How would you define personalization? Is it a quarter-end campaign? A series of campaigns? A piece of software? An idea? A philosophy to live by?
Nearly all CMOs define and follow a different version of personalization in their marketing programs. These versions are driven by the maturity of their organization’s strategic vision, the availability of data and the ability to integrate the latest stack of analytics platforms and technologies into their marketing programs. These versions can be classified into three broad categories:
- The Gen-Pop Personalization: Knowing Who Your Audience Is
This is the type of personalization that every single marketer does. At the most basic level, personalization starts with name, gender and other demographics that the marketing team has access to. Addressing the target audience as ‘Dear Mr. Smith’, ‘Hi Larry’, or ‘Resident of 2121 Hartford Drive’ is personalization at its minimum. It removes the anonymity from your relationship with your marketable audience and tells the consumer that the brand is trying to pitch to them and knows who they are. It’s a good start.
- The Data-Driven Personalization: Marketing Based on Past Purchases
Analytically-driven marketing teams do this. It’s all about approaching consumers based on their past purchases. This involves looking at transaction-level data across store and ecommerce channels, developing cohorts of categories that sell together, and pitching related products to the consumer in similar or associated categories. Knowing that the brand is looking at their purchases and trying to offer them relevant products gives the consumer confidence and helps them save time and effort. It also gives the brands to have a better chance at converting another sale.
- The NEXT-Gen Personalization: Hyper-Personalized Marketing and Campaigns
The two levels explained above do not require very advanced skills or platforms. But then the impact generated by them is limited as well. In recent years, marketers’ relentless search for the Holy Grail — improving the performance of their marketing campaigns — has brought them to the intersection of data, analytics, and technology.
Hyper-personalization involves predicting which product a consumer will buy next, at what time, and through what channel. The next step is sending them customized offers at the moment of purchase. This exercise is challenging and includes the use of all possible consumer data: demographics, preferences, past purchases, browsing history, engagement with the mobile app, mobile devices and other external consumer data. After getting the data in place, it needs to be pushed through an analytics engine to predict which consumer will have the intent to buy and what product will they buy in their next purchase.
We would love to hear what personalization means to you as marketing practitioners in your industries. Please share your views and thoughts!
Authored by Kunal Jain, Associate Director at Absolutdata