Fashion's retail cycle is dominated by endless sales and markdowns, which is highly problematic for brands and retailers. This is the ultimate race to the bottom: sales start earlier in the season, prices drop lower than before, all with the hopes of luring the increasingly fickle consumer. This approach is rationalized in the short term but is slowly crushing all the businesses involved. Call it the JC Penny effect. Sales might sound good for consumers, but over the long term they aren't. Sales erode the businesses behind the label, from the financial sustainability of the brand itself to the factories producing the clothing.
Sales exist because of one issue: the failure to successfully allocate and procure the right inventory. Technically, every product has a buyer somewhere. Someone wants it. Finding that person is the challenge. This challenge is compounded by the fact that most retailers and brands buy and design with a lot of gut and much less data. The result is endless sales because of a failure to find the right consumer season after season.
The Current Ecommerce Experience
Most ecommerce stores share a few common elements: 1) Everyone sees the same thing; 2) Items are sorted categorically, aided by search; 3) The product selection is seemingly endless; and 4) The consumer has to actively visit the website to browse and, especially, purchase.
Every one of these assumptions should be challenged inside of every brand and retailer. Now is the time to do it, because business will suffer if the status quo remains. By challenging these assumptions, we might be able to fix the inventory allocation issue that has plagued the sustainability of retail and ecommerce.
1) Everyone sees the same thing
Fashion is one of the most subjective and personal pursuits. Taste and fit are individual choices, and people have specific requirements for each. Why do ecommerce sites show most people the same thing, from the page they land on to the featured products to the way they checkout? Ecommerce today is the equivalent of everyone having the same Facebook news feed, with only one button that switches between genders. Otherwise everyone sees the same thing. This is crazy.
2) Items are sorted categorically, aided by search
Products today are categorized by their type, brand and sometimes color. If you're specifically looking for pants this is fine, but if you're just browsing it is less helpful. Maybe you will go look under "New Arrivals," but that doesn't help our inventory allocation problem because it punishes older inventory, which is not necessarily bad inventory. This is the equivalent of browsing Facebook by news source, such as having a long list of articles from the New York Times, or seeing every single bit of a friends activity sorted linearly. Again, this sounds inefficient and annoying.
3) The product selection is seemingly endless
If a store has 1000 products, maybe 10% of those would appeal to a given consumer. (Even if the percentages differ per person, the point holds that everything never will appeal to everyone.) 100 relevant products per person is a lot. Ideally, each site should feature and serve me only the 10% of products I would be interested in, and is wasting time showing me the other 90%. Instead, brands and retailers are throwing spaghetti against the wall and seeing what sticks for each customer, which is a lot of wasted spaghetti. Stores are showing customers more and more product, but not better product. More of something customers don't like or need is a waste for both parties.
Amazon is an apt example of the endless inventory problem. Amazon is really great if you know exactly what you want. Want an Echo or a refill of your shampoo? You'll be checked out in under a minute. But if you don't know what you want, you could be browsing forever. Amazon has a bad browsing experience, but a good checkout experience. Endless supply is an issue without the right curation.
4) The consumer has to actively visit the website
There are two types of shopping: Active and Passive. Active shopping is when the consumer seeks something out and goes looking for it (browsing). Passive shopping is when a brand sends a ping to a consumer, which sparks their interest and then they engage (newsletter, tweet, retargeted ad). Active shopping is great because the consumer has the intent to buy, yet it's not always easy to discern when this is. Passive shopping can also allows a brand to show a consumer something they didn't know they wanted. Passive shopping also increases the frequency at which a consumer interacts with a brand.
But Active and Passive shopping have issues of their own. Active shopping is plagued by the first three issues discussed above, mainly that the experience is bad for the consumer and unoptimized for the retailer. Passive shopping is ineffective because it's often intermediated by the distribution network outside of a brand's control, which includes social media algorithms, crappy banner ads, and inbox filters such as Google's "promotions" tab. All of these methods harm the distribution channels that could make passive advertising more effective.
The Solution: Eliminating "The Storefront"
Personalized commerce, driven by conversational interfaces (chat bots/text-based interactions) and machine learning is the answer to all four issues, and most importantly fixes the inventory allocation issue that got us here in the first place. This is mostly a mindset shift, rather than a specific solution to implement. But the key is that the brand or retailer adapts and modernizes the shopping experience for the consumer. Customized and text-based interfaces will lead this effort and convert the best, from iMessage to Facebook Messenger to Operator.
First, and most importantly, no two people should see the same storefront or have the same browsing experience. Instead, a site should make a bunch of inferences from a consumer's purchase history about what she likes and what she might be open to. Showing her anything (or everything) is ineffective, as is sorting it by chronology or brand. Search and categories should still exist, in case she knows exactly what she's looking for, but they should be a secondary interface, not the primary one she shops with. The same goes for the endless inventory. If a retailer is big enough to support a ton of options and variations, it can still have the inventory. But instead of stacking it up under pagination that goes dozens of pages deep, figure out how to show a dozen items to the right person.
Eliminating the idea of a storefront
To push this even further, conversational commerce probably should replace the storefront altogether, leading to a happy combination of Active and Passive shopping. Bundled with a sophisticated recommendation engine, brands should text a consumer a dozen or so products every week that she would be interested in. Brands now own the relationship with the customer and have a direct line to the device she spends the most time on: her phone. This fixes all of the issues with Passive shopping and distribution, since the open rates on texts and push notifications are infinitely higher than mass emails and retargeted ads. This vastly reshapes customer acquisition and marketing, and a fair amount of the paid spend could be reallocated towards moving current inventory and increasing the lifetime value of current and new customers.
This is also a better experience for the customer, who now spends less time browsing endlessly, filtering out promotional emails, and making accounts and navigating checkout pages. The incentives are aligned.
Most importantly for the brand, this new approach mitigates many inventory allocation issues, since it can now push the right products to the right people better than ever before. This will cut down on back catalogs and old products being lost in the pagination purgatory, which leads to excessive markdowns. On the backend, all of the data that comes from these heightened and more personal interactions will greatly aid the buying and procurement for brands and retailers, bringing some sense to what is sometimes a black box with a lot of gut instinct.
This is not the end of buyers, the people who select products for stores each season. Conversely, the need for more buyers and stylists will expand exponentially, as they will have infinitely more personas to work with and shop for. The days of a single store shopping for "our girl" are over. It's "our girls" and there will be dozens and hundreds of them. Now, aided by deep reams of data, buyers can make informed decisions for each person, while also delivering better, more specific results.
Luckily, testing this out costs almost nothing. All a brand needs is a Google voice account, synthesized and digestible product images and descriptions, and a test group of customers. No code needs to be written on day one. Even past purchase history can be easily found that can lead to new recommendations. Even better, tools like this nifty new keyboard from Shopify are making the startup costs near zero and lowering the barrier. Longer term, the data and machine learning will take considerable resources, but starting now is relatively cheap.
My goal here is to challenge the thinking that the fundamental assumptions in fashion and ecommerce exist for good reason. They often do not. Staying ahead is a prerequisite for existing and thriving in this immensely dynamic landscape. The blueprint above would go a long way towards building a very sturdy foundation for brands and retailers alike. This piece is best understood as a framework to look at your individual business through. These ideas apply to brands that sell their own product and retailers that wholesale other brands.
The current state of ecommerce is exacerbating brands and retailers' inventory allocation problems. The only way to make a serious, structural fix, is to rebuild the buying and selling apparatus from the ground up.