For the past couple weeks, The Parker Avery Group’s blogs and some of our thought leadership have been focused on retail store labor – how it is changing to accommodate many the pressures and dynamics in today’s retail environment. In fact, we just launched a new research study called “New Roles for Retail,” which aims to take a deeper dive into understanding how retailers are specifically handling these challenges and adapting how they handle retail store employees in their new business models. We are excited to be conducting this study, which is certain to reveal some compelling findings.

If you work for a retailer in a Store Operations, Human Resources or related capacity and are interested in participating in the study, please click the following link: We truly value and appreciate your time and perspectives.

This week, I’m taking bit of a turn and want to focus on the customer side of the retail equation. A good deal of Parker Avery’s recent work has been focused on assortment planning, including global assortments, localized assortments, digital (i.e., ecommerce and mobile) and more. It’s fascinating to understand why and where retailers are strategically placing their bets, and it’s truly exciting to help guide these decisions, develop the requirements to enable the strategies, identify appropriate technologies and design the supporting business processes. It’s even more fun to be part of the implementation and bring the strategy to life. I’ve personally always been a fan of taking something that’s outlived its useful life and transforming it into something new.

I just read an article in Retail TouchPoints about how customers are “uninspired” by online shopping. The study supporting the article revealed that customers do not really feel that online assortments and traditional search capabilities fit their needs very well. It still surprises me that with all the data and customer information available, many retailers are still not hitting the mark with personalized assortments – both online and in the store. To illustrate: B.I.G. Retailer (a fictitious store), I use your branded debit card in your stores and online, I shop or browse often on your mobile site, and you still think I’m interested in toddler and baby clothes? My son is 10 years old. I haven’t bought toddler or baby products in over 6 years. So when I search for “boys shoes,” why am I presented with toddler-sized and Thomas the Tank Engine-themed shoes? What need do I have for digital coupons for diapers?


But there is a better way.

Parker Avery has been exploring the concept of highly personalized assortments. If you’ve ever used the music service Pandora, we feel that that this type of predictive analytics is very applicable in retail. Here’s a bit of background on Pandora:

The Music Genome Project that powers Pandora collects over 400 musical attributes covering the qualities of melody, harmony, rhythm, form, composition and lyrics for a huge selection of songs. The user enters a musician into Pandora. Pandora will play a song by that artist and the user can rate the song. The next song that Pandora plays will share some of the salient traits that are characteristic of that artist. Pandora hones in on the user’s musical preferences as the listener rates the songs.

Sound familiar? Some retailers – mostly online – are getting close with product suggestions based on a customer’s purchase history and “what others have purchased / viewed,” as well as “what’s trending.” I do think some people that need to be “inspired” truly appreciate these suggestions, but this is only the tip of the iceberg.

While I appreciate knowing what others have bought – what if they’re nothing like me?

With the capture of more robust product attribute data combined with customer information from a variety of sources (transactional, social media, etc.), a mechanism similar to the analytic engine that powers Pandora could be used to predict customer preferences for both existing and new products.

Imagine if I walked into a retail store and was presented with compelling offers for products or services that were uniquely relevant to me – even to the point of understanding that my high-mileage Honda Pilot may need service while I’m in the store? Or that I hadn’t ever purchased water filters for the refrigerator I bought two years ago? I’ve provided an example of how this could – and should – happen (see the graphic). Yes, it takes some work to determine the “right” analytic engine, develop the product attributes and integrate the myriad of structured and unstructured customer data to get to this point. It also requires providing customers with the digital capabilities to take advantage of the personalization and offers (for example a mobile app or site).

The technology and capabilities do exist. It’s a matter of piecing together the old with the new and transforming the environment to one your customers will find truly…inspiring.

Shop on.

– Tricia Garrett