Home » Changing Perspectives: Will VR Disrupt Your E-commerce Data? Copy

Changing Perspectives: Will VR Disrupt Your E-commerce Data? Copy


In 2012, a Kickstarter project raised $2.5 million for a product that would literally change the way we see technology. Four years and $2.5 billion later (thanks to an acquisition by Facebook), the Oculus Rift virtual reality headset has finally shipped to consumers.

The intervening years of development have given other companies time to build similar products that will compete either by integrating with existing hardware (Sony’s PlayStation VR) or by offering different takes on what constitutes ‘reality’ in virtual reality (Microsoft’s Hololens).

Will the next era of disruptive e-commerce devices not be in your pocket but strapped to your face?

Time will tell. While developers have been making land grabs all over this new virtual landscape, many consumers aren’t sure what value this new gadget will bring. Well, gamers get it, but your great-aunt Claire may need more convincing.

The rumble of these virtual reality devices signals a new trajectory for marketers. Remember when smartphones with touchscreens came onto the scene? Product innovation met consumer adoption and sparks flew! After only a few years, sales completed on mobile devices are starting to rival other channels.

I’m not saying it’s time to slap some goggles on your noggin and build a VR marketing plan. You should, however, take this moment to see if it’s time to find a new trajectory for your marketing. Are you still innovating or have you become comfortable with your processes? Are you using your data effectively? Are you truly meeting the needs of the consumer who is using multiple devices to shop and buy on your site and in your stores?

Many marketers rely on automated messages that are triggered when there is an action (or inaction) by a shopper. Segments establish criteria that will fire off a message when the trigger is tripped. This one set of criteria will apply to all consumers. Items left in a cart, send a cart reminder email. It’s almost like a batch-and-blast automation strategy if you really think about it and we all know the downfalls of batch-and-blast!

How can you move beyond a one-size-fits-all strategy, especially with the powerful, revenue-generating messages such as cart reminders and product page abandonment emails, and gain the reach of location-based marketing and mobile messaging? One thing is certain, it requires a lot of data.

It’s time for marketers to find new ways to use the data they have collected by unifying customer profiles across channels and devices. Even if you get a thrill from working with large data sets, the mix of profile, behavioral and purchase data is more than the human brain can handle. While you may be able to see trends in aggregate, you can’t effectively market to each individual shopper, predict their next move or know what will motivate them to buy.

This is where customer intelligence and machine learning helps marketers by modelling these behaviors to ensure the right message is being sent to the right consumer. Items left the cart could result in a traditional cart reminder or perhaps an in-app push notification with an incentive to complete the order in a store. Product searches on your site could signal product recommendations based on product page views, past purchase data and user-defined preferences.

Adding this layer of logic may sound complex and slightly overwhelming but there are ways to start shifting your strategies in the direction of machine learning that don’t require too much time and resources.

The Emarsys whitepaper, Trusting the Machine: Data Science and the Multi-Channel, Multi-Device Shopper, will show you and your team how to use more advanced customer intelligence data and machine learning to shift your strategies, expand your conceptual thinking and boost the success of your marketing programs across channels.


Who knows, your customers may be months away from wanting to throw on their VR goggles and start shopping in your VR store. Will you (and your data) be ready?