Case Study: AI-driven Merchandising Optimization for Top 100 Retailer
In the past, we've spoken at great length about the overwhelming importance of consumer-driven perception and its impact on sales. In an extremely crowded and dynamic marketplace, optimizing those perceptions could very well be the difference between lasting success and constantly struggling to simply survive.
To that point, Oculus360 (O360) has prepared a case study examining AI-driven merchandising optimization for a leading department store retailer’s e-commerce website. Throughout the study, we demonstrate the unparalleled benefits of technology to organize and present your merchandise based on specific themes, including product attributes, aesthetics, and occasions of use, to personalize the customer journey and, ultimately, increase conversions. In this particular case, our AI-driven consumer insights led to a 5% bump in online sales performance for the top 100 retailer.
A Peek Behind the AI Curtain
In the case study, we meticulously detail what brands stand to gain from utilizing the O360 platform to better understand a customer's perspective on merchandise inventory and how to best appeal to specific demographics and affinities. By extracting consumer insights from various online sources of feedback, we demonstrate how the department store retailer was able to optimize their merchandising throughout their website by targeting what should specifically be stocked and promoted.
Likewise, we were also able to determine how to optimize merchandise presentation on their website based on consumer perceptions and desires of specific product attributes and occasions of use. Such insights were previously unobtainable simply due to the lack of technological innovation and expertise now uniquely provided by the O360 platform.
Merchandising Optimization with O360
As detailed in our case study, we began by analyzing over 4 million consumer comments specifically regarding luxury fashion, extracting recurring themes and then organizing those themes according to a number of different parameters. Using occasions of use, for instance, the retailer was able to personalize their own algorithms to produce a more natural shopping experience for their target audience, closer to what they would experience in the store.
Furthermore, our analysis was able to optimize their product copy to be far more impactful and relevant according to our extracted themes. The data models we created for the retailer provided a reliable and prescient guide for them to organize their digital merchandising according to the primary themes we revealed – including fashion aesthetic, attributes, product occasions of use, and others – for future use as well.
In a competitive environment where small differences can make a huge impact, our case study provides tangible evidence of the power our AI-driven platform can provide to a company. As you will see from the study, the fashion retailer was able to realize significant gains in key areas due to optimized merchandising, copy, and content throughout their site.