Not too long ago I was clearly targeted in an email campaign and banner ads as a 40-something, suburban mom with kids that was preparing for “back-to-school.” I was offered some pretty good deals on sneakers, backpacks and organizational products for my home.
Unfortunately, this retailer couldn’t have been more wrong. I am 40-something, single, live in an urban zip code and have 0 children. They placed me smack dab into the wrong demographic profile. I didn’t feel that this retailer “knew” me.
This experience made me wonder how they were analyzing, segmenting and personalizing the information they had on me. The #1 goal of personalization is to identify a person’s attributes from their purchase intent, understand online behavior and specific profile demographics; then customize that experience by presenting only the most relevant content and provide the right calls–to-action. This retailer clearly had some information right, but missed the mark on others.
The challenge is that they likely couldn’t sift through the data and make it actionable intelligence, because quite simply there is a lot of data! As a frequent shopper of this retailer, they knew a lot about me, but they picked up on the wrong data …maybe a previous purchase of gifts for my best friend’s kids or maybe it was the gift bought for a charity event made them segment me differently.
Whatever happened, it made me think more about analytics, big data and the role it plays in personalizing content for me and as the volumes of customer data increase, so does the critical nature of getting personalization right. On Thursday, Aug 20th, we will begin the discussion on big data, analytics and how it affects personalization in our next digital transformation webinar on analytics and personalization. Join the session by registering here: Leverage Customer Data to Deliver a Personalized Digital Experience.
