Keeping Your Hands on the Wheel in the Age of Autonomous Retail Pricing

Being from California, I've always loved to drive. Whether in the beautiful Sierra Nevada Mountains or along the stunning California coastline. I've 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're guardrails for me if my attention waned.

As my cars have gotten more sophisticated, technologies like “Lane Keep Assist” make 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 re-calculate 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-plus years ago) to manage margins and cost changes at the department, category or subcategory level. Others are using rules-based pricing along with competitive data so they can match or index against their competitors' retail prices.

Using rules-based approaches exclusively will result in lost revenue and profit, as they can often create pricing that's 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're 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're seeing automation in cars, we're 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 (AI) 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.

Todd Michaud drives DemandTec's vision, strategy and execution in creating and delivering the industry’s leading unified merchandising and vendor collaboration applications for retailers and their supplier partners.