I have a confession to make: I don't like shopping. It takes a lot of time, and I never find what I'm looking for. Shopping online doesn't solve the issue – once I receive the clothes I ordered, they don't fit, differ significantly from the picture, or create a completely different look from that on the model in the picture. At the same time, I'm reluctant to give up, because I do feel better when I go to work in a nice outfit. How to go about this dilemma?
If you ask me, the solution would be a self-learning algorithm, which we could label my personal shopper. Even if it would still be in a testing phase, I'd be fully committed to working with it. A 3D scan would collect all my sizes, after which I'd share some basic information with my shopper: several of my favorite brands, clothing styles, and preferred designs. With this information, my shopper could get to work. What would that look like?
Digital personal shopper: benefits for consumers and sellers
Of course, retailers such as Zalando and Maison365 provide online personal shoppers that are familiar with previous items I purchased in their shops. But the advantage of my shopper is that it only works for me – it isn't affiliated with some brand or department store. And by proposing clothes to me 'Tinder style,' it will grow more and more familiar with my preferences over time.
In a perfect world, it doesn't stop there – my shopper also assesses whether a shirt or pair of pants would fit me and if the design suits the shape of my body. All this can easily be achieved by matching the right set of data. The only prerequisite is that sellers should make this data available to my shopper – namely, the specific sizes of each piece of clothing. So, what's in it for them?
Quite a lot, in fact. Currently, at least 30-40% of all apparel purchased online in the Netherlands is returned (in Dutch). The majority is returned because it doesn't fit – often, people anticipate this issue and purchase several sizes at once. The consequences are tangible: a study conducted by NOS and Afterpay last year (in Dutch) shows that a return shipment costs 12.50 euros on average. This amount includes several costs: those of the initial shipment to the customer, transportation back to the distribution center, inspection, cleaning, and putting the wrapped items back on the warehouse shelves.
Racking your brain over returns: overcoming roadblocks
Lowering return costs is largely a logistics challenge. If many items are returned, your stock can be difficult to predict. Moreover, inspecting items is quite the task, and picking up packages at consumers' homes requires you to map smart routes.
Another disadvantage of returns is their environmental impact: transporting the return shipment causes CO2 emissions, and repackaging the items requires additional plastic and cardboard. Apparel that's declared unfit for use gets a new function or is destroyed: these items will need to be transported again, and if destroyed, all environmental impact caused during manufacturing hasn't served any goal whatsoever.
In summary, both consumers and web shops would benefit from a digital personal shopper. It saves customers time, helping them find items they like and that actually fit. The results: less returns, happier customers, a lower pressure on saving costs, and less environmental impact.
So, who will help me get the digital personal shopper that will remedy the above-described issues? If you're interested in developing it, I would like to hear from you!