Three clear customer benefits in a world of artificial intelligence (AI)
For consumers, the AI-first world is going to be wonderful. We will discover new levels of service that we could only dream of in the past. During my hundreds of visits to some of the most innovative companies in the United States, Europe, Africa and Asia, I drew up a list of benefits that we can expect to get from artificial intelligence. Three central aspects - three concrete advantages - keep on recurring, time after time.
Three clear customer benefits in a world of artificial intelligence (AI)
Time is probably the scarcest resource of any customer group. Companies like Amazon and Booking.com are obsesses with saving time of their customers. Question is: how focussed is your company on saving time of your customers. The paradox is: the more time you save from your customers, the more time (and money) they will spend with you. In a world driven by Artificial Intelligence, companies have new and more opportunities than in the past to focus on this opportunity. There are three clear benefits to help customers, to save them time and to boost the overal customer experience.
1. Faster than real time customer service: the aim is no longer to provide a faultless customer service, but to solve problems before they arise.
2. Hyper-personalization: sales and marketing are no longer about the average customer, but about the needs of the individual customer.
3. Effortless user interfaces: there is no longer any need for an instruction manual or a help function.
Faster than real time customer service
Until recently, the aim was to provide customers with a good after-sales service. This led to the setting up of well-functioning contact centres, with a team of efficient staff ready to help customers with any problems they might have. Some companies were better than others, but most of them managed to provide a service that was acceptable. With the rise of social media, speed and availability were added as two important new elements to the service equation. People began to ask questions via Facebook and Twitter, and counted on getting answers almost in real time. In reality, service via social media has turned out to be a disappointment for both companies and consumers. The response times on social media are too long for most questions – an average of hours rather than minutes. In other words, the classic telephone call is still currently the best and fastest way to get the information you want. Okay, you may need to listen to muzak for twenty minutes or so, but it’s still quicker than social media. But it won’t stay that way for long. Automated interfaces will soon make possible customer communication in real time – but even this will not be enough in the years ahead. Anticipating problems and solving them before they bother the customer will be the new norm.
Sensors linked to automatic service provision facilities are the key to faster than real time customer service. For example, modern central heating systems are already smart. The classic systems of the past can often break down without warning – which is a touch inconvenient if it happens to be the middle of winter. You arrive home after a hard day’s work to find that your house has been turned into a fridge. This is where the problems start for you as a customer. You phone the service centre in the hope of getting help quickly. Will the centre still be open? Can they send a technician this evening? Or will it be tomorrow? And does that mean I’ll have to take a day off work? Even if everything goes smoothly, customers don’t like the uncertainty and they don’t like having to invest their precious time in this kind of thing. In contrast, a smart central heating system will tell you a week in advance that a problem is going to happen. So instead of arriving home to an ice-box, you arrive home to the following friendly message: ‘Hi Steven, this is your central heating speaking. I’m afraid I’m experiencing some problems at the moment and might break down shortly. If you press now on the ‘okay’ button, someone will call around tomorrow to fix me – if that’s convenient.’ It’s almost as if the unit has come alive.
We have often had the pleasure of working together with Mickey McManus. Mickey is a visiting research fellow at Autodesk. He is also chairman of Maya Design. A few years ago, he wrote the book Trillions. His basic argument is that we are currently living in a world of billions, but in the near future this will become a world of trillions. Today, we have x-billion smartphones. Tomorrow, we will have x-trillion devices connected to the web. According to Mickey, each of these new devices will be capable of coming to life, which will open up whole new fields of application. The explosion of data will have positive consequences for many different sectors. In factories, machines will decide when they need to be serviced. Sensors in furniture will adjust its shape to match individual users. For example, an armchair will be able to take account of the different physical characteristics of the husband, wife, children, etc. Once we have trillions of devices all linked to each other, the quantity of available data increases exponentially. As a result, the number of possibilities to improve service will also increase exponentially. There is a direct correlation.
The most important benefit of the trillions phenomenon will be faster than real time customer service. Our smartphone alone contains something like ten sensors. If you combine the knowledge of these sensors with the general knowledge that the smartphone already possesses about our daily lives, the number of possible applications is almost limitless. In the near future, for example, airline companies will rebook your flight before you even know you are going to miss it. Your smartphone ‘sees’ that you are stuck in a traffic jam and relays this information automatically to the airport, where your booking is changed to the next available flight. As a result, your delay is kept to a minimum and the airline can resell your empty seat to another passenger. Win-win. In this way, it again seems as though your flight ticket has come to life and can take its own decisions.
Acustom Apparel is a great store in New York. If you look at the store window, it seems like a classic gentleman’s outfitters. The window is full of elegant designer suits. In fact, Acustom Apparel specializes in personalized made-to-measure suits. Inside the store there is a scanner that scans two million data points on the body of each individual customer. This information serves as input to make the perfect suit. And once a customer’s data is known and stored, he can order a new suit from anywhere in the world, delivered to his home in just a few weeks. In 2017, the Adidas store in Berlin also started with the design and customization of personal sportswear. And Nike is also taking its first steps in this direction, offering the option of made-to-measure sport shoes to its customers. Many other brands in the fashion world are thinking about similar ways to personalize their products. The moment companies like Amazon and Zalando succeed in better personalizing their range in this way, the number of return deliveries will fall spectacularly – and so will the associated costs.
And it’s not just products. In future, services and communication will also be tailored more closely to the specific needs and context of the individual consumer. When people spoke about personalization in the past, all they meant was that a mail was introduced with a person’s name (‘Dear Steven…’) rather than an anonymous greeting (‘Dear Sir or Madam’). A few years ago, we saw the arrival of the first personalized brochures and magazines, where the cover was adjusted to match the profile of each reader. Digital printing has made more advanced forms of personalization possible, and companies like Nutella and Coca Cola have launched interesting campaigns where even the packaging is personalized on the name of the customer. The next step will be individual made-to-measure adverts and proposals. The data and the algorithms know what the customers like and also the way they are feeling on any particular day. This will lead to a very specific and individualized form of advertising. In fact, it probably won’t seem like advertising. If Google Assistant spontaneously makes a recommendation about a possible relaxing activity for the weekend, the Google platform is taking account of your agenda, your mood, and the weather in the place where you live. This kind of advertising can actually sound more like a suggestion from a friend.
Hyper personalization will become an important trend in the world of artificial intelligence. Once again, data is central to making this benefit possible. The more data there is available, the more relevant information and products become. This evolution means the end of the road for the old-style market philosophy of segmentation. Segmentation divides the market into a number of groups with comparable needs. This allows the marketeer to match both communication and product characteristics to the needs of each different segment. Based on this philosophy, marketing people assume a high degree of homogeneity within segments and high level of heterogeneity between them. Segmentation still believes in the world of the average customer. If your market has four segments, this means you have just four types of customer. Each of these groups has its own persona and its own specific requirements. Imagine that your product is targeted at women between the ages of 35 and 40, with two children and a fulltime job. As an old-style marketeer, you will regard all these women as being more or less identical. But if you had the opportunity to see this group in real life, you would soon realize that they are far from identical! Segmentation was a good halfway-house solution in a world where personal data was lacking. But this data is now available in abundance – and it shows that every consumer has a different personal context, which means that their consumption and communication needs are often fundamentally different. Segmentation still works, but only if the maximum size of the segment is one.
Effortless user interfaces
Ready for a short test?
Do you every use Booking.com?
If you do, please name five positive things about the site in the next 30 seconds.
Super, thank you.
Third question: are you (secretly) a little bit in love with the brand Booking.com? Are you a big fan?
During the last 12 months, I have done this little experiment as part of keynote speeches in just about every country in Europe. These are my findings (the target group is, of course, a business public).
There is roughly 90% market penetration for Booking.com in the business community.
The most common answers shouted out in the allotted 30 seconds include: fast, personal, the app, easy cancellation, no advance payments, the reviews, the photos, the maps, easy, the point scores and the huge range on offer.
Just 1% is a real fan of the Booking.com brand.
To me, this is amazing. Almost everyone uses the platform. Everyone is very positive about it. But almost no-one is a fan. For classic marketing profiles, this is a remarkable paradox. But in the new marketing world, this is the new normal. People don’t fall in love with the brand, but with the brand’s interface. If a new platform is launched tomorrow that is faster, easier and cheaper, they’ll drop Booking.com like a stone. Even more, they will probably promote the new site amongst their friends.
The interface is increasingly becoming the key determining factor for brand positioning. Consider, for example, your bank. The most crucial interface for a bank, the one that can make or break it as a brand, is the mobile banking app. Why? Because people use it dozens of times each week. The impact of this app is much greater than anything that marketing and advertising can ever hope to achieve. The user interface determines market perception.
‘Convenience is the new loyalty’ is one of my mantras. In an impressive recent study, Byron Sharp came to the conclusion that classic loyalty programmes no longer work. These systems are based more on a reduction in the financial margin than on an actual increase in customer loyalty. People are less faithful to their brand than to their favourite interface. Another recent research project into search behaviour on Amazon revealed that consumers nowadays search much less on brand names than they did 10 years ago. If someone wants to buy shoes on Amazon, they search five to six times more by category name than by brand name. Once this has been done, they generally follow the recommendations suggested by the Amazon algorithms. The same is true to a lesser extent for people wanting to buy accessories. Here they only search three times more by category than by brand. One of the few exceptions is some types of beauty products, where the category is ‘only’ 30% ahead of the brand. But in every category the same general conclusion holds good: generic searching is more important than brand searching. Loyalty to a brand has been transformed into loyalty to the most user-friendly interface.