The pandemic has profoundly changed how consumers behave, at least for now. Extended work from home, fewer shopping trips, less travel and increased online buying are the norms, resulting in dramatically different behaviors than we saw at the start of the year.
Brands and agencies have needed to shift their audience strategies, in some cases building new models to ensure that their targeting capabilities are up to date with the latest behavioral trends.
An unexpected wave of unemployment, following years of job creation, can wreak havoc on audiences. A consumer who had been gainfully employed may now be under- or unemployed, having a difficult time making their mortgage, and altering their normal purchasing patterns and other behaviors, such as savings.
Change needs to occur, in both the audience solutions, as well as marketers’ perceptions of “audiences.”
While building new models or expanding a data strategy isn’t hard, assembling the foundational components can be complicated and/or time consuming.
Many brands’ CRM data is still not as clean and accessible as possible, which creates challenges and slows down the targeting process. In an era where things change by the day, lost time equals lost customers.
For years, audience-based ad planning was rooted in what worked in past campaigns and what didn’t, and then optimizing toward the most successful outcomes.
Given the massive upheaval in consumer life, it would be insane for marketers to expect the same results from the audience products they’ve used over the past several years, as well as the same behaviors from the consumers within the audiences.
The current situation requires advertisers to actively participate in keeping their CRM data clean and accessible – laying the critical foundation to rebuild their audience models and solutions.
Whether it’s layering second- or third-party data, or harnessing machine-learning or a hand-crafted model, they need to collaborate to find a combination of behaviors that reflect what is happening right now with their target consumers.
The need to understand audiences much faster has made brands’ own first-party data more important than it has perhaps ever been.
While accruing data is easy for most brands, passing that data along to an agency or audience partner can prove to be a challenge. These organizations are the ones that need to rebuild models and deliver audiences that more accurately reflect the current, ever-changing buying cycles. The best way to do this is through the fast, clean sharing of data.
Getting the data from the advertiser can be the bottleneck that prevents quick, accurate audience models from getting built. This has sped up considerably on the digital side, but it still lags behind in traditional media.
The complicating factor is often the many feeds of data that brands supply. Arriving from different sources and in different formats, they don’t all necessarily combine easily, creating more work for the agency or vendor who is modeling the data. For some, it’s a seamless process, but for others, it can be a discordant mess.
The major advances in audience-based advertising should have enticed brands to make their data as clean as possible.
But for many, they viewed this more as a long-term project or a “nice to have.” That’s no longer the case – brands that want to stay vital and survive this pandemic and beyond are living on borrowed time if their data isn’t cleaned up and maintained.
Brands that want to serve existing customers better and grow their businesses during the pandemic should focus on cleaning up their first-party data, ensuring they can pass it along easily and maintain a customer informed edge. It will speed insight, change and let them get their messages to the right people faster.
As President & CEO, JoAnne Monfradi Dunn is the architect of Alliant’s vision to deliver innovative audience targeting solutions powered by the aggregated purchase transactions of multiple direct-to-consumer marketers. Today Alliant innovates by aggregating online and offline consumer behaviors and applying machine learning to generate optimized audiences and consumer insights for U.S. multichannel marketers.
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