If we think of brands from an advertising standpoint, and we think of advertising as “behavior-based monetization,” the more intelligence a brand or media buyer has on consumer behaviors, the more relevant they can make the customer experience; and the more personalized the experience, the more chance of a purchase and efficient campaign spend. It’s using this intelligence in the form of data that we covered in the panel.
Julian opened by stating that he had seen a statistic showing that only 7% of marketers think they are exceeding expectations in the customer experience, and posing us the question: “If the customer experience and the consumer journey are tied together, how are CMOs measuring the customer journey effectively?”
Philip responded to this by talking about how a good, orchestrated consumer experience requires data integration within a company. So many companies today reach for leading edge technologies without first ensuring all of their data is utilized correctly and working for them with the right analytics. Rather than just “how do we capture data?” Philip stressed that interpreting the data and developing a strategy is where the impact lies.
In terms of location data, I spoke about how, important as it is to businesses, location data is still not very well understood. While many believe they are location enabled with merely a set of coordinates, at HERE, we stress the entire process. Rather than just points of interest, location data has the power to highlight if consumers are going into a store, as well as which stores they’re going into, and whether they’re converting purchase intent into something that is actionable. Sure there is location data for getting around, but the value of location for purchasing power is just as strong, though less understood.
Philip also made a good point that in the easiest example of location-aware advertising (e.g. geofencing around a restaurant a lunchtime with an ad about lunch), we can’t always assume that the consumer is in that mind set. Just because someone in near a restaurant, that likely doesn’t mean they want to eat. That’s where data comes in to refine the ad targeting. If a brand uses location data to look at the commuting patterns of people who walk past their restaurants on a regular basis and when they do it, and assesses these patterns over a few weeks, unique profiles of can then be derived that can then be made into bespoke targeting strategy.
Toward the end of the panel, we touched on automation and what in advertising can be automated. Automation can only be as good as the data that feeds into it so there’s always limitations that even 5G won’t be the answer to, so it’s about the data being fused and cleaned up and analyzed against patterns over time. Philip stressed that when AI comes into the equation, it’s about using this technology to better free up human time to focus on the bigger picture with AI as the co-pilot.
To close, Philip and I both had similar sentiments in that there is no cookie cutter solution for all. Brands and businesses need to first know what they want, have a plan, and then focus on the technology, partnerships and executions that will help get them there.