If 48% of consumers spend more when their experience is personalized, it’s no wonder that 90% of marketers believe personalization is “the future” and are making it a strategic priority this year.

While an ecommerce experience can be targeted by immediate signals of context like geolocation, clickstream behaviour, site-searches, cookies and campaign referrals, true personalization relies on data to drive the experience. And for many ebusinesses, Big Data is part of the equation.

Big Data’s one of several key elements of personalization covered in FitForCommerce’s annual report Let’s Get Personal, Personalization in a Hyper-Connected World. How can online businesses harness and actually use Big Data to effectively personalize customer experience?

A brief history of personalization

Beyond welcoming a returning visitor with “Hi Joe!,” the manual, rules-based product recommendation engine was ecommerce’s first and simplest personalization tool. A marketer could create associations between products A and products X, Y and Z for cross-sell and upsell opportunities, with data living in simple tables.

Automated, “collaborative filtering” pioneered by Amazon in the early 2000’s came next, recommending products based on actual customer browsing and buying behavior, rather than a merchandiser’s gut. The engineers behind this technology went on to found their own recommendation engine startup, and an industry was born. Online retailers have their choice of recommendation technology.

Beyond product recommendation

Product recommendation engines do a decent job of personalizing a user’s experience, but stand-alone, they only leverage on-site context (profile, clickstream and purchase data), often within a single or handful of visits (until the customer clears cookies, or changes devices, for example). But today’s marketers have access to much more contextual information. Email engagement and response, campaign referrals, mobile usage, social interactions, geolocation, customer service logs, in-store behaviour and optimization testing are just a few examples. And the freshness of this data is increasingly important for accurate targeting and personalization.

This means marketers have a lot more data to work with – more than a recommendation engine alone can handle.

Big Data driven personalization

Personalizing the customer experience across channels and beyond what you can target based on Web behavior and account history requires tapping into Big Data. Big Data involves the collection, management and analysis of multiple sources of data, both structured and unstructured, and each organization has its own custom blend of Big Data to work with.

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