In the fast-paced world of retail, merchandisers are hyper-focused on driving the critical success of product sales and managing inventory productivity. Their work on short-, medium-, and long-term forecasting is critical to the success of any retail brand . . . and AI can now make this work more accurate and efficient than ever before.
With AI-assisted product attribution, merchandising teams are empowered to save internal spend, while driving external revenue. This is thanks to AI’s data processing capabilities, consumer analysis, and the use of customer-centric language throughout the entire retail ecosystem. On a day-to-day level, this AI automates proxy product identification, tagging, and copywriting, saving days of manual labor, boosting your forecast volume accuracy, and increasing your full margin sales.
Here, we dive into three big ways AI can benefit merchandising teams, earning additional revenue and making their internal processes more accurate and efficient.
Three Ways AI For Retailers Benefits Merchandising Teams
Data Unlocks Better Insights on Customer Behaviors
It’s easier than ever to identify patterns on why your customers made specific choices. With AI, merchandising teams are better informed how new products will sell in the future by gaining a full grasp on how they previously performed or are performing.
The insights into each product can get quite granular, as AI examines trends, occasions, or product details (embellishments, fits, fabrics, colors, etc.) that were sold or skipped over in previous seasons. Its specificity into accounting for product details also helps products receive greater visibility, as all of its aspects are accounted for. This is especially helpful for online retailers whose customers can’t touch or feel their products. AI-powered attribution helps consumers understand products better, and therefore, it increases said products’ visibility.
This comprehensive knowledge helps to navigate inventory hurdles, such as reconciling the merchant’s desire to purchase new seasonal inventory while liquidating inventory that didn’t move as forecasted.
By forecasting demand using a language of customer-driven attributes, retailers increase their ability to sell their customers exactly what they’re looking for, whether it’s a new trend or a classic staple. When understanding what exactly the customer values in their products, retailers can then invest in maintaining or expanding their most lucrative assortments. Ultimately, AI reduces inventory risk and decreases the need to mark down inventory later.
AI for Retailers Streamlines Processes and Enhances Forecasting Accuracy
AI eliminates manual, time-consuming tasks associated with traditional merchandising processes. With its assistance, teams can move away from manual work that spans across endless spreadsheets and the issues that arise from those processes.
In fact, the right AI solution will turn hours of manual work into minutes.That’s because, as of right now, AI can analyze a massive amount of data 1000x faster than any human could.
With its inclusion in your tech stack, retailers will increase their merchandising teams’ operational efficiency by reducing manual proxy product work. This is especially beneficial for Merchandising teams who have limited resources.
Additionally, AI’s ability to analyze data at unprecedented speeds ensures more accurate demand forecasting. It understands patterns and deciphers trends, based on commonalities in attributes that tie to a product’s performance. Merchandising teams who use AI will move away from reliance on any anecdotal experiences and intuition to predict demand.
AI Drives Revenue Generated by Merchandisers
By introducing automation to your demand forecasting process and retail ecosystem, you will unlock multiple sources of value, all of which will save money or drive revenue in upcoming seasons.Forecasting accuracy is improved by up to 25% with EBITDA boosted as well.
Across the board, Lily AI delivers upwards of 9-figure revenue lift through its implementation in:
- Demand forecasting
- Marketing functions, like maximizing Google Search performance
- Richer AI-generated product descriptions to connect people to the products they’re searching for
- Excellent product recommendations and on-site search experiences
More customers are connected to your products throughout the entire retail experience.
Therefore, retailers can use their data to understand their demand . . . and merchandising teams can use AI to understand their preferences and predict what products they’ll want next.
