Prediction is very difficult, especially if it’s about the future. (Niels Bohr, Quantum Physicist)
Science fiction books and films have created new worlds, vehicles and technology: from the video phone in 2001 Space Odyssey to the USCSS Nostromo hypersleep chambers in Alien, we have witnessed how films have imagined the not (too) distant future. In some cases, the ‘future’ technology arrived with varying levels of success. For example, the Star Trek communicator device, which mobile phones can now match at least in size, if not in terms of capability.
Some films have been so innovative in their approach to technology and societal change that their contribution is beyond the pure entertainment or artistic value. Blade Runner (1982) introduced a number of innovations when it was released. Let’s take the ESPER machine: a voice controlled photography enhancing device. The device allows Decker, the main character, to identify one of the Artificial Intelligent androids he is supposed to hunt down. All the voice commands received by the ESPER are understood and acted upon, the same way we would interact with a modern AI system (Google Home, Amazon Echo / Alexa). The other piece of technology included in the film was the Voight-Kampff machine, used to identify those AIs that have been captured. Known as Replicants, these AIs had a high level of intelligence but lacked compassion and emotional intelligence. The test included a number of questions and answers designed to trip/provoke a physical reaction. Such machine does not exist today, but the relevant point is the fact that it uses a number of conversational elements to evaluate, measure and determine if the individual is a human –or not.
Artificial Intelligence has come a long way since the last century and a new crop of products have introduced AI–like capabilities. These are not science fiction services, but applications that are affecting the way consumers interact and acquire goods and services. This change impacts the world of retail commerce, which is facing a technology revolution due to omnichannel commerce, mobile technology, and AI services.
Customers carry their smartphones all day long; they are sually no farther than a metre away while we shop or even sleep. They have developed from being voice and messaging phones to multifunctional devices able to store and host a large number of applications. Despite the large amount stored, about 5 apps will be the most heavily used (Nielsen: 2015) and those top 5’s will be messaging and location apps (CommScore: 2016). These applications are kept on the phone because of their perceived value.
So why is this relevant? These apps display above average retention rates of 60% and 4.7 times more usage vis á vis other apps. Retailer and transactional apps cannot compete with this level of engagement and usage. These trends did not go unnoticed for long and in 2015, Chinese giant Tencent, creator of the WeChat app, developed voice controlled messaging and commerce into their app. The experience was managed with a single application that not only allowed the buying of luxury goods but also enabled paying the electricity bill. Currently, more than 20 transactional activities can be completed with the WeChat app using the voice interface. In the US Facebook integrated peer-to-peer payments and released a chatbot API last year for the Messenger app. The social media giant have been working with services like Spring Fashion, Kik Bot, Operator and Magic to release specialised chatbots. None of these, so far, can achieve WeChat level of capability and integration in a single application.
The integration of voice and messaging into Chatbots and Digital Assistants are creating a new model of interaction based on conversational commerce. Customers are already interacting using voice, Google reports that 20% of searches are voice driven (Google.io/ 2016) and by 2020 more than 50% of all searches will be voice driven (ComScore, 2016). Chatbots and DAs provide retailers with a new set of customer data: Requests and queries are longer and they are usually in natural language, revealing an enhanced level of intent (‘Where can I buy black shoes’); question words are used (Where, Who, What); and they are 3X times more likely to be local (as most mobile searches). The additional customer data enables physical stores to have ‘web-style’ analytics about customer preferences and favourites and could even perform predictive analysis of customer shopping missions.
In an omnichannel environment, a conversational interaction feels more personalised, like a human interaction. As such, it provides a more intimate relationship, closer to a real physical retail experience. The value of this exchange should provide an improved customer experience, especially when switching between channels and when location of the customer is captured (e-commerce-> physical shop-> Customer Services agent). Above all, it opens new opportunities for retailers to make the experience closer to the customer needs and allows for a more guided and bespoke experience in store.
Conversational commerce is now considered the third wave of commerce and retailers will have to implement changes in the way they interact with customers. The new key challenges for retailers are: SEO becomes more relevant for voice searches due to natural language search; the transactional online experience will be affected as a result of digital assistants intermediation of the transactional experience; and natural language interaction and analytics will be required to analyse user preferences. This new wave of commerce will bring sizeable revenue for retailers, research firm Gartner predicted that conversational commerce will generate about $2billion in sales annually.
Predicting the future of retail is not about science fiction, but about understanding how technology can create and enhance emotional connections with customers, something that Deckard would have been able to detect using the Voight-Kampff machine.
Mary Meeker on the 2016 Internet Trends (http://www.kpcb.com/blog/2016-internet-trends-report) reports that as the voice recognition accuracy reached 92%+, customers started using voice with Chatbots and Digital assistants. Voice search main interests: Personal Assistant (27%), Fun and Entertainment (21%), General Information (30%) and Local Information (22%)
‘How Voice Search Will Change Digital Marketing — For the Better’ by Purna Virji (Microsoft) : https://moz.com/blog/how-voice-search-will-change-digital-marketing-for-the-better
The ‘Hook Model’ by Nir Eyal: http://andrewchen.co/why-messaging-apps-are-so-addictive-guest-post/
Most downloaded apps 2016: http://mashable.com/2016/12/06/most-downloaded-apps-2016/#9z5akGmBv5qQ
On predicting the future: ‘The Signals are Talking’ Amy Webb
Gartner Predictions: www.gartner.com/newsroom/id/2971917