The Personalization Gap: Improving Data Analysis and Context

PG_2_graph-(1).jpgConsumer expectations have continuously grown over the past 2 decades, reshaping the retail landscape. They are used to instant gratification, stemming from key technological advancements like the smartphone. While shopping, consumers expect the same instant, simplified experiences that they’ve grown accustomed to.

If the shopper has high expectations and the retailer is unable to deliver a top-notch experience, then the retailer increases the risk of losing the shopper to a competitor. So, how can retailers improve the shopper’s experience to maintain loyalty and satisfaction?

Watch the original keynote address presented by True Fit's Managing Director, EMEA, Lars Rabe:

The Retailer’s Responsibility

To better personalize the shopping experience, retailers need to analyze consumer, product, and transaction data. Connected data helps the shopper because the retailer is able to put the right product in front of the right customer at the right time.

By incorporating consumer data, and product trends into business intelligence, retailers can better understand their shoppers and ensure each shopper is offered the best products to match their personal preferences.

Retailers are accountable for delivering the right content with the right context to the right person at the right time. This formula is the key to true 1-to-1 personalization.

When a consumer visits a retailer’s website, they expect to see the styles that match their individual preferences immediately - and as we discussed in the previous Personalization Gap post, rarely travel beyond the first page of search results. Why expect the shopper scroll through ten pages of dark wash denim before finding the one that suits their individual wants and needs?

If the shopper has made a previous denim purchase on the site, the retailer has the necessary data to offer an accurate style, fit, and size recommendation, eliminating much of the guesswork for the shopper. Many retailers have the data available to create these personalized experiences, but often struggle to optimize its uses.

How to Deliver 1-to-1 Personalization

By tapping into key shopper data, retailers can inspire and delight each and every shopper with products that are true to them.

Consumer data gives retailers an overview of their shopper’s historic size, style, and fit preferences. This data helps power accurate recommendations on a 1-to-1 basis and enables retailers to provide each shopper with an individualized shopping experience.

Transaction data helps the retailer answer two key questions:  Where else does the customer shop? And What other products do they purchase? An understanding of these two questions can guide the retailer in offering products that are similar to the styles they have previously purchased. If the shopper is looking for a pair of denim, and has previously purchased multiple straight-leg styles, then the retailer’s data platform knows to populate more straight leg styles compared to only skinny-fit.

Product data is useful for retailers because it can help guide style, size, and fit changes or design products that shoppers will want to purchase. Product data can include style details, the consumer demographics that purchase the product, and insights on how products fit and whether or not they were kept or returned.

Comprehensive data collection helps retailers gain a better understanding of the best styles of clothes to offer an individual shopper. This ensures recommendations are relevant and accurate for the individual, rather than the masses. Collecting relevant data and using it in turn to guide production processes is how retailers can improve the consumer’s shopping experience.

Download The Personalization Gap presentation today to reduce the gap between retailers and their shoppers, and increase consumer loyalty along the way.