Guest Column: This Might Change How You think About Price Optimization
More than half of retailers are investing in artificial intelligence (AI) this year, and if you’re reading this, you’re probably working for one of them.
The dialogue around AI in retail is endless, and it isn’t just talk anymore. AI is here. Its presence, while new, is undeniable and is progressively changing retail forever. According to the National Retail Federation, the number of retailers investing in AI technologies is expected to double over the next two or three years.
That means if your competitors aren’t using AI already, they will be soon. A profoundly different way of doing business and reaching your customers is coming into focus and moving commerce forward faster than ever before. The days of guesswork and relying solely on seasonality and historical data are history.
The new approach is centered around exacting precision and accuracy that only AI and machine learning provide. These technologies, along with the Internet of Things (IoT) and powerful shopper data, are fueling a more powerful customer experience while also raising the competitive bar for retailers. And when it comes to competing in retail, nothing is more significant than pricing.
Pricing is a demand lever that retailers can use to create powerful, profitable demand. Your pricing should align with your approach to assortment optimization, merchandising and localization. Pricing should also support how your business channels your brand and the way it is marketed and positioned. Positioning the right price with perfect timing and the appropriate medium or location is everything right now.
We are seeing technology move pricing forward in some major ways. First, let’s talk about optimization.
AI and machine learning are literally redefining price optimization Until recently, price optimization meant traditional mathematical analysis discerning how shoppers are engaging with different prices for products and services across every channel. Price optimization calculates the prices that align with business goals, including maximizing profits.
Now, price optimization is all about your data and where it’s coming from. Powerful price optimization applies forecasting in a variety of machine learning and optimization sciences. Machine learning sets processes for logical product groups (assortments and product lines) across times (seasons, weeks and months) and locations (price zones, touchpoints online and in-store). And using AI, price optimization constantly includes one important variable – what will happen next?
When it comes to pricing and demand, retailers aren’t just looking backwards anymore Retailers who previously relied on historical demand to guide pricing are asking, “What’s next?” Now, in addition to how demand looked in the past, they’re using technologies that factor in hundreds of other variables. While buyer behaviors are more unpredictable in our on-demand economy than ever before, now retailers have access to immense reams of data. This data includes past sales patterns and customer footfall, along with external information like the weather, current events and public holidays.
AI and machine learning drill down to weather, events, sharing patterns across social media and more to calculate the probability of demand levels for the future. With these technologies, retailers can mine actionable takeaways to navigate consumer preferences and demand to create more intelligent shopping experiences.
The most advanced AI solutions don’t only make predictions and insights. They actively advance your price optimization with accurate real-time data that drives more revenue and sustainability.
Better pricing means less waste and higher profits Using true AI and machine learning solutions, retailers are adopting dynamic pricing models that prevent excess stock. That means fewer products going unsold – in store or online. With AI, retailers are charging full rate for the season, and adapting pricing strategy towards season end, or when any excess stock needs to be sold.
AI also reduces waste significantly. It can predict customer demand and accurate pricing decisions across every product category and store – learning the complicated relationship between price fluctuations and demand. All the while, these technologies align to the retailer’s business strategy. At the end of the day, more intelligent pricing frees your team members up to focus on something more important, your customer experience.
AI and Machine Learning bring your team members back to the human experience When retailers tap into shopper data and deeper insights from AI and machine learning, they can act strategically and put more of a focus on their customer experience across every channel.
We are still seeing a lot of fear around AI in the retail industry and what it means for jobs. In reality, technologies like machine learning and AI are supporting more businesses in keeping their stores profitable and their employees dedicated to initiatives that drive customer loyalty and a more positive shopping experience. A higher level of innovation is necessary to maintain a competitive edge and keep pace with disruption – are you ready?
JoAnn Martin is VP of retail industry strategy and market development at JDA Software.