Revionics Gets Dynamic
Dynamic pricing is one of those dangerous subjects that for the retail industry at least is long on opinion and perhaps a little short on understanding. The subject became a front-and-center issue in late 2014 when the business press picked up on Amazon’s pricing practices. It was revealed that Amazon pays close attention to 3rd party prices offered in the Amazon marketplace in order to determine its own price (it also considers the 3d party retailer’s volume and user reviews). To an industry that at the time was still debating whether prices on the eCommerce site should be the same as store prices, the Amazon story sent shockwaves throughout multi-channel retailers. It was later revealed that Amazon also uses a concept called “surge pricing” (made popular – or maybe unpopular!) by rideshare company Uber, where the price fluctuates based on demand and availability.
It’s important to note that dynamic pricing may be relatively new to retail, but it certainly isn’t new to the world. If you’ve ever booked airline flight tickets online you know that prices adjust to the point where demand and supply are (theoretically at least) in balance. So when it comes to some purchases, consumers are already trained to expect variances. There’s also little veracity to the notion that consumers expect online and physical store prices to be the same, or even from store to store. Consumers, while amazingly price conscious, are not necessarily bottom dwellers, lurking in the equivalent of Bargain Alley waiting to gobble up the lowest priced items. What consumers are interested in is “a fair price”, i.e. one that doesn’t insult them.
So it can be argued that consumers are more ready for hyper-elastic – or “dynamic” - pricing than retailers are.
Where it gets sticky is when advocates of dynamic pricing start to talk about it in the context of intra-day price changes in the store. RSR for one has been dismissive of this notion, because the idea of prices flipping in the aisles while consumers are actively shopping seems, (1) hard to manage, and (2) an invitation for consumer fraud complaints. RSR isn’t alone. And so, as it often happens in the retail industry, “the baby gets thrown out with the bath water”, and the concept sometimes gets dismissed wholesale without any regard for the good aspects of it that can be used.
That’s a battle that Price Lifecycle optimization solution vendor Revionics decided to address head-on at its 2017 customer conference, Insight 2017. I attended the Austin, Texas event as a speaker, but I also had time to attend several breakout sessions, including an excellent one on the subject of dynamic pricing. The presenters, Anastasia Laska and Bukky Onilari-Adedeji, are both from Revionics’ European operations – and that in itself is interesting, because a popular belief (probably justified) is that European consumers are much more accepting of dynamic pricing than their American counterparts are. The Revionics team has been working with Russian retailer OZON to implement a dynamic pricing strategy in its market. OZON is an online retailer that primarily sells books, electronics, music, and movies. So by implementing dynamic pricing, it is basically executing a competitive response to Amazon (yes, Amazon can ship into Russia via international shipping specialist Borderlinx). But Revionics is confident that store-based retailers are now paying attention to dynamic pricing. That’s probably a function of two things: first, Amazon’s acquisition of Whole Foods opens up the possibility that the eCommerce giant will bring the concept to the upscale grocer; secondly that the physical difficulties associated with implementing such schemes are getting down to a manageable size.
But the biggest reason why Revionics believes that dynamic pricing has an eventual play in stores is because of consumer attitudes. Revionics’ VP of Marketing in EMEA Laska revealed in her part of the presentation that recent company research revealed that only 17% of global consumers look for “the lowest price”. Anastasia also shared that 78% of global shoppers feels that pricing based on “data science” is “fair”.
The conditions seem right. Now it’s a question of when and how retailers are going to make the leap.
What It Is/What It Isn’t
As part of her presentation, Laska framed dynamic pricing by clarifying what it is and isn’t. First, what it isn’t:
- Low price strategy
- Competitive matching strategy
- Time of the day pricing
- Price gouging/inventory based pricing
- Personalized pricing
- Only for online
According to Anastasia, “Dynamic pricing solutions monitor the market for shifts in shopper demand and the competitive landscape, only recommending a price change for an item when it’s warranted.” With that in mind here’s, what it is:
- The dynamic flexibility to systematically adjust price with the needed frequency
- Keeping the balance of the FAIR price customers are willing to pay while protecting margins for the retailer
A key component to a dynamic pricing system is its competitive price analysis capability. Revionics has developed a competitive price engine that can capture competitive data, “normalize” it (in other words, analyze an item by attribute, condition, pricing history and trend, to match it to a retailer’s similar item), and then based on a retailer’s objectives, develop a competitive response. This to me has been the missing piece in what some have called “dynamic pricing”, which more often than not was merely a low-price response capability. Much to the Austin company’s credit, it has been focused on developing this feature in spite of skepticism in the marketplace about the whole dynamic pricing concept.
The question is, can it get to the store? My own take is, “yes, but with great caution”. Discussions of dynamic pricing are inevitably tied to electronic shelf labels (ESL technologies). These have been around for 25 years – since the early 1990’s. But the cost and expected life of tags has been prohibitive, as well as the cost to prep a site to implement them. But as with most things “tech”, the prices have come down, and the capabilities and ease-of-use have improved. Still, the most frequently touted use-case (eliminating the need to manually update paper shelf labels) has never been enough to justify the cost. So what has changed? Retailers may not want hyper-elastic intra-day price changes in the store, but the ability to change much more frequently than in past times, perhaps as frequently as daily. What makes that possible to consider are those study findings that consumers are “okay” with elastic prices as long as they understand “why”.
A retailer’s ability to eliminate the lag time between a need to change prices for competitive reasons or to take advantage of dynamic shifts in demand, and making the change without the burden of labor to execute price changes in the store, could create a compelling ROI. Revionics is counting on it.
What Retailers Need to Succeed
The Revionics speakers offered advice to retailers about what is needed to consider a dynamic pricing solution. Here it is:
Understand the Consumer
•The speakers underlined that it’s crucial to understand the selling environment, the shopping journey, and to understand what influences consumers’ purchase decisions. This goes beyond price sensitivity to include other environmental conditions.
Price against Meaningful Competitors
•The emphasis here was on the word “meaningful”. Retailers need to understand which competitors truly affect their sales, and how best to position products and pricing to achieve pricing objectives.
Omni-channel Strategy & Management
•As RSR has said repeatedly, “consumers don’t see channels”. Therefore, pricing strategies (including dynamic pricing) can’t focus only on one channel.
Implement A Real-time Integrated End-to-End Solution
•Retailers need current and accurate competitive information to intelligently determine when to act, or not to act, in something approaching real time, and to execute the desired price changes.
Science & Technology Can Help
•There are a lot of different ways to say this, but short-and-sweet, dynamic pricing cannot be implemented without using modern analytical technologies that that deliver math-based results, constrained by business rules.