Top Ecommerce Ad Segments

Data-driven customer segments enable brands to personalize marketing campaigns, improving engagement and conversions.

Yet first-party data remains an underutilized marketing asset of ecommerce companies. Most focus their promotional efforts on email, SMS, and even direct mail, missing the opportunity to use their data in advertising.

My company manages paid media for big and small companies. We see performance lifts of 25% or more from targeted segments versus a broader audience.

Here are 10 segments to jumpstart your ecommerce ad performance.

Advertising campaigns are more productive when targeted to customer segments.

Ecommerce Ad Segments

The larger the customer list, the more complex the segmentation. The number of segments depends on the company, the budget, and available creative messaging.

All customers

Start with the broadest audience: all purchasers. Remarket to them with product launches or sales, and exclude this segment from customer acquisition campaigns.

Top customers

Repeat customers make or break most ecommerce businesses. Creating a top customer segment — e.g., frequency of purchases, the time between purchases, total value — helps focus on those essential buyers.

Sale and non-sale purchasers

Sale purchasers are prospects for flash promotions and discount campaigns. Excluding non-sale purchasers helps maintain their full-price purchasing behaviors.

Gift purchasers

A checkout flow should include the option of marking the purchase as a “gift” or adding a gift message. It improves the customer experience and facilitates a gift purchaser segment. That audience becomes valuable during gifting holidays such as Mother’s Day, Father’s Day, and the Q4 season.

Category purchasers

Category segments enable new-product campaigns and cross-sells. A customer who purchases from Category A is likely interested in those new or related products. Create messaging and campaigns to capitalize on that preference.

Unengaged purchasers

Lapsed or unengaged customers are another worthwhile segment. Use paid media to re-engage these buyers and reach them through a channel other than your own email solicitations.

Peak-season buyers

Brands with peak selling seasons beyond Q4 should create segments of customers who purchased during those periods. Timely targeting of those buyers often produces high ROAS.

Q4 customers

Most consumer brands depend on Q4 sales. Create a segment dedicated to those customers and message appropriately to maximize your impact.

Likely to purchase within x days

Predictive platforms such as Klaviyo, Bloomreach, and others can identify buyers who are “likely to purchase.” Create this segment and test various timeframes to avoid advertising to customers who would have purchased anyway.

Likely to have high AOV

Predictive platforms can also anticipate “high average order value” buyers. These segments can be lucrative and are worth testing.

Getting Started

To start, download customer segment lists from your ecommerce platform and upload them to Meta, Google, or other ad channels. Email addresses are required, and first name, last name, country, and postal code are helpful. Some platforms sync directly to ad channels. Klaviyo, for example, integrates with Meta and Google.

Next, activate campaigns that target these customers. In my experience, brands with extensive customer lists do not require look-a-like campaigns. With enough data, ad platforms can target broad-reach audiences as well or better.

Customize ad creative and messaging to the segment. If you’re trying to reach gift purchasers, for example, consider ads showcasing common gift products with dynamic gifting prices.

Optimizing Google Ads without Keywords

Keywords were once the core targeting mechanism in Google Search campaigns. Keywords informed searchers’ needs and advertisers’ ads and landing pages. But the importance of keywords dwindled in the last decade for various reasons, including:

• Less-precise match types.
• Intent-focused smart bidding.
• Keyword-less campaign types.

Keywords remain critical (and necessary) for standard Search campaigns. Yet other entities increasingly determine account success. Keyword queries alone don’t reveal searchers’ intent.

Here’s how to future-proof Google Ads accounts beyond keywords.

Less-precise Match Types

The problem:

Exact and phrase-match campaigns used to show only ads with the precise keywords. For example, bidding on the exact match of “baseball gloves” would only trigger ads when searchers typed that identical query. Phrase match bids would show only ads with the exact words in the same order.

Over time, Google introduced relaxed variants for similar queries, such as:

• Singular and plural (“baseball” glove),
• Misspellings (“baseeball” gloves),
• Close variants (“catcher” gloves).

Broad match keywords combined with smart bidding are now common. Google says it considers users’ recent searches, the landing page content, and other keywords in an ad group. Thus a broad match ad for “low-carb diet plan” can show for:

• “carb-free foods,”
• “low-carb diets,”
• “mediterranean diet books,”
• “how to cut carbs for beginners,”
• “carb-free meals.”

The solution:

Consider keywords as themes, a starting point. For example, a phrase match bid on “baseball gloves” could trigger searches for “baseball gloves under $100.” Yet an advertiser whose gloves cost more than $100 could opt not to assign negative keywords, as Google may know searchers’ preferences and show ads accordingly. Perhaps a searcher has queried with and without price and demonstrated (to Google) her preference for gloves costing more than $100. This leads to the next point.

Intent-focused Smart Bidding

The problem:

Manual bidding gives advertisers the most control over bidding. An example is setting a maximum amount per keyword. Furthermore, advertisers can place modifiers, such as increasing mobile bids by 20%. But those manual tactics are now outdated given the shift to intent and away from words alone.

The solution:

Google’s smart bidding uses artificial intelligence to optimize conversions or revenue. Google’s AI tracks hundreds of signals to show the right ad to the right user and adds device or location modifiers automatically. An advertiser with most sales between 1:00 and 5:00 p.m. could see its bids automatically increase during this time.

The actual keyword is less important. A query for “research baseball gloves” —  normally information-focused — could show an ad selling baseball gloves if the searcher’s previous queries were shopping-related.

Keyword-less Campaign Types

The problem:

The rise of close variants and smart bidding can seemingly mask advertisers’ keyword gaps. Yet Google claims billions of searches daily, with 15% new queries. It’s impossible to bid on every existing or future keyword, even for huge accounts.

The solution:

Shopping, Dynamic Search Ads, and Performance Max campaigns show ads on Google Search results. None use keywords, focusing instead on other factors. Shopping and Dynamic Search campaigns show ads based on advertisers’ product-feed attributes and site content. Even Performance Max, with ads on Google’s Display Network and on Search, relies on advertiser-provided signals.

In short, search intent — not keywords — increasingly determines which ads appear.

Understanding YouTube Campaign Types

Google Ads has invested heavily in video. Recent examples include new YouTube advertising formats and Performance Max video campaigns. Video isn’t solely a brand awareness play. Compelling product videos can generate sales while promoting the brand. Google refers to this method as “leveling up for action” using ABCD principles:

• Attention,
• Branding,
• Connection,
• Direction.

“Leveling up for action” progresses from Attention to Branding to Connection to Direction. Image: Google.

Google Ads offers seven YouTube campaign subtypes for video. They range from reaching users while browsing to driving conversions. The subtypes I will review are:

• Video views,
• Drive conversions,
• Ad sequence.

With all subtypes, audience targeting segments are in-market, affinity, demographics, and advertiser-created. The right targeting is critical. Certain campaigns are for prospecting, while others are down-funnel. Audience targeting and associated videos must align with a campaign’s goals.

Video Views

The “video views” campaign subtype is new and targets users likely to consider the product or brand. The advantage is the ads are responsive. Advertisers provide a long headline and description along with the video and landing page URL. Google then shows the video across the different ad formats, including skippable in-stream, in-feed, and through YouTube Shorts.

Bidding is set at a target cost per view (CPV), and advertisers must include a total budget with an end date. For example, a two-week campaign may have a $2,000 budget with a CPV of $0.05.

A couple of beginning steps are necessary to avoid showing ads on irrelevant YouTube channels and other sites. First, confirm the option in the Networks section to target video partners on Google’s Display Network is unchecked.

Then, once the campaign is live, add topic, placement, and keyword exclusions. Similar to negative keywords in Search campaigns, these exclusions stop ads from showing on the wrong sites and YouTube channels. Unfortunately, without exclusions videos will show on irrelevant sites even with precise targeting.

Drive Conversions

Advertisers using the “drive conversions” subtype can optimize for specific actions and use goal-based bid strategies such as target cost-per-acquisition and return-on-ad-spend. Ecommerce merchants can attach their Google Merchant Center feed to show products with the ads.

Test a variety of videos and lengths. For example, test three videos, each at 10, 20, and 30 seconds, for nine altogether. As with video views, “drive conversions” ads are responsive.

Here are a couple of examples, below. The first is a skippable in-stream ad on computers, and the second is an in-feed video on phones.

Sample skippable in-stream ad on a computer. Image: Google.

In-feed video ad on a phone. Image: Google.

Ad Sequence

Perhaps the most interesting campaign subtype, ad sequence tells a story through a video series. Consumers must view a video before they can see the next. Google offers many sequences. The most common is “custom” (advertisers create their own sequence) and “automatic” (Google optimizes).

As with the other campaign subtypes, ad sequence audiences can be as general or as specific as necessary. Bidding is target cost-per-thousand-impressions (CPM) or maximum cost per view. Budgets are set with end dates. Ads can show only on YouTube for 7 or 30 days — viewers see an entire sequence just once during that time.

A sample sequence can include three videos, such as:

• First video: details a problem.
• Second video: shows how the product solves the problem.
• Third video: explains how to buy the product.

Videos can be “skippable,” “non-skippable,” or “bumper.” A bumper ad is six seconds or less. Non-skippable videos are seven to 15 seconds. Skippable videos are any length but can be skipped after five seconds. Advertisers should keep video lengths in mind when crafting a story.

The transition type from one video to the next depends on the bidding strategy. The options are “impression” (ad was shown to the viewer), “view” (viewer engaged or watched at least 30 seconds), or “skip” (viewer skipped the ad). “Impression” is the most common — anyone served the video will see the next one.

Regardless, a well-aligned sequence is critical.

How to Forecast PPC Costs and Revenue

I’m often asked to project pay-per-click costs and revenue. The task is challenging owing to variables such as historical data, trends, competitors, and, critically, unforeseen factors.

Nonetheless, here’s my approach.

Historical Data

Reviewing past data is my first step in assembling projections. The static numbers are helpful, but the real value is the trends. Say I’m projecting costs and revenue for the first six months of 2024. Here are example spend, revenue, and return on ad spend figures for the first six months of the previous three years.

Note the trends:

• Spend, revenue, and ROAS increase significantly from Q1 to Q2.
• Spend and revenue have generally increased each year.
• Spend and revenue tend to increase each month of Q2.

After reviewing these numbers, I’ll look at account activity to put them into context. Rising costs make sense for more campaigns and keywords — additional coverage requires more budget. Conversely, consistent campaigns and keywords could still result in higher costs per click. Google confirmed during its recent antitrust trial that it inflates CPCs.

Keyword Planner

Google’s Keyword Planner provides search volume and cost by keyword for the previous 12 and 24 months. For example, the keyword “roof racks” averaged 27,100 monthly searches last year. Searches slowed in the winter months, picked up in the summer, decreased in the fall, and rose heading into the holidays.

Searches for the keyword “roof racks” slowed in the winter months, picked up in the summer, decreased in the fall, and rose heading into the holidays.

The tool also estimates top-of-page bids, low and high. I look only at the high range since I presume costs will increase. For “roof racks,” the high top-of-page bid estimate is $3.22. Thus the monthly cost for that keyword is:

27,100 searches * $3.22 = $87,262

A monthly cost of $87,262 could be an entire ad budget, not just a single keyword! Luckily, the number is a mirage. It doesn’t consider bid strategy, conversion choices, and negative keywords.

A more accurate projection is in the “Forecast” section, which includes bid strategy and match type but not, notably, ROAS or cost-per-acquisition targets. Thus a “maximize conversions” bid strategy will show a higher cost without those targets.

Google’s “Forecast” uses historical search data, bid competition, traffic, and ad interactions. Here is the projection, below, for “roof racks” and related keywords with a maximize conversions bid strategy over the next year.

Google’s “Forecast” uses historical search data, bid competition, traffic, and ad interactions. This example is for the keyword “roof racks.”

Again, the numbers are estimates, an educated guess. A similar tool, “Performance Planner,” projects existing campaigns.

Final Plans

Having reviewed historical and forecast data, I can create the projections. I typically provide “mild” and “aggressive” options to help clients visualize potential revenue from a higher spend. I sometimes project in more detail, such as by account or initiative.

I’ll start with a conservative “mild” plan and focus closely on goals while accounting for likely higher costs.

Here’s an example. The client aims to increase monthly revenue by 10% while keeping target ROAS within 5% of 2023 performance. The January 2023 metrics were:

• Spend: $40,000
• Revenue: $83,000
• ROAS: 107.50%

A 10% revenue increase would be $91,300, and the ROAS can be no lower than 102.13% (5% less than 2023). A spend of $45,000 will yield a 102.89% ROAS:

($91,300 – $45,000) / $45,000 = 102.89%

Adding $5,000 to the January 2024 budget is a 12.5% increase over January 2023 — for a 10% revenue gain and a 4.29% lower ROAS. The projections presume CPC increases with a minimum (5%) ROAS loss.

The “aggressive” plan typically focuses on customer acquisition — additional revenue from higher spend — not ROAS. I’ll likely use Google’s projections, which are aggressive by default, combined with realistic adjustments, such as a client’s risk level and max budget.

Continuing the example, Google’s projections show a $60,000 spend in January 2024, a 50% increase from last year. Achieving a ROAS at least 96.76% (10% less than last year’s) would result in a 42.2% increase in revenue, to $118,056.

($118,056 – $60,000) / $60,000 = 96.76%

Forecasting costs and revenue from Google Ads is not an exact science considering all the variables. But it’s helpful to set goals and expectations for advertisers.

Google Ad Tactics for 2024

Big changes are coming in 2024 to paid search. Chief among those is Google’s deprecation of third-party cookies by Q3. Advertisers will need to rely on their own first-party data. Artificial intelligence will change the way advertisers manage accounts. AI is an effective tool that complements advertisers’ efforts and cannot be ignored.

A strategy of “the more data, the better” will dominate.

First-party Data

Recent data-privacy restrictions (such as Apple Mail removing tracking parameters) confirm the importance of advertisers collecting and using their data. Effective data collection begins with the Google tag (formally called the global site tag). When placed sitewide, this short JavaScript tag allows for custom configurations, such as capturing email addresses and other user-provided info. The data is hashed to maintain users’ privacy.

The second data-collection step is via Google Ads’ enhanced conversions at Tools and Settings > Conversions > Settings. There are three items to configure:

• “Customer data terms,”
• “Enhanced conversions for leads,”
• “Enhanced conversions.”

Accept “Customer data terms” to use enhanced conversions. Advertisers should set up enhanced conversions (through Google Tag Manager) so Google Ads can match user-provided data. For example, through enhanced conversions, Google can match a customer’s email or phone number as provided on the conversion event (checkout) page.

“Enhanced conversions for leads” is helpful to advertisers tracking offline sales.

Collect data via Google Ads’ enhanced conversions, with three items to configure.

Artificial Intelligence

AI is upending search engines. Google Ads has already incorporated AI into its admin interface, including:

• “Automatically created assets,”
• “Image generator,”
• “AI-powered insights.”

“Automatically created assets” are available in individual campaign settings. The feature allows Google to create headlines and descriptions based on landing pages, domains, and existing ads. Microsoft Ads also has a similar feature called “auto-generated assets.” Along with testing new messaging, ACAs help increase the ad strength score, which likely results in more impressions. Still, advertisers should monitor ACAs closely and remove them as needed, anytime.

The AI-powered “Image generator” helps Performance Max campaigns. From an ad description, Google can create relevant images. In the example below, the AI generator produced images of sporting goods equipment based on my description.

Separately, advertisers can create videos based on provided templates, text, and images. In my testing, video quality is poor and unacceptable to brands. But it will presumably improve over time.

From a description (on the left), Google Ads can create relevant images, such as sporting goods equipment in this example. Click image to enlarge.

More Data

Google’s machine learning is extremely powerful and effective, provided it can access enough data. For example, a Responsive Search Ad needs at least 2,000 impressions across 30 days to display a performance rating. Highly segmented campaigns with too many ad groups will never meet that threshold.

Here’s an example. Assume a campaign for winter jackets has two hypothetical structures. The first structure has five unique ad groups averaging 30,000 impressions each. The second has just one group, consisting of all keywords from the five, for 150,000 impressions.

The single ad group would not have “green” in the ad copy from a search of “green winter jackets,” but it would still include messaging about winter jackets. Google could optimize this single group better because it has more data.

Furthermore, match types are becoming less important. Phrase and broad match keywords can trigger queries that don’t contain the terms. An exact match can show non-exact variations of the keyword. User signals beyond keywords increasingly influence what ads show.

The bottom line: Google Ads works best when given enough autonomy to learn, which requires the correct data. Advertisers seeking on-site purchases should optimize campaigns for that specific conversion (purchases), not any other, such as a contact-us submission or email signup. Bid strategies are more accurate and truer with target CPA and target ROAS goals.

Google Ads Holiday Timesavers

The busy holiday-selling season is here. Now is the time for merchants to assemble ad copy and creative for the rest of the year.

The axiom “work smarter, not harder” is critical for the holiday season. Advertisers can easily spend time on menial tasks that won’t move the performance needle. Here are four timesavers to streamline the management of Google Ads.

Google Ads Editor

Merchants often run Google Ads promotions throughout Q4 with only minor changes to the copy. The ad below references a Black Friday sale. All copy except the headline is generic and suitable for other offers.

The body copy in this ad (“We Have All Sizes…”) is suitable for other offers. Image: Google. 

A headline of “Cyber Monday, Buy 2 Get 1 Free” could easily replace “Black Friday Sale – 20% Off – Fast Shipping & Easy Returns” with no other impact on the ad.

Google Ad Editor can implement the change in bulk. Under Editor’s “Edit” menu is the “Replace text” option. This feature can find and change text, such as a headline, across any number of ads in seconds.

The “Replace text” feature can find and change text, such as a headline, across any number of ads.

Alternatively, copy and paste the text to maintain separate reporting for each ad.

Editor can also add labels to organize entities by theme (such as “Holiday 2023”) or for holiday-specific keywords. Certainly advertisers can create and deploy labels directly in the Google Ads admin, but it’s much quicker in Editor.

Automated Rules

The most common use of automated rules is enabling and pausing ads. Instead of manually launching Black Friday ads at midnight and then pausing them 24 hours later, set automated rules.

In the Google Ads admin, filter by label, such as “Black Friday ads.” Check the ads and click “Edit” and “Create an automated rule.” The example below instructs Google to enable the selected ads one time on Nov. 24, 2023 (Black Friday) from 12 AM – 1 AM. A similar rule could pause those ads. Automated rules do not require labels, but I prefer them to streamline management and reporting.

Automated rules in the Google Ads admin can enable and pause ads, such as this example starting an ad on Nov. 24.

Adjusting manual bids (versus automated) is another common use of automated rules. An example is increasing bids by 25% at midnight each day from Thanksgiving through Cyber Monday. A separate rule could decrease bids by 25% afterward.

Assets

Ad extensions in googlespeak are now “assets.” Various copy assets can help drive holiday offers. A “promotion” asset is the most common. Place your offer in an additional line of text. It could be a percent or monetary discount and include a promo code and end date.

A promotion asset, such as this Black Friday sale, appears below the body copy.

As with automated rules, advertisers can easily enable and pause promotion assets. Price assets highlight discounts, such as the example below. By default, “from” appears before the price — “from $50.00.” Price assets can apply to a single product or an entire category, such as backpacks and insulated jackets.

Price assets can apply to a single product or an entire category, such as backpacks and insulated jackets.

Sitelinks and callouts appear below the ad copy and can highlight ongoing holiday promotions. Merchants often have a sale page throughout the holiday season containing discounted products. Though the ad copy can address the page, sitelinks take searchers to specific sale items and emphasize the offer. Similarly, callouts can reference general sitewide messaging such as “Free Shiping” or “Holiday Deals.”

Countdown Ads

The final task is a scheduled ad copy tactic in an automated rule: ads that count down to the end of an offer, from days to hours to minutes.

The counts can start anytime but generally work better when it’s near the deadline. Google defaults to five days. Countdown ads are an excellent way to drive urgency.

Countdown ads are an excellent way to drive urgency. Image: Google.

New ‘Search Themes’ Boost Performance Max Ads

A new audience targeting feature in Google Ads Performance Max campaigns could empower advertisers and improve performance.

The beta feature, “search themes,” began its rollout to select Google Ads accounts earlier this fall, with widespread availability on October 26, 2023.

Google’s automated Performance Max campaigns are the most recent evolution of the company’s advertising services.

Search themes bridge AI automation and human insights. Click image to enlarge. Source: Google.

Search Themes

Performance Max has relied on assets, feeds, and landing pages to predict optimal placements. However, with search themes, advertisers can now add custom information about their business.

Search themes inform Google’s AI about a business or customers that might not be immediately discernible. For instance, if a company’s landing page doesn’t fully detail a new product or service, search themes could help target the right audience.

Here is how search themes could work.

• Add search themes. Performance Max advertisers can now add 25 unique search themes per asset group. Advertisers originate their own custom themes, akin to keywords. Some themes, such as “kitchen” and “culinary,” might have the same audience.

• Prioritization in Search inventory. Search themes are equivalent to phrase match and broad match keywords in Search campaigns. However, exact-match keywords that align perfectly with search queries will still take precedence over search themes and other keywords.

• Enhanced control. Advertisers have tools such as brand exclusions to help control the types of search traffic suitable for Performance Max.

Beyond broadening reach, the feature also enhances precision. By combining human expertise with Google’s AI capabilities, advertisers (hopefully) ensure their ads are more relevant, leading to better performace.

Tools such as search themes underscore the importance of blending human insight with machine intelligence.

About Performance Max

At the heart of PMax is machine learning and automation. Google’s algorithms analyze many data points, from user behavior to market trends, to optimize ad placements dynamically. This ensures ads appear in front of the right audience at opportune moments.

Performance Max campaigns offer many advantages. A unified approach means advertisers have a consistent presence across all Google platforms, such as Search and YouTube, for example. This consistency, combined with the campaign’s dynamic optimization capabilities, helps ads align with conversion goals, such as brand awareness, lead generation, or sales.

Furthermore, the potential for increased reach cannot be overstated. With Performance Max, businesses can tap into new audience segments, drive more traffic, and achieve better sales outcomes.

PMax Search Themes

Performance Max campaigns have relied on a set approach — analyzing assets, feeds, and landing pages. This structure allowed Google’s AI to predict where and when to place ads for optimal engagement and conversion. However, the approach had limitations.

One was the dynamic nature of business, especially ecommerce. Assets might not reflect the most recent promotions, products, or market shifts, leading to missed opportunities from AI using outdated info.

Enter search themes. It acts as an additional data layer, allowing advertisers to supply their own insights, bridging the gap between PMax’s automation and advertisers’ realities.

For instance, consider a merchant introducing a new product line. Without “search themes,” Google’s AI might not immediately recognize the relevance of this new offering. Ditto for a retailer’s seasonal sale or a B2B seller entering a niche market segment. Search themes can pinpoint specific interests, ensuring ads resonate with the right demographic.

AI in Advertising

AI represents a seismic shift in digital advertising. Gone are the days of static campaigns and manual optimizations. Today, AI drives dynamic, responsive, and highly targeted ads — responding to market trends, user behaviors, and other data points.

Moreover, AI can streamline repetitive tasks. Marketers can delegate routine activities to algorithms, freeing time for strategy and decision-making.

Improved targeting and personalization are also outcomes of AI-driven marketing. Using vast data, algorithms can craft messages that resonate with individual users, enhancing engagement and conversions.

However, there’s a balance. While AI offers unparalleled efficiency and precision, the human touch remains irreplaceable. Marketers must leverage AI’s capabilities while retaining control, ensuring campaigns align with brand values and resonate authentically with audiences.

AI’s influence on advertising will surely dramatically increase. Tools such as Performance Max and features like search themes are the start. As technology advances, expect ever-more sophisticated and effective AI-driven ads, reshaping how brands connect with their audiences.

Value-based Bidding Drives Google Ads Success

Three years ago I addressed Google Ads bid strategies. The post described each strategy, including the pros and cons. Though some strategies remain, automated bidding has changed.

Automated bidding works best with values. Every conversion action, from a purchase to a form submission, should have a value. Google can optimize for conversions, but without a value those conversions may not be the most profitable for advertisers. For example, a purchase is presumably more valuable than an email signup. But a campaign optimizing for both could result in more signups than purchases.

Every campaign should target just one conversion point. For ecommerce, that tends to be purchases, though softer conversions such as signups aid top-of-funnel campaigns.

Regardless, designate the goal in the Google Ads campaign settings tab. For purchases, it’s “Revenue.”  No matter the bid strategy, Google will optimize to the desired goal.

To maximize purchases, set a campaign goal of “Revenue.” Click image to enlarge.

Setting Up Conversion Values

Conversion values in Google Ads are dynamic or static. Dynamic is best for purchases. It requires adjusted conversion codes to track each product’s ad costs and revenue. B2B advertisers often import offline conversion values as the sale process can be lengthy.

Dynamic values are best for maximizing purchases. Click image to enlarge.

The value of form submissions can be tiered — important conversions have higher hypothetical values, such as:

• Contact us: 60.
• Demo request: 40.
• Email signup: 20.

A “maximize conversion value” bid strategy will optimize value instead of volume. Traffic may be less because Google targets users likely to complete the higher value conversion.

Nonetheless, some advertisers prefer conversion volume to acquire top-of-funnel customers for repeat sales. Google’s “conversion value rules” allow advertisers to adjust values by audiences, locations, devices, and more.

Regardless, a bid strategy of “maximize conversion value” facilitates using “target return on ad spend” (tROAS). A tROAS bid strategy is the best way to optimize for profit instead of conversions or revenue.

Google defines tROAS as Conversion Value ÷ Spend. If revenue is $200 and ad spend is $100, the tROAS is 200%. Google’s formula differs from a common ROAS calculation of (Revenue – Cost) ÷ Cost.

Climbing the tROAS Ladder

Consider automated bidding as a ladder wherein each progressive step is more targeted.

• First step: Manual cost-per-click bidding without considering searchers’ signals. Inefficient.

• Second step: Enhanced CPC bidding with manual bids but allowing Google to adjust for likely conversions.

• Third step: Maximize conversion value bidding, where Google controls all bids based on the searchers likely to convert at a higher value.

• Fourth step: Maximize conversion value bidding with tROAS. Google controls all bidding based on the searchers likely to convert at a higher value and the advertiser’s desired return on ad spend.

The goal is to reach the top step for tROAS bidding. A tROAS portfolio bid strategy — i.e., for multiple campaigns — can chart performance over time.

Chart performance over time with tROAS portfolio bidding. Click image to enlarge.

Long-term Success

Keep conversion lags in mind for any bid strategy, including tROAS. If conversions generally take seven days from the first click to purchase, exclude the most recent seven days of data when evaluating the strategy.

In short, value-based bidding is the key to long-term Google Ads success. It provides advertisers and Google with a clear priority for each conversion.