Retooling Research to Properly Measure the Short and Long-Term Effects of Advertising

Retooling Research to Properly Measure the Short and Long-Term Effects of Advertising
Retooling Research to Properly Measure the Short and Long-Term Effects of Advertising

All CMOs who I have spoken with agree that a big issue they constantly grapple with is how to balance their investment in short-term performance marketing versus brand-building.

But this is a blog for researchers, analytics, and data science so let me bring this around: When analysts report campaign tracking results from surveys and sales lift analyses as if they are two ways to measure the same thing – is the campaign working? Actually, they are conflating two very different effects that mostly come from two distinct populations of consumers.

Consider a long purchase cycle category: New vehicles. At any point in time, actives (currently shopping for a new vehicle) are, say, 5% of the population of those who drive, with the remaining 95% being dormants (not currently shopping). Ignoring some impulse purchasing, all of your short-term sales lift will come from the 5% of the population who are active.

So, note the disconnect: Nearly 100% of MTA or marketing mix results are driven by the 5% who are actively shopping; while in contrast, 95% of survey results are driven by dormants whose purchases will occur some time in the future, perhaps years away.

Fixing the disconnect in campaign trackers

Basically, trackers are usually mis-designed to look at the 95% who are dormant to explain why you are seeing ad effects from the 5% who are active! I recommend to those who manage trackers (brand or campaign) to get some behavioral and shopper thinking into your tracker.

Boost the sample for those who are actively shopping and measure the effect on brand favorability among those who are active versus dormant. By so doing, new and powerful metrics emerge – ones that are more likely to show movement and be predictive, such as winnable journeys and win rates (of winnable journeys). A winnable journey occurs when a consumer is shopping in a category (the journey) and where your brand is under consideration. Win rate is the degree to which you get the prize versus other brands being considered. If either metric is growing, you are certain to grow sales, and so these are not only brand metrics, they are sales predictors (changing your tracker from retrospective to future-focused).

The idea of winnable journeys brings together the two perspectives of brand preference with shopper intention.

Another benefit – now movement in attribute ratings and other softer brand metrics might make sense relative to sales movement. Look for attitude shift among actives. (And I bet you’ll see more movement too because the 5% who are active will find your advertising more relevant and worth paying attention to!)

Use this metric of winnable journeys to bring together a survey and behavioral perspective from your various tracking sources. You can calculate winnable journeys and win rates from digital behavior tracking. Which IDs exhibit any shopping interest in the category? Which exhibit any interest in your brand? Which IDs ultimately convert?

Now, what about the 95% who are dormant? What do survey results from that segment tell us? That is where the long-term effects of advertising mostly reside. If you do create improvement in brand perceptions from dormants, when they shop, this preference should carry over into advantage as their own shopper journeys begin. However, we don’t really know the rate at which advertising affects dormants or how that translates into future annuities. To what extent does initiation of the journey occur while the brand perception change caused by ad is remembered?  This will be studied by the MMA under my thought leadership.

If the balance between performance versus brand marketing is the most important question to CMOs, you should retool to become the most important source of insights for this most important question.

Header Image: John Jackson, Unsplash

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