You Don’t Abandon a Profitable Ship: Personalization Drives Profits, Despite Naysayers
Last week, we discussed the importance of creating an SCV or Single Customer View. But data and insights are only valuable if they drive a better action or decision. So what kinds of better actions can be taken? Many companies start with personalizing interactions with consumers. But this isn’t easy.
As I’ve mentioned before, in late 2019 Gartner predicted that 80% of marketers will abandon personalization efforts by 2025. This decision will be driven by the difficulty in managing customer data, lack or ROI, or both, Gartner said.
And Gartner isn’t alone in its thinking. This LinkedIn post, “There is such a thing as too personal,” shares an interesting point of view. The author argues that personalization will fall out of favor because:
- Consumers are going to put more value on privacy versus having personally tailored experiences and content.
- Marketing planning, investment, and execution takes place at a more aggregated level than the individual consumer, and the additional cost and complexity to manage the data exceeds any potential return on the investment.
We have discussed privacy and the value of winning consumer trust previously. But I recently had a conversation with my Gen Z daughter, Megan, who reinforced my belief that consumers are conscious of the trade-offs related to data privacy and value. For example, Megan has downloaded an app from her insurance company that tracks her car usage and driving behavior in exchange for monetary rebates for good driving habits.
She knows her insurance company is collecting very specific data about her, but trusts that they will use the data in a fair and transparent manner. While this isn’t a consumer packaged goods (CPG) example, it showcases the ability to use granular, consumer shared data to personalize a product (in this case my daughter’s insurance coverage) while balancing the respect of her personal data.
Giving Consumers Control Over Customer Data Works
What makes this exchange work? Importantly, her insurance company has given her some level of control through the ability to turn the data collection process off at her discretion. This is just one example of how consumers are becoming more sophisticated and comfortable with sharing data in return for value; PepsiCo’s Chief Data and Analytics Officer sums it up this way: “Their level of maturity around data will undoubtedly endure post-pandemic.”
The second point—that there can be added complexity and cost to customer personalization—is a good one, and historically that was true. But as a current view, it ignores recent advancements in technology. It is absolutely possible—right now—to operate at the speed and scale required to deliver personalized experiences to individual consumers. A useful example is one from retail, where Treasure Data enables Wish to deliver real-time personalized product recommendations to millions of customers (using billions of data points) on a daily basis. According to Wish, 95% of the products that customers see on their mobile Wish app are tailored and relevant to their specific needs.
Wish Succeeds In Part Because of Customer Personalization and Smart Data Use
How is Wish doing this? They are using Treasure Data’s CDP to ingest customer purchase and behavior data. Next, this data is integrated together and ML-powered recommendation analytics are used to predict what the most relevant products will be for this individual. These personalized recommendations are then served up to the consumer through the app.
Granted, Wish has the advantage of being an ecommerce company with access to a broad set of data—a breadth of data outside the scope of most CPGs. But lack of data is a different issue than lack of technical capability; and there are multiple strategies (retailer partnerships, DTC initiatives, recipe sites, customer call centers, etc.) that a CPG brand can use to gather first-party data. My recommendation is to not let a misconception of a technology gap prevent you from exploring personalization opportunities.
CPG Companies Use Data to Better Understand Consumers
Some CPG companies are using customer data platforms (CDPs) to piece together information that’s already available, with data they’re now collecting via their nascent DTC channels. Consider, for example, global beverage company AB InBev. As a CPG company, it rarely gets a full picture of consumer behavior from its retailers around the world. And it finds this to be a big problem—one that can be addressed through customer personalization and customer data platforms, which are designed to handle complex customer data environments.
“One of the biggest challenges for CPG companies like us, is really how to connect directly to consumers and how we can break this wall with them,” says Lucas Borges, senior global martech manager at AB InBev. “To support this mindset, we have been building our own pubs, direct to consumer channels, loyalty programs and much more.”
“Then, with all these data points, ABI needs to have a way to connect all of this channel data into a single database, where we will be able to build a unified consumer understanding and have the opportunity to learn more about our consumers,” he says. “Here at ABI, the CDP is our single source of truth talking about our consumer data and it is positioned in a strategic place in our martech stack.”
How Customer Personalization Fuels Longtime Loyalty
Let me close with another example from my daughter Megan that brings home the power of delivering a personalized experience. She worked as a barista and became very aware and attentive to her regular customers. She had one customer who used a cane to assist with walking, so her walking made a very distinctive sound. Megan could hear her coming into the store and have her drink ready for her before she even got to the counter. The woman would always sit in the cafe to enjoy her drink, and when she would leave, she alway asked for a to-go item. Megan could hear the sound of her chair being pushed in and the woman walking up to the counter—where Megan would already have her drink ready for her. When my daughter was moved to another store location, this customer followed her there. Now, that is the power of loyalty driven by personalization!
What was required to deliver this personalized experience? The first requirement was the ability to collect different, disparate pieces of data—past purchase behavior, time of day of visits, and specific sounds of walking and a chair being moved. Second was the need to integrate this data together and then predict future actions to take. Third was the delivery of the personalized experience.
Now, that sounds strikingly similar to the process Wish employs! But clearly it would be difficult for a person to do all of these things for more than a few dozen consumers. That is why we have CDP technology, to allow us to do things at a speed and scale well beyond our human capabilities.
Let’s not abandon the personalization ship—ask yourself, are you ready to use technology to take your consumers’ experiences to the next level? Because the companies that have discovered how to do that, are the ones that are succeeding on a global scale.
Stay tuned, and in the meantime, check out Episode 15 of CPG Bytes, where we talk about democratizing consumer data for personalization at scale.