The goal of Stily is is to combine stylists and machine learning to make a personalized shopping experience of cloths online
Stily aims to present fewer and more personalized products to customers looking for cloths online. The goal is to make the shopping experience less overwhelming as well as fight buyer?s remorse. This last part can have great environmental effects by decreasing the high level of returns in today?s online shopping.
Online shopping has made buying clothes a lot easier. Seemingly unlimited purchasing options are at the consumer?s fingertip. This is in many ways great, but creates new issues related to The Paradox of Choice. Having so many options make the shopping experience overwhelming and increases the likelihood of experiencing buyer?s remorse, and thus sending the products back to the store.
Being presented with 100 pairs of jeans intuitively seems better than having the option between 3 pairs, but as it turns out ? the opposite is true. The first option naturally makes the decision-making process more difficult, but even more importantly; the customer leaves with the nagging feeling of not having made the optimal choice. Give him or her three options instead, and the satisfaction after making the purchasing decision is higher.
Stily was launched as an early beta in 2019. Users were asked to go through a four- minute-long signup process, providing information like height, age, hair color, budget and so on. 200 consumers completed the registration indicating an interest for this kind of service in the market. We are now working on a full-fledge service where stylists and machine learning algorithms will help users get personalized recommendations.
We have seen a lot of interest especially in simplifying online shopping by making it less overwhelming and by making the checkout process smoother.
In the past few years several companies have succeeded with basing their online store on personalization rather than displaying a huge amount of purchase options. A few especially successful companies in this sphere are American ?Stich Fix?, British ?Thread?, and the most recent, German ?About You?. There are still no companies in Scandinavia who has succeed on doing the same. This is where Stily aimed to market itself.
Starting an online store with a wide enough product offering to give each customer good, personalized suggestions require a lot of both time investment and capital, even for Stily who aimed solely on men?s fashion. Stily?s solution was to build the technology for data collection and machine learning algorithms. This technology was aimed at being integrated into existing online retailers. After talking to many relevant companies in this market it became clear that more personalization was something of interest, but the way the new wave of companies in the market is doing it is too far from the existing solution of traditional online stores. The companies we talked to seemed more interested in personalization in the way of improving the well-known ?You might also like this? section rather than filtering out options to make the shopping experience less overwhelming.
To reduce the risk of potential partners, Stily built it?s own platform where online retailers could put out their products without having to take the risk of integrating the technology directly into their own platform. We saw some potential for partners, but a couple of key points stopped these negotiations:
1. Companies are risk averse to being the first partner, and we experienced this to be especially true after the pandemic which hit the market hard.
2. Giving Stily the window to face customers ment potentially losing out on up-sales that they would potentially get from having the customer on their own platform.
The work we have conducted indicates that customers are interested in online retail stores that offer a more personalized and less overwhelming shopping experience. At the same time, the transition to this kind of solution is too far away from the current solutions of traditional online retailers. Personal shopping solutions seem best suited for companies that have enough capital to build out both the retail solution in addition to the technology needed for this kind of personalized shopping experience.
We hoped to prove that personalization could help online retailers create better shopping experiences that would in turn reduce a big issue in their industry; returns.
The issue is both a problem for the retailers because the market expects free returns, which is a huge cost to the companies. The other issue is related to the environmental impact the return issues in the industry creates.
We hoped to create technology that traditional retailers could integrate to achieve this goal. The technology got to the point where it was ready for testing, but despite meetings with several relevant companies in the industry we could not manage to conduct a pilot project.
Thus we cannot conclude whether simplifying and making online shopping more personalized will reduce the number of returns in tradition online retailers. Our research during the project period does however report far fewer returns for companies who built online stores from the ground up with personalization in mind.