I am not surprised if anyone who wants to buy a dress says that the process is 'complicated'. Thanks to social media, a shopper is not only fully aware of the latest designer styles, she is even influenced by her circle on the purchase she is about to make. She wants to buy the "look" she just saw on Pinterest. With rich content and awesome user interface, the web store brings all the details to the shopper on her mobile device. When she walks into the store, she expects the experience to be personalized and supplemental to the research she has already done. She expects the convenience to buy the entire "look" in a single transaction. She gets instant feedback on Instagram on how the dress looks on her.
Apparel and Fashion companies today face many challenges as they transition into this fully digital world. Specifically in analytics, the challenges are three fold:
- In the Shopper Centric world we are living today, everything is connected. However, most companies carry out analytics in silos. Social media insights are not enriching the CRM systems, nor are they influencing late stage product designs. Very few companies are able to match the fast fashion requirements.
- The analytics capabilities supporting B2B area are at infancy in most companies. The B2B shopper today expects a similar experience in terms of product recommendations, relevant promotions from B2B partners as she would get from companies when she buys for herself.
- By 2020, there will be more connected devices on this earth than the human population. The availability of data from these devices will create newer opportunities for the enterprise. Most apparel and fashion companies are not yet ready to handle this flood of data.
In order to overcome these challenges, first and foremost, apparel and fashion companies must connect the various data silos. Some companies have a head start as they have centralized BI teams comprised of people from every function. For fast followers, a solution such as Data Discovery Platform (DDP) can help consolidate the data silos into one logical view. Wouldn’t it be nice to use shopper centric demographic information to enhance collaboration with your B2B partners - i.e., by sharing your direct-to-consumer/retail sizing insights with them and learning/teaching a tip or two about the shopper in the geographic area?
Companies that are investing heavily in enhancing their B2B capabilities, must also enhance B2B analytical capabilities as part of their digital transformation journey. A robust platform must include brand awareness/engagement tools, recommendations engine, integrated sales and promotion planning, supply chain event management along with the core commerce engine.
To handle the data explosion in the coming years, enterprises must create an analytics organization that is nimble and one which has a startup mindset. This organization must be tasked to build 'analytics apps' which are self-contained, yet if required can look at every corner of the organization for the relevant data and provide revenue generation or profit enhancing insights.