3 Ways Brands Can Thrive in a Dynamic Retail Industry

Traditional retail may be doomed, but its complexities extend far beyond common scapegoats, the Internet and eCommerce. The retail industry is more dynamic than ever before, and it’s driven by customer preferences and demand.

In this post, we’ll discuss today’s dynamic retail industry, and we’ll offer some solutions for thriving in this increasingly cutthroat environment.

The end of “bad and boring retail”

John Costello, former president for global marketing and innovation at Dunkin’ Brands, said recently, retail isn’t dead, just boring retail is. Echoing this sentiment, CVS Pharmacy President Kevin Hourican declared, “Retail isn’t dead. Bad retail is dead.” 

But how do you characterize boring or bad retail?

In truth, it all comes down to data and traditional tactics, from universal store inventories to promotional flyers, no longer meeting customer expectations. By way of eCommerce, customers have come to expect experiences that are convenient and personalized, so it should come as no surprise that they’d expect the same upon walking into a store. 

Data is the key to making this expectation a reality; advanced analytics, AI and ML afford the insights necessary for improved store-level inventory and pricing decisions, and they can help you determine which opportunities will yield the most profit.  

Three Ways to Thrive in Today’s Retail Industry

1. Enhance the customer experience

We’ve said it before and we’ll say it again – today’s customers DEMAND better experiences. This begs the question, what more can retailers do?

Simply showcasing the latest styles won’t suffice, but retailers can offer complementary styling appointments, tailoring services and in-person previews of upcoming trends. Each of these enhances the customer experience, and it incentives customers to visit a store.

You may be wondering, how is this tied to advanced analytics?

Well, of the slew of advantages advanced analytics affords, one is the ability to build complex consumer profiles and segments.

What customers will most likely to respond to promotional styling? Which products are the right products to highlight? Advanced analytics can answer these questions and more, and with this knowledge, retailers can confidently offer new products and services.

2. Personalize your offers

Services aside, dynamic promotions and enhanced personalization improves customer loyalty and, by extension, sales. In one Promotion Optimization Institute survey, 70 percent of millennials said they are very or somewhat interested in personalized offers, and these shoppers are happy to provide information about themselves to get them. 

To strengthen loyalty and sales, retailers will need to employ advanced analytics and AI. Using a customer’s purchasing history, AI delivers personalized offers directly to an individual’s phone, and these offers include, but are not limited to, relevant sale items, related products, and even notifications on a local store that’s started to offer additional services, like the aforementioned complementary styling appointments, tailoring services and in-person previews of upcoming trends.

3. Identify the right ways to grow

There’s intense competition from eCommerce and other retailers, so being strategic is hugely important.

One of our clients mailed over one million catalogs each year that didn’t deliver sales. We determined which catalog recipients were least likely to buy, thus enabling the client to redeploy funds more effectively to high-propensity shoppers. 

Using deep learning, a subset of AI, we created quantitative models to help us predict who, out of the 1.2 million non-buyers, wouldn’t buy. We divided the non-buyers into three segments:

  • Recent buyers (12-0 months)
  • Lapsed buyers (13-24 months)
  • Prospects

We also had access to transactional data (orders placed, average order value, first transaction date, discounts, etc.), SKU attributes data (colors/sizes ordered, departments, etc.) and mailing lists, and every customer had a unique profile with detailed preferences, like;

  • Wears blue and green
  • Can’t resist a 20% discount
  • Shops early spring
  • Prefers skirts over pants

AI helped us unearth customer preferences for more targeted messaging and personalized offers, and our analytics delivered a net benefit of more than $10M for our client; our predictions on non-buying customers were 99.8% accurate, by removing non-buying customers, our client saved $7.3M, and they also saw $2.9M in additional profits.

Thriving in today’s retail environment

Today’s retailers have to evolve; brick and mortar stores must have product assortments that reflect their local clientele, and retailers should drive foot traffic through specialized services and personalized offers.

Today’s industries are driven by data, and the retail industry is no exception.


See how Antuit helps multi-national and high-growth companies around the world predict, shape and meet demand.

Learn more