How Can We Use AI To Measure Performance Marketing Results More Accurately?

This is article #3 in a series aimed at helping marketing leaders understand and maximize the AI opportunities in Performance Marketing.

●  Article #1: From Hype to Impact: Quantify the AI Opportunity in Performance Marketing

●  Article #2: How Can We Leverage First-party Data and AI to Help Us Acquire New, Loyal, and Profitable Customers?

It may seem counterintuitive, but the limitations imposed by GDPR, CCPA, and iOS 14 have expedited positive change in broken measurement systems. 

Data privacy regulations have forced marketers –some kicking and screaming, others with great gusto–to move away from click-based attribution models that have failed to show true incrementality. 

As it’s no longer feasible to track user-level data, multi-touch (MTA) and last-click attribution are becoming extinct. 

While these models provided valuable insights into the customer journey and allocated credit to different marketing touchpoints, they have had their limitations. 

The main problem is that MTA and last-click attribution tend to assign too much value to converter channels with low new customer percentages and low incremental value to the business, such as PPC Brand. 

Now, performance marketers are adopting an aggregate view of how channels or campaigns affect outcomes.  

Rather than analyzing which user clicked which ad at what time before they converted– we must think more holistically: What is happening at a channel or campaign level? 

Measuring outcomes with Media Mix Modelling (MMM) and incrementality are two such approaches that enable marketers to value how much ads are driving conversions–without needing to know the user-level path to purchase.

Why Last-click Attribution Can Lead to Misdistributed Ad Spend  

Relying on conversion data from the last-click attribution could lead you to under-invest in introducer channels while over-investing in converter channels, despite their relative insignificance in generating sales.

Over time, this misdistribution of ad spend towards converter channels may decrease the percentage of new customers and the overall number of orders. How? When existing customers churn, if you aren’t actively seeking out new customers, those who could have been potential buyers start to purchase from competitors. This can lead to an overall reduction in your customer base.

Incrementality Tests Show: “Did This Ad Campaign Cause Any Conversions?”

On the other hand, measuring the incremental value of each channel using AI can offer a more accurate and actionable understanding of the impact of your marketing activities.  

Unlike MTA, incrementality measurement pinpoints causality, seeking to answer the question, “Did this ad campaign cause any conversions?” Using AI tools to measure the impact of new customers per channel can help businesses identify areas where they can cut waste and uncover opportunities for expansion and growth. 

For example, you can run incrementality tests on Google’s PMax to take a baseline before activating first-party data, then measure the incremental lift after data activation.  

Here’s an Example 

When assessing attribution, it’s essential to consider the incremental value of each channel, especially in the case of PPC Brand ads. 

These ads often have low incremental value, especially if they face minimal competition, resulting in a free, organic result following the brand ad’s appearance in the top search position. If brand ads were to disappear, over 90% of users would click on the organic result, leading to conversions while saving ad budget.  

This raises the question: Why allocate resources to this channel if brand ads don’t contribute significantly to revenue? On the other hand, certain channels exhibit a spillover effect, as demonstrated in the attribution example mentioned earlier.  

Without the initial non-brand ad, the subsequent brand conversion would not have occurred, making the incremental value to the business greater than the revenue initially attributed to the channel. 

Uncover the True ROI of Performance Marketing

You must be 100% certain that you set up your advertising strategy to maximize profitability. And this means using AI to measure the incremental value of each channel to audit current performance and unlock growth opportunities. 

Over the last 13 years, we’ve analyzed millions of dollars in marketing spend to unlock growth opportunities for our retail clients. 

We frequently see retailers leaving money on the table… sometimes to the tune of 30M. 

Our Marketing Opportunity Audit is designed to: 

  • Uncover True ROI
    • Analyze the current profitability of paid media channels, looking at factors including incrementality, eCommerce (contribution) margins, and CLV.
  • Unlock Hidden Profit/ROI Lift
    • Break down your growth potential with three key levers: data activation, operational improvements, and budget reallocation.
  • Action New Insights with a Profitability Plan
    • Get a prioritized roadmap to maximize your paid media investment, from short-term quick-wins to longer-term strategic improvements

In three weeks and for less than a half-day’s advertising spend, you could have the insights you need to unlock the next level of growth in 2023. Up for a no-strings chat to learn more about our Marketing Opportunity Audit? 

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