Ensuring your data answers the right questions for 1:1 hyper-personalization
Consider this: 63% of consumers said they’ve stopped buying from a brand that employed poor personalization activities, coming across as creepy or annoying; however 77% of consumers have chosen, recommended, or paid more for a brand that provides a personalized service or experience. Statistics such as these have inspired businesses to take a “more is always better” approach to data collection. Yet, not all data is created equally, and not all data should be employed equally during the customer journey. In fact, utilizing too many data dimensions has been seen to detrimentally impact customer experience and perception. This leaves businesses with a critical question: how can they differentiate between the right data to collect and utilize and when data is collected for data’s sake?
It is all about finding a happy medium. While sticking to traditional channels of customer data acquisition such as website patterns and in-store interactions scratches the surface of personalization, they often fall short of empowering true 1:1 personalization. In similar regard, data overload where all known elements of a customer are considered at every interaction can prevent businesses from effectively identifying when intervention is necessary. The key to successfully collecting and using customer data is tapping into the right information and applying it in effective and innovative ways.
Forrester’s VP and Principal Analyst Brendan Withcer very aptly said in in a Q&A: Top 5 Questions About Intelligent Personalization: “Retailers often make the mistake of putting a priority on collecting more data. … However, the key is to collect or access the right data – that which allows the retailer to take a specific action.”
Here are the questions businesses should be asking in order to determine the right data to collect and apply:
1) What was the customer doing yesterday?
Businesses first began to truly understand customers by using past purchases, search history, and in-store engagements as benchmarks for future interactions. For example, if a customer only historically browses in the women’s section of a department store, then the retailer will know to serve up ads for women’s apparel. Keeping track of past purchasing behaviors helps businesses understand consistent patterns and trends of each individual customer; however, it’s important to remember historical data does not account for changing needs or contextual details. Therefore, it must be paired with additional data dimensions.
2) What is the customer doing now?
To gain a better understanding of customer intent, it is imperative to understand real-time data in conjunction with historical data, empowering businesses to react instantly and steer customers in the right direction. 83% of organizations find the ability to translate data into actionable insight at the optimal time to be important to the customer journey. The right information used at the wrong time loses its power; however, leveraging relevant offers and promotions in the right moments increases customer satisfaction and transaction success.
3) What is going on around the customer?
The final part of the customer data trifecta is gaining a contextual perspective of each customer. Although the combination of historical and real-time data provides a complete view of customer preferences, personalized offers and promotions can quickly become irrelevant when environmental factors, changes in weather, or events are not considered. In 2018, the quick service restaurant Subway boosted store traffic 31% by changing its ads to correspond with weather shifts. By understanding a customer’s current location, businesses can more effectively serve up ads based on crucial environmental elements that impact in-the-moment purchasing decisions.
The Right Platform to Collect and Glean Insights from the Data
72% of companies place “personalizing the customer experience” at the top of the list for opportunities to improve the customer’s on-site experience. Yet, with the right personalization platform, businesses can do more than just collect the right data—they can understand, interpret, and act on it.
While there are many ways to gather and interpret customer data, there is one solution that can help your business to intelligently leverage the right data dimensions. ZineOne’s AI-driven Intelligent Customer Engagement (ICE) platform leverages predictive models based on in-session user behavior paired with historic and environmental conditions to achieve up to 90% accuracy detecting customer action. Contact ZineOne to discover how our solution is the right tool for your 1:1 personalization efforts.