Another guest post by Matt Buskell, head of customer engagement at Rainbird.
There was a time when booking a holiday meant a single trip to the high street travel agent. Nowadays, the process of online research seems to take longer than the holiday itself. The difference, back then, was the travel agent – a human being who could look you up and down, talk to you about your preferences, and make a recommendation based on their judgement.
In the world of AI, we like to call this ‘inference’. Travel agents never asked any questions like the filters and features you find on travel websites today – location, price range, number of stars. Nothing. Instead, they inferred what we would like, basing their judgement on factors such as how we were dressed, what we liked to do, and how we spoke to them.
Where does the time go?
The average time spent researching holidays in 1997 was just 45 minutes. Now, it’s over eight hours.
The pattern is the same with other retail sectors that have moved online – from books, to groceries, music, clothing, and even cars. Hours are whittled away on websites like ASOS, TripAdvisor and Amazon. Imagine walking into a real-life store, asking the assistant for advice, and being handed a mountain of products and reviews to spend the next few hours scouring through. You’d probably just walk straight back out. So why do we settle for it online?
Convenience is one thing: for most of us, the ability to browse during the morning commute or on a lunch break is more appealing than a trip to the high street.
Many of us have also convinced ourselves that spending time looking at different online retailers and social media sites is the best way to ensure we have all the facts we could possibly need to get a ‘good deal’.
But when the choice of online stores and the availability of information was limited, it was a much simpler task. Now, we’re faced with an overload of choice, and the process of doing thorough research can feel laborious.
So why is it that targeted personal advice is lacking in online stores, whilst it is universally expected in the physical stores of our best retailers?
There are three main problems with online retailers today that limit their ability to provide the most suitable recommendations for individual customers:
1) You search for a product using narrow features, e.g. price, size, or category.
2) The system does not explain or offer a rationale for any recommendations it makes.
3) It’s a one-way interaction. You click, the computer displays.
Back to the future
The good news is that ‘conversational commerce’ and cognitive reasoning are going to bring the human element to online retailers. Ironically, the latest trends in AI are actually sending us back in time to the days of personalised shopping.
Imagine an online store in which an artificially intelligent assistant has been trained by your best human retail assistant, your favorite DJ, an experienced travel agent, or a stylist. You ask for advice or a product recommendation, and the system conducts a conversation with you, just like a real-life shop assistant.
Let’s take holiday booking as an example. The cognitive reasoning system, channeled via a chatbot – let’s call it Travel Bot – asks you a range of questions to gauge your priorities and their order of importance. During this interaction, you say that you like the beach, enjoy city breaks, hate long journeys, and indicate that price isn’t your deciding factor. Travel Bot recommends a five-star beach resort in Cannes. You baulk at the price and ask for an explanation, and Travel Bot explains that beach property is fifty percent more expensive than inland. You decide that the beach isn’t that important – to which the Travel Bot responds with an altered recommendation.
You end up with the perfect compromise – a reasonably priced hotel stay in the centre of Nice, ten minutes from the beach.
In this instance, Travel Bot mirrors a human travel agent. It makes inferences, explains its recommendations, and continuously alters its advice to cope with uncertain customer responses.
A computer cannot completely replace a good human adviser- yet. We are just too complex to model. But by bringing back the human element of customer service and combining it with the retail arena of the future, we can take a lot of the stress out of online shopping.
Rainbird is a leading Cognitive Reasoning engine that is re-defining decision-making with AI in Financial Services and Insurance.