail
  • Home Services (HVAC, plumbing, roofing)
  • B2B SaaS with structured sales pipelines

How To Set Up Automated PPC Campaign Launching

The Manual Way:

  1. Build templated campaign structures with core keywords, ads, and extensions.
  2. Pre-create negative keyword lists to prevent budget waste.
  3. Use shared audiences and budgets across locations.

Easy Way With CallRail:

  1. Connect CallRail and your CRM to automatically trigger ad group or campaign launches.

Tip #3. Maximize ROI: Make Budget Optimization Dynamic With Real-Time Call Quality Feedback

Prioritizing ad spend on only the highest quality leads gives you better results without raising your budget.

Is This Change Worth It?

Definitely.

Budget optimization with real-time PPC feedback ensures that you’re spending on what actually drives value: qualified leads.

It’s one of the fastest ways to improve ROI and prove your worth to your clients.

What’s New That You Should Change & Try

Google Ads Offline Conversion Imports and Enhanced Conversions for Leads now allow you to sync call quality and CRM outcomes directly into Google Ads bidding models.

Why Do This

Prioritizing your budget based on high-quality leads maximizes your ROI, eliminates wasted ad spend, and delivers more valuable outcomes for your business or agency.

Which Industries Benefit Most From This Budget Optimization Technique

  • Healthcare & Dental Clinics
  • Legal & Financial Services
  • Auto Services

How To Optimize Your Budget Based On Real-Time Call Quality

Manual Way:

  • Score calls manually within your CRM for quality.
  • Adjust campaign-level bid adjustments or device-level bidding based on quality trends.
  • Create automated rules to pause poor-performing keywords or boost strong ones.

Easy Way With CallRail:

  1. Use call scoring to automatically sync quality signals.
  2. Set Google Ads offline conversion imports to trigger budget shifts based on call outcomes.

Tip #4: Boost Engagement: Use Enhanced Click-to-Call Campaigns With Visual SERP Signals

Visual and call-first strategies make it easier for customers to connect and convert faster.

Is This Change Worth It?

Yes, especially if your audience is mobile-first.

Adding call-focused enhancements and visuals doesn’t just boost engagement—it shortens the path between search and conversion, making it easier for ready-to-buy users to reach you.

What’s New That You Should Change & Try

Google Ads Call Ads, Image Extensions, and Microsoft Ads Multimedia Ads now create visually compelling, mobile-first experiences optimized for immediate customer action.

Why Do This

Upgrading your ads with richer visuals and call-driven formats helps you drive higher engagement on mobile, improve click-to-call rates, and accelerate customer connections.

Which Industries Benefit Most From This Engagement-Boosting Technique

  • Restaurants & Local Retail
  • Urgent Services (locksmiths, HVAC repair)
  • Senior Services (assisted living, home care)

How To Enhance Your Click-to-Call Campaigns

Manual Way:

  • Add call extensions and image extensions to mobile ads.
  • Schedule call ads during business hours only.
  • Use structured snippets highlighting key services.

Easy Way With CallRail:

  1. Integrate CallRail click-to-call tracking.
  2. Analyze peak call times and optimize ad schedules accordingly.

Tip #5: Smarter Targeting: Layer First-Party Lead Journey Data Into Performance Max Campaigns

Bringing offline lead intelligence into your campaigns boosts targeting precision and conversion rates.

Is This Change Worth It?

Absolutely.

Using your first-party data to influence Performance Max campaigns gives you more control, better targeting, and higher returns, especially in a world where third-party cookies are disappearing.

What’s New That You Should Change & Try

Google Ads Performance Max campaigns now support Customer Value Mode (2024 smart bidding innovation) to better optimize for high-value leads.

Why Do This

Feeding your first-party lead journey data into campaigns improves your targeting precision, nurtures your prospects at the right moment, and increases your conversion rates while lowering acquisition costs.

Which Industries Benefit Most From This Smart Targeting Strategy

  • Real Estate
  • Home Improvement & Contractors
  • Higher Education & Vocational Schools

How To Layer Lead Journey Data Into Your Performance Max Campaigns

Manual Way:

  1. Export CRM lead journey stages manually.
  2. Create custom audience segments inside Google Ads.
  3. Build distinct asset groups based on customer intent (“researching,” “ready to buy”).

Easy Way With CallRail:

  1. Use CallRail to sync call outcomes and CRM data into Google Ads.
  2. Automate audience signal feeding to Performance Max.

Tip #6: Lower CPCs: Run Campaigns By Location With Local Keyword + Phone Call Clustering

Geo-targeted strategies help you win more conversions while keeping your ad costs low.

Is This Change Worth It?

Definitely.

Location-based clustering lets you dominate profitable micro-markets without blowing your budget. It’s one of the smartest ways to lower CPCs and outmaneuver bigger competitors.

What’s New That You Should Change & Try

Google Ads Location Extensions, Dynamic Location Insertion, and Microsoft Ads Location Extensions now provide better local customization tools, enhanced by AI call tracking.

Why Do This

Using hyperlocal targeting based on real-world call and keyword data helps you increase your relevance, lower your CPCs, and dramatically improve your local conversion rates.

Which Industries Benefit Most From This Geo-Targeting Upgrade

  • Multi-Location Healthcare
  • Legal Services in competitive markets
  • Home Services (regional licensing differences)

How To Run Localized Campaigns With Call Clustering

Manual Way:

  1. Segment geo-targeted campaigns by ZIP code.
  2. Analyze location performance reports weekly.
  3. Use ad customizers to insert city/region names dynamically into ad copy.

Easy Way With CallRail:

  1. Leverage CallRail’s AI keyword clustering to identify top-performing regions.
  2. Automatically adjust geographic targeting based on call conversion trends.

Scale Smart, Not Wide

Scaling PPC for your SMB clients across different sectors is no longer about throwing more campaigns against the wall and hoping something sticks. It’s about smarter personalization, automation, and quality-driven optimizations.

Tangible PPC elements like keywords, ad groups, budget rules, and conversion actions remain critical to long-term success, especially when fueled by clean first-party data.

By implementing even 1–2 of these new methods per client vertical, you can reduce your manual work, improve your lead quality, and drive better outcomes for your agency and your clients.

Ready to future-proof your PPC strategy?

Start with data. Start with automation. And start by refining the tangible parts of your campaigns to dominate every sector you serve.

Ecommerce MGMT 0 Comments
Apr 16 2025
How AI Is Changing The Way We Measure Success In Digital Advertising via @sejournal, @LisaRocksSEM

Success in PPC has historically been measured using performance indicators like click-through rates (CTR), cost per acquisition (CPA), and return on ad spend (ROAS).

However, with the rise of AI, new technologies are having an impact on how we approach and measure performance and success, causing a major change in customer behavior.

From Click-Based Metrics To Predictive Performance Modeling

PPC has relied heavily on click-based metrics, it’s even in the name “pay-per-click.” This has always provided immediate but narrow insights.

AI changes this by integrating predictive performance modeling: Machine learning algorithms analyze historical data to predict which campaigns will drive conversions.

Predictive modeling in AI-powered marketing is revolutionizing how advertisers allocate their precious resources by identifying high-converting audience segments before campaigns even launch.

Instead of reacting to past performance, AI-driven predictive analytics helps businesses forecast:

  • Future customer behaviors based on past interactions.
  • The likelihood of conversion for different audience segments.
  • The optimal bid adjustments for different times of day or geographies.

This allows a more in-depth and detailed budget allocation and performance optimizations beyond simple impressions or clicks.

Quality Score 2.0 – AI-Driven Relevance Metrics

Google’s long-standing Quality Score is based on expected CTR, ad relevance, and landing page experience.

With the current tech advancements, it no longer provides a complete picture of user intent or engagement. AI provides a more advanced approach that some in the industry refer to as “Quality Score 2.0.”

AI-powered relevance metrics now analyze:

  • Deeper contextual signals beyond keywords, including sentiment analysis and user intent.
  • Engagement and behavior patterns to determine the likelihood of conversions.
  • Automated creative testing and adaptive learning to refine ad messaging in real-time.

Google’s AI-driven Performance Max campaigns now use advanced machine learning techniques to optimize ad relevance, suggesting that the traditional Quality Score may soon be obsolete.

Automated Bidding & AI-Driven KPIs

Automated “smart” bidding has changed the way advertisers manage campaign performance.

Manual bid strategies have always required constant monitoring, now AI dynamically adjusts bids based on real-time data signals such as:

  • User device, location, and browsing behavior.
  • Time-of-day performance variations.
  • Probability of conversion based on previous engagement.

Automated bidding strategies like Maximize Conversion Value and Target ROAS are outperforming manual CPC approaches, increasing account efficiencies.

AI-driven key performance indicators (KPIs) are helping advertisers shift to goal-based strategies tied directly to revenue.

Campaigns hitting the revenue goals can be easily scaled, which is a big step in maximizing PPC investments.

The Rise Of New AI-Generated PPC Metrics

Beyond improving existing measurement models, AI is introducing entirely new ways to assess digital ad performance.

These AI-driven PPC metrics offer more holistic insights into customer engagement and lifetime value.

AI Attribution Modeling

Attribution has always been a challenge in PPC.

Traditional models like last-click and linear attribution often miss the full picture by giving all the credit to a single touchpoint, making it hard to understand how different interactions actually contribute to conversions.

AI-powered attribution models solve this by using machine learning to distribute credit across multiple interactions, including clicks, video views, offline actions, and cross-device conversions.

This approach captures the complete customer journey rather than just focusing on the last click interaction.

AI attribution models typically include:

  • Data-Driven Attribution: Measures the true impact of each interaction, whether it’s a click, view, or engagement.
  • Dynamic Adaptation: Continuously adjusts as new data comes in to keep the model accurate and up-to-date.
  • Cross-Channel Integration: Combines online and offline data to reduce gaps and blind spots in tracking.

AI Attribution Modeling is a measurement tool and provides a comprehensive view of how interactions contribute to long-term value.

It is also a strategic approach that connects both Engagement Value Score (EVS) and Customer Lifetime Value (CLV).

EVS measures the depth and quality of interactions rather than just clicks, while CLV focuses on the long-term worth of a customer.

By combining AI attribution with EVS and CLV, marketers gain a deeper understanding of the customer journey and can optimize campaigns for both meaningful engagement and sustainable growth rather than just short-term conversions.

Let’s dive into these two more specific metrics.

Engagement Value Score (EVS)

A growing alternative to CTR, the EVS measures how meaningful an interaction is rather than just if a click occurred.

Unlike CTR, which assumes all clicks are valuable, EVS pinpoints users who genuinely engage with your content.

To measure EVS, combine different engagement signals into one score. Start with your key engagement actions, like:

  • Time Spent on Site: How long users stay on your pages.
  • Multi-Touch Interactions: Video views, chatbot conversations, or content consumption.
  • Behavioral Indicators of Intent: Scroll depth or repeat visits.

After assigning points to each action, create a custom metric in Google Analytics 4 that calculates the total EVS score from these individual actions and integrates into the Google Ads account.

Implementation Steps:

  1. Create Events: Set up custom engagement events with conditions that match high EVS behaviors.
  2. Mark as Key Events: After creating these custom events, mark them as ket events in GA4.
  3. Import to Google Ads: Once the custom conversion is set up in GA4, import it into Google Ads.
  4. Align Bidding Strategies: Use automated bidding strategies that optimize for conversions rather than just clicks.

By using this EVS methodology, Google Ads can optimize campaigns not just for clicks, but for meaningful interactions that drive high value.

Customer Lifetime Value (CLV)

Rather than optimizing for one-time conversions, Customer Lifetime Value (CLV) focuses on the long-term value of a customer.

AI-driven CLV measurement looks beyond quick wins and digs into the total worth of a customer over their entire relationship with your brand.

It’s similar to using EVS in that is focuses on meaningful interactions rather than quick clicks.

To measure CLV accurately, AI models analyze key data points like:

  • Past Purchase Behavior: Predicts future spend based on historical transactions.
  • Churn Risk and Retention Probability: Identifies how likely a customer is to leave or stay.
  • Cross-Channel Interactions: Tracks engagement across social media, email, and customer support.

Just like EVS, CLV requires combining multiple signals into one clear metric. After gathering these data points, create a custom metric in GA4 that calculates the total CLV from individual interactions.

Implementation Steps:

  1. Create Events: Set up custom engagement events for key behaviors (like repeat purchases or social interactions).
  2. Mark as Key Events: Once created, mark these events as key events in GA4.
  3. Import to Google Ads: Bring the custom conversion data into Google Ads to guide bidding strategies.
  4. Optimize with AI: Use automated bidding and predictive analytics to prioritize high-CLV customers.

AI-powered CLV analysis is gaining traction as businesses move toward sustainable, long-term growth strategies rather than chasing short-term conversions.

Take a scientific deep dive into this topic, including risk-adjusted CLV, here.

Challenges And Considerations

While AI-driven measurement is transforming PPC advertising, it is not without its challenges. Decision-makers need to consider the following:

Data Privacy & Compliance

AI’s ability to collect and analyze large amounts of user data raises concerns about privacy and compliance.

General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) are data privacy laws that regulate how businesses collect, store, and use personal information from consumers.

With these regulations, advertisers must balance data-driven insights with ethical and legal responsibilities. AI-powered models should prioritize anonymized data and ensure transparency in data usage.

AI Accuracy

Machine learning models rely on historical data, which can sometimes lead to inaccuracies.

If an AI model is trained on outdated or incomplete data, it can result in poor decision-making. Human oversight is needed to reduce these risks.

Algorithmic Bias

AI models can sometimes reflect biases present in the data they are trained on.

If left unchecked, this can lead to skewed campaign recommendations that favor certain demographics over others. Businesses must check that AI tools are built with fairness and inclusivity in mind.

Interpreting AI-Generated Insights

AI provides highly complex data outputs, which can be difficult for marketing teams to interpret.

Businesses should invest in AI literacy training for decision-makers and teams to ensure that insights are actionable and interpreted correctly.

Key Takeaways

AI is fundamentally changing how we measure success in PPC and digital advertising.

From predictive performance modeling to AI-driven attribution, CLV, and EVS, these advanced metrics are helping marketers move beyond basic clicks and short-term conversions.

Instead, they focus on deeper insights that drive sustainable growth and long-term value.

However, leveraging AI responsibly requires navigating challenges like data privacy, accuracy, algorithmic bias, and the complexity of interpreting insights.

Marketers must prioritize transparency, fairness, and continuous learning to make the most of these powerful tools.

The future of digital advertising lies in bringing together data insights and thoughtful strategy and sustaining that success over time.

More Resources:

Featured Image: metamorworks/Shutterstock

Ecommerce MGMT 0 Comments
Apr 9 2025
Ecommerce PPC Challenges & Strategies For Second-Hand Retailers

The second-hand ecommerce sector is significant.

The market for global resale apparel alone reached $227 billion in 2024 and is projected to hit $367 billion by 2029.

This once traditional way of shopping in thrift stores and auction houses has changed drastically. U.S. online resale is expected to nearly double by 2029, reaching $40 billion.

What’s referred to as the “second-hand economy” represents a shift in how people shop, their adaptability to economic changes, and a way of acting on growing sustainability concerns by buying pre-loved items.

As this market expands at pace, brands are ramping up their investment in paid search, with major players like eBay spending over $150 million per year on Google Ads alone.

With this growth in PPC spending, brands are looking to scale and scale fast.

However, running PPC for second-hand or resale ecommerce is a very different ballgame from a traditional ecommerce model, where brands are either manufacturing the items they sell or reselling new items.

In this post, I’ve shared five ecommerce PPC strategies for second-hand retailers that will help find success.

Before we jump into them, let’s dig into a few key challenges that are unique to managing paid search in this market.

Key Challenges Unique To PPC For Second-Hand Retailers

Inventory Turnover And One-Of-A-Kind Products

The flow of products will vary by retailer.

Take eBay, for example. It likely has hundreds (even thousands) of certain items, but for smaller retailers or specialised brands (such as antique or vintage resellers), it is most likely dealing with one-of-a-kind products.

In this scenario, once a product is gone, it’s gone.

Bidding algorithms get little time to learn which products convert the best, as many items may only be in the feed briefly, whereas others may remain in the product feed for a long time and be deprioritized by newer items.

Frequent Product Updates & Data Quality

For some second-hand retailers, inventory can change daily (or hourly) as new products are acquired and are listed on the site to sell through as soon as possible.

This movement, whether fast or slow, impacts both PPC campaigns that use product feeds (such as Google Shopping or Performance Max) as new data is fed into the campaigns on a frequent basis.

It can also impact search campaigns as products move in and out of stock.

Let’s say a brand has a search campaign bidding on keywords themed around “second-hand Herman Miller chairs.” It sells through 80% of the stock and is waiting for new SKUs to be added.

The efficiency of the campaign will decline, and spend could be wasted. This isn’t just for second-hand retailers; it also applies to all PPC ecommerce strategies.

In addition, data quality has to be bulletproof to ensure that products are entered into the most relevant auctions and searchers are provided with the best possible data prior to clicking through.

For example, say one product is uploaded with the title: Nike – Air Force 1 ’07 – White – Size 10. And another: Carhartt Hoodie.

In this scenario, retailers will be forever going back and forth across various teams to fix data issues with the feed (something I’ve seen firsthand).

Then, throw in brands such as Depop and Vinted, which have user-generated listings, and the task of creating a refined, rich data feed becomes even more complex.

Dynamic Budget Allocation

With an ever-changing flow of products and search queries, accurately forecasting and allocating budgets can be a difficult task.

A category may perform great one month, where SKUs that are in high demand are in stock, then drop off the following month as the conversion rate declines due to a less desirable product selection.

Dynamic budget allocation is essential, as there are so many moving parts.

Advertisers must monitor stock levels across many touchpoints (e.g., brand, category, material) and trends in search queries, and undertake systematic performance reviews to feed into how much budget to cut out for PPC and where to allocate this.

Complex Measurement And Reporting

With SKUs coming and going, traditional product reporting is limited.

Advertisers can’t rely on item-level metrics alone, as many items have zero sales (or a single sale) before being removed from the feed and out of product/listing groups.

This essentially takes away the traditional strategy of catering to your “best sellers” first – a strategy that relies on accrued product-level data to feed into various characteristics set by advertisers (e.g., X number of sales over X days at a ROAS of X = best seller).

Second-hand retailers must aggregate their product data to uncover trends in brands, styles, materials, product types, and more.

This comes with a level of expertise in creating these reports and the time to maintain, update, and actually use them to inform the PPC strategy.

So, How Can Second-Hand Retailers Succeed In Paid Search Given The Limitations?

Despite these challenges, second-hand retailers can thrive with PPC.

Here are five strategies that are tried and tested and will lay the groundwork for creating a second-hand PPC powerhouse.

1. Optimize And Enrich Your Shopping Feed

Product feeds are the heart of PPC for ecommerce.

Campaign types that use product listings, such as Google Shopping and Performance Max, allow advertisers to get their products in front of searchers prior to clicking through.

Google search for the query Screenshot from search for [second hand supreme jackets], Google, March 2025

As with a couple of points raised so far, this isn’t a strategy exclusive to second-hand retailers, but the importance of making sure data is rich and processes are in place is critical with many different SKUs flowing in and out of the inventory.

So that you can sleep at night knowing you’re matching the most relevant queries and ensure you have the best possible data in your feed, I’d recommend this approach:

  • The Basics: Create a structure and put a process in place that accounts for every stakeholder who will be involved in feeding data at any point. If you want to ensure you spot any anomalies immediately (definitely recommended), you could use a third-party tool, export your feed to a sheet, and build a script to check that all SKUs follow the same pattern.
  • The Next Step: Custom labels, keyword research, supplemental feeds, and more. This could be:
    • Adding detailed information on the condition of an item in the description, with a summary in the title (e.g., new with tags, used once, X number of owners, etc.).
    • Qualifying that the items are not brand new. This will help with both entering into ad auctions for pre-loved/second-hand queries. It will also help qualify traffic as your listing will clearly show up front that it is not new.
    • Categorizing groupings such as era, designer, or material for antique and vintage stores. This is useful for structuring both the feed and the way campaigns are grouped in the ad platform.

2. Think Categories (Or Bespoke Groupings), Not Individual Product Sales

Ecommerce PPC strategies are often built on best-selling product data.

This segment naturally demands the highest budget allocation as conversion rate, return on ad spend (ROAS), etc., is often the highest.

However, many second-hand retailers may only ever have one (or a handful) of every item, which almost breaks apart the traditional approach of managing paid search for ecommerce.

All is not lost, though. Brands can find success by segmenting (and reporting) by category and using this to steer budgeting, forecasting, day-to-day optimisation, and more.

Aggregating this data helps to:

  • Uncover meaningful trends to both share with the wider business and feed into bidding algorithms.
  • Set the foundations for adapting to change. For example, say a luxury handbag reseller receives a high intake of products from a new brand/designer. A category-level split will help facilitate driving visibility for these items through PPC, whereas if a “best-seller” structure were used, it would not contain the new items and wouldn’t prioritize them.
  • Assist with flexing media budgets, as depending on size, some retailers may be dealing with hundreds of thousands of items and being able to pull back and scale spend on what works is crucial.

3. Don’t Be Afraid To Broaden Your Reach, With Care

I have seen many brands in this space doubling down on Search and Shopping, with strict query funneling to only serve ads for queries that contain “second-hand”/”pre-loved”/”used.”

This is logical and may work well. However, for this theoretical example where we don’t have data, this strategy neglects multiple audiences who are not only in the market for the items, but may convert higher for the short term and help drive up Customer Lifetime Value (CLV) in the long run.

This strategy makes the assumption that if the query has been pre-qualified (second-hand/pre-loved/used, etc.), the audience searching will be the most profitable, which, in my experience, is not always the case.

Take a second-hand camera retailer, for example. If it only bids on pre-qualified queries such as “used Canon cameras” or “second-hand point-and-shoot cameras,” it would miss all users who are looking for the brands they sell, general camera queries, longer-tail searches, and more.

This is where campaign types such as Performance Max and especially Dynamic Search Ads (DSA) are certainly worth testing to expand your reach and serve ads for intent-driven searches across a wide range of audiences.

4. Align PPC Efforts With Inventory And Operations

This isn’t exclusive to second-hand retailers, but it is especially important.

Cross-team collaboration is a must when products are flowing in and out of stock, and retailers have an ever-changing number of products on site.

Data should flow both ways:

PPC → Wider Team (Merchandising, Buying, Operations, etc.)

  • Which categories/brands/designers have indexed up or down vs. average over a certain time period?
  • Are there any new queries that can help with product acquisition?
  • How has category X trended over time since stock volume increased considerably?

Wider Team → PPC

  • We’ve got X units of brand A and more to come over the next three months. How do we prioritize this?
  • The stock of category X has begun drying up. There’s not much on the market, so a restock is unlikely soon.
  • Returns for brand X are 50% above average. How much are we spending on these items each month?

Creating a virtuous cycle will only improve PPC performance and build relationships.

Finding the best way to pull this data may take time, as teams will need to share various datasets (stock reports, CRM, order books, etc.) to then feed into a centralized report, but the payoff is definitely worth it.

5. Think Outside Of The PPC Box

In the world of second-hand retail, the importance of PPC teams having a clear understanding of profitability outside of account-level KPIs such as ROAS or cost per acquisition (CPA) is crucial.

Unlike a traditional ecommerce model where brands manufacture the products themselves, the second-hand market, whatever the product may be, will likely make less margin comparatively due to lower prices, costs of acquiring the product, operational expenses, etc.

Here are a few metrics I would highly recommend keeping close to when making strategic PPC decisions:

  • Return Rate: The average return rate for ecommerce was 16.9% in 2024, with products that require specific fits (clothing, shoes, etc.) rising as high as 30%, and even further during peak. With margin front of mind, weaving these rates into PPC budgeting, forecasting, and setting KPI is essential.
  • New Customer Acquisition Cost (nCAC): This measures the average expense incurred to acquire a new customer and is calculated by total new customer marketing expenses/number of new customers acquired. While it may not be the primary goal, nor are all accounts built to accommodate clear, new, and returning budget splits, this is a metric that must be observed in line with CLV, ROAS, etc.
  • Customer Lifetime Value (CLV): PPC teams operating within this business model have to look past the first sale. CLV helps quantify the long-term value of a customer, which unlocks more informed decisions for budgeting, forecasting, and optimization, especially when acquiring new customers.

In second-hand retail, where margins are tighter, understanding the full customer journey and setting KPIs using a clear view of profitability will empower PPC teams to make smarter, more commercially aligned decisions.

Summary: A Different Approach, A World Of Potential

With changing inventory and tighter margins, advertisers need to adopt a different approach to PPC.

Whether a billion-dollar resale store with self-serving listings or a small clothing store, the same principles apply. As with most things PPC, it all comes back to having clear, accurate data.

Advertisers have a wealth of tactics to consider, from ensuring the feed is the best it can be to setting targets using bespoke groupings that change over time.

One-size-fits-all approaches may bring short-term stability, but for long-term growth and scalability, the teams that think and adapt quickly will lead the pack.

More Resources:

Featured Image: Wayhome Studio/Shutterstock

      Ecommerce MGMT 0 Comments
      Mar 24 2025
      Ad Platforms: Should You Or Shouldn’t You Take Their Recommendations? via @sejournal, @jonkagan

      Recently, I did the math, and realized I’ve been in the biddable media business (search, social, programmatic, etc.) for over 20 years now.

      (Shoutout to Didit.com for taking a chance on a Hofstra University senior with no experience and giving me a paid internship.)

      In those 20 years, I have looked back at all of the changes within the industry, including but not limited to:

      • Being able to advertise on Meta.
      • Yahoo used to be the biggest search engine.
      • I spent ad dollars directly on AOL and AskJeeves.com (RIP Jeeves).
      • We didn’t call display ads “Programmatic.” It was just “banner ads.”
      • Google Analytics/GA4 was previously known as Urchin (Fun fact: UTM stands for Urchin Tracking Module). Before that, we used Omniture (now Adobe) as the analytics “North Star.”

      But, what really has changed in my mind is how we view support and insights from the platforms.

      Google and Yahoo had true human support, and we took their recommendations as gospel.

      There were few to no automated recommendations telling us to spend more, and when the platform reps made a suggestion, it was taken as a degree of good faith.

      Before I go off on a rant, I should provide a disclaimer that I have numerous friends at all the major platforms in the U.S.

      I’ve applied for jobs at all of them and have also been offered jobs from some of them. So, this article is not directed at a particular person or platform but the industry, in general, from the vendor side.

      Backstory

      While I can’t pinpoint a precise date, I’d say around 2012 is when we really saw consistent evidence of shifts in platforms moving from “We want what is best for you and your ads” to “We have recommendations to move your business forward if you can just spend more, or adopt these things that will cause you to spend more.”

      I was with a large holding company agency, running a bit of pharma and a lot of financial services advertising with a small team.

      In my not-so-humble and completely biased perspective, we had one of the best search marketing teams around. We knew the industry standard and best practices, and we knew what would help or hurt the business – and so did our reps at “big search and big social.”

      Suddenly, their recommendations were not best practices and would clearly drive higher spend and lower efficiency.

      Even more noticeably, when something went awry, the reps we turned to to help troubleshoot would say something to us that gave me a cold chill down my spine: “You’ll need to file a support ticket for that. These are now handled by a different department.”

      This was the beginning of us really having to scrutinize what was recommended to us.

      Human Vs. Machine

      Yes, I am well aware that robots are on their way to take our jobs.

      But, I keep getting reminded that if I let the machines have at it, several brands would lose a lot of money for absolutely no logical reason.

      Google budget reco for a lot more money but not a lot more productionGoogle budget reco for a lot more money but not a lot more production (Image from author, March 2025)
      Meta making a recommendation for a function we don't even haveMeta making a recommendation for a function we don’t even have (Image from author, March 2025)
      Bing recommending a move with a questionable networkBing recommending a move with a questionable network (Image from author, March 2025)

      These are samples of the same suggestions I get every day. The platforms want to drive our business forward, but ignore the following facts:

      • The first image shows a 261% increase in spend, for a 94% increase in clicks, 13% more conversions, and a 42% drop in conversion rate (CVR).
      • The second image wants to automatically optimize 10 ads (which by the way, given it is a government regulated vertical, that is prohibited) all to lower my cost per acquisition (CPA) by 10%, but fails to note that we don’t even have a conversion pixel, or even record conversions.
      • The third image wants to expand into the entire network, one known for notorious amounts of fraudulent activity or the fact that there are no incremental funds to drive that excess traffic.

      Yes, I recognize that these recommendations are both automated and optional.

      But does that mean scenarios like these should be given a discount and not held to the same industry standards as others? There is only one correct answer: No.

      We observe that the automated recommendations are faster, more real-time, and more correlated to actual data. But, the human-based suggestions have a human objective and the little bird saying whether these are actually a good idea.

      We also note – and this is more specific to advertisers with a dedicated rep (and I don’t mean those you get for a fiscal quarter and call you at inappropriate times of the day) – that recommendations coming from them (while still salesy), are taking a look at the bigger picture, and making more specific recommendations to enhance your business.

      Google wanting to expand into a network known to have questionable placementsGoogle wanting to expand into a network known to have questionable placements (Image from author, March 2025)

      This is a machine/AI recommendation to opt into a network I intentionally opted out of due to extreme amounts of invalid activity coming from it. (I have more trust in Jenn Shah of RHOSLC safely holding onto my SSN than this recommendation.)

      This ratio of Google Search vs Partner Network does not make senseThis ratio of Google Search vs. Partner Network does not make sense (Image from author, March 2025)

      Rule of thumb: If the click volume in your search partner network is grossly exceeding your Google search volume, then there is likely something wrong.

      Play stupid games win stupid prizes...in credits, months laterPlay stupid games, win stupid prizes … in credits, months later (Image from author, March 2025)

      Look at all those credits tied back to that April campaign (this outcome reminds me of Aaron Rodgers leading my NY Jets in 2024).

      Meanwhile, my account rep gives me emails like this:

      What a proper recommendation should look likeWhat a proper recommendation should look like (Image from author, March 2025)

      Net-net: Quantity (machine/AI) is not better than quality (human), but I will admit, it is faster.

      Don’t Disregard Automated Recommendations Completely

      While I may sound like a spokesperson for the anti-AI/anti-machine lobbyists, these systems can help save your butt here and there.

      But, review these recommendations with a grain of salt while using them for a gut check.

      Showing when something was forgottenShowing when something was forgotten (Image from author, March 2025)
      Catching conflicts I would've missedCatching conflicts I would’ve missed (Image from author, March 2025)

      Not Controlling What Happens Is The Devil

      Yes, rep support is helpful, and sometimes, machine/AI can be helpful, too.

      But, if you are not reviewing what happens in terms of placements, creative, or optimization, you may find yourself up a creek. This is particularly important on the creative side, especially if there are multiple layers of creative approval.

      If you do not disable auto-apply, or you let Advantage+ run without oversight, then creative may not meet legal department guidelines.

      Nothing gives you a heart attack on a Saturday more than when your client calls to let you know that they saw their ad in a live video on a social platform about some nefarious activity, with part of the creative cut off inappropriately.

      If you run Performance Max, you definitely want to keep a close eye on this.

      What does this mean? If you have a degree of control over the machine rather than letting it run with it, take control. An extra hour of work now will save you 12 hours of fixing problems later.

      Having Control Of What Happens And Not Handling Properly Makes You The Devil

      Yes, you read that right. If you want to test out the machine functions and AI suggestions, and you have the control to decide how and when it executes the work, and you still don’t use it properly, well, then that is your fault.

      This isn’t just isolated to creative, but it definitely is much more awkward with it:

      I really don't know how Meta thinks this will sell Corned Beef HashI really don’t know how Meta thinks this will sell Corned Beef Hash (Image from author, March 2025)
      Bing thinks that this is a Jamaican Beef Patty...it is notBing thinks that this is a Jamaican Beef Patty … it is not (Image from author, March 2025)

      But, this is the tip of the iceberg; this is the easy stuff to prevent.

      When you allow it to add in music, create videos, adjust text, etc., you have the ability to prevent that. You’re even notified if you want to use it, and if you don’t take action, it’ll implement it. That is on you.

      What Is This Rant Really About?

      To do a very long-winded cut to the chase, this is about separating support and recommendations made by the platforms and the reps from what are industry and standard best practices.

      No, your Google Adwords (it’ll always be Adwords), Bing Ads (I refuse to call it Microsoft Advertising), and Meta reps are not out to ruin you financially, with the sole goal of getting you to spend more, by any means necessary.

      But, they have quotas and adoption requirements they have to meet. Companies that are not charities are money-making machines.

      So, sales-focused recommendations, auto-apply functions, and AI-generated suggestions are designed to ultimately get you to spend more money.

      It is your job as the digital marketer to recognize which function, recommendation, and capability your brand should utilize.

      Do not be bulldozed – push back. If the platform or the rep makes a recommendation, ask them to show the work and explain how it will help you meet your goal. After all, the platform’s goals may not be your goals.

      More Resources:

      Featured Image: Roman Samborskyi/Shutterstock

      Ecommerce MGMT 0 Comments
      Mar 18 2025
      Google PMax: Inside The Negative Keyword Limit Increase & What’s Next via @sejournal, @adsliaison

      As Google’s Ad Product Liaison, I often share updates and insights with the community of digital advertisers and, best of all, get to hear your feedback first-hand.

      We heard quite a lot after our recent announcement that, after a period of beta testing, we’re rolling out negative keywords in Performance Max (PMax) campaigns with a restriction.

      We had set a cap of 100 negative keywords per campaign.

      While the ability to add negative keywords in PMax directly in Google Ads without having to request them through Support or an account rep has been a long-time ask, we heard very quickly that the cap of 100 negative keywords felt too restrictive for many.

      Here’s a look behind the scenes at the reasoning behind the initial cap, what we learned from your feedback, and the subsequent decision to increase the limit to 10,000 negative keywords per campaign.

      Why The Cap In The First Place?

      AI, by its nature, thrives on flexibility, adapting to real-time data and user behavior.

      Performance Max is an AI-powered, goal-based campaign type that’s designed to find conversions based on the goals you set.

      The intention of capping negative keywords in PMax at 100 was to give advertisers additional control while still giving PMax the flexibility to achieve your campaign’s stated goal – a limit of 100 negatives felt like a reasonable starting point.

      To arrive at that number, we analyzed PMax campaigns in which negative keywords had been added via Support or their account rep.

      We found that the 100-keyword limit would cover the vast majority of campaigns using negative keywords.

      We also saw that the majority of submitted negative keywords had no actual serving impact – their ads already weren’t triggering for terms advertisers had concerns about.

      In many other cases, other targeting exclusions would have been more suitable for blocking unwanted traffic.

      We saw this in our beta testing as well. In short, 100 felt like a good compromise between offering enough flexibility without dramatically increasing the risk of accidentally blocking valuable traffic.

      Negative keywords are just one way to control where your ads show on Search. Other controls such as brand exclusions, account level negative keywords and keyword prioritization are also available.

      The initial cap of 100 negative keywords aimed to:

      • Preserve AI Optimization: Excessive negative keywords can act as rigid constraints, preventing the AI from exploring valuable search paths and hindering its ability to identify emerging trends. Essentially, it can stifle the algorithm’s ability to find the most efficient conversions. Very large negative keyword lists can potentially negatively impact the machine learning systems and hurt performance.
      • Prevent Accidental Traffic Exclusion: We aimed to prevent advertisers from inadvertently excluding valuable traffic through overly broad negative keyword scopes and missing potential high-intent customers.

      What Your Feedback Told Us

      We heard advertiser feedback loud and clear that while negative keywords are welcomed, the cap of 100 felt too restrictive.

      We heard from brands that quickly hit the 100 limit before including the key themes they wanted to negate. In short, it wasn’t a practical solution for many.

      After looking at options, the team agreed to align with the limits in Search campaigns and raise the threshold to 10,000 negative keywords per PMax campaign.

      That’s obviously a significant jump from 100 and way more than nearly every business will need or should use, but aligning on one common threshold simplifies things and gives advertisers plenty of room to experiment.

      Actionable Insights And Considerations For Measuring Impact

      Adding negative keywords to a Performance Max campaign can, of course, impact where your ads show on Search and Shopping inventory.

      While the increased limit provides greater control, it’s crucial to use negative keywords strategically. Here are several things to keep in mind when applying negative keywords in PMax:

      • Judicious Application: Avoid overly broad exclusions that might hinder the AI’s ability to find valuable conversions. Prioritize high-impact negatives that address specific ROI concerns. Keep in mind that account-level negative keywords you’ve added for brand suitability purposes already apply to your PMax campaigns.
      • Match Type Precision: Understand the nuances of broad, phrase, and exact match negative keywords in PMax. Negative match types work differently than their positive counterparts. For negative broad match keywords, your ad won’t show if the search contains all your negative keyword terms, even if the terms are in a different order. Phrase match negatives exclude queries containing the exact phrase, while exact match excludes only the specific query. Use them strategically to balance precision and reach.
      • Performance Monitoring: Closely monitor key metrics like conversions, conversion value, and conversion rates to ensure negative keywords have a positive rather than negative impact on performance.
      • Conflict Resolution: Be aware that if a user search matches both a positive signal and a negative keyword, the negative keyword will take precedence, and your ad will not be eligible to serve for that query.
      • Beyond Negative Keywords: Remember that PMax offers other control mechanisms to inform when your ads can trigger on Search.
      • Regular Audits: Just as with your Search campaigns, be sure to regularly audit your negative keywords to identify where you might be blocking potential valuable traffic. And Search Term Insights can help you identify query themes and individual search terms you might want to block with negative keywords.

      Your Questions Answered

      I received several questions about this update from advertisers on LinkedIn and X (Twitter) and want to address some of those here.

      “The real challenge is how negative keywords interact with PMax’s black-box decision-making. Will we get more visibility into which search terms PMax is actually serving against? And how will negatives impact machine learning optimization long term?”

      While PMax is designed to automate many aspects of campaign management, we recognize the importance of providing advertisers with meaningful insights.

      The introduction of negative keywords is one of several recent steps towards providing additional controls.

      Search Terms Insights for PMax provides a view of the search term categories as well as specific search terms that triggered your ads in Search. You’ll find performance metrics at the search term level.

      Search Terms Insights is designed to make analyzing search term data easier by already grouping similar searches into broader categories, saving you the time to sift through individual search terms.

      This data can be downloaded and available via scripts and the Google Ads API.

      As for the long-term impact of negative keywords on campaign optimization, it’s important to strike a balance.

      While negative keywords provide crucial control, an overly restrictive approach could limit the system’s ability to learn and adapt to new opportunities.

      As noted above, our recommendation remains to use negative keywords strategically to exclude truly irrelevant traffic, allowing the AI to continue exploring and finding valuable conversions within the defined boundaries you set.

      Reporting and insights are areas the team is actively focused on. Stay tuned for more on this.

      “Google never needed <100 negative keywords in order to have>

      Our intention was never to encourage spending on irrelevant queries.

      Performance Max is a goal-based campaign type which means it’s designed to find more of the conversions that you indicate are valuable to your business.

      The initial cap of 100 negative keywords was tested in beta and seemed to provide a reasonable level of control while still allowing the AI the necessary flexibility.

      We acknowledge that our initial assessment was not sufficient for many advertisers, and that’s why we listened to your feedback and made the significant increase to 10,000.

      “Why can’t negative keywords be limitless at any/every account level? Are there technical/operational issues that would be impacted?”

      This is a fair question. There are limits on certain entities in Google Ads accounts to help ensure system and process stability. We have more details on various entity limits here.

      “Will Google give us the ability to see the previously applied negative keyword lists we used to do via Support or our reps.”

      Yes, you’ll be able to see and edit negative keywords and negative keyword lists that were previously added by Support or a rep.

      “Why weren’t negative keywords available from the very start when PMax launched.”

      The core principle behind PMax is leveraging AI to discover conversions across Google’s channels.

      When PMax launched in 2021, the vision was to give advertisers a streamlined way to tell Google what they want to optimize for and then allow the system to learn and find those desired customers across all of Google’s inventory.

      Exclusions were seen as unnecessary and potential impediments to optimization.

      Over time, and with advertiser feedback in mind, features within PMax have expanded. And the pace of new insights and controls has been accelerating in recent months.

      “What about negative keyword lists?”

      Many of you asked about the possibility of using negative keyword lists within Performance Max campaigns, as you can in Search campaigns.

      We are actively working on this and expect to have more to share on support for negative keyword lists in PMax later this year.

      How PMax Is Evolving

      I recently shared the overview below of many of the recent reporting and control updates for PMax at the Paid Search Association Conference.

      These features are aimed at giving you more tools and information to steer PMax to find more of the conversions you want to generate for your business.

      Features like brand guidelines help ensure your responsive display ads and auto-generated video ads reflect your brand’s visual identity.

      Ginny Marvin presented recent PMax controls and insights updates at the Paid Search Association ConferenceRecent controls and insights updates for PMax. Image from author, March 2025

      Stay tuned for more on search terms data and analysis capabilities as well as additional insights this year.

      This is an area we are actively focused on. And keep the feedback coming.

      More Resources:

      Featured Image: Gorodenkoff/Shutterstock

      Ecommerce MGMT 0 Comments
      Mar 18 2025
      The State Of Performance Max: How To Optimize Google Ads In 2025 via @sejournal, @MenachemAni

      In the beginning, there was only Search. Then Google said, “Let there be Shopping.” And so began the golden age of search advertising.

      Fast forward, and machines now perform the more granular and recurring optimizations at scale that we had to manually.

      Algorithmic campaigns like Performance Max have become Google’s golden goose. They claim that in the near future, businesses will be able to input their goals and information, and Google’s system will run its advertising program for them.

      Agencies and marketers have naturally pushed back, claiming that Google wants to put them out of business when they’re still needed. Some even say that machine learning isn’t necessary when brilliant human minds are on the job.

      The truth, as always, is somewhere in the middle.

      Performance Max isn’t going anywhere, and neither are agencies and marketers. And if you plan to manage Google Ads this year, you will need to accept both sides of that coin.

      So, with some very welcome changes from Google behind us, here’s the state of Performance Max and what I envision for it going forward.

      Why Does Performance Max Have A Negative Reputation?

      PPC marketers have many complaints about Performance Max. Some are valid, and others feel unfair.

      The inability to see most of your keyword data is one of the reasons I hear the most.

      The introduction of search categories is welcome, but they are not necessarily the keyword a user searched for.

      You can expand the category somewhat and get an idea of intent, but it’s not a one-to-one deal like seeing the actual query.

      And while longtime advertisers are accustomed to seeing every search term, the reality is that Google has been removing more and more data for years, all in the name of privacy.

      This limited and unclean data around what people search for – what we’re used to seeing in the search terms report – is a valid frustration, especially when budgets are limited, or the pressure to deliver is particularly high.

      There are improvements to take note of, though.

      By default, the system shows seven days, and you can go back to the last 28 days. Google has also added the ability to look at longer time frames for search terms.

      The addition of these new capabilities – even if they don’t cover everything we want – tells me that Google sees that the adoption of Performance Max is not going to reach the desired levels unless we have the tools we need to make use of it.

      And even though this data only started in March 2023, having it now is helpful.

      Another reason why Performance Max has a negative reputation is its attribution shyness. You can’t fully see where success or failure is coming from, which is a challenge in performance marketing.

      A campaign could show you 10x return on ad spend, but you may have, at best, a sneaky suspicion that it’s coming from primarily retargeting traffic. There’s no real way to see the data that confirms that hypothesis (or refutes it).

      And so the mindset shifts to one of “it’s not worth the hassle,” compounded by the fact that third-party attribution tools like Triple Whale are still unable to weigh Performance Max very well within its system because it cannot see view data for YouTube like it does for Meta.

      This makes Performance Max look like it’s not working as well as it is.

      One of the trickiest pieces of Performance Max is that people just have a hard time reconciling the data that Google shows and that they want to get from the campaign, which is typically profitable net new customer acquisition.

      By moving back to Shopping – even if it shows a slightly lower return on ad spend (ROAS) – marketers at least know what they’re getting for their money as the reporting and attribution are clearer.

      On the flip side, while third-party attribution tools do underreport for Performance Max (likely because of channels like YouTube and Display that affect performance), my experience is that mixing the two – putting some products in Shopping and some in Performance Max – often works well if the campaigns are being used properly.

      Do We Need Granular Control In Performance Max?

      Playing the devil’s advocate for a minute, I think the whole idea of Performance Max is that you shouldn’t have to add negative keywords.

      You’re meant to optimize the campaign based on your bidding strategy, ROAS or cost-per-acquisition (CPA) target, account and campaign structure, landing page, and proprietary data.

      This ties into another source of frustration: low-quality ad inventory.

      My answer to both complaints is to focus on getting the best performance out of the campaign, or switch back to Search or Shopping.

      I think we have to accept some amount of poor traffic and unwanted conversions in exchange for incremental gains in profitable new customer acquisition.

      In the bigger picture, search terms and placements don’t really matter as much as the system will learn to focus less on that kind of traffic if it’s not converting.

      Performance Max does take time and money to get going, so it’s fully understandable if your niche or vertical means you can’t justify the investment due to factors like limited budget, low search volumes, unavailability of data inputs, or tight industry regulation.

      This is your reminder that Performance Max is an option, not a necessity.

      The Resurgence Of Search And Shopping: Why Performance Max Won’t Replace PPC Marketers

      Performance Max saw widespread adoption at launch, even though we were coming from Smart Shopping, which worked far better at the time.

      Still, we were quick to adopt and switch because Google pushed hard on the narrative that it was the future.

      Over time and as reality set in, many advertisers started to move back to Search and Shopping for three primary reasons:

      1. A high proportion of spam and low-quality leads.
      2. For ecommerce, a lack of control over products and campaign behavior.
      3. Cannibalization of non-algorithmic legacy campaigns by Performance Max.

      Today, I find that we create the most success for clients by running a mix of Shopping and Performance Max side by side.

      We haven’t moved away from the latter completely, but I have heard from others that they’ve returned fully to standard Shopping.

      This will be furthered by recent developments around which campaign is valued by Google.

      Upon the launch of Performance Max, both campaigns running alongside each other meant that Performance Max always took priority while Shopping didn’t enter auctions.

      Over the years, there have been some changes to that prioritization. Anything you excluded from Performance Max (such as brand terms) would always fall back to Shopping. And now, Google has announced that Performance Max will not override Shopping.

      Both will enter the auctions they qualify for, and ad rank will determine which one shows.

      Performance Max In 2025: 5 Optimizations For Better Results

      So, how do you regain control when Performance Max takes it away? What can you really do to improve campaign performance, and what options are realistically at your disposal?

      Here are five of my Performance Max optimizations to never leave home without.

      1. Data input quality is absolutely critical to success with Performance Max and is virtually essential if you run lead generation campaigns.

      Offline conversions, audience signals, and enhanced conversions all help improve results.

      Synchronizing your customer list and having the campaign focus solely on new customer acquisition is a great way to avoid spending money on people who have already bought from you, improving profitability.

      2. Asset group segmentation and how you set up a Performance Max campaign really make a difference in what kind of traffic it brings in.

      Without the right decisions here, the campaign will automatically go after traffic that it believes is most likely to convert – site visitors, people searching for your brand, and past/existing customers.

      3. The quality of your creative assets and landing pages has a direct impact on your ability to get those big performance lifts that aren’t really possible any longer through old-school account optimization.

      You simply must stand out and be relevant in a market where competitive saturation is at its peak, and consumers are bombarded with messages to buy things everywhere on the internet.

      4. For ecommerce, feed quality and optimization are non-negotiable for both Performance Max and Shopping.

      The feed is the heartbeat of the account – it’s where the system looks for information on your products to help it decide who should see them.

      Skipping this step or running a poorly written feed will directly and negatively impact your marketing efficiency.

      5. Sculpting options are limited but should still be employed where they make sense. One option is to remove branded traffic using brand exclusions.

      You can also add negative keyword lists through Google support and then just block specific keywords. Soon enough, you’ll be able to add campaign-level negatives to Performance Max yourself.

      Ultimately, you’ve got to optimize where you can to improve the consumer experience.

      This might be something as fundamental as tracking the right conversion actions, writing a sharper landing page with stronger social proof, improving mobile responsiveness, and setting up rules to only advertise products that are in stock.

      In short, focus on what you can control and do a wonderful job with those things.

      Google Is Listening To PPC Advertisers And Agencies

      The PPC community complained about the lack of negative keywords – Google gave them to us. We asked for more detailed reporting – we got it. The cannibalization of Shopping became a problem – Google resolved it.

      I think, at this point, Google is due the credit for listening to us.

      Not only is it adding more (and more relevant) features to Performance Max, but it is also seeing that agencies and marketers have a role to play in the future of search advertising.

      I think the decreased adoption and vocal critique on social media have undoubtedly influenced the decision to give us back a portion of control and visibility.

      It’s our turn to adopt these features, adapt to the limitations of Performance Max (when it makes sense for the account), and, most importantly, keep a fair and honest dialog open on social media with Google’s representatives.

      More Resources:

      Featured Image: Jack Frog/Shutterstock

      Ecommerce MGMT 0 Comments
      Mar 18 2025
      [SEO & PPC] How To Unlock Hidden Conversion Sources In Your Sales & Marketing Funnel via @sejournal, @calltrac

       This post was sponsored by CallTrackingMetrics. The opinions expressed in this article are the sponsor’s own.

      Did you know 92% of all customer interactions are from phone calls?

      And very few know how to track conversions from phone calls.

      Brands meticulously track clicks, impressions, and online interactions through SEO, pay-per-click (PPC) ads, and data-driven strategies.

      Yet, one critical piece is often missing: offline conversions.

      Many high-intent customer interactions, especially in industries like healthcare, legal, home services, and B2B, happen over the phone.

      If you’re in an industry that receives any number of calls, you may be struggling to connect these calls to your digital marketing efforts, leading to:

      1. Inefficient marketing strategies.
      2. Wasted ad spend.
      3. Difficulty proving ROI.

      How do you fix this? Call tracking.

      By leveraging AI-powered tools and advanced attribution technology, marketers can bridge the online-offline gap, ensuring no lead goes unnoticed.

      How To Attribute Sales To Phone Calls

      TL;DR: Historically, you could not attribute conversions to phone calls; now, you can.

      Yes, offline conversions can be tracked.

      And despite the high percentage of customer interactions happening over the phone, many brands fail to track which ad or campaign led to those calls.

      This could stem from knowledge gaps, tight budgets, or reluctance to integrate more technology into their stack.

      Without call attribution, businesses are left guessing about what’s driving revenue.

      What Is Offline Conversion Attribution?

      Offline conversion attribution is the process of linking your online marketing efforts to offline sales or actions.

      It helps you understand which digital marketing channels and campaigns contribute to offline conversions, such as in-store purchases, phone call inquiries, or signed contracts.

      How Offline Conversion & Phone Call Attribution Works

      By paying attention to phone call conversion data, you can:

      1. Connect Online Interactions To A Phone Call: A user clicks on a digital ad, visits a website, fills out a form, or calls a business after seeing an online campaign.
      2. Store User Data In One Place: Data from these interactions (such as email, phone number, or a unique tracking ID) is captured and stored.
      3. Match Callers With Offline Events: When a purchase or conversion happens in-store, over the phone, or through a sales team, businesses match it back to the initial online touchpoint.
      4. Analyze & Optimize Webpages With Content That Converts: You can analyze which digital campaigns, keywords, or ads drive the most offline conversions, optimizing their marketing strategy accordingly.

      What You Can Do With Phone Call Conversion Data

      When you introduce a tool that acts as Google Analytics for phones, you’ll be able to:

      • Improve ROI Measurement: Helps businesses understand the real impact of digital marketing on offline sales.
        Enhance Ad Targeting: Enables better retargeting of high-intent users.
        Optimize Budget Allocation: Allows marketers to invest more in channels that drive actual sales, not just clicks or website visits.
        Bridge the Online-Offline Gap: Particularly important for industries like retail, automotive, healthcare, and B2B, where many transactions happen offline.

      Examples of Offline Conversion Attribution

      1. A customer finds your business through organic search.
      2. They see a retargeting ad on Facebook.
      3. Finally, they click a PPC ad and call to book an appointment.

      Without call tracking, the PPC ad might receive full credit, even though SEO and social played key roles. Choosing the right attribution model ensures data-driven marketing decisions.

      Best Tools for Offline Conversion Tracking

      • Google Ads Offline Conversion Tracking
      • Facebook Offline Conversions API
      • CRMs like HubSpot or Salesforce
      • Call tracking software like CallTrackingMetrics

      SEO & Call Tracking: Connecting Organic Efforts To Real-World Conversions

      Gain Keyword Attribution Beyond Clicks

      Rankings, traffic, and forms typically measure SEO success fills. But what about phone calls? Call tracking technology with dynamic number insertion (DNI) allows businesses to:

      • Identify which organic search queries lead to phone calls
      • Optimize content around real customers’ questions and concerns
      • Understand which landing pages drive the most offline conversions

      For example, if multiple callers reference a specific product-related question, that insight can inform new blog topics or FAQ pages to improve SEO efforts, driving even more right-fit traffic into your sales funnel and conversion metrics.

      Optimize For True Local SEO

      Local search is a major driver of inbound calls. When combined with call tracking, businesses can finally understand:

      • Which local listings (Google Business Profile, Yelp, etc.) generate the most calls?
      • What information do customers search for before calling?
      • How to refine location-based content for higher engagement

      How Call Insights Can Strengthen Your SEO Strategy

      Phone calls aren’t just conversions—they’re valuable sources of customer insights that your teams can use to refine ad strategies, train teams on sales pitches, and identify areas for growth in your content strategy. Each conversation has the potential to reveal the common questions, pain points, and content gaps that businesses can address to improve their marketing performance.

      1. Identify FAQs for Stronger Content

      Often, customers call a company’s support phone number when they can’t find information online, either about a product or service they’re considering buying or one they’ve already purchased. By analyzing call transcripts, businesses can spot recurring questions and proactively address them in blog posts, FAQs, or product pages.

      For example, if a home services company frequently gets calls asking, “Do you offer emergency repairs on weekends?”, this signals a need to make that information more visible on their website. A dedicated service page or blog post could reduce unnecessary calls while improving customer experience.

      2. Refine Your Website Messaging

      If callers repeatedly ask about pricing, product differences, or service details, your website messaging probably isn’t clear enough.

      For instance, an e-commerce brand selling fitness equipment might notice that callers often ask, “What’s the difference between your basic and premium treadmill?” Adding a simple comparison chart or explainer video can help lessen confusion and improve conversions.

      3. Fill Content Gaps To Reduce Sales Friction

      Repeated calls about the same topic are a good indicator of missing or unclear content. A B2B SaaS company, for example, might receive frequent inquiries about integrating with a particular CRM or social platform. Instead of solely relying on customer support, the marketing team could identify this pain point and create a step-by-step guide or video tutorial to address it, which would reduce friction and improve self-service for prospects.

      PPC & Call Attribution: Maximizing ROI With Better Insights

      Tracking clicks alone doesn’t reveal the full ROI of PPC campaigns. Many conversions, especially phone calls, happen offline and go untracked. Without attribution, businesses may waste ad spend and overlook high-intent leads. This section explores how call tracking connects PPC efforts to real conversions, improving marketing efficiency.

      Paid Search: Wasted Spend Without the Full Picture

      A high cost-per-click (CPC) doesn’t guarantee strong ROI if businesses aren’t tracking offline conversions. Without call tracking, marketers risk:

      • Over-investing in underperforming keywords
      • Missing opportunities to optimize campaigns for call-driven leads
      • Failing to attribute revenue-generating phone calls to PPC efforts

      When a business fails to account for ROI in the form of phone calls, they’re losing an opportunity to accurately account for their real CPC and allocate resources accordingly.

      Call Tracking + Google Ads = Smarter Bidding

      PPC campaigns are only as effective as the data behind them. Without tracking phone calls, businesses risk misallocating budgets to keywords that drive clicks but not conversions. Integrating call tracking with Google Ads provides a clearer picture by linking calls to the specific campaigns, ad groups, and keywords that drive valuable conversions.

      With AI-powered call scoring, marketers can identify high-intent leads and adjust bidding strategies based on actual conversion data—not just clicks. This ensures ad spend is focused on quality leads rather than wasted traffic.

      Retargeting with First-Party Data

      Not every caller converts immediately. Call tracking allows businesses to retarget high-intent leads with personalized follow-ups. By analyzing call topics, marketers can tailor ads or email sequences to address specific customer concerns, increasing the likelihood of conversion.

      Additionally, integrating call data with CRM platforms like HubSpot and Salesforce ensures sales teams can nurture prospects effectively, preventing lost opportunities. By combining PPC insights with offline conversions, businesses gain a clearer understanding of customer behavior, leading to smarter ad spend and more targeted outreach.

      Back To Basics: Omnichannel Attribution & The Power Of Call Data

      As marketing shifts to a mix of online and offline tactics, attribution models must evolve. By integrating call tracking with Google Analytics, CRM systems, and automation tools, businesses can gain a complete view of the customer journey.

      A company that integrates CallTrackingMetrics with Google Analytics and its CRM can:

      • See exactly which campaigns drive calls.
      • Automate follow-ups based on conversation insights.
      • Optimize for higher-value interactions.

      AI & Conversation Intelligence

      Call tracking is no longer just about recordings or basic attribution. AI-driven call analysis provides deep insights, such as:

      • Customer intent and sentiment analysis.
      • Common objections that impact sales.
      • Automated lead qualification based on real conversations.

      By leveraging AI, businesses can better understand customer needs, improve sales strategies, and ensure marketing efforts are driving meaningful engagement. Implementing AI-driven call tracking empowers teams to make data-backed decisions that enhance both customer experience and conversion rates.

      Proving Marketing’s True Impact

      Marketers are often challenged to prove ROI beyond what we might call “vanity metrics”, like impressions and clicks. Though these have a place in any strategy, these metrics don’t necessarily move the needle toward sales goals.

      Call tracking, on the other hand, delivers revenue-focused attribution, showing exactly how digital marketing contributes to bottom-line growth. This kind of revenue-focused attribution can help an entire company analyze past efforts and accurately forecast revenue based on real campaigns, real calls, and real results

      Case Study: This study from CallTrackingMetrics demonstrated how AI-driven call tracking optimized PPC ROAS and improved lead quality​.

      Want to see how conversation intelligence can improve your marketing performance? Check out our guide to building an effective omnichannel communications strategy.

      Ready to get to work? Book a demo with our team and see how CallTrackingMetrics’ products can help you.

      BOOK A DEMO NOW

      Image Credits

      Featured Image: Image by CallTrackingMetrics. Used with permission.

      Ecommerce MGMT 0 Comments
      Mar 7 2025
      10 Top Converting Landing Pages That Boost Your ROI [With Examples] via @sejournal, @unbounce

      This post was sponsored by Unbounce. The opinions expressed in this article are the sponsor’s own.

      Want to increase sign-ups, sales, or demo requests from your landing page?

      How can you ensure your landing page is optimized for conversions?

      Landing pages can make or break your conversions.

      A well-designed landing page doesn’t just look good; it also seamlessly guides visitors toward action, such as signing up, purchasing, or booking a demo.

      A high-performing landing page should align with your goals:

      • Capturing leads.
      • Driving sales.
      • Promoting an event.

      The best landing page templates are designed with conversion in mind, featuring strategic layouts, persuasive copy, and clear calls to action.

      So, let’s look at a few top-performing landing page examples to learn about why they work and how you should implement them.

      1 & 2. FreshGoods & Radiant Yoga Studio: Great For A Clear & Compelling Unique Selling Point

      The secret to beating the competition is positioning your brand so you’re the only one in your specific space.

      How? By honing in on your Unique Value Proposition (UVP):

      • What is the one reason to choose you, your products, or services?
      • Where does your competition fall short?
      • How do you make your UVP stand out?

      FreshGoods Landing Page

      Landing pageImage by Unbounce, 2025
      Copy This Landing Page Now

      Radiant Yoga Landing Page

      yoga landing pageImage by Unbounce, 2025
      Copy This Landing Page Now

      Why They Work

      These conversion-optimized landing page templates effectively highlight a USP throughout the design.

      • A clear and bold headline that immediately communicates the core benefit.
      • The supporting subheadline allows brands to reinforce the core USP message by expanding on the offer in a way that adds clarity without overwhelming visitors.
      • The strategic use of whitespace and strong typography ensures that the USP remains the focal point, making it easy for visitors to grasp the value of the offer at a glance.

      How To Recreate These Landing Pages

      Step 1: Define Your Unique Selling Proposition

      A strong USP makes visitors feel like they’ve found exactly what they need. Instead of blending in with competitors, it positions your brand as the only choice.

      • Ask yourself: What is the one reason customers should choose you over others?
      • Example: FreshGoods & Radiant Yoga Studio’s landing pages showcase a crystal-clear UVP in their messaging and design.

      Step 2: Craft a Compelling Headline & Supporting Headline

      Your headline is your first impression, so you have to make it count. The supporting headline expands on that core message.

      • Best Practices:
        • Be specific: Instead of “The Best Marketing Tool,” try “Turn Clicks into Customers with AI-Powered Marketing in Minutes.”
        • Reinforce value: “No coding, no guesswork. Just smarter campaigns that drive real revenue.”

      Step 3: Address Concerns with Reinforcing & Closing Statements

      • A reinforcing statement builds trust (“Trusted by over 10,000 businesses…”).
      • A closing statement eliminates hesitation (“Every second you wait is a sale you’re losing. Start your free trial now.”)

      3 & 4. Vita Health & Orbit SaaS: Great For Hero Images & Visual Storytelling

      Before visitors read a single word, visuals will capture their attention and convey meaning.

      A strong hero image isn’t just decoration,  it sets the tone, builds trust, and instantly reinforces your message. The right imagery makes your offer feel more tangible, relatable, and desirable.

      Vita Health Landing Page

      health wearables landing page exampleImage by Unbounce, 2025
      Copy This Landing Page Now

      Orbit Flow Landing Page

      SaaS landing page example and inspirationImage by Unbounce, 2025
      Copy This Landing Page Now

      Why They Work

      A landing page’s imagery is a strategic tool that helps communicate your offer, build trust, and nudge visitors toward conversion. Choose visuals that don’t just look good but work hard to sell.

      A well-chosen visual:

      • Supports the UVP.
      • Evokes an emotion that drives action
      • Showcases the product, service, or outcome in action
      • Makes the page feel polished, professional, and credible

      In addition to the visual, the full landing page benefits from:

      • Strong hero image placement
      • An opportunity to reinforce the messaging conveyed with the hero image throughout the page
      • White space highlights supporting visuals
      • Visual hierarchy guides site visitors down the page to the parts that matter.

      How To Recreate These Landing Pages

      Step 1: Choose the Right Hero Image

      Before visitors read a word, visuals capture attention. A great hero image should:

      • Support the USP
      • Evoke emotion & drive action
      • Showcase the product, service, or outcome

      Step 2: Guide the Visitor’s Eye

      Strategic use of visuals can nudge visitors toward your CTA:

      • Eye gaze: People follow where others are looking in an image.
      • Angles & positioning: Lines or arrows subtly direct attention to the CTA.
      • Contrast & color: Key elements should stand out.

      Step 3: Reinforce Messaging with Supporting Imagery

      Don’t rely on just one image. Use:

      • Icons & illustrations
      • Graphs & charts
      • Customer photos & testimonials
      • Short videos or GIFs

      Bonus Tip:

      Use A/B testing to find the ingredients for maximum impact.

      The right image can make or break conversions, so test different options. Some images resonate better with your audience, drive more engagement, or feel more aligned with your brand.

      Some elements to test include:

      • People vs. product-focused visuals.
      • Static images vs. motion (GIFs or videos).
      • Close-ups vs. wider perspective shots.
      • Different background colors or lighting.

      5 & 6. Serene Vista & Digital Foundry: Great For Clearly Conveying Benefits

      Visitors specifically care about what it does for them.

      That’s why benefits should take center stage on a conversion-optimized landing page, not just a list of features.

      Serene Vista

      Travel website landing page inspirationImage by Unbounce, 2025
      Copy This Landing Page Now

      The Digital Foundry Landing Page

      Marketing agency landing page inspirationImage by Unbounce, 2025
      Copy This Landing Page Now

      Why They Work

      • The benefits are concise and audience-focused
      • Each feature section is well-spaced to garner attention
      • Benefits are integrated well into the page structure with the subheadings and images to help visitors scan

      How To Recreate These Landing Pages

      Step 1: Translate Features into Benefits

      • Feature: “AI-powered keyword research tool”
      • Benefit: “Find high-converting keywords in seconds—no guesswork needed.”

      Step 2: Address Pressing Concerns

      • What pain points does your audience face?
      • How does your product solve them better than competitors?

      Step 3: Qualify Your Audience

      • Use benefit-driven copy that attracts the right people:
      • Example: “Perfect for fast-growing teams who need to scale without the chaos.”

      7 & 8. Revive Aesthetics & Smile Dental: Great For Social Proof That Builds Trust

      Not all social proof is created equal.

      The best reinforces your UVP, addresses concerns, and speaks directly to your audience.

      See what we mean here.

      Revive Landing Page

      Health and spa landing page inspirationImage by Unbounce, 2025
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      Smile Kids Landing Page

      Dentist landing page inspirationImage by Unbounce, 2025
      Copy This Landing Page Now

      Why These Landing Page Templates Work

      • The headshots paired with the social proof enhance trustworthiness and make a connection with site visitors because they can see themselves in the experiences being described.
      • The rounded shape and contrasting colors make the social proof stand out.
      • Located near the point of conversion.

      How To Create This Landing Page

      Step 1: Choose the Right Type of Social Proof

      • Customer testimonials & reviews
      • Case studies & success stories
      • Logos of recognizable brands
      • Ratings & review scores
      • Media mentions & awards

      Step 2: Strategically Place Social Proof

      • Near the CTA: Reinforces trust before action.
      • Midway down the page: Nudges hesitant visitors.
      • In the hero section: Puts endorsements front and center.

      9 & 10. Livewell Lifestyle & Inner Handyman: Great For Turning Interest Into Conversions With Calls To Action

      A landing page without a strong CTA is like a roadmap without a destination.

      Your CTA is the single most important element that tells visitors what to do next.

      And if it’s unclear, compelling, and easy to find, you’ll lose conversions.

      A compelling CTA is a combination of copy, design, and placement that removes hesitation and drives action.

      Livewell Landing Page

      Healthy living landing page exampleImage by Unbounce, 2025
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      Inner Handyman Landing Page

      Local business landing page and website inspirationImage by Unbounce, 2025
      Copy This Landing Page Now

      Why They Work

      • CTAs can be customized to stand out and get attention
      • CTA sizing and positioning make them clear focal points despite having multiple elements on the page. It ensures you get the most conversion power in every pixel
      • The CTA buttons are placed where it matters throughout the page, making sure the page attempts the conversion when and where it matters most

      How To Recreate These Landing Pages

      Step 1: Craft a Clear, Compelling CTA

      A high-converting CTA should be:

      • Action-oriented: “Start Growing Today” vs. “Submit”
      • Benefit-driven: “Unlock Exclusive Access” vs. “Sign Up”
      • Urgent (if appropriate): “Claim Your Spot Today”

      Step 2: CTA Placement for Maximum Impact

      • Above the fold: First CTA visible immediately.
      • After key information: CTA follows value explanation.
      • Near social proof or benefits: Reinforces trust.
      • At the end of the page: Captures hesitant visitors.

      Step 3: CTA Design That Stands Out

      • Color contrast: The CTA should pop from the background.
      • Size & positioning: Large enough to be noticeable but not overwhelming.
      • Whitespace & directional cues: Ensures the CTA is the focal point.

      Bonus Tip:

      A/B test your CTAs for better conversions.

      CTAs aren’t one-size-fits-all. Even small tweaks can make a huge impact on conversions, so A/B testing different variations is essential:

      • Wording – Try “Get Started” vs. “Try It Free”
      • Color – A bold button color vs. a softer, branded one
      • Placement – Above the fold vs. midway down the page
      • Size and shape – Larger buttons vs. compact ones
      • Personalization – “Start My Free Trial” vs. “Start Your Free Trial”

      Build High-Converting Landing Pages Faster

      A great landing page isn’t just about design.

      It’s about strategy.

      Every element, from your USP and hero images to your social proof and CTAs, is critical in guiding visitors toward conversion. When these elements work together, your landing page drives action.

      But building a high-converting landing page from scratch can be time-consuming and complex. That’s why using proven, conversion-optimized templates can give you a head start.

      With Unbounce, you get access to 100+ professionally designed landing page templates built for maximum conversions. Whether capturing leads, promoting a product, or running a campaign, these templates help you launch faster, test smarter, and convert better—without needing a developer.

      Ready to build an optimized landing page that converts?

      Explore Unbounce’s best-performing templates and start optimizing today!

      Get  25% Off The 1st 3 Months!

      Image Credits

      Featured Image: Image by Shutterstock. Used with permission.

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