Are the Machines in Control of Dynamic Pricing?

A member of our sales team was conducting a demo to a European retailer who was interesting in implementing dynamic pricing for his ecommerce outlet. The two of them spent the better part of an hour talking about artificial intelligence (AI), going over the way the system worked, and discussing the bottom-line benefits our clients typically experience. The demo seemed to be going well, but our sales rep could sense something was bothering the retailer.

As the session neared a close, the retailer was finally able to articulate his concern. “If I implement a Quicklizard system with artificial intelligence,” he asked, “will I lose control of my pricing?”

It’s actually a really common question, and one that we hear frequently while talking to potential customers. How much control will you give up when you introduce an AI-based pricing system.

Keeping on Top of Pricing

There are several controls put in place in the Quicklizard system, which allows you to keep or cede as much control as you’re comfortable with. For starters, pricing is based on several elements. There is the AI and machine learning (ML) element of course, but there are also user-based rules that you control to ensure that the pricing engine doesn’t recommend prices that are too high or too low.

For example, users can control minimum and maximum margins. With this in place, the system’s price recommendations will never go below or above an unacceptable threshold. Users can also create rules regarding frequency, so that pricing recommendations are only offered once a day, once a week, or once a month. Users can also ensure that prices stay within a set percentage of competitor offerings. In general, we recommend that prices be 20% controlled by user rules, and with the other 80% AI-driven, but that 20% puts users in the driver’s seat.

Another control put in place is your ability to accept or reject the system’s price recommendation. If you prefer to maintain a specific price on an item or line of items, you can easily reject the system’s price recommendation.

Growing with AI-based Dynamic Pricing

As our customers get more comfortable with dynamic pricing, and start seeing increases in revenues and profits, they typically start to increase their trust the system. User rules are used to define pricing strategy rather than to limit the AI component of the system.

With a user-defined pricing strategy in place, retailers allow the system to automatically adjust prices without requiring pricing manager approval. This typically happens in stages, where initially the system can implement recommendations for pre-defined lines of products, before eventually having the ability to change prices on all lines and products.

Is the User or AI in Control?

With Quicklizard’s dynamic pricing platform, even our most advanced users guide the AI engine, by defining a pricing strategy through user-defined rules. However, beyond setting a strategy, our users have the option to be as hands-on or hands-off as their comfort level allows.

Find out how Quicklizard can get AI working to increase your bottom line. Click for a Demo today!

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