The retail industry and marketplace has continued to evolve and transform over the years – especially since the onset of the pandemic – making the transformation to digital truly a revolution worth talking about. So let’s discuss how exactly the industry has transformed, particularly with the help of AI.
COVID-19’s Impact
From the get-go, the COVID-19 pandemic threw the retail industry for a loop. Organizations were no longer able to run their businesses as usual – whether a trade show, Fashion Week, or attending a showroom – the whole ecosystem was halted. Showrooms, trade shows, and traffic from there moved entirely virtual through the use of mobile devices, iPads, and into virtual events.
Now, however, the industry is roaring back. However, it’s now with more of a hybrid-based approach. For instance, physical shows are present again but with the use of mobile tools being incorporated into the experience, with QR codes still available to provide the option to shop digitally.
The Digital Escalation of Online Shopping
One of the most unalterable changes the industry has seen in the last few years is the desire of consumers to shop online. It’s easy, it’s relevant, and that is truly evergreen, but with that said the digital experience also needs to continue getting better in order to be sustainable.
The expectations of the customer are at an all-time high, and in order to maintain loyalty retailers need to go the extra mile to meet them where they’re at.
Some of the best ways to do that are through better personalization efforts, enhanced demand forecasting, and improved search diversity.
The Language of the Consumer and the Digital Stack
For digital transformation to be successful, a retailer’s digital stack also needs to have the right assets in order to keep up. A massive opportunity out there right now pertains to the customer and how they are looking for different things online – the ways they are searching and the unique language that they use to do so – the language of the customer.
When the language of the customer isn’t present in the existing e-commerce retail stack, then the shopper may have difficulty finding what they’re actually looking for. This can be tackled effectively with the technology of AI and its ability to rapidly extract attributes, paired with the behavior of the shopper or the language of the customer within that product attribution data.
If merchants are manually attributing their entire catalog with only a few basic attributes, then the shopping experience will be a struggle for the customer within the merchant’s on-site search engine. Because products are not going to be comprehensively described nor relevant enough to match them with what shoppers want when they search for an item, conversions are going to be far less than they might otherwise be.
This is also relevant with SEO and SEM because if products aren’t attributed accurately right at item set-up then someone searching for a product, say in Google, isn’t going to find the product because it’s not going to come up as it should. Having the language of the consumer completely permeating the digital stack can truly have a massive impact in how a retailer optimizes their entire retail value chain.
Lily AI and JOOR’s Partnership
Lily AI and JOOR are working together to transform the retail industry with digital and AI on a daily basis. To take retailers to the next level, Lily’s machine learning approach and JOOR’s ecosystem approach to digital transformation have helped retailers to move things upstream with their product attribution data.
For instance, together Lily and JOOR are able to help retailers automatically add more attributes per product item; work to strengthen the moment of intent in wholesale buying, and replace the manual attributing of items with Lily’s advanced AI technology.
In one example, Lily and JOOR worked with a partner that was initially only able to manually attribute six attributes per item. Together, Lily and JOOR were able to not only replicate those six attributes per item, but also added, on average, six more.
