The danger to retailers who fail to evolve through innovation

The danger to retailers who fail to evolve through innovation View from the Front Lines: Retailers Must Innovate – or Risk Failure
March 22, 2019 Michael Terpkosh

Retailing is Not for the Faint of Heart

The complex, fast-paced state of retailing today is not for the faint of heart. In the relentlessly competitive environment, the stark reality is survival of the fittest. And it’s imperative that retailers must innovate to evolve and survive. Merely trying to define “retail” is becoming more challenging – the new reality is that the definition of retail must include the perspective of the consumer. When looking at retail (or the competition within retail), including brick-and-mortar, omnichannel, e-commerce and everything in between, the awareness that today’s consumer has a very dynamic definition of retail is critical. The term “channel blurring” no longer applies only to the consumer perception of retailers in a particular type of channel, department or category, but is also a competitive term as more and more retail channels compete for consumers dollars in each particular category.

The New Competitive Landscape

For decades, the grocery retailing channel limited its focus to competition within a narrow definition of the grocery channel itself. Then came along the industry’s most feared competitor, Walmart. Soon after, the industry introduced category killers like PetSmart and PetCo. followed shortly thereafter by the dollar stores. Today, competition comes from a proliferation of retail formats and channels as well as convenience stores, home improvement stores, and of course e-commerce. Being competitive in retail is much like the imperative for adaptation over time in order to survive. You can hope for a lucky positive environmental change, but a more proactive and deeper understanding of the retail environment, along with a strategic focus on how to chart the journey, is necessary to allow you to not just survive, but adapt and thrive. This means understanding the continually expanding competition while also diving deep into understanding the consumer. Retailers today can easily miss consumer and competitive signals, but a retailer’s inability to comprehend and interpret these signals can lead to certain extinction.

The Need to Evolve & Remain Relevant

Many retailers over the years have started out innovative in a particular retail space. They were considered progressive and leading edge, the new “bogeyman” of competition that would take the retail industry by storm and destroy perceived lesser competition. Consumers loved them (not to be confused with any sense of customer loyalty). Many of these retailers who patted themselves on the back, congratulating themselves on their innovation, no longer exist today or only exist as a pale shadow of what they once were. Their downfall was their inability to continually improve, stay nimble, and remain relevant with the consumer.

In other words, they failed to understand the changing consumer signals and adapt to the changing competitive, retail environment. Today’s consumer is more diverse ethnically, economically and generationally. Their shopping journey expands across more channels and their loyalty is virtually non-existent. Being the bright shiny new retailer of today could easily be the old, tired retailer of tomorrow if they fail to evolve and remain relevant. Even in the fast-paced world of digital and e-commerce, a consumer preference on where to shop may be influenced by something as nebulous as fewer clicks to purchase or the consumer perception of price.

For a retailer to adapt and stay relevant today means understanding a dizzying abundance of data from consumers, shoppers, competition and internal data sources. Signals come from everywhere in the form of data and overwhelm the limited human ability to interpret them. A retailer’s internal data about shoppers alone is only part of the holistic data puzzle. A deeper understanding of the greater retail world and greater consumer understanding is necessary to complete the data puzzle, including the complete purchase path of a consumer being drawn into retail to become a shopper with the hope of creating a repeat customer. When the data puzzle is assembled, it is still only one step on the retailer’s adaptive journey.

The scale of data can easily create a scenario of becoming painful overhead… costly to maintain, unmanageable and unactionable. In the past, retailers had to hire an army of programmers, analysts, thought leaders and management to wade through all of the data in hope of signal interpretation, and it took an inordinate amount of time to analyze and create the actionable insights from that interpretation. Adaptation to today’s changing retail environment to handle overwhelming abundance of data, shifting marketing conditions, short lead times, increased costs and competitive pressures is absolutely necessary but not possible using historical approaches and spreadsheet technology. Just as survival of the fittest is the law of nature, it applies today in a data-driven retail environment.

Winning at Pricing Through Artificial Intelligence

Fortunately using Artificial Intelligence (AI) science capabilities offer a realistic path for any retailer to adapt, evolve and stay consumer relevant. They deliver faster analytics and insights for retailers, allowing for nimble decision making, both strategic and tactical, to quickly respond to the changing nature of the business. Regardless of whether your shoppers, consumers or competitors are changing the retailer gains the ability to immediately detect signals and appropriately react to succeed rather than go extinct.

When properly implemented, AI \ can move a retailer beyond signal recognition and reaction to real-time changes to also start to analytically look forward, predicting where their shoppers and the consumers are headed. With these forward-looking insights they are rewarded by the consumer as “on trend” or “fashion-forward”, translating into retail sales.

Better insight into the changing retail environment is only part of the abilities of AI. All retail channels struggle more than ever with their pricing and promotions, competitor pricing and promotions and the consumer perception of pricing/promotion. In our digitally connected, e-commerce world, price/promotion shopping is frictionless, and in many applications seamless, and they remain key purchase drivers. What makes AI critical in this space is the ability to identify shoppers’ sensitivity to price and handle extremely large amounts of pricing and promotion data (internal and competitive) to understand the most efficient and effective pricing tactics to create consumer interest, positive price perception and ultimately drive purchases. The traditional practice of set a price or try a promotion (trial and error) is not a viable approach.  Only through the use of AI pricing science can a retailer analytically determine the optimal price/promotion combinations that are the most efficient for the retailer and most effective for capturing consumer dollars and loyalty.

Find the Right Partner

Retailers need to understand that they can’t go it alone to develop their own internal AI shops. Just as it is no longer feasible to hire the army of associates needed to analyze immense amounts of signals and data, it is generally not possible for retailers to build their own AI platform or team. Partnering with the right AI solution provider who have spent years building refining techniques and building the right models that have been learning and reaching new heights of intelligence allows a retailer to leverage deep AI expertise, quickly moving their data from being company overhead to driving actionable analytics, nimble decision making and fast retail execution. Being truly adaptive can mean partnering to create symbiotic relationships, and finding the right ML and AI partner can create an adaptive leap forward for any retailer. A good AI partner will have a strong toolkit that will be analytical, predictive and more important, prescriptive. It should allow for “what-if scenarios” to model different pricing strategies, be SKU/location specific, provide complete transparency into its recommendations, referenceable and proven in the marketplace.

In Summary

As the retail environment continues to evolve and become more complex, one fundamental retail fact never changes… understanding the consumer is paramount to survival and success. Interpretation of signals and acting upon these signals is no longer optional. AI is now foundational table-stakes to creating and maintaining retail success. In fact, a recent Revionics-commissioned global study conducted by Forrester Consulting found that 76% of retailers believe AI-driven pricing would have a positive impact on shoppersi. But knowing and doing are two different things. Will these retailers adapt, survive and thrive in the future? Survival through evolution often means taking small but deliberate steps to adapt to a changing world. This remains true in retailing today and AI is here to help.


iRetail Success Requires Personalized, AI-Driven Pricing Strategies, a Revionics-commissioned study conducted by Forrester Consulting, October 2018