Conversational commerce offers great opportunities to improve the customer experience. But as Duncan Keene, UK Managing Director at ContentSquare explains, the quality of that experience is not a given; behavioural analytics are essential if organisations are to maximise the value of chatbots and drive up both engagement and revenue.
Chatbots are at the centre of the conversational commerce movement and are fast becoming a part of everyday life for most ecommerce brands. They’re changing the way brands interact with their visitors and adoption rates are rapidly growing. Chatbot technology is becoming increasingly sophisticated and while the debate remains contentious about chatbots replacing human customer support agents, they are undoubtedly becoming more ‘human-like’ in their ability to respond to a diverse range of commands, questions and even emotional sentiment.
The Holy Grail for many ecommerce teams is to truly understand how visitors behave and navigate through their sites on both desktop and mobile. Brands have been building towards this for over a decade with varying degrees of success; but in terms of analysing the behaviour of visitors when it comes to chatbot interaction, most teams are in the dark regarding the effectiveness of their automated bots. This is a huge grey area for the vast majority of organisations and is doubtless a source of lost revenue.
Aside from price and product, the quality of experience is proven to be one of the most effective ways to compete for consumers’ hearts and wallets: this continued lack of understanding regarding the way consumers interact with chatbots could be extremely damaging to a brand.
Understanding the UX
A poor chatbot experience will cause significant user frustration and risk damaging both brand engagement and perception. Organisations cannot afford to introduce chatbot technology without proactively monitoring and optimising the way in which visitors interact with chatbots from day one.
The ability to measure behavioural analytics is essential to understand how customers are interacting with chatbots across a website. It enables companies to rapidly identify problem areas and ensure they can be addressed, as well as pro-actively enhancing the experience based on trends in user behaviour. For example being able to see a visual map of visitors’ chatbot ‘journeys’ can identify high drop-offs and site exit rates at a particular stage of a conversation. Brands can also explore how specific visitor segments then behave after a bad chatbot experience – do they continue browsing on the site, end up making a purchase or instantly leave? The ability to rapidly identify and remedy such problems will be key to minimising revenue loss and brand damage.
Fully utilising chatbot UX analytics will also enable brands to explore the most effective time to deploy the bot on a visitor’s desktop or mobile journey; while further insight can inform the order of the questions surfaced, the effectiveness of various answers and the way different visitor segments behave when engaging with a chatbot.
Conclusion
While chatbots are becoming an increasingly mature and widely deployed technology, in reality, organisations still have much to learn about the way consumers interact with chatbots to maximise the value of conversational commerce. It is likely that as consumers become more familiar with day to day chatbot exposure, their behaviour will change and evolve – just as it has with websites over the past decade. The ability to track and understand this evolution will be important for companies to further improve that experience and fine tune the way in which chatbots are introduced within the consumer journey.
By Duncan Keene
UK Managing Director
ContentSquare