“Excess” goods in store warehouses are a $500 billion problem 😟. Need more accurate planning for purchases? But in the clothing and footwear market, where every item also has colors and sizes, the task seems overwhelming. However, there’s a platform that’s already solving it! Considering the market size of $2 trillion, this platform urgently needs to be replicated and sold 😉.
Project Essence
Syrup helps clothing and footwear stores to purchase the optimal assortment of goods so that a) they don’t have to hold sales for items lying unsold in stock, and b) they don’t find themselves in a situation where ordered goods suddenly run out in the warehouse.
Essentially, Syrup builds forecasts of future sales so that a store only purchases those items, and in quantities, that it can sell at regular prices in the foreseeable future. Not too much to avoid overstocking, and not too little to always have something to sell.
To get Syrup to start delivering results, it needs to be properly connected to the sales management platforms used in the store, like Oracle NetSuite, SAP, Salesforce, or Shopify, so it can begin receiving all necessary data and start analyzing it.
Getting Syrup fully operational takes 3-4 weeks, during which the startup’s specialists will assist in integrating and setting up the system.
For more accurate forecasting, Syrup uses not only past sales data. It also pulls in information about weather, holidays, social media trends, and other data that have influenced and can influence the sudden popularity of certain types of goods.
One of the main reasons why Syrup is beneficial for purchasing clothing and footwear is that it can forecast not only by types of goods but also by their sizes and colors!
Another interesting feature of the platform is that its creators understand that every store owner has their own ideas about what they want to sell 😉, as well as external limitations on purchases – for example, minimum order size and assortment requirements from suppliers or order fulfillment time. Therefore, the platform allows setting a set of additional rules that Syrup will later use to issue purchasing recommendations.
These recommendations are the result of the platform’s work. Syrup monitors sales dynamics and the store’s warehouse state to issue recommendations to the purchasing department at what it considers the right moment about what goods need to be purchased now.
These recommendations can be accepted, edited, or rejected. Syrup will use each such action for further training of its AI machine, to issue fewer recommendations that go against the purchasing department’s logic.
The first version of the platform was launched three years ago, and during this time, the startup has already attracted a notable number of clients, some of which are well-known brands.
Stores using Syrup have managed to reduce the size of warehouse leftovers by 20%, and the volume of manual work required for this has decreased tenfold!
Meanwhile, the number of goods sold at regular prices without discounts has increased by 10%, and the number of unfulfilled orders due to the absence of needed goods in the warehouse has decreased by 80%.
The total volume of warehouse stocks of the platform’s clients now amounts to $5.2 billion, which represents 13.7 million ‘store-product’ combinations even without considering colors and sizes. Clients of the platform have already managed to gain additional revenue exceeding $100 million.
Syrup is growing at a very good pace. In the summer of 2021, they raised their first $1 million in pre-seed investments. In the summer of 2022, another $6.3 million. And at the beginning of December this year, another $17.5 million.
Interesting Points
Syrup is growing rapidly, not just because it has such a smart platform, but because the problem of unsold warehouse goods is very big and unpleasant 😉
Firstly, unsold goods represent ‘frozen’ money that the store cannot use to purchase more sellable goods to make a profit.
Secondly, to sell off these unsold goods, stores are forced to hold sales with discounts, which reduces profits and gradually teaches customers not to buy goods at regular prices, as they begin to wait for the sales season.
To grasp the magnitude of the problem, it’s important to understand that at any given moment, $500 billion worth of goods are lying unsold in the warehouses of retail sellers!
Moreover, of the clothing and footwear purchased by a store for stock, only 24.3% of goods are sold within two months, 45.5% within six months, and 68.75% within a year. In other words, at least 75% of the seller’s working capital is frozen for two months, at least 55% for half a year, and at least 30% for a year.
To at least partly free up these funds, sellers are willing to pay. Otherwise, they have to take loans for new purchases, which will still accrue interest. That is if they are given the loans, of course 🙁
More accurate sales and purchasing forecasting, as Syrup does, is one way to solve the problem of excessive warehouse stocks. But there are others.
For example Ghost helps stores sell unsold warehouse goods without announcing sales to their customers. For this purpose, the startup created a closed marketplace for the sale of large batches of unsold store goods to discount chains, foreign distributors, and other wholesalers. Ghost has already raised $68 million in investments.
A similar scheme is used by Max Retail– but they focus on smaller sellers and buyers of unsold goods. They raised $8.2 million in investments.
Yaysay, which I wrote about in October, chose an interesting model. They made an app for discount sales of designer clothing, shoes, and accessories to retail customers. The trick is that each user of the app receives a daily individual list of goods – which they can either buy today or never see again in their feed. Moreover, if a user postpones a liked item, they must decide on its purchase within 30 minutes, or it will also disappear from their basket forever. The app was just released at the time of the review, but the startup managed to raise $10.3 million in investments for it.
Where to Run
Syrup claims that the most technically challenging part of the task is accounting for colors and sizes.
The startup is currently working with a relatively small number of brands, each of which has an average of 15,000 item names. Nevertheless, the ‘store-product’ combination already amounts to 13.7 million combinations, which the platform’s AI machine must take into account for demand forecasting.
If the combination is expanded to ‘style-size-color-store’, the number of combinations becomes so large that a human simply cannot cope with such a volume – this task becomes feasible only for AI.
However, adding these parameters significantly improves the quality of forecasts. Syrup claims that their platform has provided some of their clients with a 46% increase in efficiency compared to older platforms of well-known players.
Thus, platforms for forecasting sales and planning purchases, taking into account such extended combinations, should soon become the standard in the clothing and footwear market.
The size of the clothing and footwear market will grow to almost $2 trillion by 2027. This means that the demand for such solutions will be huge. And one platform is unlikely to cover it all 😉
So, the direction to move in is creating platforms similar to Syrup, which are expected to be in high demand soon.
The main thing is that their forecasts should really be top-notch. But that’s a technical problem. And as we all understand, technical problems are the lesser of all possible evils awaiting new products 😉 The worst evil is the lack of demand, which in this case is unlikely to threaten us.