3 Ways Retailers Can Harness Consumer Data to Up Their Game

In the not-too-distant future, your mobile device could order clothes, furniture, groceries, and other items for you based on your favorite brands, price limits, sizing, purchase frequency, and other factors. Why? Because of the data that accumulates with every action you take online (and even in brick-and-mortar stores).

Retailers are already using big data to optimize pricing, forecast demand, and predict trends, as a Forbes article pointed out last year. Yet as the technology around collecting and connecting data continues to improve, retailers are upping their game in an effort to meet lofty customer expectations. Below we discuss three ways retailers can harness consumer data in the digital age to better entice and retain customers.

1. Personalizing the Shopping Experience

Thanks in part to brands like Amazon, patrons today expect personalized recommendations and tailored messaging. With consumer demand high for quality customer experiences, the pressure is on for retail businesses to satisfy their shoppers. Better utilization of consumer data will help retailers meet those expectations and understand the priorities of their customers.

Personalized messaging matters because it can positively impact purchasing behaviors, help retailers retain customers, and create stronger brand loyalty. In a survey by Infosys, 86 percent of respondents said personalization influences their purchases, and 31 percent wished their shopping experience was more personalized.

Most retail technologies already aggregate consumer data to help forecast inventory, understand buying patterns, and evaluate the effectiveness of campaigns. Retailers can expand their use of that data to discern shopping behaviors, priorities, messaging effectiveness, and more — then craft a unique shopping experience for every individual. Women’s clothing retailer Ann Taylor, for example, provides site visitors with custom recommendations based on browsing history and similar purchases by other consumers (shown in the screenshot below). The company also sends personalized emails to accountholders with product suggestions based on their past purchases.

ann taylor personalized recommendations

2. Powering Promotions with Data

Retailers must also face the fact that one-size-fits-all promotions are becoming obsolete as consumer preferences migrate toward more personalized messaging. In this case retail businesses can again use interpretations of consumer data to formulate personalized coupons, real-time offers, localized promotions, and product recommendations.

For instance, data reflecting a consumer’s shopping decisions and inclinations can tell a retailer which product-specific promotions would most interest that consumer. Dunkin’ Donuts uses customer data to identify the best targets for promotional offers, then tracks the generated revenue and whether the customers are more likely to return without incentive. And by monitoring shopping history, retailers can offer custom promotions on recently viewed items or for abandoned items in the consumer’s virtual shopping cart.

Geotargeting is yet another valuable tactic for applying consumer data to create more relevant offers. A retailer can use geolocation data to identify weather patterns for a customer in a specific region, then provide a deal for products related to that climate — say a 20-percent discount on raincoats for customers in an area forecasting rain storms.

3. Reimagining the Consumer’s Journey

Artificial intelligence (AI) is a less-explored but promising technique for retailers looking to take their data-driven strategy to the next level. Theoretically, AI could be used to bridge the gap between understanding a customer’s shopping behaviors and knowing what the customer will want to buy next.

As Sentient co-founder Babak Hodjat put it, AI could transform “the online experience into something more like talking to an experienced salesperson at a brick-and-mortar location.” Hodjat also notes the potential for retailers to apply AI to how their consumers shop, giving the example of shoppable images. Companies like CamFind and Pinterest already offer a visual search tool with snap-and-buy capabilities (see Pinterest’s app, right).

pinterest visual search

Imagine how widespread use of this technology combined with consumer data could revolutionize shopping. What if every time you took a picture with your mobile device, an app could recognize the purchasable items and recommend similar products based on your shopping preferences and behaviors? From where we’re standing, it’s not such a far-fetched idea.

Stay tuned for more insights on the retail industry — and don’t forget to check out Numerify’s retail webinar!

[Image courtesy of flickr user Caden Crawford.]

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