The Rise of Voice Commerce and its Impact on Retail

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By Published On: July 12, 20180 Comments

Simon Clarkson, the managing director of ChannelAdvisor APAC, looks at the rise of voice commerce and the impact it's likely to have on the e-commerce industry.

With the rise of the Internet of Things (IoT), digital assistants have exploded over the past year, with Amazon’s Alexa and Google Home becoming more commonplace in Australia. In the US, digital assistants have become one of the fastest-growing segments of consumer electronic devices. In fact, ComScore estimates that voice search could jump to as much as 50 percent by 2020.

Why should retailers care? The rise of these digital assistants has tremendous implications for brands and retailers that rely on search marketing to drive traffic to their website. The very nature of voice search completely changes the way we think about search today. It also represents another area of consideration for retailers who are only just adjusting to an e-commerce landscape, where the majority of traffic takes place on mobile devices.

While voice search has been around since the introduction of Siri (which arguably had little to no impact on a retailer’s digital strategy) the new wave of digital assistance is pushing voice search into the mainstream across both old and new devices. Amazon’s Echo launched in Australia in early 2018 with competition from Google Home and Apple HomePod.

While previously digital assistants were used for playing music, streaming services, news, podcasts, cooking instructions, creating shopping lists or home automation, their uses are expanding, as will our reliance on them for basic tasks like making appointments and shopping online.

When it comes to the digital voice scene, it’s important to understand the motivations behind each device. Google, for example, has entered the space to protect its positioning and to continue to adapt to consumer shifts in behaviour. Amazon’s motivation is to sell more (with user experience all tied in here as well). Both of these motivations are clearly relevant for online retailers.

While the current capabilities of these devices have limitations, we can see where they are headed. Just thinking about the possibilities of a shopping list and how this data could impact user experience and retailers is exciting.

Imagine the capabilities of a brand being able to strategically advertise when they know a consumer has added ‘tomato sauce’ to their shopping list. Or how certain attributes, like the date something was placed on a shopping list, could be used to encourage the consumer’s purchase journey. Opportunities exist to mine this data both at an individual line-item level (eg. ‘You have tomato sauce on your list. There is a promotion on tomato sauce today at Store X”) as well as at an aggregate level (eg. grocery items that stay on the list for several days, especially essentials, that may indicate a busy week requiring the assistant to initiate a reminder for an online order to Store X). Throw predictive commerce in the mix and a basic shopping list that originated essentially to replace scribbles on a piece of paper becomes a goldmine for retailers.

Companies that control the gateway to purchase intent data and have a wide selection of products have a huge leg up as this technology becomes more mainstream, with a significant proportion of consumer spending going to recurring items (such as groceries).

Another aspect to consider is that consumers search with different terms by voice than the terms currently included in e-commerce sites. The way consumers shop online has shaped SEO and SEM. We know what it takes to get what we want quickly, but this isn’t how we talk. Search by voice is more akin to how you would talk to a sales assistant than how you search online.

Voice is predominantly one dimensional, which makes it hard to present a set of choices when it comes to search. Taking out the visual and scrolling element changes a critical element of transactions. Humans can’t store dozens of options that are read out to them, so only one or two options could be presented at any time as a result of a search (much of the time based on the search history or other relevant search terms). Again, this relates to more specific search terms, which can often be brand specific.

So, with these technologies still in the comparatively early stages and their usage, especially for online retail, what do retailers need to do?

  1. Become a user. If you want to know how your future consumer is going to start relying on voice, start by getting familiar with what’s out there.

  2. Think about the products you sell and some potential logical and innovative intersections of voice search.

  3. Evaluate a shopping list that integrates with your website for easy reordering.

  4. Evaluate Data Structure: Think about how your data is structured and how voice search could interact with your products.

  5. Sell on Google Shopping and Amazon to set yourself up for early integration. Amazon has an enormous head start at this point in terms of usage and skill development and of course, can tightly integrate Alexa to shopping (after all that is sort of the point). If you aren’t already selling on Amazon, it might be the time to change that. Additionally, existing sellers or vendors should double-check that their data is robust and complete. Alexa is smart but can’t make up for gaps in your data when it comes to retrieving search results.

  6. Voice will become the ultimate in personalisation as the voice engines get better at distinguishing individual users. Think about how voice can be integrated into your current personalisation strategy — and consider adjusting your existing strategy if it can’t be.

While this generation of internet users are used to keyboards, the next set of internet users will become accustomed to using voice for their needs. While voice search doesn’t necessarily seem like something that should be a priority at this point, the reality is that there’s going to be a changing of the tide and retailers need to ensure they don’t get left behind.

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