For the Love of Shopping

For the Love of Shopping

I know some of you might not believe me, but before the internet, people used to spend hour-after-tedious-hour combing through shopping malls and stand-alone stores to find just the right item to satisfy our wants and desires. Yes, that’s right, with the rally cry, “Shop ‘til you drop!” we canvased town – often several times over - to walk aisle after aisle, compare items and (*gasp*) talk to people about whether or not products were “any good.”  

And so, because of the exhaustive nature of this practice, the Personal Shopper was born.

This mystical, magical creature would ask what you were looking for, gather the specifics and go out into the wild, returning with the perfect item – much to the marvel and amazement of the would-be shopper who gushed, “You saved me so much time!”

Which begs a question that a handful of you won’t understand . . . if video killed the radio star, did online shopping kill the personal shopper?

With an ever-growing emphasis on “customer experience,” retailers seek to merge old-school customer service with new-school technology. The result? Mobile as a Personal Shopping Assistant.

“Hold the phone,” you say. “How is that even possible? And even if it is – that service couldn’t be ACCURATE!”

How accurate was the ad for XYZ product you mentioned, in passing, to your co-worker the other day that just happened to pop up in the right rail of your personal email account?

Artificial Intelligence is growing smarter and stronger every day – which means smarter, stronger retailers are capitalizing on it with Personal Shopping apps.

Whether retailers sign up for a Personal Shopping Service (i.e: buy space on someone else’s platform) or they hire a developer to create a Personal Shopping app branded for their store, there are many unlimited advantages.

Retailers can monetize their own apps by selling advertising space, charging commissions on their sales or creating membership-based structures for pay-to-display.

In return, shoppers enjoy a more personalized experience because AI learns their shopping trends, personal habits and individual preferences. Additionally, they can watch prices rise and fall, potentially capitalizing on great discounts. They can also track past purchases and receive recommendations from the app that directs them to similar or corresponding items.

If you’re not already thinking about creating the store of the future in your own retail space, it’s time to start. Business Insider predicts that M-Commerce will reach $284 billion by 2020. That’s 45% of the E-Comm market. (E-Comm defined as online shopping from a computer, M-Comm defined as shopping via mobile device.)

Perhaps Lowe’s wasn’t so wrong a few years ago when they introduced a life-sized, animated virtual shopping assistant in their stores. She welcomed guests and encouraged them to ask questions, but no one did because the exchange was a little too . . . weird with a side of creepy. But, now that Alexa has us trained to speak to our technology, it might be time to revisit the concept.

For retailers who want to capitalize on the trend, your developer needs to build a user account, shopping cart, payment portal and order tracker. Of course, this works in conjunction with your online store to offer the home furnishing products and design services that your customers want to shop.

To ensure reliability when AI makes a product recommendation, your online product data must be accurate and up-to-date. So, in addition to budgeting man-hours for your developer, look at paying an employee to refresh and double-check your details and improve the romance copy. Or, make it easy on yourself; work with a service that automates product data refresh and updates your system to ensure that your website is always on target with specifics and inventory.

Either way, your Mobile Shopping Assistant possesses the capability to recommend items of interest to your customers based on previous purchases or other searches. In addition, some retailers include features like image recognition, which gives item recommendations from a picture of something else they liked enough to snap a photograph. For example, if your customer likes her friend’s sofa and takes a picture – your app can recommend a similar item from your inventory.

It’s just another of the million ways that technology changes the way retailers and designers do business. If you want to learn more, check out SHIFT Tech Summit, where technology’s best minds mix with leaders from the home furnishings industry to help every manufacturer and retailer advance.

Rachel Giza1 Comment