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11050_Peter_Zemsky_AI_Business_School_3_Retail_FINAL_V2

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[Driving Business Value from AI] >> Peter: Retail is a very important setting for understanding the business value that's coming from AI. From search to e-commerce, digital has been disrupting the sector and AI promises to accelerate. At the same time, retail as a sector, prone to intense competition and tight margins. A strategic approach to AI focused on value is really critical. Fabletics, a born-in-the-Cloud fashion e-tailer, illustrates this well. Founded in 2013 and operating across ten countries, they focus on women's sportswear and accessories in the growing ath-leisure category., Leggings are a key product. Like for most retailers today, Amazon is a key and demanding competitor. In the old physical world, specialist stores like this could carve out niches next to general department stores. Not true with the endless options available with e-commerce. Here, for example, is Amazon's dedicated page just for women's leggings. They themselves have the depth of offer you'd expect at a specialist, including a set of partner brands attracted by the large user base of Amazon and, of course, the site has access to Amazon's full suite of e-commerce capabilities, prime delivery search, easy access to user ratings. Now, as a key differentiator, Fabletics has pursued a membership model, where users get monthly shipments. They've also pursued a celebrity endorsement approach to branding with co-founder Kate Hudson, among others. In summary, the company is an early mover in an emerging new category, and has leveraged e-commerce for a fast global entry with already over 1.3 million members. As one of their strategies for avoiding direct competition with the online cost leader Amazon, they pursue a subscription model, a model which shot to prominence in the retail sector with the success of Dollar Shave Club, which Unilever purchased a few years ago for a reported $1 billion. Our question is how can AI contribute to Fabletics developing a winning value proposition in this demanding space? Let's consider key elements of their baseline value creation. First, they're looking to attract members with a strong, celebrity lifestyle brand and the authority on the category that comes from being a dedicated specialist. On the cost side, they have benefits as well. First of all, from lower marketing expenses on their existing customers, and they get supply chain efficiences from the more predictable shipments from a membership model. However, like any business model, there are negatives, as well. For the users, they risk getting unwanted shipments. They have until the 5th of each month to decline a monthly order if they don't want it. and the company has the heightened risk of returns of merchandise that customers don't like, which we know are a key cost driver in e-commerce. Also, it's worth noting that initial customer acquisition costs can be very high because you're asking members to commit to ongoing monthly orders. So, how can AI drive a leap in value creation for a company such as Fabletics? Well, the core application of machine learning is to make predictions based on rich data sets. This is critical for retail, whose core value creation comes from connecting customers with the right products. Machine learning, for the first time, makes possible fast, high quality and mass personalization of these kind of product recommendations and general selections. I think the thing to note is this kind of capability is especially useful in a subscription model. The personalized selections only deepen the members' connection to their brand, and moreover, the better match the selection to each individual, the lower their anxiety of getting unwanted shipments. On the cost side, a KPI of the algorithm will be the rate of costly returns. And finally, supply chain management can be improved by machine-learning predictions, not at the individual level, but on the aggregate ordering of the entire membership, based on their latest data; for example, on their website browsing. Thus, we see here another AI use case which is compelling for the retail sector. But what about execution? We know that the key to effective machine learning is building the right data sets, and this typically needs attention from across the organization. At Fabletics, the data gathering actually starts from the first click. A user attracted by one of their new member promotions is of course asked to enter a host of sizing information, which you see here. However, note that this is only on screen five of the sign-up process. The first screens ask the new member about the type of exercise they do, then where do they like to exercise and even some initial color preferences. Why? Well, this is exactly the sort of information that can be useful to seed machine-learning algorithms, and will help drive high quality predictions and recommendations when combined with data on the member's browsing history and, ultimately, on their possible returns. One can simply not underestimate the importance of such an integrated approach to data gathering and storage for AI strategies like this. So, there are really two headlines so far from the Fabletics case. First, the ability of high quality, personalized recommendations to drive value creation in retail. It's a huge development. The second, the need to have a culture of data capture across your organization. And let's now move on and consider one of the biggest trends in retail today, omni-channel. Should this born-in-the-Cloud online retail open physical stores? Does AI help make this significant investment a value-creating move? Well, we know from Apple that retail stores can be a great way to reinforce a brand. We know from retail banking and telcos that physical locations can be critical for customer acquisitions. So these benefits are highly relevant to Fablitics' value creation, and they've actually opened 24 initial stores already in 2017. However, true to their culture of data gathering, this was an integral part of their store designs from the very beginning. For example, through the use of employee handhelds, they're able to track what customers are selecting to try on and observe which items are then purchased and which are left sitting on the changing room floor. On a website, when an items fails to sell, it's often very hard to disentangle why. Is it the color? The picture that you displayed? Is it the price? You can get, often, much richer information inside a store. As the Fabletics president summarized, more data does not equate to more insights. We needed better, more contextualized data. This is the reason we decided to open stores. Their data flows both ways. When a member walks into a physical store, the sales associate is fed user preferences and recommendations based on their prior online shopping behavior, and when a customer tries on an item but does not complete the sale, it can be added to their online shopping basket for later consideration. Store inventory, obviously critical for the success of physical retail, can be optimized based on analysis of the data of your local members, social media sentiment and in-store heat-mapping data. Now, one challenge of extricating these AI-infused digital strategies is to cost-effectively build the range of organizational capabilities required, especially for a brand like Fabletics that is still busy scaling up. So in the case of Fabletics, they overcome the scale requirement through their parent company, the TechStyle Fashion Group, which is able to provide them a common set of digital tools and infrastructures, not just to Fabletics but to its range of online fashion companies. This is really not an area of strategy where you want to go it alone, especially as a smaller-sized unit. We've now seen several other key takeaways from this case. Fabletics is a great example of brick mining, using physical stores to augment and enrich your online customer data. Fabletics demonstrates the power of AI predictions to drive not just customer recommendations, but also predictions to improve inventory and supply chain management. You see as well that AI strategies cannot be separated from the rest of your digital initiatives. This is logical because it's actually proliferation of digital data coming from across your enterprise that is fueling the value creation from AI. Finally, as attractive as these AI and digital strategies are, you need to be careful about finding ways to share the fixed costs to assure that you're driving a strong ROI. This can either involve shared efforts across a larger corporation, as in the Fabletics case, or it can involve teaming up with external partners. Retail, a dynamic sector for digital and for AI, indeed.

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Posted by: csintl on Jun 18, 2019

11050_Peter_Zemsky_AI_Business_School_3_Retail_FINAL_V2

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