Most marketers think that they do not need to advertise to their best customers. No upside, already heavy buyers, etc. Evidence suggests that this is wrong and, in fact, your best customers should be your top priority for receiving additional media weight.  Conversely, most non-buyers are your worst target, having little or no interest in the brand, and you should reduce wasted advertising to them.

Here is the supporting evidence…insights that most marketers haven’t discovered about their best customers (and worst prospects).

比较好的付费ssr节点*, who does receipt scanning, graciously shared a database with me that contained 15 months of sales data on a frequently bought frozen foods category. I broke up the data into 3 5-month time periods, and divided consumers into heavy, medium, light (1/3/, 1/3, 1/3) and non-buyers within each period.  I closely studied one of the leading mature brands (“G”), and here is what I found.

1.Heavy brand buyers are your best customers in terms of future sales while non-buyers tend to contribute very little.

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• Non-buyers generated one-tenth the average future sales rate of heavy buyers. Even when non-buyers became buyers, their average rate of sales was that of light buyers.
• Heavy buyers also contribute about 20 times as many repeat purchases of the brand vs. non-buyers, per capita, and repeat purchases are much more important than one off switch-in purchases to sustaining market share.  That is because, mathematically, the number one driver of market share is repeat rate (switch/repeat matrix can predict market shares for all brands with r=.98…happy to discuss the math).

2. Heavy brand buyers still offer huge upside potential and should not be taken for granted

• Despite their value, the upside is huge. Brand G’s own heavy buyers were buying other brands more than they buy brand G…with brand G only winning a 40% share of wallet.
• Period to period retention of heavy buyers was not a given…only about 45% were retained as heavy buyers and about 30% did not even buy the brand in the next period.

3. When buyers lapse, they are your best target for efficient customer acquisition

The conundrum for marketers is that while non-buyers (period 1) are not worth as much individually to period 3 sales, they are worth as much collectively because there are so many more of them. So how can a marketer go after non-buyers smartly?

• I broke up non-buyers in period 2 into lapsed buyers (bought in period1 but not 2) vs. confirmed non-buyer groups (non-buyers two periods in a row).  Lapsed buyers were 13% of period 2 non-buyers but contributed 60% of brand G sales from period 2 non-buyers.
• Bottom line: lookalikes for buyers, obviously including lapsed buyers, should be your primary target within non-buyers.

4. Heavy brand buyers are much more responsive to advertising

Let’s reprise learning from my Persuadables white paper. We know that advertising to heavy brand buyers (defined by prior 12 months of data) is massively profitable, as they respond up to 16 times greater to advertising vs. non-buyers.  And now we know why. Heavy buyers offer enormous upside for your brand and advertising to them unlocks this potential. This pattern only exists because brand preferences have persistence.

5. Heaviness of category buying is persistent

One argument for untargeted mass marketing is that heaviness of CATEGORY buying (part of the brand “heaviness of buying” equation) is unpredictable (heavy buyers become light, etc.) That is clearly not the case in the Persuadables or Numerator data sets. From Numerator we see that only 20% of heavy category buyers become light or non-buyers in the next period. Another way to look at it is that only 10% of current period heavy buyers came from prior period non-buyers. Conclusion: heaviness of category buying is a persistent consumer characteristic.

What should marketers do differently?

Knowing brand and category buying patterns tend to be persistent, it suggests target marketing. I’d advise marketers to test a new strategy. Reduce reliance on mass marketing that is demographically driven and redeploy to achieve heavier media weights against heavy brand buyers, moderates, light, and lapsed brand buyers, in that order. Based on the evidence, this should result in considerably higher ROAS (return on ad spending) and sustained higher market share.

What’s next?

I am continuing to analyze Numerator data, across brands and across categories to ensure these patterns are generalizable. Via an MMA initiative, I am working on additional insights and simulations. I will share findings and my resulting theory of brand growth as part of the Great Marketing Growth Debate program offered by the MMA (with the support of technical advisor, Neustar). My presentation slot is October 14. You can register for the whole series here.

* Numerator is a data and tech company serving the market research space. Headquartered in Chicago, IL, Numerator has 1,600 employees worldwide. The company blends proprietary data with advanced technology to create unique insights for the market research industry that has been slow to change. The majority of Fortune 100 companies are Numerator clients.