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In the first part of this blog series, we wrote about how smartphones have changed the way consumers shop and search for products. Conversational commerce, a.k.a. conversational shopping is a trend that has emerged from the use voice search via mobile personal assistants. But this is still a one-way communication. The next step is an actual customer dialog, that can scale with the help of artificial intelligence. This development is known under the term “conversational commerce”.
In this part, we show you how the industry is adjusting and what the future might hold.
We learned that consumers are warming up to voice search with mobile assistants like Siri, Ok Google and Cortana and that this new way of looking for products lends itself to using a more natural, conversational language. Search results also tend to provide the search results in a more “human” way.
Nevertheless, the introduction of voice search was just the beginning. Consumers want these artificial virtual assistants / digital assistants to be more helpful to their purchase journey for a more enjoyable shopping experience. To fulfill these needs, brands and retailers have started a more conversational approach online (evident in the rise of curated shopping services). But with the use of artificial intelligence and the combination of different services, this is now possible on an efficient scale. The e-commerce industry has needed to adapt fast and with this, the term “conversational commerce” was born.
Conversational commerce transforms all interactions with a brand or merchant into a natural conversation – from shopping assistance to customer support.
Conversational commerce mostly refers to the use of intelligent chatbots and other services like real-time digital customer support on all sorts of devices. Not only have we begun talking to our smartphones and smartwatches but we’ve also begun to have conversations with artificial services on social networks.
The most popular apps out there are social networks and chat apps (actually chat apps even eclipsed social networks). We spend hours on these platforms to connect with people and brands, share our thoughts and interests and to discover news and trends. This interaction makes these apps perfect for integrating shopping services too.
Consumers are already used to interacting with brands on these platforms. Messaging apps, in particular, are becoming more crucial as a means of providing customer support. For now, the actual shopping and billing process happens on the brand or retailer’s webshop or mobile app – but conversational commerce could change that completely.
Some retailers and brands have already designed internal solutions for their web page or app. An example of such an “independent” service is The Northface.
The Northface launched a virtual shopping assistant that wants to find the perfect jacket for you. Users have to answer different questions like “Where and when will you be using this jacket?” you can see some example answers like “Hiking Iceland in November” to get an idea how to phrase your answer. This way the brand can interact with customers in real time and can learn from them, finding out how and when they use their products. Collaboration with a tech partner is crucial to this new kind of technology. The Northface launched this service with the help of IBM Watson.
But most of the new conversational commerce services are going to be integrated into social networks and messaging apps. Messaging apps are also transforming beyond communication tools to e-commerce platforms. They are are investing heavily in artificial intelligence (AI), big data science and API’s to integrate 3rd party services. Particularly Facebook and WeChat, are working hard to become an all-in-one platform for e-commerce firms to launch their conversational shopping services. China’s messaging app WeChat is evidently in the lead, where you can search for a nearby café, make appointments, get news updates while drinking their coffee, chat with friends, pay for the coffee or send money to friends in the end – all in a dialog style. Facebook wishes to become the international version of WeChat with the introduction of M – your own “virtual personal assistant”
Bots on Facebook Messenger were introduced in April 2016 with a new service called “Facebook M”. Facebook M is the social networks text-based virtual assistant platform with a Send/Receive API that allows developers to set up intelligent chats. The bots are able to respond with structured messages, multimedia, product carousels, links and different action buttons (click, order, send, … and in the future: pay). Currently ,beta testers can order flowers, get news or get updates for their flights.
Other messaging apps like Slack, Telegram, Kik and Amazon Echo are also investing in their bot infrastructure. One great example of how a bot can be used to raise brand awareness and to drive sales is the Sephora chatbot strategy. The cosmetic retailer uses a chatbot on messaging app Kik (which is mostly used by Generation Z or even younger millennials) to combine content marketing and product placement. After a short quiz with the chatbot, teens get relevant how-to videos, product reviews, and tips.
The Sephora example shows how bots can be used for two-way communication, and also as a promotion channel for e-commerce businesses. Nowadays brand relationships are very important as competition is rife and products have little differentiation, meaning they can easily be replaced. Aside from personal recommendations by friends and family, nothing is more powerful than a direct interaction with – and personal attention from – a brand. As chatbots can appear quite human, they build trust for shoppers. Another plus of using social networks as a platform is the targeting and personalization for user profiles.
On social networks, users are already sharing their personal preferences. If you can master the combination of the conversational approach with personal preferences, you will make sure to show only the most relevant products to your most relevant audience, which will increase your conversion rate while creating a stronger brand loyalty, as people feel understood and well served.
We’re talking about the best-case scenario here. The challenge is obviously to deliver a flawless customer experience. Most people won’t understand if a bot suddenly can’t answer a question or worse gives an answer that doesn’t relate to the question at all. At the moment nearly all chatbots have human support. If a bot can’t find an answer it will forward the chat to a real human. The bots then are learning from that human-powered conversation.
And even if it’s all working out fine customers expect different levels of interactions and services within the chat. Those services are limited to easy action buttons as mentioned earlier. One pain point is transactions. That’s why we think that as soon as the platforms integrate a payment option within the bots, shopping will become even more convenient for the user. At the moment e-commerce can be a real hassle (seriously, how many emails can you get for one simple amazon order). Integrating all services in one central point, that also allows the user to interact with those services on a personal, human level will be a great improvement. On the downside, the platforms that will master the service best will dictate the rules.
We think that conversational commerce will definitely become a part of the daily shopping routine for consumers – both mobile and desktop users alike. Consumers already reach out to customer support via chat apps and are likely to adopt their behavior for their shopping decisions.
Having said that, it’s difficult to predict how new hardware and software will accelerate or even change user behavior. On the one hand, Amazons “Dash Buttons” eliminate any conversation with the customer to keep things as simple as possible, while virtual reality gadgets and augmented reality software add an extra layer of interactivity. Just think of putting on your VR headset to enter a virtual showroom of your favorite brand. You tell the digital virtual assistant that you only want to see business outfits that you can wear in summer. The assistant then asks you some more questions about color, size and other style options until you only see products that are specifically selected and suited for you.
But back to the present: The most crucial success factor for conversational shopping campaigns is a well-structured file containing all the correct and complete information about the products that you want to sell. This so-called product data feed must be tailored to meet the requirements of your selected shopping platform or network. As an early adopter of new e-commerce channels, Productsup allows you to create custom export feeds for any channel and we’re already speaking to the most promising chatbot solutions out there. We are ready to help marketers to face this new exciting shift.
What do you think about conversational commerce? Share your thoughts in the comment section below!
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