• Aaron Fetters

Marketers, Want More Budget? Get Your Data Right

Have you ever met a marketer who didn't wish to have more budget with which to work? I haven't, nor would I expect any of you to have. Perhaps the linkage between a marketer's budget and the quality of data they employ is not at first directly obvious, but I believe it is something to consider carefully.


At the end of October, Truthset, in partnership with Sequent Partners, completed research on behalf of the ANA AIMM (Alliance for Inclusive and Multicultural Marketing). AIMM asked us to perform an examination of the coverage and accuracy of multicultural attributes attached to consumer data within today's marketing data ecosystem. You can view a recording of our webinar discussing the results of this study here. With enthusiastic participation from leading data providers including Acxiom, Throtle, Bridge, V12, Speedeon Data, and Webbula, we were able to benchmark how well data assets available to marketers represent various ethnicities within the US such as Hispanic, African American, Asian American, and White. Overall, what we found is when one considers accuracy and coverage together, less than half of US multicultural consumers are "visible" in today's data assets. In fact, relative to the % of the population they make up, only around 25% of African Americans and Asian Americans are accurately represented in online data assets.


Now, these results got me reflecting back on multicultural marketing initiatives from my time inside both P&G and Kellogg's. I recall many occasions when those on the consumer research side would rightly point out the disparity between what was happening with consumers and where marketing budgets were being placed. Specifically, US Hispanics had represented the fastest-growing segment of consumers for several years in a row and today are over 18% of the total US population. However, brands struggled to allocate more than 10% of their marketing budgets toward multicultural initiatives. In fact, just this past month Jill Kelly, Chief Marketing Officer at GroupM, stated at AdAge's Town Hall on Multicultural Marketing,"If we are not doing multicultural marketing today, we are not marketing for our future or to our future. The population transformation in America today is demanding a new majority marketing readiness. …how do we fight for more funding? My response to that is, 'the business case is really in the numbers'."


And there it is; the business case is really in the numbers. One of the primary reasons for this disconnect between consumer dynamics and marketing investment was the results from previous campaigns in the form of Market Mix Models (MMM), Multi-Touch Attribution (MTA) models, or general sales lift studies. These results very often appeared poor in relation to general market campaigns and other advertising tactics. But guess what? Data quality actually influences this outcome in two big ways.


First is the more obvious impact on results due to data quality - the ability for a marketer to effectively and efficiently reach their desired target audience. When brands construct a multicultural campaign, they do so based on powerful cultural insights. From the language, images, messaging, even color palettes, every aspect of a campaign is chosen based on insights into the intended audience. Now imagine all the media investment spent to deliver that well constructed creative and messaging reaches the intended audience less than half the time! This is exactly the case today, as indicated by our data "visibility" (coverage and accuracy combined) research and campaign measurement results we currently see from working with specific brands. By all measures, this is less than ideal from an effectiveness and efficiency standpoint and is part of the reason results may look poor.

The second impact of data quality on campaign results may be a bit more surprising, but it takes shape through the efficacy of the models themselves. MMMs, MTAs, and other sales lift studies all attempt to not only measure the total impact of advertising campaigns but to attribute the impact to specific things - e.g., media types, media properties, regions, types of retail, and importantly - consumer segments. The models typically rely on data attributes when attributing outcomes to a particular consumer, either individually or as part of a larger segment. But we have already established, with the data available multicultural consumers are less than "half-visible". Quite simply, the overall quality of data, or lack thereof, can have a clear and direct impact on how well modeled results reflect the reality of a campaign's effectiveness, particularly within a specific segment of consumers such as US Hispanics. Carlos Santiago and I will discuss more on this at the ARF Attribution and Analytics Accelerator 2020 on Nov 17 at 12:30 pm EST. Join us if you can.


So let's add it up. Based on compelling consumer and market insights, you are given a budget to market to a particular segment of consumers. You do a fantastic job of planning and constructing your campaign. When you go to execute, you are limited in your efficiency of delivering your campaign to the intended segment due to data quality. Weeks, months, or even years later, you measure the effectiveness of your campaign. Despite the delivery limitations, the campaign did indeed have a positive impact on the brand. Yet, the measurement models' ability to correctly attribute that impact to your specific campaign, targeted to a specific audience is further hindered due to data quality. The net result is that it appears the budget handed to you for this effort delivered a lower ROI than typical; implication - no growth in the budget next year. It may sound a bit dramatic, but this is very often the reality facing marketers today.

While the above discussion is centered around multicultural data, the impact of data quality applies much more broadly. The same challenges to effective media placement and accurate attribution caused by poor data quality are felt in any type of addressable marketing, not just multicultural initiatives. But there is a way to get the data right. With Truthset's ability to measure data accuracy at the record level, marketers can now analyze, improve, and measure their data-driven spend on a record-by-record basis. That is giving brands a new level of insight, accountability, and control over their marketing spend - and much-needed transparency and accountability for the marketing supply chain. Ultimately, through accuracy comes growth. Growth of confidence in the data driving today's marketing ecosystems and growth in the investments marketers can make, knowing the results will reflect the very real impact of their campaigns. So, want more budgets for marketing? Let's get the data right!



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