Jul 25 2024
Charts: How CIOs View AI

Roughly one-third of U.S. chief information officers believe technology is the primary force behind their companies’ success and growth, according to EY’s “2024 CIO Sentiment Survey,” conducted in March 2024, which provides insights on how CIOs of leading organizations are addressing challenges in pursuing a growth agenda in the age of generative AI.

The respondents were 500 U.S.-based CIOs from various industries, including consumer products and retail, healthcare, life sciences, advanced manufacturing and mobility, tech media, and telecom.

According to the survey, when CIOs adopt a more ownership role in digital initiatives, they can lead to notable gains.

–

In addition, CIOs anticipate that data analytics (43%) and IT and cyber due diligence (41%) will improve the transaction process owing to the use of AI.

–

The data also shows that many CIOs still view generative AI as in the pilot or proof-of-concept phases.

–

Moreover, revenue generation is the primary motivation for over 37% of CIOs for using generative AI, while 27% point to the technology to reinvent their business model. Roughly 19% claim that cost reduction is the primary AI driver.

Ecommerce MGMT 0 Comments
Jul 18 2024
Charts: Outlook of Gen Zs and Millennials 2024

Roughly 30% of Gen Zs and Millennials believe the economic situation in their countries will improve over the next year.

That’s according to Deloitte’s “2024 Gen Z and Millennial Survey” (PDF), published in May. Deloitte surveyed 14,468 Gen Zs (teenagers to late 20s) and 8,373 Millennials (late 20s to mid-40s) across 44 countries to explore their attitudes about work and the world around them.

While the data shows just over 30% believe their overall national economy will improve, many more believe their personal financial situation will get better.

–

–

In addition, per the survey results, Gen Zs and Millennials are willing to take action on environmental issues.

–

Moreover, according to the data, frequent generative AI users across both cohorts are likely to think the technology will improve their work/life balance and positively impact their work.

Ecommerce MGMT 0 Comments
Jul 11 2024
Charts: Global Ecommerce Stats and Forecasts

There are roughly 26.2 million ecommerce websites worldwide. That’s according to BuiltWith, which tracks 2,500 ecommerce technologies and attributes, such as spend, revenue, employee count, social media count, industry, location, and rank.

Per BuiltWith, the U.S. has 13.3 million ecommerce sites, the most of any nation.

–

According to Statista, ecommerce produced approximately 19% of global retail sales in 2023 and will account for about 25% by 2027.

–

In addition, Statista estimates Turkey will experience the most retail ecommerce growth worldwide between 2024 and 2029, with a compound annual rate of 11.6%. Also, with growth rates exceeding 11%, India and Brazil rank among the ecommerce markets with the fastest expansion rates in the world.

–

Moreover, according to Statista, by  2029 retail ecommerce in the United States will produce $1.88 trillion in revenue, although the projected annual growth will slow from 30.2% in 2020 to 4.7% in 2029.

Ecommerce MGMT 0 Comments
Jun 26 2024
How To Develop Great Data Studies – The 5R2 Roadmap To Great Data Story via @sejournal, @InsightNarrator

This edited extract is from Data Storytelling in Marketing by Caroline Florence ©2024 and is reproduced and adapted with permission from Kogan Page Ltd.

Part One of this book outlined the need for data storytelling, the benefits of data storytelling for the marketing function, and the prac­tical barriers that can get in the way of creating a great data story.

Part Two answers the question: ‘What do I need to do to create a great data story in practice?

The 5R2 roadmap has five key stages with expected outcomes, each supported by three practical steps.

Screenshot from datastorytellinginmarketing.com/toolkit, June 2024

Make It RELEVANT

A relevant data story must focus on the audience’s knowledge levels, needs and preferences and should include:

  • A clear premise that will generate a transformation in the hearts and minds of the audience.
  • A clear understanding of the context aligned to the audience’s needs.
  • A focused story that answers the killer question for the audience.

A relevant story requires strategic thinking skills to outline the story plan.

There are several benefits to this stage, including:

  • The opportunity to gain early input, collaboration and co-creation to feed into your story development.
  • A clear sense of purpose to keep your story development on track.
  • A chance to get nearer to right first time, thus saving significant iteration time at the later stages of your story development.

Make It ROBUST

A robust data story must stand up to scrutiny and should include:

  • A solid interpretation drawn from a range of reliable data sources.
  • A data-driven argument and recommendation based on accurate and up to date information.
  • An insightful point of view providing the audience with a ‘So what?’ and ‘Now what?’

A robust story requires strong analysis skills to surface and discover the key insights.

There are several benefits to this stage, including:

  • The opportunity to uncover new insights and ideas, rather than predictable findings.
  • A chance to draw out richer, nuanced insights that can give depth to your data story.
  • A sense of confidence in the credibility of your interpretation and recommendations.

Make It REFINED

A refined data story must provide a clear and compelling narrative and should include:

  • A story resolution that is synthesized and distilled into a key message.
  • A stress-tested story resolution that can drive real decisions and actions.
  • A compelling structure that makes it easy to follow the argument.

A refined story requires critical thinking skills to build a data story that is easy to follow and engage with.

There are several benefits to this stage, including:

  • The chance to pinpoint the specific ask the data story needs to get across to the audience.
  • A sense of confidence that your data story offers the audience solutions that are both commercially viable and practically feasible.
  • The opportunity to focus your audience on decisions needed or actions required, rather than all of their energy being used to understand the insights.

Make It RELATABLE

A relatable data story needs to enrich the insight message with an emotional connection and should include:

  • An empathetic understanding of the humans involved in the data story.
  • A personalized approach that speaks to the specific target audiences’ hearts and minds.
  • An engaging story flow that draws the audience in.

A relatable story requires emotional intelligence to create a story grounded in real life and enriched by human experience.

There are several benefits to this stage, including:

  • The increased likelihood of cutting through and resonating with the audience.
  • The chance to influence real results and meaningful outcomes.
  • A sense of confidence in your ability to integrate data, logic and emotion in your data storytelling.

Make It REMARKABLE

A remarkable data story must cut through the noise, land the message and provide a catalyst for action and should include:

  • An easy-to-follow and accessible data story presentation.
  • A range of digestible micro-content that appeals to a wide range of audience needs.
  • A storytelling delivery that is provocative and stimulates reflection and debate.

A remarkable story requires creative thinking and flair to execute a story that will stand out from the crowd and drive action.

There are several benefits to this stage, including:

  • The ability to keep a distracted audience’s attention.
  • The opportunity to drive further interest in your data story.
  • The chance to disrupt the status quo and move beyond default thinking.

To read the full book, SEJ readers have an exclusive 25% discount code and free shipping to the US and UK. Use promo code SEJ25 at koganpage.com here.

More resources: 

Featured Image: Visual Generation/Shutterstock

Ecommerce MGMT 0 Comments
Jun 19 2024
The Impact Of AI And Other Innovations On Data Storytelling via @sejournal, @InsightNarrator

This edited extract is from Data Storytelling in Marketing by Caroline Florence ©2024 and is reproduced and adapted with permission from Kogan Page Ltd.

Storytelling is an integral part of the human experience. People have been communicating observations and data to each other for millen­nia using the same principles of persuasion that are being used today.

However, the means by which we can generate data and insights and tell stories has shifted significantly and will continue to do so, as tech­nology plays an ever-greater role in our ability to collect, process, and find meaning from the wealth of information available.

So, what is the future of data storytelling?

I think we’ve all talked about data being the engine that powers business decision-making. And there’s no escaping the role that AI and data are going to play in the future.

So, I think the more data literate and aware you are, the more informed and evidence-led you can be about our decisions, regardless of what field you are in – because that is the future we’re all working towards and going to embrace, right?

It’s about relevance and being at the forefront of cutting-edge technology.

Sanica Menezes, Head of Customer Analytics, Aviva

The Near Future Scenario

Imagine simply applying a generative AI tool to your marketing data dashboards to create audience-ready copy. The tool creates a clear narrative structure, synthesized from the relevant datasets, with actionable and insightful messages relevant to the target audience.

The tool isn’t just producing vague and generic output with question­able accuracy but is sophisticated enough to help you co-author technically robust and compelling content that integrates a level of human insight.

Writing stories from vast and complex datasets will not only drive efficiency and save time, but free up the human co-author to think more creatively about how they deliver the end story to land the message, gain traction with recommendations and influence decisions and actions.

There is still a clear role for the human to play as co-author, including the quality of the prompts given, expert interpretation, nuance of language, and customization for key audiences.

But the human co-author is no longer bogged down by the complex and time-consuming process of gathering different data sources and analysing data for insights. The human co-author can focus on synthesizing findings to make sense of patterns or trends and perfect their insight, judgement, and communication.

In my conversations with expert contributors, the consensus was that AI would have a significant impact on data storytelling but would never replace the need for human intervention.

This vision for the future of storytelling is (almost) here. Tools like this already exist and are being further improved, enhanced, and rolled out to market as I write this book.

But the reality is that the skills involved in leveraging these tools are no different from the skills needed to currently build, create, and deliver great data stories. If anything, the risks involved in not having human co-authors means acquiring the skills covered in this book become even more valuable.

In the AI storytelling exercise WINconducted, the tool came up with “80 per cent of people are healthy” as its key point. Well, it’s just not an interesting fact.

Whereas the humans looking at the same data were able to see a trend of increasing stress, which is far more interesting as a story. AI could analyse the data in seconds, but my feeling is that it needs a lot of really good prompting in order for it to seriously help with the storytelling bit.

I’m much more positive about it being able to create 100 slides for me from the data and that may make it easier for me to pick out what the story is.

Richard Colwell, CEO, Red C Research & Marketing Group

We did a recent experiment with the Inspirient AI platform taking a big, big, big dataset, and in three minutes, it was able to produce 1,000 slides with decent titles and design.

Then you can ask it a question about anything, and it can produce 110 slides, 30 slides, whatever you want. So, there is no reason why people should be wasting time on the data in that way.

AI is going to make a massive difference – and then we bring in the human skill which is contextualization, storytelling, thinking about the impact and the relevance to the strategy and all that stuff the computer is never going to be able to do.

Lucy Davison, Founder And CEO, Keen As Mustard Marketing

Other Innovations Impacting On Data Storytelling

Besides AI, there are a number of other key trends that are likely to have an impact on our approach to data storytelling in the future:

Synthetic Data

Synthetic data is data that has been created artificially through computer simulation to take the place of real-world data. Whilst already used in many data models to supplement real-world data or when real-world data is not available, the incidence of synthetic data is likely to grow in the near future.

According to Gartner (2023), by 2024, 60 per cent of the data used in training AI models will be synthetically generated.

Speaking in Marketing Week (2023), Mark Ritson cites around 90 per cent accuracy for AI-derived consumer data, when triangulated with data generated from primary human sources, in academic studies to date.

This means that it has a huge potential to help create data stories to inform strategies and plans.

Virtual And Augmented Reality

Virtual and augmented reality will enable us to generate more immersive and interactive experiences as part of our data storytelling. Audiences will be able to step into the story world, interact with the data, and influence the narrative outcomes.

This technology is already being used in the world of entertainment to blur the lines between traditional linear television and interactive video games, creating a new form of content consumption.

Within data storytelling we can easily imagine a world with simulated customer conversations, whilst navigating the website or retail environment.

Instead of static visualizations and charts showing data, the audience will be able to overlay data onto their physical environment and embed data from different sources accessed at the touch of a button.

Transmedia Storytelling

Transmedia storytelling will continue to evolve, with narratives spanning multiple platforms and media. Data storytellers will be expected to create interconnected storylines across different media and channels, enabling audiences to engage with the data story in different ways.

We are already seeing these tools being used in data journalism where embedded audio and video, on-the-ground eyewitness content, live-data feeds, data visualization and photography sit alongside more traditional editorial commentary and narrative storytelling.

For a great example of this in practice, look at the Pulitzer Prize-winning “Snow fall: The avalanche at Tunnel Creek (Branch, 2012)” that changed the way The New York Times approached data storytelling.

In the marketing world, some teams are already investing in high-end knowledge share portals or embedding tools alongside their intranet and internet to bring multiple media together in one place to tell the data story.

User-Generated Content

User-generated content will also have a greater influence on data storytelling. With the rise of social media and online communities, audiences will actively participate in creating and sharing stories.

Platforms will emerge that enable collaboration between storytellers and audiences, allowing for the co-creation of narratives and fostering a sense of community around storytelling.

Tailoring narratives to the individual audience member based on their preferences, and even their emotional state, will lead to greater expectations of customization in data storytelling to enhance engagement and impact.

Moving beyond the traditional “You said, so we did” communication with customers to demonstrate how their feedback has been actioned, user-generated content will enable customers to play a more central role in sharing their experiences and expectations

These advanced tools are a complement to, and not a substitution for, the human creativity and critical thinking that great data storytelling requires. If used appropriately, they can enhance your data storytelling, but they cannot do it for you.

Whether you work with Microsoft Excel or access reports from more sophisticated business intelligence tools, such as Microsoft Power BI, Tableau, Looker Studio, or Qlik, you will still need to take those outputs and use your skills as a data storyteller to curate them in ways that are useful for your end audi­ence.

There are some great knowledge-sharing platforms out there that can integrate outputs from existing data storytelling tools and help curate content in one place. Some can be built into existing plat­forms that might be accessible within your business, like Confluence.

Some can be custom-built using external tools for a bespoke need, such as creating a micro-site for your data story using WordPress. And some can be brought in at scale to integrate with existing Microsoft or Google tools.

The list of what is available is extensive but will typically be dependent on what is available IT-wise within your own organization.

The Continuing Role Of The Human In Data Storytelling

In this evolving world, the role of the data storyteller doesn’t disap­pear but becomes ever more critical.

The human data storyteller still has many important roles to still play, and the skills necessary to influence and engage cynical, discerning, and overwhelmed audiences become even more valuable.

Now that white papers, marketing copy, internal presentations, and digital content can all be generated faster than humans could ever manage on their own, the risk of informa­tion overload becomes inevitable without a skilled storyteller to curate the content.

Today, the human data storyteller is crucial for:

  • Ensuring we are not telling “any old story” just because we can and that the story is relevant to the business context and needs.
  • Understanding the inputs being used by the tool, including limitations and potential bias, as well as ensuring data is used ethically and that it is accurate, reliable, and obtained with the appropriate permissions.
  • Framing queries appropriately in the right way to incorporate the relevant context, issues, and target audience needs to inform the knowledge base.
  • Cross-referencing and synthesizing AI-generated insights or synthetic data with human expertise and subject domain knowledge to ensure the relevance and accuracy of recommendations.
  • Leveraging the different VR, AR, and transmedia tools available to ensure the right one for the job.

To read the full book, SEJ readers have an exclusive 25% discount code and free shipping to the US and UK. Use promo code SEJ25 at koganpage.com here.

More resources: 

Featured Image: PopTika/Shutterstock

Ecommerce MGMT 0 Comments
May 31 2024
Charts: Global Consumer Trends Q1 2024

Nearly half of global consumers (46%) have increased their consumption of climate-sustainable products, while an overwhelming number (85%) have experienced the disruptive effects of climate change. That’s according to PwC’s annual “Voice of the Consumer Survey,” titled this year “Shrinking the consumer trust deficit.”

In January and February 2024, PwC surveyed 20,662 consumers across 31 countries and territories. The respondents were at least 18 years old and were asked about a range of topics relating to shopping behaviors, emerging technology, and social media.

—

Per the survey, worldwide shoppers have trust concerns with the social media industry, questioning its safety and reliability.

–

In addition, 83% of respondents state that safeguarding their personal data is critical to a company’s ability to earn their trust.

–

Moreover, consumers seek personal connections when discovering new brands and products. According to the survey, 55% of respondents prefer visiting physical stores and interacting with salespeople, compared to 49% who rely on recommendations from family and friends and 46% who opt for online browsing.

Ecommerce MGMT 0 Comments
May 23 2024
Charts: U.S. Retail Ecommerce Sales Q1 2024

Every calendar quarter the U.S. Department of Commerce releases total domestic retail sales and ecommerce only. Newly published figures for Q1 2024 (PDF) show total retail sales of $1.820 billion (a slight decrease over Q4 2023) and ecommerce-only retail sales of $289 billion, a growth of 2.1% over the prior quarter.

According to the DoC, ecommerce sales are for “goods and services where the buyer places an order (or the price and terms of the sale are negotiated) over an Internet, mobile device, extranet, electronic data interchange network, electronic mail, or other comparable online system. Payment may or may not be made online.”

Ecommerce accounted for 15.9% of total U.S. retail sales in Q1 2024, up slightly from 15.6% in the prior quarter.

–

The DoC reports U.S. ecommerce retail sales in Q1 2024 grew by 8.6% compared to Q1 2023, while total quarterly retail sales experienced a 1.5% annual rise over the same period last year.

Ecommerce MGMT 0 Comments
May 21 2024
7 Ways AI Took My Job [To The Next Level] via @sejournal, @CallRail

With AI-powered call attribution, you can gain valuable insights into which channels are driving the most conversions.

How Call Attribution Works

  • Step 1: Assign – Select unique call tracking numbers to assign to each campaign or listing.
  • Step 2: Track – Potential customers see your ad or listing and call the associated phone number.
  • Step 3: Forward –The calls ring directly into your main business phone, regardless of which number they use.
  • Step 4: Analyze – Because they used one of your tracking numbers, you instantly know which ad or campaign inspired them to call.

With AI-powered call tracking, gone are the days of wondering how your digital marketing efforts are tied to high-value inbound calls.

For agencies, this helps prove the real value of your services and extend the life of your client relationships.

2. AI Can Help You Save Time On Manually Reviewing Calls

Listening to and analyzing phone calls manually can be time-consuming and inefficient for agencies.

However, it’s an important part of understanding the customer experience and sales team performance.

With AI-powered call analysis tools, you get quality, keyword-tagged transcriptions with near-human-level accuracy.

Not only can this technology help you save over 50% of the time spent listening to phone calls, but it can also help you deliver actionable recommendations to clients and drive better results.

Conversation Intelligence, for instance, is trained on over 1.1M hours of voice data and enables real-time analysis for instantaneous results.

This advanced tool provides opportunities for you to improve your strategy through the following granular insights:

  • Spotting disparities in the industry-specific lingo your sales team uses, compared to the lingo your prospects are using to describe their business challenges and goals.
  • Identifying trends or gaps in your service offerings based on what your prospects are asking for.
  • Identifying frequently asked questions and other important topics to address through content marketing.
  • Setting goals for lead qualification — not just the quantity of leads generated for your business.

Conversational AI is perfectly suited to summarize the content of long conversations – however, the call summaries still require a human to read them and determine the main takeaways.

But if you work in a bustling small business, it’s unlikely you’d have the bandwidth for tasks such as call transcription, summaries, keyword spotting, or trend analysis.

Rather than displacing human labor, conversational AI is assisting businesses in taking on tasks that may have been overlooked and leveraging data that would otherwise remain untapped.

3. AI Can Help You Lower Cost Per Lead / Save Money On Tools & Ad Spend

Ever wonder why certain campaigns take off while others fall flat? It’s all in the data!

Even failed campaigns can offer invaluable insights into your client’s audience and messaging.

But if you can’t spot the underperformers quickly enough, you risk wasting your ad budget on ineffective tactics.

The quicker you can identify what’s working and what’s not, the quicker you can pivot and adjust your marketing strategy.

With AI-powered tools, agencies can access instant insights that enable them to reduce wasteful spending and improve overall campaign efficiency.

How To Deliver More Value With AI

  • Make a bigger impact in less time: AI-powered technology creates a force multiplier within your agency, allowing you to make more of an impact with the same level of inputs you’re already using.
  • Unlock actionable insights from call data: AI is revolutionizing the way companies leverage call data by enabling them to gain insights at scale. As a result, businesses can increase their ROI and deliver greater value to their clients by analyzing hundreds of calls efficiently.
  • Foster alignment with data-driven strategies: By analyzing customer conversations with AI, businesses can align their marketing strategy with data-driven recommendations, enhancing overall coherence. Additionally, the ability to create triggers based on specific phrases enables automated analysis and reporting, further streamlining the alignment process.
  • Drive effectiveness with rapid insights: Leveraging Conversation Intelligence enables agencies to deliver better insights faster, increase conversion rates, refine keyword strategies, and develop robust reporting capabilities.

With the right AI-powered tools, you can access the insights you need to ensure maximum ROI for your clients.

4. AI Can Help You Improve Overall Agency Efficiency

Are you spending too much valuable time on tasks that produce minimal results?

Many agencies find themselves bogged down by routine, administrative tasks that don’t contribute much to their bottom line.

But with AI automation, agencies can streamline their operations and redirect their energy towards more strategic endeavors.

From email scheduling and social media posting to data entry and report generation, AI can handle a wide array of tasks with precision and efficiency – giving you time to focus on high-impact activities that drive growth and deliver tangible results.

Ways Your Business Can Benefit From Automation

  1. Automatically transcribe your calls to boost close rates: See how your team is handling difficult objections and ensure that they’re delivering your businessʼ value proposition in an effective manner.
  2. Score calls based on quality and opportunity: Take the time-consuming work out of scoring your calls and determine which campaigns drive the best calls to your business.
  3. Classify calls by your set criteria: Qualify, score, tag, or assign a value to the leads that meet your criteria, automatically.
  4. Automatically redact sensitive information: Protect your customers by removing billing or personal information. Keep your data safe and secure through complete HIPAA compliance.
  5. Monitor your teamsʼ performance: Use Conversation Intelligence as a valuable sales training tool to ensure your team doesn’t miss any key messaging marks.
  6. Know your customersʼ needs: Identify conversation trends in your phone calls and stay privy to evolving customer needs.
  7. Improve your digital marketing strategy: Use AI-powered insights to inform your digital marketing strategy and boost your online presence.

By automating mundane tasks, agencies can optimize workflows, increase productivity, and improve efficiency across the board.

Looking for 5 – 7? Download The Full Guide

Rather than fearing AI, the future belongs to those who embrace it.

By strategically combining human creativity with artificial intelligence, you can unlock capabilities that transcend what either could achieve alone.

Want to discover even more ways to level up your agency with AI?

Get the full guide here.

Ecommerce MGMT 0 Comments
May 16 2024
What Is Conversion Rate & How Do You Calculate It? via @sejournal, @coreydmorris

Conversion rate is one of the most common metrics used by marketers, sales folks, and business professionals.

It is discussed often and taken on the surface as an important metric or key performance indicator (KPI) for most businesses.

However, it can also be misapplied, misunderstood, or improperly established for use as a key metric.

It is important to revisit conversions, conversion rates, and the use of the metric periodically.

It is even more important for any new initiative to have the metric well defined and understood before positioning it as a key KPI.

In this guide, I’m going to dive deeply into what conversion rate is, how to calculate it, why that’s important, and ways to improve it.

What Is Conversion Rate?

Google provides one of the more concise definitions of conversion rate:

“Conversion rates are calculated by simply taking the number of conversions and dividing that by the number of total ad interactions that can be tracked to a conversion during the same time period.”

Now, let’s get into what it all means.

Conversions

Unlike some business and marketing metrics, understanding conversion rates require some self-definition.

It starts with defining what a conversion is – which can mean different things for varying types of brands and organizations.

You can have more than one type of conversion. As a goal, you can have it factored into a marketing funnel or customer journey. Or, it could be a firm financial metric your business hinges on.

Step one is to clearly define what a conversion is for you.

One of the most common definitions I see relates to someone becoming a lead for a business that is focused on driving leads via its website.

Another applies to ecommerce businesses, where the conversion is the completed sale transaction.

Other common definitions include certain engagement metrics for businesses that rely on ad revenue generated by page views.

Secondary types of conversions get into events, engagement, and other things like email signups that help support funnels, customer journeys, and overall sales processes.

Conversion Rate

Conversion rate is a %.

In high-level terms, it tells you the % of how many people came to your site who took the conversion goal action you defined.

Some sources provide benchmarks for specific industries or areas to help you understand a good conversion rate and offer some objectivity.

I’m not telling you to copy your competitors, but I think if you want to value conversion rate, you need internal and external research to validate where you stand and where you want to be.

Match this up with your persona research, target audiences, marketing funnels, and customer journeys.

You likely know what you want your site visitors and audience to do.

How many of them do you want to do it? How big is the universe of your target audience? What is realistic regarding the number of total visitors you think you can get?

Find answers to these questions along with mapping out your conversion goals and conversion rate goals.

How Do You Calculate Conversion Rate?

Conversion Rate Formula

The formula to calculate the conversion rate is straightforward:

Conversions / Visits* = Conversion Rate

*I have to include an asterisk, though, as some definitions might not be as straightforward.

You could also call these “clicks” or “sessions” or look at them more granularly.

My definition here can be adapted based on the language and definitions used by your analytics platform and your other KPIs.

An example in calculating conversion rate for my site (a marketing agency providing services to clients) with the inputs and calculation:

  • August 2022 website visits: 1,122.
  • August 2022 contact form submissions (my conversions): 61.
  • 61 conversions/1,122 visits = 5.4% conversion rate.

Getting It Right

Again, conversions are custom-defined by you.

It can be a common conversion goal like a lead form submission, something more secondary, or something more obscure.

That part can be somewhat custom or variable for you as well.

You can look at it as clicks to a website from a specific channel or ad campaign.

You can get really granular with the segmentation of your data, source and channel filtering, and even with the definitions themselves.

That becomes especially variable or custom if you’re tracking specific actions that lead up to a conversion goal and how granular you want to be with it.

Make sure the definition of what you’re counting as a conversion and what you’re counting as the total audience (clicks, visits, or some other “total” metric) is mapped out in a meaningful way.

Why Do I Need To Be Able To Calculate Conversion Rate?

First, where do you measure and track conversion rate? You can use Google Analytics, other analytics suites, or any data you must manually calculate.

Google Analytics

If you’re relying on Google Analytics (GA), you’ll want to ensure you have your “Goals” set up properly and test them. Conversions are reported based on the goals you configure.

Out of the box, Google has no context as to what a conversion is for you and no ability to calculate a conversion rate off of it.

If you use GA, dive into conversion goal configuration and testing to ensure things are in a good place before you trust the metrics you see (if you inherited the setup) or move forward with any measurement and improvement plan.

And, speaking of mapping out – tracking and measurement are critical.

You want to ensure that your tech stack and tools can help you properly track visits, conversions, and the overall conversion rate in alignment with your definitions and goals.

Getting this right is critical, whether it is Google Analytics or third-party reporting tools.

Segmentation & Filtering

Plus, you’re able to then segment at the levels you want to with examples, including:

  • By conversion type (if you have more than one).
  • All website traffic.
  • By source or channel.
  • By pages/actions/events in the session.
  • By campaign or initiative.

There are many more segments and ways to filter and slice up conversions and conversion rate reporting.

You want to be able to calculate the conversion rate and get into the details with segments of traffic and your audience to help understand where you can improve.

What Is a Good Conversion Rate?

Calculating conversion rates and having the data is one thing; using it to make improvements is where the real work starts.

Improving Conversion Rates

You can look for improvement in two broad areas, and I strongly recommend evaluating both.

One is sources of traffic and the influences that drive visitors to your site.

That includes advertising, referrals, and any awareness activities and campaigns you have that generate traffic.

The other area consists of what influences the traffic that has already arrived at the site – things like UX/UI evaluation, review of messaging, calls to action, and ways that users navigate through and engage with the site.

Improvement in this arena is often called Conversion Rate Optimization or CRO.

Traffic Sources Optimization

In the case of the traffic you’re sending to the site, you can look at targeting, ad creative, and keywords you’re organically ranking for – the ways that ad targeting and creative provide the first impression or directly funnel traffic into the site.

There are a variety of optimization and refinement tactics to shift your focus to higher quality traffic and aim to increase conversion rate by getting more qualified visitors from external sources that you influence.

Beware, though, that you need to have a good idea of your customer journey and not knock out traffic that is awareness focused or at the top of the funnel (e.g., traffic tied to thought leadership).

Increasing the conversion rate is important, but make sure you segment well enough to not inadvertently stop targeting the top of the funnel, awareness-level visitors, and sources.

Conversion Rate Optimization

Now, onto looking inward at the traffic you already have.

This is where most people start digging into CRO tactics. Web analytics can help you see where people exit, bounce, and stop short of getting to your conversion actions.

Beyond that, great heat mapping and CRO tools will give you insights into UX and UI issues and how people truly engage with your site versus how you intended in your design.

By focusing on CRO and putting a strategy into place, you can evaluate everything from site speed to content, messaging, and UI.

I strongly encourage you to do so.

Conclusion

Conversion rate continues to be a valuable marketing metric.

Understanding it, defining it for your organization, measuring it, and improving it are all important.

Whether you have a small business or enterprise-level website, you likely care about specific conversion goals.

In short – for conversions and conversion rate – understand, define, measure, and improve it.

Yes, we all want more traffic. And maybe a static conversion rate is fine if you add more traffic.

However, wouldn’t you like more traffic and a higher conversion rate?

It is possible to have both, and crucial to understanding what levers to pull to influence it.

More resources: 

Featured Image: eamesBot/Shutterstock

FAQ

What is the significance of conversion rate in online marketing?

Conversion rate is a crucial metric for assessing the effectiveness of online marketing strategies. It represents the percentage of visitors who complete a desired action, such as making a purchase or signing up for a newsletter. Understanding this rate helps businesses evaluate the success of their marketing efforts and identify areas for improvement. Accurate measurement and analysis of conversion rates can lead to better targeting of marketing campaigns, improved user experiences, and increased return on investment (ROI).

What are some effective strategies for improving conversion rates?

Improving conversion rates involves optimizing both the sources of traffic and the user experience on your site. Key strategies include:

  • Refining ad targeting and creative to attract more qualified traffic.
  • Enhancing site usability and navigation to make it easier for visitors to complete desired actions.
  • Testing and updating calls to action (CTAs) to ensure they are compelling and clear.
  • Employing A/B testing to compare different versions of landing pages and identify the most effective design and messaging.
  • Using analytics and heat mapping tools to gain insights into user behavior and address any barriers to conversion.

Why is it important to periodically revisit and redefine conversion metrics?

Periodically revisiting and redefining conversion metrics is essential to ensure they remain aligned with evolving business objectives and market conditions. As your business grows and changes, the definitions of conversions and the goals associated with them may need adjustments. Regularly updating these metrics helps maintain their relevance and ensures that your marketing strategies continue to drive meaningful results. This practice also allows for the incorporation of new insights and technologies, keeping your approach current and effective.

Ecommerce MGMT 0 Comments
Apr 25 2024
Google Universal Analytics 360 Sunsetting Soon: Migration Tips & Top Alternative Inside via @sejournal, @PiwikPro

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

This year, Google will finally phase out Universal Analytics 360, requiring paid users to switch to Google Analytics 360.

This is not something you can skip or postpone, and the clock is ticking.

The new analytics differ significantly from the previous version, and you can’t migrate data between them, so the transition can be challenging for organizations.

Since you’ll be starting from scratch, now is a good time to explore other options and determine if there are better solutions for your needs.

The three main areas to consider when deciding if you want to stay with Google or move to another platform are: the migration process, privacy and compliance, and ease of use.

When Is Google Universal Analytics 360 Sunsetting?

July 1, 2024 is when Google will phase out Universal Analytics 360.

What Should I Do Next?

Google encourages you to migrate to Google Analytics 360 as quickly as possible.

If you don’t, you could:

  • Lose critical advertising capabilities.
  • Lose the ability to export historical data.
  • Face delays in setting up Google Analytics 360.

    How To Migrate To Your Next Analytics Platform

    Moving to a new platform is much more than just implementation; it is vital to plan your migration properly. Below are five steps to help you through the entire process.

    Step 1. Evaluate Your Stack & Resources

    Before you switch analytics tools, take the time to evaluate your entire stack, not just the tool you’re changing. Ensure that your stack is up-to-date and meets your current business needs. Migrating to a new analytics vendor almost always requires more people and more time than originally estimated. It’s a good occasion to remove redundant tools from your stack; it might also allow you to integrate with new ones that can help you run your analytics and collect data more comprehensively.

    Step 2. Tidy Your Data

    Over time, data collection may get messy, and you find yourself tracking data that isn’t relevant to your business. A migration gives you a chance to clean up your data taxonomy. Ensure that your new tool allows you to use the same categories of data as the previous one. Pay close attention to any data that needs to be collected automatically, like location data (country, region, city), and device details (device type, browser). Finally, make sure the SDKs you need are supported by your new tool.

    Step 3. Implement A New Platform

    This step involves setting up the tracking code that collects data about visitors to your website or app and making any necessary modifications. Remember to set up tags to gather more detailed data through events or connect third-party tools.

    Speed Up The Transition: If you switch to Piwik PRO, you can use a migration tool to easily transfer your settings from Universal Analytics (GA3) and Google Tag Manager.

    Step 4. Evaluate Tour New Data

    Once you’re done implementing your new platform, you should run it parallel to your existing tool for a few months before finalizing the migration. During this time, you can audit your new data and correct any errors. In this manner, you can retain your historical data while simultaneously generating new data segments on the new platform.

    Step 5. Provide Training For Your Team

    All end users need training to comprehend the platform’s operations, retrieve necessary data, and generate reports. This step is frequently missed as it falls at the end of the project.

    Upon finishing this step, you will be set to switch to your new platform fully. If you find the migration process challenging, consider getting help from outside sources. Some analytics vendors offer hands-on onboarding and user training, which accelerates product adoption.

    Is Switching To Google Analytics 360 Worth The Hassle?

    You might be thinking, “Migrating to the successor of UA 360 won’t be a walk in the park,” especially if you work for a large organization.

    In addition to subscription and data migration costs, you may also need to train your staff or increase fees for external marketing agencies that will face new challenges.

    While Analytics 360 has incredible use cases, there may be other tools that better suit your needs.

    Switching to alternative solutions may be a good option for you.

    How To Pick A Replacement For Universal Analytics 360

    To decide whether to choose a new platform or stick with Google, consider a few important factors:

    1. Because GA 360 is a different software, your marketing and analytics departments will need to allocate extra resources to learn the new platform. You will also need the support of analysts, developers, and data architects to help you reconstruct reports based on the data architecture of the chosen platform. Choosing a solution with similar features and user experience to UA 360 can be a good option, because it saves resources, making onboarding faster and easier.
    2. You will also need to redesign your entire customer journey, because the data model in GA360 has changed from sessions to events. This process can be more challenging and costly than choosing a session-based platform or one that offers you freedom of choice.
    3. Another important consideration is the level of support offered by the vendor. This can greatly affect the quality of the migration and onboarding to a new platform. Although Google Analytics is currently the most popular tool for analyzing web traffic, the level of support it provides is limited. Other companies like Piwik PRO can offer more in this area, including personalized onboarding, product implementation, training, and dedicated customer support at every step.

    Consideration 1: Think About Privacy & Compliance

    Organizations around the world are increasingly concerned with data privacy and compliance. A 2023 Thomson survey found that 80% of business professionals acknowledge the importance of compliance as a crucial advisory function for their organizations. Gartner, on the other hand, predicts that, by 2025, 60% of large enterprises will use at least one privacy-enhancing computing (PEC) technique in analytics, business intelligence, and/or cloud computing.

    This is due to a growing number of new regulations that place greater control over personal data at the forefront. The EU’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) are two of the most prominent examples. The landscape has been further complicated by events such as the Schrems II case, Brexit, and China’s Personal Data Protection Law. Data protection is also increasingly important in some sectors, such as healthcare, where regulations like HIPAA are mandatory.

    If your company operates globally or has ambitions to do so, the first thing to consider is who has full ownership of the data, where the servers hosting the data are located, and who owns them. Google Analytics 360 only offers cloud deployment in an unknown location, which means that data might be transferred between data centers in the Americas, Europe, and Asia. This makes it difficult to know exactly where the data is stored and ownership is unclear. For now, the issue of data transfers between the US and the EU has been resolved by the EU-US Privacy Shield framework agreement, but the future stays unclear. Last year, NOYB, led by Max Schrems, announced that it would soon appeal this decision to the Court of Justice of the European Union (CJEU).

    To meet privacy and compliance requirements in different countries and industries, choose a platform that allows you to customize your hosting plan and set specific parameters for data collection and analysis. Platforms like Piwik PRO Analytics Suite enable you to store your data on servers in Europe, the US, and Asia, based on your preferences. This translates into flexibility and security of your data.

    Consideration 2: Ease Of Use & Integration

    This may sound counterintuitive, but the new GA 360 might be too complex for many. While it offers numerous advanced functions for data analysts, it lacks features specifically designed for marketers. As a result, marketers may need help in configuring the system to efficiently use the data.

    On the other hand, in GA 360, the data model shifts from session-based to event-based. This is especially important if your teams depend on UA 360 behavioral reporting, benchmarking, and e-commerce flow reports, as these features are unavailable in the new release. You also need to revise all the reports for all the stakeholders.

    Conversely, Piwik PRO strongly emphasizes simplicity and enables marketers to quickly access the necessary data. Additionally, the data model combines both session-based and event-based structures. This approach ensures that you can start working with the data faster and deliver the reports that stakeholders are used to. Another big advantage of Piwik PRO is its model for working with raw data, which is a valuable source of knowledge about users and provides richer reporting in more contexts. Google Analytics does not provide raw data exports, so you have to use various services and tools to accomplish this. To be fair, however, exporting large raw data packets with Piwik PRO software may take longer than with Google solutions.

    The new GA 360 is most effective when used mainly with products from the Google ecosystem. When considering data activation, Google Ads is the most suitable option. When it comes to Piwik PRO, you still have this option, but integrating with other solutions is much easier. The platform offers four modules: Analytics, Tag Manager, Consent Manager and Customer Data Platform (CDP). The CDP module, available in the paid plan, lets you create detailed customer profiles and categorize your data into various audience segments. You can activate them to provide a personalized experience and run effective campaigns across multiple channels.

    The landscape of modern analytics is constantly changing. On the one hand, there are ongoing discussions about privacy and compliance regulations, while on the other, companies are trying out various methods to collect and analyze data. In the end, your choice of analytics platform will impact the performance of your marketing and sales efforts. So take the time to explore, and you may find other solutions that better suit your organization’s needs.

    Piwik PRO is a solid choice to explore for your next primary analytics solution. Book a personalized demo of the Enterprise version and see the benefits of introducing Piwik PRO Analytics Suite in your organization.

    REQUEST A DEMO

    Image Credits

    Featured Image: Image by Piwik PRO Used with permission.

    Ecommerce MGMT 0 Comments