Conventional wisdom reminds us to see the forest for the trees. Today, however, that wisdom is being turned on its head. As digital technology creates new torrents of data, how do we see the trees for the forest?

Let me explain.

With every action in our increasingly digital lives, we generate vast sums of data – big data, as it’s known collectively. The resulting high-dimensional data sets are far too massive and complex for the human brain alone to analyze. Following our analogy, our brains see a big, dense forest, and not much else. But deep within the dense data forest are patterns and relationships that can reveal important insights.

We have the tools to solve this modern data dilemma – tools that don’t just help us see the trees, but also the branches, twigs, and leaves.

Neural networks are one of those tools. A form of artificial intelligence, neural networks process information in a manner similar to the human brain, but with the ability to tackle much, much larger amounts of information. In a neural network, data moves through multiple levels, or nodes, where each output is informed by previous information that informs the subsequent output.

Just as humans gain more wisdom with experience, neural networks gain new levels of clarity as data moves through each feedback loop. This provides the ability to detect patterns and relationships the human brain can’t. The implications for hyper-personalized marketing are major. Here is just one example…

A Discida financial services client was able to drill down into customer data like never before, using neural networks to develop a richly detailed picture for unique, hyper-targeted marketing campaigns. Here are just three ways the client put its newfound intelligence to use:

  1. The institution was able to identify new life stages and financial needs. This created increased opportunities for more relevant and meaningful customer outreach.
  2. Customers were segmented by specific characteristics, such as vehicle preference. The neural network data processing was capable of detecting, for instance, if Subaru owners prefer certain types of financial products. This paved the way for highly effective cross-sell opportunities.
  3. More fully fleshed-out customer personas will be developed in the future. Personas that include details like mid-life, two-car, house-owning customers who like travel, along with the corresponding product and service behavior patterns. The institution will then build “mind-reading” marketing campaigns with significantly better response rates.

The reality is that consumers expect hyper-personalization, and it’s one of the most effective ways to capture their limited attention. Smart marketers can now access the data science tools that not only see the trees for the forest – but tell them exactly which tree to bark up.