10 Ways to Future-Proof Your Ecommerce Fashion Store

Selling fashion is easy. Selling fashion online is another beast entirely.

The trouble with ecommerce fashion is the same trouble any highly experiential good faces when it goes digital: Nobody wants to buy it until they try it. While the total US fashion and apparel sector sits at $359 billion, a mere 17% of that — $63 billion — belongs to ecommerce.

Sadly, even after you manage to overcome the try-then-buy divide, making sure those purchases stay purchases is even more daunting. According to Shopify’s recently published report on the future of ecommerce fashion and apparel, “The inability to physically interact with ecommerce items has resulted in an online return rate as high as 50% in some cases.”

 

However, having an online store isn’t an excuse to shy away from creating rich and deeply personalized customer experiences. Here are 10 tips to get ahead of ecommerce and future-proof your online store.

1. Virtual fittings

First and foremost, would-be customers want to know that your clothing isn’t tight in all the wrong places. Old-school size guides are a confusing maze of measurements that most visitors simply ignore. Virtual fittings change all that. For instance, Fits Me, an online fitting room, allows shoppers to enter simple information about their body type — height, age, weight, and body shape — and then Fits Me selects not just the size, but even specific products just for them.

2. Augmented reality

Right after fit, shoppers want to know, “How will it look?” And models aren’t enough.

They want to know, “How will it look on me?” Enter augmented reality. Outside of initial forays by the likes of XBox Kinect, full-scale AR is still a ways off.

However, for accessories, the future is now. Take Glasses.com. Its app gives users the ability to upload a photo of themselves and preview the entire inventory on their very own face. This creates a sense of ownership common in in-store buying but often lost in online.

3. Social approval

We all want approval, especially when it comes to fashion. In fact, social approval is often more powerful than self approval. In other words, it’s comforting to think you’ll look good in something. But hearing someone else say it? That’s ecommerce gold. 

Stylinity leverages this social drive. Whenever someone uploads a photo, other community members can “Like” or “Favorite” their outfit and — get this — can then buy those socially approved looks … piece by piece.

4. Crowdsourced design

If you could find a way to predict what buyers like before you even start production, would you pass it up? Of course not. And that’s why you need to start crowdsourcing your designs. Betabrand, an online clothing store, even goes a step further by asking its customers to vote with their wallets and fund the new products they want most. Not only does this meet the predictive requirement as well as raise funds, it’s also amazing content for social media campaigns. It’s a win win . . . win.

5. Gamification

Want to really engage your customers? Make it a game. Covet Fashion created a free app where users compete to dress up an avatar in real clothes. The outfits are then posted and other users can vote on the best of the best on a leaderboard. Covet awards prizes — i.e., clothes — to top picks and uses its combinations on product-description pages. It’s fun and engaging, and — naturally — the more your visitors engage, the more they’ll buy.

6. Big-data analytics

Analytics is as critical to online sales as stitching is to spotting knockoffs. Could you go without it? Sure. But you might regret it. Unfortunately, most small-to-midsize fashion stores don’t have access to the kind of big-data analytics that Amazon does. StyleSage — where “fashion meets big data” — is changing that. StyleSage’s database combines over 1,000 retailers, 53,000 brands and 64 million products. Oh, and they’ll even keep an eye out for retail-partnership opportunities.

7. Machine learning

Unfortunately, simply having data isn’t enough. You have to know what to do with that data to put it to work. Or do you? Google Cloud Platform leverages machine learning on your store’s behalf. Its product recommendations engine analyzes past purchases, related searches, popular images and even text to deliver — with near artificial intelligence clairvoyance — exactly what each customer wants.

8. Deep personalization

As a subcategory of machine learning, let me just say: It’s easier for you if people buy from robots, but people don’t want to feel like they’re buying from robots. The answer? Dynamic Yield offers customer personalization using flexible algorithms that create messages in accordance with the user and how they’ve interacted with your store in the past.

It’s still a robot, but I won’t tell if you don’t.

9. Wearable tech

As if you haven’t picked up on the dominant trend here, technology and fashion have officially merged. The Apple Watch and Fitbit Blaze revolutionized why we buy technology. And that was just the start. New entries like Ringly — a “smart” ring that syncs with any mobile devices and alerts you when you’ve missed a call, message or email — and Top Shop’s line of bPay Wearables (shown below) that contain Barclaycard payments chips are continuing to push the two closer and closer.

10. Visual search

Most of us are used to the search bar, but pictures are way more fun. Not to mention, far more relevant to fashion. Imagine your customers starting their search with a series of images. When they find something they like, they click on a specific piece of clothing. That product enlarges, along with a host of similar offerings. This is exactly the dream Wide Eyes has made into reality.

Source:

https://www.entrepreneur.com/article/286769

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