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Using Predictive Personalization to Enhance Your Products

Data analytics may seem to be a step removed from software requirements, but it is intertwined with every aspect of the product management lifecycle.

Using elicitation with a client to unearth their base needs is an exciting adventure. It is a wide open field, especially when you come prepared with suggestions for your client to build off of. Enter the room prepared to help brainstorm a solid product that will increase profits for your client.

Business-savvy companies are forward thinking. Instead of just focusing on current state enhancements, they are constantly striving to be ahead of customer requests. Performing trend analysis and market research are imperative to obtaining this information. Instead of being responsive to issues within the business, be a proactive product manager and provide the customer with products before they mention it in customer satisfaction surveys or complaints.

I recently read an article discussing trend analysis for product development. How do you determine what your clients’ customer wants without being reactive? Quick answer: Data Analysis.

Gather the data on your client’s customer satisfaction surveys, user testing comments and customer usage data. The aforementioned article points out a useful addition to product marketing – Predictive Personalization.

Let me make an important point before we get too deep in predictive personalization – there is a line that can be crossed in assuming what your customer needs. If you have a Facebook or other social media page, you may see advertisements for products that seem oddly familiar (or maybe just offensive). For example, when I was nearing the ninth month of my pregnancy, the predictive personalization product advertisement on Facebook crossed that line into the offensive. “Lose 25 pounds in 10 days!” Alright Facebook advertisers, thanks for the hint!

Now, back to the positive aspect of predictive personalization. Direct customer data, based on purchases or associated products, provides a more useful data set to analyze.  Let’s say the customer has a ten-year old computer, and has authenticated to their account for this computer on your client’s website. After the user authenticates, the website recognizes the computer (including the original configuration, date of purchase or date shipped). Well, a computer purchased in 2003? This customer needs an upgrade. A software system that detects this type of data and turns around with a solution to the customer uses predictive personalization. Showing the customer an advertisement for a new 2013 laptop while they are logged in to your client’s site provides a meaningful way to market a new product.

The example outlined in the article discusses a British company that used data analysis to formulate coupons for its customers. Research into its customers showed that new fathers who were first time purchasers of diapers at the store were more likely to miss out on “pub time” (I’m assuming the mothers were missing out on this as well…) The company used this predictive personalization analysis to advertise beer to these particular customers.

Predictive personalization is one of the many different utilizations of economic research in product management. Have you utilized data analysis in a recent project? Let us know!

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