Crawl, Walk, Run: A Phased Approach for Adopting a Pricing Strategy

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Crawl, Walk, Run: A Phased Approach for Adopting a Pricing Strategy

By Cheryl Sullivan - 08/17/2017

There is a paradigm shift taking hold in retail. The growth of e-commerce, a hyper-competitive market environment and dramatic changes in shoppers’ purchasing behaviors is driving retailers to close stores and file for bankruptcy at record rates. Bloomberg cites Credit Suisse research showing that year-to-date store closings in the U.S. are outpacing even 2008, when the Great Recession was at its most acute.[i]   

Retail as we knew it no longer exists, and the days of long lead times, Excel spreadsheets, and “gut feel” are dead.  Today retail winners are powered by cloud-based technology, big data and science, moving at speeds no one could have predicted.  As Warren Buffett said of retail at the Berkshire Hathaway annual meeting, "The world has evolved, and it's going to keep evolving, but the speed is increasing."

In order to survive, retailers are being forced to dramatically reinvent their supply chains, restructure their organization, and redefine their core business process – a daunting and very expensive undertaking.

With price as a primary purchase driver and a major contributor to margin leakage, it’s no wonder many retailers place it at the top of their challenges to tackle. Fortunately, price optimization can be implemented in a crawl, walk, run paradigm for easy implementation and adoption. With the ROI from each stage more than funding the next, retailers can even reinvest in other areas of innovation.

Crawl

At the “crawl” stage, retailers need to gain a solid understand of both shoppers and competitors and a clear-eyed view of how effective their pricing and promotions really are:   What worked, what didn’t and why?  They need to build solid pricing and promotional strategies – driving margin, growing basket, generating traffic, enhancing price image – and know which products can help achieve them. 

In addition, they must understand which items are important to most customers, commonly referred to as KVIs (Key Value Items), whether their price zones are accurately defined, and what basket affinities exist. Good analytics typically reveal counter-intuitive insights. For example, did you know for a typical retailer that 90% of its promotional revenue comes from the top 30% of promotions while 85% of profit comes from just 15% of promotions? And a third of promotional revenue lift comes from the cannibalization or drag effect of other items while only 5% of promotions drive incremental profit – in other words, 65% of promotions add to profit, which is in turn wiped out by the remaining 35%?

Walk

During the crawl phase, retailers can get the low-hanging fruit and dramatically boost margins.  

In the walk stage, retailers move on to implement price management (rules-based pricing) and forecasting, allowing them to align their pricing to key policies such as good-better-best relationships, family and promotional groups, end number rules, MAPs, etc. The underlying science understands how shoppers react to price and can predict with high accuracy the impact of systematic price changes that are aligned to support category strategies and business rules or policies.  Retailers can model different strategies, see them side-by-side and implement new strategies with ease.  Additional ROI can be derived in the walk stage.

Run

In the run stage, retailers move to price optimization, applying Artificial Intelligence (AI) science to determine the shoppers’ price sensitivity or elasticity level by item and to see how raising or lowering a price will impact demand and overall performance.  It leverages the information as a key driver to recommend optimal price that shoppers are willing to pay across a retailer’s entire assortment.  In addition, it determines competitive elasticities, isolating the key competitors who matter and leveraging that information within its overall recommendation.

The Run stage has been around for a long time and the AI or Machine Learning science continues to advance. Today, many retailers are even moving to a “sprint” stage, utilizing dynamic price optimization to monitor the market and dynamically adjust prices at a high frequency (typically daily or even intra-day). Dynamic pricing is automated and runs in a hands-off mode, adjusting prices when market shifts such as shopper demand or price sensitivity changes warrant it. Although it can fully operate on its own without human intervention, it will only make a price change that is within the retailer’s predefined guardrails, flagging exceptions and alerting retailers so they can manually review them.

Implementing pricing and promotional solutions and getting to full adoption can seem daunting. However, cloud-based technology and science is now modularized to enable adoption at whatever speed is suitable for a retailer’s unique situation. It can provide substantial ROI at each stage, providing retailers with the funds necessary to propel them to their optimal end state with very little initial investment. 

-Cheryl Sullivan, Chief Marketing and Strategy Officer for Revionics