In her first exclusive guest blog for WhichPLM, Elizabeth Shobert, Director Marketing & Digital Strategy for StyleSage, explores the rise in personalisation using real-world examples. Elizabeth speaks with both the consumer and retailer in mind, and discusses personalisation from a price and product perspective, as well as an experience. StyleSage is a retail analytics company that helps fashion brands track and optimize their competitive pricing, assortment, promotion, and trend adoption strategies, using image recognition and machine learning technology.
We live in a world full of choices. Whether it’s something as simple as what you order for lunch to a more complicated set of choices, like the design of your new living room furniture set, the option to customize something to your exact specifications can bring delight like few other things can. And, while personalization has historically meant something made by hand, labor-intensive and costly, in today’s day and age it is increasingly powered by technology which levels the playing field for consumers and retailers.Let’s explore how technology, and the world of data it uncovers, enables retailers to create a bespoke customer journey, from start to finish.
A welcome mat with your name on it: Personalized Experiences
When you log onto a site and see a set of products featured on the homepage, have you ever stopped to consider whether all customers are seeing the same thing? The chances are, you’re seeing something curated specifically for you. Sometimes it’s quite apparent, as you’ll see the exact products you browsed previously in your suggested products feed, while other times it’s less obvious (but effective nonetheless). Smart retailers – the likes of Amazon and Macy’s – will sort items on browse pages and place first those items which reflect your previous journey and that of consumers with similar profiles. If you have browsed a product in the home section of a department store’s site, they will likely recommend products in complementary home categories to pique your interest, rather than trying to force you down the virtual apparel aisle.
While a great e-commerce site is intuitive and encourages browsing, how can the human part of the shopping experience, which can be readily had in a bricks-and-mortar space, be replicated online? This is where chatbots, when brought to ‘life’ properly, can personalize the virtual shopping experience. I recently logged onto a fast fashion retailer’s site and wanted to ask some questions about how their denim styles fit: how much stretch did they have, and should I size up or down? Let’s call my virtual shopping assistant ‘Erin S.’ She helped me pick a size in two different styles based on my usual sizing and other styles I had previously purchased. If I’m being honest, the assistance I got from Erin was at least as good, if not better, than my past experience in their physical stores. And she even told me ‘those jeans will look great on you!’ before I signed off. Yes, I let myself be flattered by a machine, but the point was I received the assistance I needed, checked out in a timely fashion, and felt confident in my purchase. While chatbots, which are trained and improve over time via machine learning, are a good solution for more typical questions, the technology does at times falter with more involved and infrequent questions. But with the speed at which these machines are learning, there is no doubt that Erin and her virtual band of assistants will continue to help resource-constrained retailers improve and personalize the customer experience in the virtual world.
Maximizing the Value of the Transaction: Personalized Pricing
Across consumer profiles and product categories, price is one of the most important purchase considerations and constraints. Yet, as a consumer, if you’ve watched an item go from full-price all the way down to 60% off, you start to figure out that there is some amount of flexibility built into pricing. So what does pricing that is optimized for both the consumer and retailer look like? To start, from a retail-centric view, a personalized price takes into account a number of consumer data variables including purchase history, demographics like age or gender, and location, with cost of goods, margins, and projected consumer demand already factored in. Technically speaking, an e-commerce platform does give retailers the power to change and charge different prices to consumers based on analysis of their respective data sets. If the one-sided and seemingly intrusive nature of that move makes you slightly uneasy (and you wouldn’t be alone), most retailers have historically shied away from directly charging different prices to consumers. However, they do offer up promotions that are tailored to your profile and purchase history.
Let’s look at an example. Two weeks ago, you bought a pair of running shoes online, and one week later, a unique discount code for a future activewear purchase landed in your inbox. It doesn’t take a genius to figure out this promotional offer was powered by data analytics. The retailer identified a strong likelihood that you (and your new running hobby) would also be interested in buying a pair of running tights, if the right incentive was in place. A discount code is nothing new, but the discount code that takes into account your specific interests and behavior is the foundation of a relationship that profits both parties over the long run.
Another example of personalized pricing in play is the marketplace. Sites like eBay and Tradesy are growing in relevance and trading power as consumers seek out unique and hard-to-find products—on their own terms. In 2016, eBay recorded gross merchandise values of over $21B USD on their platform, and their site was the second most-visited e-commerce site during the holiday season. These marketplaces allow the buyer to bid, on an individual basis, to a seller who decides what their minimum (reserve) price is. It’s up to the two parties to make a deal or walk away from the table.
While these are two very different takes on personalized pricing, the overarching themes are the same: price is fluid and subject to a mutually beneficial exchange agreed upon by individual buyers and sellers. And it bears repeating, the retailer-consumer relationship thrives when the consumer believes that data gathered about them is harnessed in such a way as to benefit and give them the final say in the transaction.
Bespoke for All: Personalized Product
I don’t know about you, but there’s nothing I love more than getting an off-the-rack dress or pair of pants tailored to fit me perfectly. While it’s an added expense, it makes that item mine and mine alone. Personalization beyond the basics has previously been out of reach to the average consumer due to cost, but a bespoke revolution is well underway in fashion retail. Some of the most exciting examples of this? Fame and Partners, a vertically integrated women’s apparel brand, takes a customized, ‘atelier’ approach to shopping. Customers browse a set of base designs and can either select the standard sizing and color options, or they can select from a set of material, color, embroidery, length and fit choices to create a customized garment. With production lead times under two weeks (not to mention messaging centered around women’s empowerment and sustainability), their approach has been very well received amongst shoppers looking for bespoke sans the unattainable price point.
Another successful example of mass customization is Australian handbag retailer Mon Purse, who recently opened a pop-up store inside Bloomingdale’s NYC flagship. Mon Purse lets shoppers design their handbag from a plethora of options including the color of the leather, handbag shape, handles, and monogramming. By putting the consumer in charge of the design (while still giving them a framework within which to work), they also have a more transparent view of pricing as they add and subtract components. Without a doubt, the wave of mass customization will continue to rise and disrupt, as consumers navigate and acclimatize to this new world of one-of-a-kind retail.
While the benefits of customization to the consumer are clear, how does it benefit the retailer? Data from returns logistics provider Optoro estimates that the rate of returns in apparel is three times higher than that of other retail categories and a clear drain on the bottom line. By giving consumers a hand in the design of the product, retailers can increase the odds the consumer gets the product they want the first time around and ultimately decrease waste that occurs in the design and development process.
As you think about personalization, a 360-degree view of the customer journey is critical to get the e-commerce consumer through the door all the way to a successful checkout …and come back for more.