Katie Hanifi, senior director of media strategy and investments at PepsiCo Beverage, said that fact is one of the things that keeps her up at night.
“The process has changed,” Hanify said on the latest episode of the Digiday podcast. “In fact, there are probably three things that will ultimately impact our process: the rapid growth of the creator economy, the rise of CTV and retail media.
In this episode of the Digiday Podcast, we interview Hanify about the changing media landscape, how PepsiCo Beverages is responding to the media landscape, and of course, what measurement looks like in a fragmented market. We talked about.
Below are highlights from the conversation, lightly edited and condensed for clarity.
Internal data subject to privacy regulations
We are 100% privacy compliant and must maintain all consumer privacy and data at all times. That's the top priority. Interestingly, we've been on this data journey for the past two years in preparation for moving basically everything to some kind of digital advertising technology platform. We have a great in-house solution. We call this CDNA (consumer DNA). This is a combination of first-party and third-party data, from shopper behavior to behavioral insights and passion points. You can scale that data up or down. That data is actually used to inform how brands and creatives connect with consumers, from the planning stage to the digital activation stage. Being able to leverage this data to fuel media buying is highly efficient and effective, and knowing a little more about your consumers can have an immediate impact on how your creative messages can reach the right consumers. It has increased.
AI hot topics
When it comes to AI, and especially when it comes to media, there are certainly use cases in creative places and other places within organizations, but especially when it comes to media, we've been testing AI with a lot of partners. OMD, specifically, our agent of record and an incredible partner who uses AI to optimize our digital purchases in real time. So we take some of the manual keyboarding out, we set the KPIs and then we let machine learning actually optimize to find the right consumers at the right time and deliver the message. We've definitely seen early success with this, increasing visibility and increasing sales. There is also some cost efficiency. This is something you'll want to start expanding on as features grow within and outside your walled garden.
measured melee attack
[Unstandardized measurement] Traditional mix modeling poses even more challenges. We have a proprietary in-house tool called his ROI Engine, which is currently the only source of truth we have, and which measures all of our marketing efforts holistically, including media in particular. Masu. You can analyze specific platforms and campaigns at a granular level, so you can see which ones have a better return on investment compared to others. That's the best source of information we have at the moment. Going forward, we will definitely supplement that measurement with third-party research and brand lift research. Going back to retail media, they all have solutions, and we work with them to run tests and see what drives sales growth, what drives brand association. We've learned strategies for understanding what's going on.
https://digiday.com/?p=533831
