Robert Keith, a Pillsbury marketing executive first outlined the shift towards customer-centered marketing in his article “The Marketing Revolution.” Learn what the consumer wants; create advertising copy that captures their attention; and success will come, he said.

As Keith wrote this in 1959, we can be sure he was thinking surveys to determine consumer wants, not digital audiences and insights. Yet, few marketers today would debate the importance of consumer focus. Indeed, today’s walled gardens have built a competitive advantage in their understanding of customers not just at a macro level, but at the individual level. Product recommendations, as well as search and social-media ads, are all predicated on knowing the interests and desires of the individual.

Your own walled garden

In today’s hyper-competitive world where Amazon, Google, and the like wield considerable advantage, it’s worth rethinking how best to deploy Keith’s wisdom. Companies with vast troves of consumer level insights in their walled gardens can leverage them to drive results for their business and their clients. While every other consumer focused business tries to grow their own first party datasets, these insights require a boost, beyond first party data, to deliver broad campaign reach and significant business impact.

Proxies such as demographics and psychographics can help drive reach, but at the cost of watering down your laser focused campaigns.

The Rise of Transaction-based Audiences

Few words in the marketing profession have seen their meaning change as much as “audience.” Once an audience was understood as something broad and connected by a viewing behavior: the people who watched Monday Night Football versus those who watched General Hospital.

But today, massive amounts of data from in-person and online purchases — powered by artificial intelligence — allow for the creation of highly targeted audiences built on actual transactions.

For example, Verisk Financial’s Commerce Signals company builds audiences based upon credit and debit transactions made with Visa and Mastercard from 40 million households! Even more powerful is that, Commerce Signals unique consumer wallet view unites spend across all cards in an anonymized consumer’s wallet.

Commerce Signals applies artificial-intelligence modeling against that data using more than 600 demographics and psychographics categories.

The result is that these transaction-based audiences predict spend with 90% accuracy. That allows a marketer to target and measure a digital marketing campaign with even more precision than the tech giants who own walled gardens.

Transaction-based audiences are built on what members of the audience actually did with their money. That’s considerably more accurate than the contextual, behavioral, and demographic data typically found in a data management platform.

Transaction based audiences fit a broad spectrum of use cases, for example, want to market to consumers who haven’t been to your store since the pandemic began but who have shifted to an online rival? Want to understand customer loyalty? Propensity to price shop? All of that and more is possible through transaction based custom audiences.

And all of the power of transaction-based audiences are available now in the LiveRamp Data Marketplace. There’s no need for new dashboards, new products, or a months-long onboarding process with a new martech vendor before you can market to a transaction-based audience. Everything you need is already available.

Making a choice

If you’re considering transaction-based audiences, there are three, key areas to look at:

The accuracy of the underlying data: The results gained from transaction-based audiences are only as good as the data used. To ensure accuracy Commerce Signals uses raw, anonymized transaction data from 40 million U.S. households. These consumer-level card spending details are pulled from the most-recognized and trusted partner banks and their processors, such as Visa and Mastercard.

The potential reach: As with most audience data, the larger the reach the stronger the impact the data will have on your results. Commerce Signals takes a small seed data file and then runs proprietary AI models on a full dataset of 162 million consumers to ensure a large, accurate reach. Then those results are backtested on historicals from their data to confirm reach accuracy.

The impact: The bottom line is that better data yields better results. Commerce Signals’ 90 percent accuracy means that applying transaction-based audiences to a digital marketing campaign leads to impactful results that vastly improve ROI and achieve a dramatic reduction in wasted spend.

Reaching the consumers that you need for your business to succeed is now easier than ever, but it relies on accurate data involving a large number of your specific audiences. Transaction-based audiences make that possible for all marketers.

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