Personalized Commerce: Coming to an Internet Near You

Retailer Strategies Using Data Can Have A Personal Effect On Buying Habits

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Retailer strategies leveraging data can have a personal effect on buying habits sooner than you know it.

From the perspective of a modern retailer, data is pushing pricing and promotion strategies in two directions -- toward both national and personal pricing. Data insights, retailer infrastructure and consumer tools are developing quickly but unevenly. This gives innovative retailers an opportunity to shape the pricing and promotion practices of the future, all the while technologists are keen to develop new tools to disrupt those plans.

Yet, on the front end, consumers expect an omni-channel retail experience. In a recent survey by Empathica, more than half of smart phone users admit to using their mobile devices to do research product prices. When this research happens real-time in stores, it is commonly referred to as "Showrooming." And as such, these consumers are currently better informed than the retailers in many aspects.

Price Changing Explodes

Retailers, now aware of the information gap between them and their customers, are not ignoring this trend. New data tools enable retailers to price and promote more frequently. Amazon trashed the traditional retailer model of re-pricing once a week and instead re-prices products several times per day, making thousands of small pricing adjustments for peak traffic lunch hours. Channel-wide, the breadth of products with frequent price changes exploded in 2012. During the last holiday season, we at Dynamite Data detected up to a three-fold increase in the relative quantity of price changes over 2011 across major retailers.

An increase in price changes is a significant benchmark for an increase in market efficiency, ultimately driving more real-time price competition among retailers. Although retailers are known for relying on complex and inflexible legacy systems, many are actively improving their infrastructure for the new super "showrooming" era. The ultimate goal for most merchants is to at least have the capability to dynamically price and promote at least once per day while synchronizing price across the omni-channel (mobile, social, email, ecommerce and retail).

Value-Adds And Regional Pricing

Being able to react faster to market forces is just one option available to retailers looking to personalize commerce. Another is to create a value-add layer between the retailer and the consumer, simultaneously increasing pricing opacity while also strengthening the brand proposition. This might be achieved with the introduction of house brands, price segmentation or even personal pricing.

For instance, retailers such as Microcenter price their products regionally to reflect the local competitive dynamics. This price segmentation strategy is fair to the consumer and the retailer, but only possible with the type of data infrastructure that supports multiple price points on an individual item. Lowes, another franchise retailer, is also known for regionally pricing end-of-life products. For example, last summer I was able to save almost $1,000 on a refrigerator by buying it from a store a few miles away.

(A personal note: The advantage of my job is that I always pay the lowest price. The disadvantage is that I buy a lot.)

Personalization extends online. The Internet has become an extremely personal experience. Even though billions of people connect to an instant, ubiquitous network, everyone experiences it differently. For example, the news consumption model changed dramatically with the introduction of personalized news portals. My Google News feed heavily rotates international and technology news, while my wife's feed pulls local and business news. Even within categories that we share a mutual interest, like genetics, Google's algorithms recommend different news sources for each of us. She also sees different ads and comments, even when we do end up on the same article.

Online advertising was one of the first purveyors of personalized Internet content. Consumers see different ads based on their browsing history, down to the individual. My wife and I were surfing baby stroller reviews when we stumbled upon a seemingly benign website that recommended we HAD to get a particular model at Amazon. A week later I revisited the review site on my laptop, only to notice the same webpage was no longer pushing the stroller. My wife's laptop continued to insist the stroller was a must-buy. This dubious, though ingenious affiliation is likely a herald of things to come.

Processing a customer's entire purchase history just to recommend a single, custom-tailored promotion seemed far-fetched even just a few years ago. But now, big data-enabled personalized promotional offers are becoming commonplace.

Grocery stores led the way with personalized coupons tied to a shopper's basket. Regional grocers, like Chicago-based Dominick's, a Safeway subsidiary, launched the generally well-received personal discount program JustForU in 2011. Consumers enter their Dominick's preferred card in the JustForU portal to enroll in the program. Over time, the portal tracks purchase history and location factors in order to recommend personal discounts that are applied directly to the loyalty card. Judging by Safeway's strong earnings, programs like JustForU are here to stay.

Most of these new frontiers in retail will continue to gain momentum. With new advances in data, retailers will push the hyper-local shopping experience while simultaneously creating new value in the greater national marketplace.

So as you fight the power machine of modern retail, take a closer look at personalized buyer options that will keep you ahead of, not subject to, the game.

Kristopher Kubicki is chief architect of Dynamite Data.
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