- Product sorting has become increasingly powered by algorithms.
- Data is often siloed, and in order to become customer centric, retailers need to leverage connected data.
- In an omnichannel environment, it is crucial to connect and understand data across channels.
- AI analytics tools allow you to increase relevance and personalization in your product sorting, increasing customer engagement and sales.
Accurate Product Sorting Is Imperative to Success in Retail
One of your repeat customers, Mary, tried on a sweater at your store a few weeks ago. She has been thinking about it ever since. Finally, she decides to buy it. However, when Mary goes on your website, the sweater is nowhere to be found. Mary starts googling keywords to locate the sweater, and a similar product comes up through your competitor's website. Mary buys the sweater there instead.
Mary is just one example of the importance of product placement and product sorting. Luckily, with dynamic and data-driven product sorting technology, you can optimize this process so customers like Mary are able to find the items they are most interested in on your channels.
The Importance of Algorithms To Optimize Product Sorting
Managing the exposure of products in digital channels has become increasingly powered by algorithms. One challenge is that on-site and off-site algorithms typically focus on siloed objectives, and are owned by digital and marketing teams. By leveraging connected data, cross-functional teams gain access to previously unseen insights and analysis which drive customer-centric planning, trading and marketing strategies.
In the omnichannel world in which we operate, your customers interact with brands across physical stores, ecommerce platforms and social media channels. By utilizing AI analytics tools, you have the power to convert this information into customer profiles and gain insights into behaviors to produce more personalized experiences.
One way we see this taking place is with product sorting. The decision on whether to boost or bury products needs to be dynamic, driven by the product’s inventory position and personalized based on the customer’s attributes.
Data-Driven Product Sorting – Relevance and Personalization
Product sorting incorporates AI technology to understand customer queries and produce a sorting algorithm in line with the specific search criteria, with the most relevant items appearing at the top. Search relevance ensures your customer does not waste time digging through your website to find a product, because the search results match their criteria. EDITED’s Dynamic View allows retail teams to overlay metrics on their product page to see in real-time how a product is performing including conversion rate, sales, weeks on hand and product views. From here, retailers can determine if a product is over or under exposed and increase relevance accordingly.
AI product sorting software also helps retailers personalize their website content based on each customer’s browsing and purchase data. By taking a more personalized approach and understanding an individual’s preferences rather than those of the “average customer,” the system will share products that are most in line with your customer’s interests, inevitably driving higher sales. With AI product sorting tools, you can now automate actions across product recommendation, ecommerce, search, customer marketing, pricing / markdowns and replenishment to allow for a more personalized shopping experience.
The automation of product sorting through AI technology has tremendous benefits for retail companies by increasing relevance and personalization for your customers. By integrating an AI-driven product sorting software, you will improve your website sorting and filter algorithms, ensuring the most relevant and appealing items are given priority in sorting order, thus increasing customer satisfaction, profit and competitive advantage.
Learn more about how EDITED saves you time by automatically improving your sort order here.