Dressipi

Before we start with the next series of blogs, I’d appreciate it if any fashion or apparel retailers out there could complete the next series of survey questions:  #productenrichment #productdata #structureddata #fashionai

Nike’s massive 20% share price drop: time to revisit the growth at any cost model? Nike is not alone. Looking at the top 10 sportswear brands, it is a similar picture for Lululemon, UnderArmour, JD Sports, Wolverine, and Puma. On average their share prices are down by 10% over the last 6 months, 17% over the last year, and 20% over the last 5 years. Having a quick look at the business fundamentals, there is a story in the numbers. Here are the averages across that group: Net revenue growth: up, averaging 15% (if you exclude 2020) Gross margins: down, by 1.65% pts (from 47.97% in 2019 to 46.32% in 2023)  Operating margins: down, by 2.25% pts (9.08% in 2019 to 6.83% in 2023), and  Inventories as % of net revenue are up 2.2% pts (16.1% in 2019 to 18.2% in 2023) The numbers suggest that there needs to be some realignment across the various internal functions. Inventory management remains a key challenge for these companies as they manage overstock and demand volatility. The good thing about activewear as a category is that certain areas are easier to predict - it behaves more like continuity than fashion items so it is easier to forecast from a demand planning perspective.  This was echoed in McKinsey’s Activewear report see exhibit 3. This is also exactly the kind of job that advances in AI & ML are good at. Working with large fashion retailers Dressipi has seen up to 4% points improvements in full-price sell-through rates. This isn’t just a big hit for these companies on their profit margins but also a big sustainability issue too. If I take Deckers and Fraser Group by contrast. Both are seeing similar average revenue growth (14% and 10% respectively) but have costs and stock under control (2023 GM, operating margins, and inventory either in line with or above 2019 numbers). A cautionary tale perhaps - to get the alignment done now to ensure that growth continues to be profitable. #profitablegrowth #sustainablesupplychains #predictiveAI #retailai

Responding to a great article in The Business of Fashion about why fashion’s curation problem is so hard to solve. The problem is multi-dimensional. As the article states, to do a really good job would, “require cataloguing each product at the same level of granularity.” As Spotify. Therein lies the issue, What is the right data? What is the right level of granularity? Most retailers’ product data is organisational-led, it is not customer-led, it is focused on the “what” not the “why”. Fashion, as a domain, is much more dynamic, on every level, than every other category. Fashion is inherently about “newness”, clothes only exist to be sold for 3-6 months, tastes change as trends change or as we get older. What suits us and makes us feel great depends on body shape, lifestyle, ethnicity, sensibilities. Our experience at Dressipi tells us that customers are evaluating 1000s of product dimensions to decide whether that particular item is right for them, the event they are going to, the weather, whether it will work with those jeans they bought last week... Most retailers rely on personalisation engines that have been built to service all categories. They typically use basic collaborative filtering models, these models completely fail to understand the preferences and intent of the customer and some of the nuances as to why building genuinely good recommendations in fashion is much more challenging. Here are just a few examples: - Our tastes change as trends change. You may have customers like Anabel in the article but equally you might be someone who likes to follow trends. For those customers, they may have previously disliked gingham or checks or florals but if gingham or check or florals are THE key trend this season then that customer won’t just like gingham/checks/florals – they’ll probably end up buying that previously disliked trend. So you need to have a way of figuring out which of your customers are trend-led and which are not. Likewise having bought into that seasonal trend that customer will probably not want to now only be shown gingham/checks/florals - Body shape, gender, ethnicity, and sensibilities matter. An example we often use is that of necklines and large busts - the difference between a crew neck and a round neck is very real when it comes to return rates. - Fashion is one of the only categories where we are buying something to go with other items we own – so styling is key but styling in the context of that customer not only in terms of their preferences but also working with what they already own That doesn’t even touch on size, return propensities, and fragmentation avoidance. All-in-all a complex problem that needs careful, considered thought. Something we have been doing at Dressipi for over a decade. If you’d like to chat more about the product data or the personalisation APIs please DM me. 👗 📈 👖 https://lnkd.in/emwyXr4V

Back with the pink suit for #nrf2024. Really looking forward to seeing everyone and so some exciting meetings with clients and partners. Am well rested and ready for the onslaught! Please give me a shout if you are a fashion retailer and want to know how to close your profitability gap! Looking forward to hanging out with the Nibble team and the brilliant Rosie Bailey - definitely come by their stand #340 - Rosie and her team are building the future of AI negotiation! Also checking in with James Brooke who is now CEO Sweft - automating and digitising the product workflow processes - much needed cash can be released quickly once that process has moved from analogue to digital. And a shout out to Jim Herbert Patchworks, John Williams Amplience, Andre Brown Advance Commerce AB, Kelly Goetsch commercetools See you all there. #predictiveai #fashionai #closingtheprofitabilitygap

Retailers, do not miss this webinar! 🎉 With the launch of our upcoming Retail Radar report, we're digging into the 202 million purchases analyzed to spot consumer trends with insights that retailers cannot ignore! Join us at Voyado and our industry experts Laufey Lúðvíksdóttir, CRM and Loyalty Expert at By Malene Birger and Sarah McVittie, Co-founder at Dressipi, where we discuss how that there's no such thing called "business as usual". We have entered a state of a new abnormal. Register now to join the webinar on November 7th: https://lnkd.in/dhDR4Y3C