Is your ad really contributing to sales? Exploring the limits of attribution and the true value of incrementality

Does this ad really drive sales?

Have you ever had this question in your daily reports or meetings? Even though you have all the numbers, graphs, and materials, you still feel like you can't understand it. What is the true nature of that feeling?

Many companies and marketers tend to fall into this "illusion" of "thinking they are correctly evaluating results." Behind this lie two important concepts in measuring marketing effectiveness:"Attribution"と"Incrementality"There is confusion.

Contribution"Allocation"Attribution and measures“Net increase effect”These two are similar but not the same, and understanding the difference between them is the first step to making essential decisions based on data and building a "winning organization."

In this article, we will clarify the difference between these two concepts and explain their essence in an in-depth and easy-to-understand manner.

"Attribution": The idea of ​​"allocating" contributions

AttributionLiterally, it means "attribution" or "allocation." In the marketing world, it refers to the concept or method of "evaluating how much each ad or channel contributed to a conversion (result) and allocating that contribution."

For example, in a soccer match, it may be easier to understand if you think of it as not just recording who scored the goal (conversion), but also evaluating the entire sequence of events, such as "who made the final assist" and "who made the pass before that."

What attribution analysis can tell you

The most common and familiar model for most marketers is "last click" attribution, which assigns all credit to the ad clicked immediately before the conversion. Because it's simple and easy to understand, it's the standard for most online advertising reporting.

There are also various other analytical models, such as "first click," which evaluates the first ad that a user interacts with, and "linear," which allocates credit equally to all interactions.

The Limitations and Pitfalls of Attribution Analysis

Attribution analysis is extremely effective in visualizing the customer journey that leads to conversion.

However, attribution analysis is ultimately a discussion of "how to allocate the contribution of results that have already occurred to past touchpoints." What is often overlooked here is the idea of ​​"would those results not have occurred if that touchpoint (advertising) had not occurred in the first place?"

For example, if a customer who was originally a fan of the brand and had decided to buy a certain product on their next payday happens to see a retargeting ad just before making the purchase and then clicks on it, the last-click model would attribute 100% of this result to the retargeting ad. However, there is a pitfall in that the customer would likely have purchased the product even without the ad.

In this way, when attribution analysis relies too heavily on simple models, especially last-click models, it can lead to overvaluing measures that reach customers who already have a high intent to purchase, known as "harvesting," and overlooking the value of measures that build brand awareness and favorability over time (such as television commercials and magazine ads).

"Incrementality": A perspective of measuring "net incremental effect"

The concept of "incrementality" was born from an awareness of the challenges that this type of attribution faces.

IncrementalityThis is a concept that measures the "pure increase in results (= net increase effect)" when a certain marketing measure is implemented compared to when it is not implemented.

In the soccer example mentioned earlier, this would be a perspective to examine, "Did the addition of a star player to the team really increase the number of goals scored by the team as a whole?" Incrementality seeks to determine not only the number of goals scored by the player (attribution), but also the "net incremental effect" of whether his presence has enabled the other players to perform better and raised the overall performance of the team.

Why is the "net effect" important?

For example, let's say a local supermarket puts out a sale flyer and the store is extremely busy during the sale period. What the store manager really wants to know is, "How many new customers came to the store after seeing the flyer?" and "How much sales were made from customers who would not have come to the store if the flyer had not been there?"

Perhaps most of the customers were regulars who would shop every week even without the flyer. In that case, the net increase in sales from the flyer was low, and it would not have been worth cutting into profits to hold a sale.

In this way, measuring incrementality allows you to objectively determine whether a measure is truly contributing to business growth. This allows you to obtain more fundamental insights, such as "That measure has a high yield rate, but it hasn't actually led to a net increase in sales," or "This branding measure, whose effects are not apparent at first glance, is actually building a long-term customer base and generating stable sales."

What is the crucial difference between attribution and incrementality?

Let's clarify the differences between the two.

Neither of these two is absolutely correct, but rather they are methods that should be used according to their respective purposes. It is best to think of attribution as contributing more strongly to "tactical optimization" and incrementality as contributing more strongly to "strategic decision-making."

The important thing is to understand the limitations of attribution, be aware of incrementality from a broader perspective, and use the two in a complementary manner.

However, in reality, there are many cases where these differences in perspective are not fully understood, and effectiveness measurements and judgments that rely solely on attribution analysis become the "standard for discussing results" within organizations. As a result, an "illusion of results" that differs from reality is created, leading to incorrect decision-making.

In the next chapter, we'll look at what the "illusion of results" is, how it affects organizations, and why now is the time for marketing leaders to confront this challenge.

Why Marketing Managers Should Break Away from the "Illusion of Results"

If organizations rely solely on attribution metrics without considering incrementality, they face a serious problem called the "illusion of results."

For example, many marketing managers at fast-moving consumer goods (FMCG) manufacturers who use only attribution struggle to prove the sales contribution of television commercials or large-scale in-store promotions, because attribution reports tend to give higher marks to online advertising, which has a lower CPA and produces more immediate results.

"Illusion of results" refers to a situation where the reported results of advertising actually include results that would have occurred even without the advertising. This results in a vicious cycle like the one below.

1. Overconfidence:We determine that the ROAS of harvesting ads is high and will concentrate our budget on them.
2. Stagnation:However, this only cuts off people who were planning to buy at some point, and does not increase the number of new customers, slowing down the growth of the business as a whole.
3. Doubts:Management and other departments have become concerned about the marketing department, asking, "Why isn't overall sales increasing despite all that investment in advertising?"
4. Stray:Those on the front lines explain that "the attribution shows that it's effective," but in the end, in addition to branding measures, even harvesting-type advertising is subject to cuts, resulting in a reduction in overall marketing activities and further worsening the situation.

In this way, when attribution metrics are the only basis for evaluation without taking into account incrementality, it creates a serious sense of distrust and a loop of confusion within the organization.

Why is this discussion important now?

The limitations of attribution and the importance of incrementality have been debated for some time, but why is this debate now going beyond mere differences in analytical methods to become a topic that has a major impact on corporate marketing activities?

The background to this isTighter regulation of third-party cookiesThere is a global trend toward privacy protection, as exemplified by the recent trend toward privacy protection. Conventional attribution methods, which involve tracking individual users across devices and allocating credit for a given result based on their behavioral history, are becoming technically and ethically difficult to implement.

This suggests the limitations of an approach that tracks the behavior of individual users at "points." Therefore, going forward, effectiveness measurement will need to move away from relying on tracking individual users and instead adopt the concept of incrementality, which provides a holistic and integrated understanding of how much net increase in results has been achieved through advertising and measures.

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Summary

Finally, let's summarize the main points of this article.

• Attribution is a concept that evaluates how much each contact point or measure contributed to the "results" and allocates the degree of contribution.
• Incrementality is a concept that measures the "pure increase" (= net increase effect) in results when a certain measure is implemented compared to when the measure is not implemented.
• Attribution is effective for short-term tactical evaluation, but relying on it too much risks making fundamental investment decisions.
• When marketing and business managers adopt an incrementality perspective, organizations can evolve from partial optimization to holistic optimization, building a foundation for sustainable growth.

To achieve sustainable growth, it is essential to share the perspective of incrementality across the entire organization. This requires a shift in perspective from simply looking at the results of individual measures, such as "which ads were clicked," to asking, "Which investments have truly grown our business?"

First, reassess your company's effectiveness measurement and marketing investment practices, and share with the entire organization a perspective that properly evaluates "net incremental effect" rather than simply "allocating contribution." This should be the first step toward achieving sustainable growth.

Other helpful related articles

• What is the optimal attribution model? Comparing the mechanisms of the representative analysis methods MMM and MTA
• What is MMM? An explanation of the basics, analysis procedures, and implementation points of Marketing Mix Modeling.