Have you heard the urban marketing myth about the 1% Black Friday promotion? A retailer reduced online prices by 1% every time a shopper purchased a particular item. The marketing team thought this retail pricing promotion was genius. Shoppers did not.
Shoppers kept refreshing their screens, expecting others to buy and the prices to drop. But the (heavily inflated) prices didn’t budge, as shoppers continued to wait. Some vented on social media and many abandoned their carts. That kind of promotion can generate a lot of buzz, but it won’t win wallet share or customer loyalty.
More than half of consumers expect inflation to affect their holiday purchases this year, with two-thirds saying they’ll buy items on sale. Half say they will buy less overall. There’s no denying competitive pricing will play a big role in winning shoppers’ business. The good news is AI can give you a competitive edge by recommending dynamic price and promotion strategies that make shoppers merry.
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You may already use predictive AI to analyze historical data and predict supply and demand. But generative AI takes that analysis to the next level. The technology looks at your historical sales data and pulls in real-time store videos and photos, social media posts, competitor websites, online reviews, and more to gauge consumer interest and generate competitive landscapes. AI can then create retail pricing scenarios that balance inventory, demand, and margin – along with generating new and innovative content based on that analysis.
By combining AI with your trusted customer data, you can inform and transform your promotional calendar from Prime Day straight through Cyber Monday.
Choose base prices that please shoppers and CFOs
Price comparisons have influenced 51% of shoppers to change where they shop. Since price sensitivity likely will continue through the holiday shopping season, price optimization remains essential for meeting business goals. Finding a price shoppers will love and your margins can bear yields higher sales volumes, improved conversion rates, and increased revenue.
Price optimization isn’t new. But complementing historical sales data with price elasticity, customer preferences, and market trends in real time is the latest shift. You won’t gain traction, though, by manually scrolling Instagram or comparing spreadsheets to gather data. Instead, prompt AI to analyze things like last year’s sales, competitors’ sites, economic predictions, and trending products on Twitter.
Predictive AI can forecast the hottest toys of the season or the running shoe millennials will be hoarding, and then generative AI can recommend competitive retail pricing that will bring shoppers to your site and stores. The technology can build multiple models and recommend price adjustments based on if/then prompts.
This helps your sales teams quickly set base prices that make you more competitive with other retailers. It also helps you plan markdowns throughout the season to optimize demand and margin. You’ll finish the season selling as much inventory as possible at the highest price the market will bear.
Pro tip: To get the most from AI’s price recommendations, look to your team’s marketing, pricing, and product expertise to validate strategies against demand forecasts. Human experts know what works and what doesn’t for retail pricing strategies that move inventory. They also make empathetic judgment calls that reflect your company values, social norms, and customer expectations.
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With 95% of shoppers tracking and comparing prices online when shopping in-store, dynamic pricing could make or break your Cyber Week sales. Retailers use dynamic pricing to adapt to evolving real-time market conditions and customer demand. A fluid pricing strategy works alongside your seasonal promotional calendar – central to your merchandising strategy and execution – with price adjustments based on product category, shopper demographics, inventory thresholds, and other related criteria.
Of course, it’s much easier to carry out dynamic pricing online than in-store. With AI, you can easily automate immediate pricing changes across your website, but to make the change in stores, be prepared to ask employees to manually update signs and labels.
By continuously adjusting online prices throughout Cyber Week, however, retailers can make the most of high-demand periods to maximize revenue and increase profit margins. And when demand is low, dynamic pricing can help stimulate sales through discounts or promotions. You also can use AI to automate pricing adjustments to reward loyal customers.
As AI monitors demand, you can be alerted when inventory levels and pricing trends change throughout Cyber Week. When competitors raise their price on a popular gaming console that’s low in stock, for example, you can make a similar adjustment. The generative AI algorithm can recommend a price tweak and, if you’ve set predefined rules, the technology can automatically update prices on your website. If you want to make changes in-store as well, AI can update store computer systems to the new pricing and alert store associates to make the change at the shelf.
Pro tip: Be sure to keep humans in the review process to balance perceived value and price. It’s tempting to undercut your fiercest competitor with a too-good-to-be-true deal, but shoppers might question your prices later when they bounce back to normal. Similarly, charging too much for a hard-to-find item can make shoppers feel you’re gouging them, compelling them to buy from a competitor.
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Test and tweak strategies continually
Once generative AI has made its recommendations, you can use the technology to test base pricing, markdowns, and promotions. It can simulate and compare the outcomes for a range of prices to show how fluctuations affect sales, revenue, and other key metrics.
Generative AI can also carry out testing in real-world situations, monitoring and adjusting pricing based on real-time data and feedback. The technology can assign pricing options to customers and adapt the base or discounted price according to test results. If one price proves more popular with shoppers, you can quickly pivot and assign that price across your stores and website.
For greater accuracy, you also can add real-time data sources like foot traffic sensors and heat maps to aid in-store testing for real-time analytics. As shopper behavior fluctuates, AI can flag the changes and recommend updates to your strategy.
Pro tip: Choose metrics that tie directly to your goals, and clearly define them in your AI prompt. For example, if you want to increase sales, ask AI for recommendations that boost sales volume or conversion rates. If customer loyalty is your priority, ask AI for prices that spur repeat purchases and increase customer satisfaction levels.
While AI is a powerful tool for developing effective retail pricing and promotional strategies, your shoppers ultimately make the final call. Actively seek out and evaluate their feedback — continually and in real-time — on your prices, product offerings, and discounts.
Use AI to help monitor customer reviews, process surveys, and gather qualitative feedback to understand the effectiveness and appeal of your pricing strategy. Then use that data to plan for long-term success and to continue training the AI algorithm to make more relevant recommendations in the future.
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