‘More doesn't mean better’ – enterprise data strategies to solve measurement changes
“What good is data if you can't use it fast enough to make decisions?” A recent webinar saw experts at Intel, Twitter, Wunderman Thompson and Claravine discuss the critical data strategies they're deploying to solve today's pressing measurement challenges and queue up lasting success.
Brands face pressing challenges in data privacy and measurement
Entire industries had to transform into a predominantly digital space during the pandemic, creating an avalanche of new data for organizations ill-equipped to handle it. How best then to re-prioritize data and develop strategies to navigate that volume, in the context of new privacy and measurement issues?
These were among the questions tackled by The Drum in a webinar with Claravine, entitled ‘Enterprise data strategies to solve measurement changes’. The Drum’s Webb Wright was joined by Chris Comstock, chief product officer, Claravine; Casie Jordan, senior director of professional services and partnerships, Twitter; Radhika Marini, director of data management, Intel; and David Butt, data consulting director, Wunderman Thompson, to explore strategies with measurable financial benefits.
Privacy and measurement challenges
Brands face pressing challenges in data privacy and measurement. Government regulations like GDPR in Europe and CCPA in California have put privacy settings more into the hands of consumers. App stores and browsers are taking a tougher approach to consumer privacy management to ensure users opt-in to personalized advertising – vital to marketers.
“This disrupts the behind-the-scenes mechanics of almost all kinds of digital ads, especially those that confirm an action, a purchase, or a download,” Jordan claimed. “It's a major attribution problem.” Meanwhile, marketers just want to answer a basic question: is my digital advertising working?
With further changes to privacy laws afoot, Butt contended that brands would feel “more pressure” in compliance, data collection and management. He said: “The challenge for brands is how do you create more trust (with consumers), but at the same time get the right data when various rules are limiting (that) ability?”
Collaborative data management
Comstock claimed adtech had long over-relied on cookies and explored how enforced change affected measurement: “When you move to aggregate data, how do you understand what went into that aggregation before it gets aggregated?”
Marini focused on “consent management” and the need to evolve new first-party data strategies as brands go from being cookie-based data management platforms to customer database platforms: “Taxonomy and metadata management are critical and start to move the reliance away from cookies.”
Comstock argued that transformation “takes culture change”. “For 20 years, we've said that if we saw someone do something, we can trust that they're engaged, they saw an ad. That was based on user ID use.” How do we trust that aggregate data is driving revenue?
This, in turn, forces organizational restructure, added Marini: “We're no longer thinking about channel by channel or keeping data strategy within a different team.”
Brand and agency data alignment
Butt added that data was reshaping client-agency relations: “(Agencies) sometimes become the custodians of data, they can collect it through campaigns. Agencies require data, but they need to share their data back to brands, make sure it’s the right quality, and it's usable in a day.”
Marini called this a value exchange. “We count on our agency to apply taxonomy, keep data clean.” Brands then connect that data through their channels. “And then we want to bring the agency into that conversation.”
Jordan cautioned that these changes are strengthening the advertising prowess of the likes of Apple and Google, adding it’s critical “to step up to that David and Goliath match.” She noted that the reason marketers love digital advertising is that unlike classic advertising formats, “you can bring your product to the audience”. We must not “regress” and “erase” the past decade: “We have to work with what we have and get creative.”
“We have to be able to compete,” Marini argued. “Our sellers need to be able to scale digitally.” Efficiencies would come when brands create more dynamic content, particularly via omni-channel where siloed budgets are merged together, more automation, taxonomy and AI models to segment audiences. Brands need to be more strategic about the long-term value of data strategies and see beyond short-term higher set-up costs.
“We're starting to think about data as the oil to both power digital and human experiences… a big change culturally,” Marini continued. “We're talking about data democratization; how we increase data literacy within our organization.”
“Have some focus,” Marini added. “You don't need all the data just to manage it, because that's inefficient. I'm trying to progress people through the funnel. That informs what kind of data you're collecting.”
Butt agreed: “More data doesn't mean better. Can a data scientist leverage it?” Collecting so much data created big cost and privacy challenges.
Comstock concluded that because cloud data storage had become cheaper, everyone just kept data to use “one day”. Today, data strategy is required. What are we trying to solve? How do you align people and move fast?
“What good is that data if you can't use it fast enough to make decisions?” he said.
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Claravine is redefining data integrity for the global enterprise. Our platform, The Data Standards Cloud makes it easy for teams to standardize, connect, and control data collaboratively, across the organization. Leading brands use Claravine to take greater ownership and control of their data from the start, for better decisions, stickier consumer experiences, and increased ROI.Find out more