Retail marketing teams are staring down the eye of a perfect storm:
- Marketing and sales is the #1 field of expected AI impact because of its direct tie to revenue
- Retail is the #1 industry of expected AI impact because of its close feedback loop for collecting, analyzing and using consumer data
But before we barrel head first into the era of AI, it’s important to understand where we’re coming from and the challenges that exist currently.
Shifts in Retail: The Era of the List vs. The Era of AI
To date, most retail marketing teams have operated in the era of the list, in which each channel for execution has its own team that uses customer lists pulled from a single source of truth. However, these lists don’t have context on customer behaviors and they are manual and time-consuming to produce, meaning they become stale quickly.
AI changes all of that.
In the era of AI, teams will observe, decide and act all in one place, making it possible to take action seamlessly across channels and automatically deliver personalized recommendations to individual customers. AI-driven technology not only makes observing and acting on data easier, but it also provides regular feedback to power consistently more intelligent campaigns.
To successfully move into the era of AI, retailers need a system that provides data analysts and marketers alike visibility into customer data and the ability to act on those insights quickly.
Embracing AI in Retail: Enormous Opportunities Exist
As we move into the era of AI, enormous opportunities abound for retailers. Some of the most notable and immediate opportunities that exist include:
- Democratizing access to data. It’s finally possible to stop holding data hostage by making it searchable, visible and accessible to all business users. Even if only a small group of people can actually use the data to run campaigns, allowing everyone to view and query customer data to better understand shopper behavior delivers tremendous value.
- Increasing speed of execution. AI not only helps get campaigns out the door faster by taking over previously time-consuming and manual tasks, but it also gives marketers faster insight into data. This speed to insight ultimately delivers more useful data. For instance, marketing teams using AI can identify shoppers who are at risk of churning and then take action to save them rather than learning about the risk after the shoppers are already lost.
Overcoming Challenges to Effective AI in Retail
Despite the enormity of these opportunities, a lot still needs to happen before the promise of AI in retail can reach its full potential. Specifically, brands face common challenges in fully embracing AI, including:
- Maintaining promises made to shoppers. Many brands have asked shoppers to sign up for different types of communications. Delivering on those promises and managing the experience as expected still requires lists. To get past this challenge, retailers need a sophisticated system that can act as a middle layer between data storage and channels of execution and that can manage communications at an individual level.
- Giving AI constraints. There’s no doubt that AI can supercharge marketing campaigns by using large datasets to make decisions of which humans simply aren’t capable. But we also can’t let AI make decisions alone. Rather, we need to give it constraints, for example to preserve margins. To get past this challenge, retailers need a solution that offers the power to focus AI toward specific goals.
- Balancing shopper behaviors and desires when they’re at odds. Using AI to adjust email frequency based on each shopper’s engagement can go a long way when it comes to inbox management, but what happens when shopper behaviors and desires are at odds? Consider the case of a shopper who wants to receive a brand’s emails and engages with them, but still only wants three emails a week, not one email a day. Typically, AI will read this shopper’s engagement as a sign to send more emails, even though that’s not what the shopper actually wants. To get past this challenge, retailers need to find a balance in which they can use AI to be productive but still listen to customers and override things based on individual customer preferences as needed.
What’s Next for AI in Retail?
The era of AI is fast approaching retail, and brands must take action to make the shift from the era of the list to the era of AI effectively. Fortunately, once they do, opportunities to increase performance with less effort are plentiful.
But what exactly does success for retailers look like in the era of AI? And what does it take to get there? Find out how Sephora has made the shift by improving data activation and accessibility.