From the magazine: Can dynamic pricing work for the aftermarket?

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[Trigger warning: The following article may upset Bruce Springsteen fans.]

Dynamic pricing is all around us.

If you book a flight, ticket prices can vary by day, season or proximity to travel date, among other factors. If you load up your Amazon cart and leave it sitting around, you can watch the prices of your selected items change every day — sometimes by just a few cents, sometimes by tens of dollars.

And if you tried buying tickets to a Bruce Springsteen concert recently, you may have had to fork out up to $5,000 for the privilege of watching “The Boss” in action — all thanks to event retailer Ticketmaster’s demand-driven strategy. The resultant outrage highlighted the double-edged sword that is dynamic pricing. Think Uber and surge pricing: It is a love-hate relationship, right? Sporting events are famous for dynamic pricing with ticket costs changing based on the opponent and day of the week.

So dynamic pricing is not exactly new. But the aftermarket has remained largely insulated from this approach. That is slowly changing. U.S. parts retailers — both traditional competitors and e-commerce pure players — have started to introduce real-time pricing across their platforms. The current inflationary environment and the recent supply chain issues are speeding up the process.

Even automakers and parts suppliers are beginning to roll out automated, multi-variate pricing strategies in response to market pressures.

Dynamic pricing: The good

The benefits of dynamic pricing are clear. At a fundamental level, it allows a company to modulate its product pricing in real-time based on evolving business conditions.

Other pricing approaches are one-dimensional. With a cost-plus strategy (still the default mode for a broad swath of the aftersales business), companies are simply aiming to protect a fixed margin target. With a competition-based or value-based approach, businesses are relying on market positioning or customer preferences.

Dynamic pricing puts all the above into an algorithmic pot, adds other inputs such as seasonality, inventory levels and more, and serves up an optimized price. Price actions do not follow a pre-determined schedule. Rather, changes are triggered by the magnitude and frequency of the inputs.

Let’s say, if freight costs go up, prices are adjusted according to profit targets. But, if the product faces stiff competition, the adjustment factors in both margin and market position. If the product is also highly valued by customers, the output now trades off between the relative influence of the three inputs — margin, market, and customer. You get the picture; the combination of influences is endless.

Dynamic pricing cannot be executed manually because it would take too many people. Companies rely on sophisticated software that work on rules-based machine learning and artificial intelligence to monitor and action price changes. The software, in turn, acts on the basis of high-frequency, automated data streams to power these changes.

How can dynamic pricing work for the aftermarket?

For the do-it-yourself (DIY) market, dynamic pricing is already in action. Most aftermarket retailers have implemented pricing tools, particularly for their e-commerce platforms.

But, unlike the U.S., Canada is still largely a do-it-for-me (DIFM) market. Can a vacillating pricing strategy work in this business-to-business (B2B) dominant environment? The answer is yes — if you have a clear view of its benefits.

For a supplier, it provides a mechanism to adjust prices according to customer urgency, lead times, and manufacturing capacity for a particular product. It allows sales teams to create automated selling processes based on previous wins and losses as well as current and future market conditions.

The advantages are even more apparent for distributors and retailers selling into automotive aftermarket maintenance and repair shops.

Currently, aftermarket B2B transactions are increasingly happening through digital platforms — a prerequisite for a dynamic pricing strategy since e-commerce enables a feedback loop of data and insights. For instance, what are daily the purchasing patterns of a technician? What products are being purchased by the business? A dynamic strategy allows a near, real-time understanding of such behaviour, enabling the distributor to understand cross-selling and bundled pricing opportunities for that buyer.

Dynamic pricing can also reward both buyer and seller.

Let’s say a particular shop is undergoing a sudden spike in repair traffic. Under static discounting frameworks, installers get price breaks on a pre-determined volume, driven by seasonality and prior purchase behaviour. But within a self-regulating environment, these rebates could be applied based on ongoing purchasing patterns, thereby creating greater loyalty and purchase satisfaction.

For the distributor, the benefit comes from any increase in order volume and revenue spurred by such spot discounting.

Is the aftermarket ready?

Dynamic pricing is a delicate dance. Get it wrong and you risk alienating customers for real or perceived “price-gouging,” as in the Springsteen-Ticketmaster case. Even worse, you risk squandering revenue from potentially “pricing down” a product.

To make dynamic pricing work, businesses need a steady stream of accurate and diverse data. The trouble with the aftermarket is there is precious little of it. And to be very honest, there seems to be little appetite to share and use data in the industry. The U.S. is bad and Canada is even worse.

For instance, granular, industry sales volumes are a given in most industries — even in certain B2B-heavy sectors such as the medical industry. No such luck in the aftermarket. Most competitors rely heavily on internal data and simply extrapolate those numbers to generate industry guesstimates. Many think that price crawlers — the use of automated data extraction to match market pricing — alone can power dynamic pricing.

If the aftermarket wants to take dynamic pricing seriously, it must up its data game. It must create internal processes to create, consume, and digest data. The industry must also create mechanisms to share data more effectively.

Without the right data, dynamic pricing might as well be … dancing in the dark.

Kumar Saha is the Toronto-based vice president (U.S.)/managing director (Canada) of global automotive intelligence firm Eucon. He has been advising North American automotive industry for over a decade and is a frequent conference speaker and media commentator.

This article originally appeared in the September/October issue of Jobber News