Taking Your Hands Off the Wheel in the Age of Autonomous Retail Pricing

What’s Autonomous Pricing? And how it is different than Price Optimization

By: Todd P. Michaud, President & CEO

Being from California, I have always loved to drive. Whether in the beautiful Sierra-Nevada Mountains or along the stunning California Coastline. I have always appreciated having the steering wheel in my hands, and the wind blowing in my now departed hair. (Cue Telly Savalas, “Who loves ya, baby?”).

Despite being an “excellent driver” (if I say so myself), from time-to-time in years past, I unintentionally have veered out of my lane. Fortunately, the rumble strips just outside the lane give me and everyone else in the car a wake-up call. They were like guardrails for me if my attention waned. 

As my cars have gotten more sophisticated, technologies like “Lane Keep Assist” made sure that I don’t veer out of the lane or trail the car in front of me too closely. The result: I have less dependency on the aforementioned rumble strips.

Today, even more automation is coming to market with the most innovative cars having autonomous features, like hands-off-the-wheel autopilot and/or self-driving mode. These cars can recalculate the best way to get to your destination avoiding traffic, and they can even park themselves once you get there. Despite these advancements, there are some roads where it’s best that the driver has their hands on the steering wheel.

What does this have to do with Pricing?

As you think about my analogy above, similar advances have occurred over the past two decades with retail pricing technology. A little history is in order.

Today, many retailers still depend on simple, rules-based pricing (that originated 20+ years ago) to manage margins and cost changes at the department, category, or subcategory level.  Others are using rules-based pricing in concert with competitive data so they can match or index against their competitor’s retail prices. 

Using rules-based approaches exclusively will result in lost revenue and profit, as they can often create pricing that is out of line with the needs and expectations of your shoppers. More importantly, most retailers simply can’t afford to play “follow-the-leader” when competing with low price leaders or discount chains. 

Recognizing this, some retailers have deployed advanced price optimization solutions to inject consumer demand signals derived from transaction data, into the pricing process. The ability to analyze elasticity at the item and location level enables retailers to understand where shoppers are price sensitive and where they are not. 

Price optimization solutions are intrinsically data-intensive and depend heavily on user adoption and a significant commitment of time on the part of merchants, category managers, and pricing analysts. As a result, driving adoption for advanced pricing solutions has always been a critical success factor when compared to much simpler rules-based pricing solutions. Retailers able to successfully deploy price optimization and drive adoption have generally been able to deliver stronger financial returns for their shareholders, while also being more shopper centric.

Retail pricing in the age of autonomy

In the same way we are seeing automation in cars, we are witnessing a transformation in retail pricing. Autonomous pricing blends the best of rules-based and demand-based pricing into a single platform.

Merchants, category managers and pricing analysts using the latest in artificial intelligence can decide when to take their “hands off of the wheel,” leveraging a strategy-driven autonomous mode and taking full advantage of integrated guardrails. The goal is to eliminate the tedious, mundane, and wasteful interactions required in performing ordinary pricing actions, allowing the system to free up the user to focus on the higher-value areas that actually need human intelligence.

Another key aspect of autonomous pricing is that these platforms leverage machine learning to continuously read signals in the real-time dataflow. They look for anomalies, deviations, trends, and alerts. Prescriptive analytics can then recommend actions to take. Harkening back to my automotive analogy, think of this in the same way that you think of a car that automatically tunes itself.

One of the most important aspects of an autonomous pricing application is a beautiful, intuitive, and fast user interface. Today’s pricing solutions need to be easy to learn and incredibly easy to use. And they must build trust and adoption with their users through transparency.  

Interested in learning more about Autonomous Pricing?

If you are a retailer and are concerned about the effectiveness of your current pricing solution, we’d love to introduce you to our Unify by DemandTec platform and demonstrate our Autonomous Pricing application. Contact us today.

About DemandTec

A pioneering leader in retail pricing, promotion, and markdown technology for decades, DemandTec is ushering in the new era of unified autonomous merchandising. With Unify by DemandTec — the industry’s first — retailers can unite their data, systems, internal teams, and collaborate with suppliers to generate profitable revenue growth with the power of AI.

From food to fashion, DemandTec partners with more than 700 customers around the globe.  To learn more, please visit us at

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