“Mapping customers’ journey & building engagement all along essential for future- proofing of fashion retailing”: Ranjan Sharma

When you consider digitisation from fashion retail perspective, the complexity introduced by the fashion industry in terms of colours, sizes, seasonality and numerous other variables results in an enormous amount of data collected every day. I believe that Covid has played a crucial role in spearheading and compelling brands to intensify their efforts in digitising processes within the supply chain. However, the entire digitisation process of the fashion retail industry began a decade ago, primarily aiming to enhance speed, agility and responsiveness.

Customers have become more educated, so trace their purchase journey

The goal of an apparel brand should be to effectively connect with the consumers and fulfil their specific requests, acknowledging the increasing expectations of an educated consumer base. The necessity for discipline and efficiency in meeting these expectations is now more apparent than ever before. Nowadays consumers already do their research on the internet and they do not come to your store to conduct product research, let’s say on denim. They come to your store to purchase a specific denim item that they have already researched on. They are well aware of current fashion trends. With such educated and informed customers, offering generic products or asking what type of denim or trousers they want is no longer effective. Instead, you need to analyse their past behaviour, considering the traces they have left in various places and use that information to identify their needs and propose a product accordingly.

A brand may have hundreds of thousands of styles and designs available for sale in-store or online, but it doesn’t make sense for the consumer to spend time searching through the entire product portfolio. Brands must become more targeted and specific in how they differentiate themselves from others. This is where the entire digitisation journey is pushing us to operate and manage our businesses more efficiently.

Future-proofing demand-driven retail with AI and Digitisation

Demand planning actually went out of the window when Covid hit us. People were just wearing shirts, T-shirts and shorts! This made us nimbler in our demand planning. That is where we began gathering data through different mediums. This data includes customer’s intent, discovery and purchasing traces across different channels. Maybe for the customer, he didn’t click the image shown on your e-commerce platform, but since he had looked at the product, based on that, you are making sense out of it and saying, “Hey, this is what is interesting to this individual customer.” So, what impact will it have? First, you will be able to use the data to predict what, how much, when, where to produce, and then, importantly, when to get that product into your supply chain!

So, with digitalisation, it is becoming easier to enhance a brand’s predictability and this is becoming important to be able to reduce your entire supply chain and sourcing cycle. Because previously what we were struggling with a lot is predicting demand and trend at least nine months ahead! Things change really fast in this evolving industry and trends change in weeks now! So, brands need to ask themselves – “How do you create a mechanism to react to these new trends?” and “How are you going to convert that fresh trend into a fresh product quickly?” This is where whole digitisation and demand both are coming in handy because now you are able to take the data which is as close to the season within the season itself.

For example, if you have launched the Spring/Summer collection in February, two weeks later, you are able to look at your data and be able to identify where you have gaps in your planning and presentation and where you need to change and how much you need to change. So, you need to come out of the traditional way of working if you are a retailer. You have to cut down on a lot of processes – the whole design process and the whole sampling process are actually managed through digital tools. Sales is not the end journey for a retailer and brand; the end journey is getting the customer back and that would happen if you manage to understand his post-purchase behaviour, which includes studying the shipping process, customer service process like his return/refund query. This is where AI is helping brands like BESTSELLER in managing customers.

E-commerce photoshoots with AI integration for cost and time efficiency

We had an interesting case during Covid when we had to run our e-commerce and no physical models were available for a photoshoot. We collaborated with an agency, utilising shots of international models by incorporating their faces onto the images. To streamline the process and reduce lead time, we established a studio in our distribution centre, where we photographed the products on mannequins.

The agency was based in Bengaluru and the distribution centre was in Mumbai, resulting in a lengthy lead time for sending the product from Mumbai to Bengaluru and back. To address this issue, we expedited the process by immediately having the product reach the distribution centre. In many cases, we even started shooting on samples before the shipment arrived. This is when we began incorporating AI into our workflow.

After the mannequin shoot, AI seamlessly integrated the model’s face onto the images. This wasn’t a straightforward and a simple process, as the mannequin’s face might have a different colour than the model’s. Additionally, managing different backgrounds posed a challenge, given our website’s defined background compared to the varied requirements of online marketplaces. As a result, we successfully reduced photoshoot costs by approximately 50 per cent and decreased the time required by 40 per cent.

AI use extended to create content for better searchability of a product

By extending AI in image search, we rapidly generate content by employing keywords from our SEO optimisation tools and partners. By associating specific keywords with each product, we enhance its searchability and improve tagging. Before the product even reaches the distribution centre, we have the content and catalogues prepared, featuring sample products. In contrast to our previous process of tracking product arrival and shoot scheduling, which typically took two weeks, we have successfully reduced this time significantly.

Customer advocacy is becoming bigger

Feedback from customers may not only come on your website but also on social media or any other channel. It’s challenging to extract this detail as a lot of this data is unstructured. However, that’s where AI and digitisation come in to help. If you can locate the digital traces of your brand and any information related to your brand and integrate it into the landscape you have created, stitching it with your product and sales data, you can start making sense of this data to reach out to the customer. Catering to feedback is essential not only to assist customers in resolving their queries but also to turn them into advocates for your brand and influential customers. However, brands should realise that ultimately product is the king and it would not make sense if they try to bring some external factors into the brand and try to prioritise over products.