AdExchanger Talks is a podcast focused on data-driven marketing. Subscribe here.
This week on the podcast, Katrin Ribant joins us in the studio for a discussion of the ever-more-complicated data landscape.
Ribant spent many years at Havas and helped build its Artemis data platform before co-founding Datorama in 2012.
“I was always very interested in the data aspect of how we managed media buys,” she says of her time on the agency side.
Datorama’s platform helps clients integrate data from many sources into a single dashboard so all members of a marketing organization can look at the same truth set. It can aggregate from almost any source, including DSPs, DMPs, social platforms, email marketing platforms, content management systems, CRM databases, web analytics tools, ecommerce platforms and ERP systems.
Ribant says the rise of terms like “AI” and “machine learning” suggest the industry is gaining maturity in its use of so-called “big data.”
“In the early years of big data there was a big emphasis on the volume of the data but not as much emphasis on the variety or the velocity of data,” she says.
As data use scaled across industries, however, it became clear that the variety and velocity at which we need the data are critical factors.
“There’s a point where you need a level of machine learning and AI to help you with the ingestion of the data with insights into a data set that is so complex that you are really only going to ask a certain number of questions,” Ribant continues. “The biggest help from AI will come in supporting complex, rapid decisions.”
