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The retail environment for convenience stores has never been more challenging and the list of influences that can negatively impact profitability is growing. Although convenience stores are known for providing speed and convenience, today’s shoppers are more price-sensitive, have complete price transparency, and are becoming more resistant to paying a premium price.
According to Nielsen, only 44.2 percent of convenience channel shoppers are willing to pay a premium price, ranking last behind grocery, club, drug and mass. With price being one of the highest influencers, it's not surprising that use of price optimization within convenience stores is nothing new. Many convenience stores jumped on that bandwagon over a decade ago, and the pace at which more convenience stores globally are climbing aboard is at an all-time high.
Convenience stores are heavily dependent upon drivers for in-store traffic. The percentage of 18-year-olds with drivers’ licenses has declined from 87 percent to 69 percent over the past 30 years, and the number of trips is down more than 1 million since 2012, according to Nielsen.
In addition to the decline of in-store traffic and a price-sensitive shopper, the competitive threat against convenience stores becomes more hostile as retail channels become more blurred due to the growth of e-commerce, easy pickup and delivery options, and the growing trend toward smaller store formats, directly competing for the same shoppers.
What Is Price Optimization?
Price optimization leverages machine-learning science to determine the most optimal price shoppers are willing to pay, while successfully helping the retailer compete and achieve their strategic and financial objectives. Consuming massive amounts of shopper behavior data, along with competitive pricing, seasonality and much more, it can dynamically learn and pick up shifts in the market such as the changing price sensitivity or elasticity of the shopper. Also, it can understand (or rather learn) the competitive elasticity and predict the impact of competitive prices on your demand.
Price optimization can sense and predict where and when shoppers are willing to accept price changes. It then leverages this intelligence to align a retailer’s pricing to deliver the most optimal price at the item/store/channel level, creating a win-win for the shopper and the retailer.
Overcoming Early Failures
Price and promotion optimization have been around since the beginning of the 2000s. Many early solutions failed to gain adoption for several reasons They were not strategically oriented to help retailers achieve specific strategies such as margin enhancing, basket building, or traffic driving, to name a few. Most importantly, the science was “black box” and non-productized. Retailers were expected to trust recommendations that went completely against their gut instincts.
Not knowing they would need to periodically bring back a team of the vendor’s data scientists to refresh the scientific models meant that the models grew more and more out of sync with the market and shoppers. The result: lack of adoption and massive flipping of the switch to the off mode.
There have been many advancements in innovation since then, resulting in much-improved second-generation price optimization solutions. The science is more advanced, productized, and self-learning. Complete transparency in the "why" behind the recommendation has replaced the black box.
As a result, price and promotion optimization are rapidly gaining adoption and moving more into the mainstream for retailers.
Is Dynamic Pricing the Silver Bullet?
Now that we have established that convenience stores have been successfully using price optimization for years, let's shift to the highly charged topic of dynamic pricing — or more accurately, high-frequency pricing.
Today, retailers are limited in how many price changes they can execute due to store labor constraints. Price optimization solutions can work within these limitations. If a retailer can only implement 50 price changes, price optimization solutions are intelligent enough to recommend the top 50 that would deliver the biggest bang for the buck. However, the full value of the solution is untapped, as these solutions can optimize across the full assortment at an item/store level.
The luxury of long leads and making price changes to only a fraction of the retailer's assortments are no longer a sustainable approach. Retailers, including convenience stores, are unleashing the full power of price optimization by employing dynamic pricing.
Dynamic price optimization, when combined with electronic shelf labels (ESLs), allows retailers to execute more frequent price changes on items that require it. Dynamic price optimization systematically adjusts prices when it's necessary due to a shift in shopper's price sensitivity levels, or as needed to maintain a competitive strategy. Although automated, it runs within particular guardrails and will alert the retailer for manual approval if the price recommendation falls outside those guardrails.
Convenience store retailers need to continue to look for ways to remain relevant and protect margins. Dynamic price optimization has been giving retailers of all shapes and sizes globally a competitive edge — and it’s not exclusive to the online world.
Editor’s note: The opinions expressed in this article are the author’s and do not necessarily reflect the views of Convenience Store News.