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Artificial Intelligence and the impact on personalised experiences

Artificial Intelligence and the impact on personalised experiences

If you close your eyes for a moment, stop and think about a customer experience which stands out to you. Think about what makes you remember that particular engagement and what this means to you.

Customer Experiences which stay with you – which leave you with an impression – positive or negative – almost always have one thing in common. An emotional reaction.

When I think through both the positive and negative experiences which I recall most frequently, I can summarise them as:

  1. Did the experience add or remove complexity and decision making from my day?
  2. Was the experience personalised to my interests/preferences/behaviour?
  3. What was the emotional reaction following the experience?

These interactions occur across multiple channels – in person, online, in social forums, by phone. And these experiences have a direct correlation to our engagement, and spend with that company.

American Express have quoted that customers who have a positive customer experience spend 74% more! Whilst McKinsey have reported that 70% of buying experiences are based on how an individual “perceives” they are being treated.

This perception comes back to the simplicity and personalisation of the engagement – and again the emotional reaction of the experience.

Personal, simple and emotionally connected experiences – piece of cake right…??  In 2015, Forrester reported that only 1% of companies are delivering excellent customer experiences. The creation of amazing customer experiences is becoming the competitive battle field. In 2016, IBM interviewed over 300 global CEOs, CMOs and Chief Customer Officers, and it was evident that those companies who put the customer at the centre of their design point for digital transformation, were rapidly achieving competitive advantage. And the foundation to achieving this advantage – data and technology.

The ongoing development of Artificial Intelligence, that is the augmentation of human expertise with technology, means that technology no longer sets the limit to what can be achieved. The only limitation is our imagination. This is because AI  understands all types of data, it provides recommendations not only based on the data but also based on personality, tone and emotion, it learns and enhances decision making based on the actions taken from previous recommendations, and I personally think, most importantly of all, it allows you to interact with the data – be it as a professionally, engaging with the data in a simple way to make decisions, or as a customer engaging with the organisation at your convenient time – not theirs.

So, let’s explore the creation of personal, simple and emotional experiences that we have each day in our day to day lives, and how data and technology are the foundation to achieving this.

A. Creating Personal Experiences

Case Study 1: Vodafone Qatar

Vodafone Qatar serves 34% of the Qatar population with mobile communications services, and generates over $USD527 million in revenue each year. To increase revenue further, the strategic priority was to nurture the loyalty of its existing customers and ultimately increase the average revenue of each user. But how does it do this?

In Qatar, most customers have multiple SIM cards and they decide which card to top up based on the most attractive offer personalised to their specific needs. For instance a customer who wants to call their family back home in Egypt will want to use their phone at a very different time to an individual wanting to call their family home in the Phillipines. Some customers want to speak to their call centre in English and others in Arabic. Vodafone meanwhile had different systems to manage each of the customers interactions. For instance, one system governed the call centre data whilst another managed their outbound marketing. Imagine sending an upgrade offer to a customer with an open customer complaint with the call centre. Now think about how you would react to this experience and your likelihood of responding to the offer.

The Vodafone team made the decision to transform. They put the customer at the heart of their customer experience design to ensure all teams were able to leverage and interact with all the data and insights, and personalise each and every offer, message and engagement based on the very personal behaviours and needs. The results were compelling.

By building, a 360 degree view of every customer, using all the data it has, Vodafone have been able to enable deep insight into individual customer preferences and behaviour, improve up and cross sell conversation three times, and deliver a three times boost to below the line marketing revenue.

Case Study 2: Deakin University

University life can be complex. You may be studying today, or can still recall the first moment you started university – managing that transition from a known high school environment to a large university experience where everything is new and just a little overwhelming.

At Deakin University, experiences are now more personal – and more convenient – with students are able to engage with Genie, a virtual assistant, designed as a companion for students to help them learn about life on campus. In the first year of pilot, students asked over 55,000 questions,  and on average now ask over 1600 questions a week. Genie today is helping students to walk through processes ranging from the submission of assignments, to paying for car parking and even how to re-enrol in study.

Genie interacts with the student to understand which campus they are in, and if they are an international or domestic student to tailor the answers to the personal needs of the student. And will even let the students know how confident Genie is with the recommendation provided. And the most common questions – how do I meet other students from my course, where can I get food on campus, when is my exam, when will I receive my course material – are just a few examples.

Case Study 3: The Hospital Experience

The hospital experience is one which we can all relate to.

In Philadelphia, a hospital is leveraging AI to personalise and improve the simplicity of the experience for every patient – whilst also freeing up their valuable nursing team for more complex issues and patient care. Each of my three children were delivered by emergency C-Section. Following surgery, for 24 hours I was not able to leave the bed. I was completely dependent on the nursing staff for every request and every question. And, as someone who likes to be in control of their own destiny, asking for help did not come easily.  I was also acutely aware that every time I asked for help, I was taking the nursing team away from another situation which was potentially far more important. Recognising that patients craved for some independence in the hospital environment, they partnered with IBM and Harmon to create a digital voice assistant which could be summoned by one simple word “Watson”. Using natural language, the assistant is trained to help for a range of requirements – from the temperature of the room, opening and closing the blinds, turning the lights on or off – as just a few examples. Moving forward, the assistant will         be trained to ask questions about the surgeon or doctor, or on personal care plans. A great example of how an often unpleasant experience can be turned into a more positive one.

Case Study 4: Sesame Street

OK I love this story. When I think back to my childhood, I think of chocolate eclairs eaten with my Nanna, of collecting cicada shells with my brother, and, my all time favourite hero, Snuffleupagus, from Sesame Street. For many of us, our earliest memories begin with Sesame Street – and it invokes memories of happiness and fun. I recall having stuffed toys which I dragged around everywhere. My son meanwhile had an Ernie which yelled out in Spanish and kicked a soccer ball.

Children of today however will be treated to a more personal and interactive engagement with Sesame Street.

Sesame Workshop has launched a new vocabulary learning app which enables teachers to monitor student reading and vocabulary development, and then personalise the learning for every student. The app adjusts the pace of learning, and the delivery of new words based on the student personal learning preferences and learning level. Experiences are tailored for each child, adapting exercises and coursework as the child progresses. The app also challenges previous teaching biases, for instance, words like camouflage were considered too difficult for children, yet         the app shows that the children are using and understand the meaning behind this word. It removes bias or previous opinions, and allows a more data-driven teaching methodology. Whilst still in pilot phase, the plan is to roll this app out across the globe.

Now imagine how this could be taken to children in every home, embedded in a toy, for instance, in an Elmo toy. If equipped with natural language and machine learning, the toy could understand what the child is saying, and then change the games for the child based on the way the child is interacting and engaging. If the child can easily count to 10, let’s now expand that to 50!

The experience of learning and play has never been more fun.

This concept already exists today. The Cognitoy Dino, developed in partnership with Elemental Path, is recommended for children from 5 through to 9 years of age. Connected to the Wi-Fi via the Cognitoy app, the Dino can interact and answer age appropriate questions and engage in age appropriate games and activities. Using tone analysis, the Dino will understand if a child is scared, or happy or sad and provide recommendations. For instance if the child is sad it might suggest telling them a funny joke, or if they are scared suggest they go and talk to a grown up they trust. The responses to questions are adapted based on the child’s preferences, personality and learning capability. For instance, if a 5 year old child asks the Dino how far the moon is from the earth, it might say “Oh my goodness that is a long long way away” however for the 9 year old the Dino might respond with “The moon is 384,400 Kilometres away” . And as the Dino is connected to a Cognitoy app, the Dino is always learning and providing new content, new jokes and new responses to the child.

B. Simple customer experiences

Have you ever walked out of a store because you could not find someone to answer your question? Or given up on a shopping cart because it was just too difficult to complete the online ordering process. Personalisation is important – but the foundation needs to be an easy experience. The great news is that there are some amazing companies out there creating simple and engaging experiences designed to make it easy for us to engage and buy!

Case Study 1: Macys

This weekend, I was shopping in the city. As I entered a large department store, the lovely employees pushed a flyer full of offers in my hand requesting that I read these. I declined. This is a department store who HAS MY DATA. They know what I do, and do not buy, and the frequency of purchases. They know my average spend per visit, and my location by using geospatial data. Why oh why am I receiving an impersonal flyer – which cost money and effort to create and print – and of which would just be thrown away?

As a marketer I scratch my head wondering what their KPIs are and why the team is not optimising their campaign performance through the use of data and technology. And as a shopper I am frustrated as the experience was not personal. It was not designed for me. And as someone who loves technology, I leap with excitement, because there is a solution.

As a starting point,  I love what Macy’s is doing. Last year, Macy’s announced the pilot of Macy’s on call, a mobile web tool which is powered by AI. Customers can ask questions like “where are the ladies shoes” or “where can I find a specific branded item”, and they will be provided clear directions on where to find what they are looking for, and customised to the specific layout of the store the customer is shopping at.  They can ask for offers on particular items of interest and receive a view of the offers they want to know about on the day they are in the store. No more flyers! Macy’s on call is being customised for Spanish language to serve a broader customer base. And by learning what questions customers have most in each store, the tool learns and provides more customised responses and proactive content. And if the question is more complex, the tool allows the customer to summon a customer service representative to come to wherever they are in the store! Bliss. In the future Macy’s is looking at providing personal styling advise to customers … and more!  Watch this space!

At the core of this pilot, is the creation of simple engagements with the brand of Macy’s. But the future transformations bring forward personalisation and emotional connection.

Case Study 2: Staples

Ordering stationary for the office. It sounds simple to order a blue pen, but this process is surprisingly difficult – What brand? What type? How many? Staples wanted to simplify the ordering process – to provide a seamless experience to quickly order or reorder your stationary and office requirements, track shipments or engage with their customer service team. At a touch of a button you can order your pens or even your coffee, using natural language, and find out when it will be delivered.

Watch this video to see how easy Staples has made the process of ordering and managing office supplies.

Case Study 3: UBank

UBank are a disruptive and challenger bank. And they are doing just that. Imagine you run a call centre, and your customers are waiting on hold to speak to the customer service team with long periods of time. They are regularly hanging up without getting the advice they need. How would you ensure simple and quick questions are supported, through repeatable models, whilst the valuable customer service team are freed up to spend more time on complex questions. There are a myriad of questions in which your customers ask, and will ask, about your business and solutions. Some of which can be answered quite easily and others which require the assistance of a human. Not all simple questions can be found on your web site – or – customers do not wish to scroll through pages of Q&A. A virtual agent, built on AI, will understand natural language, in context to your business. A customer can ask questions and receive responses, often fast tracking to purchase from there. This reserves the call centre wait time, for those who genuinely need to talk to one of your call centre customer service reps. UBank are doing this with their RoboChat offering, leveraging AI to help customers with their home loan questions. It is in market now. Check out their web site!

Case Study 4: Meet Ivy by Go Moment

For many of us, travel and tourism is a welcome escape from the increasingly busy lifestyles we live. For me personally, I adore visiting new places and exploring the world, learning and being inspired. Yet it is also, something which fills me with dread. From hotel check-in, to navigating new places with children – jet-lagged and hungry – to trying to communicate without a common language. Today, those moments of stress are being removed by artificial intelligence driven travel partners.

For instance, Go Moment’s “Ivy” can now understand and answer 90% of questions asked of guests from a specific property. Guests can rate experiences and moments of truth in real-time. They can ask for room service, or a bottle of wine to be delivered by the pool, or perhaps extra towels. The request will be sent to the appropriate team in the hotel, and delivered based on the location of the guest. And if the tone of the request clearly demonstrates that the guest is extremely unhappy, Ivy will opt to ensure that a customer service representative is contacted and the guest called — by a human — to address personally. As hotel operators, Ivy provides real-time satisfaction monitoring throughout the experience and have a chance to address and turn a negative experience into a positive one, before you and many other potential guests read about it on Tripadvisor!

Case Study 5: Personal Concierge at Pebble Beach

Pebble Beach is a golf resort at California who has launched a personal concierge for their guests, allowing interaction by voice or by text, to answer questions relating to dining, shopping and drinking destinations at Pebble Beach. There is even an audio tour which can be played as the guest drives around the resort.

I can imagine leveraging this type of concierge in theme parks, or in major cities as I travel with my children. The experience of travel need not be complex any more. Pebble Beach is showing how this can be achieved.

Case Study 6: Roskilde Rock Festival

Meanwhile in Copenhagen, the Roskilde Rock Festival is an annual event attracting over 130,000 visitors for 10 days every year.  So how do you manage the experience of ticket sales, food and merchandise sales, communication of activities and even the maintenance of toilets. Leveraging Artificial Intelligence and IOT technology, it is possible to provide recommendations and alerts via an AI powered app to festival attendees on where to purchase food where there are no long queues, or what festival activities are happening right now. With weather data, festival goers can be alerted on rain or hail, or other weather conditions which will impact their experience. With IOT across the festival, alerts can be sent to the maintenance on emerging issues for instance if a toilet has not been used for a period of time, it may indicate a blockage or issue that needs to be addressed. The experience of festival attendance is now smarter and more convenient than ever before.

Case Study 7: IBM, General Motors and Mastercard

I spend a lot of my time in the car, and as I drive along, I think about all the things I need to do and just do not have time. So how do you make the experience of driving a car, personal and simple?

Mastercard is partnering with General Motors and IBM to implement a new system in cars to make it easy for you to get through your to do list, safely and conveniently. Imagine being able to interact with your car and ask to place an order from a partner restaurant. The OnStar Go System will prompt the driver on previous order history, offers which are personalized and tailored to the individual and allow for payment to be made, all whilst you are driving along. Or perhaps your car is ready for its next service and you can be prompted to make this appointment, book and pay, without leaving your car. Convenience is now more than drive through takeaway – it is a personal, easy to use engagement, maximising the time of the time poor. I am looking forward to this concept expanding to other payment methods and other vehicles!

C. Customer experiences which create an emotional connection

So we have touched on personal and convenient. Now emotional. In all those examples, the end outcome ultimately creates an emotional connection. I think joyfully of navigating holiday travel with my children with ease and simplicity, and I dance a happy dance at the thought of being provided concierge assistance and personalised information whilst shopping in a store. Emotion triggers memories and action. It is the core of being human.

Case Study 1: Horror Movies

When I think of emotional connection to experiences, I do often think about horror movies. My first horror movie was IT — and to this day I am still scared of clowns!

Morgan is an AI Horror Thriller. And IT.IS.SCARY! If you have not seen this movie, it centres around the character Morgan, a human like robot powered by Artificial Intelligence. Morgan can converse like a human, engage in conversation and learn like a human. However what Morgan ultimately cannot do is self regulate and make moral and ethical decisions. The consequences are horrifying. And the trailer provides the teaser of how frightening this movie will be. The producer of the film, Fox, approached IBM and asked if Watson could analyse the movie and generate a trailer automatically. Challenge accepted. Watson was able to analyse and interpret salient moments, to identify whether moments were scary, tender, happy or sad, and provide recommendations on a sequence of moments in the film which would have the highest emotional connection with the viewers. My children were leaping at the chance to watch this film once their experienced the trailer – I curiously joined them, with a comfort blankie close at hand.

Check out the trailer here:

Case Study 2: Pizza Hut, Mastercard and IBM

On the complete opposite spectrum, ordering fast food rarely elicits a reaction from me. It is an exchange where you know you will typically receive consistency of food in a convenient engagement. It is a low value, low exchange experience. But what if you could add some fun to the experience – what if you could create a memorable and personalised experience that goes beyond self serve machines and kiosks? The pilot in Asia, allows diners to synch their Masterpass account to Pepper and for the robot to them make personal suggestions and recommendations from the menu, no calorie judgement, and allow you to pay at a simple command. It is fun, interactive, possibly a little creepy. It is definitely memorable. It  is not perfect – there are squads of children who have the intent on creating confusion – and the inebriated adult who wants to have a little dance with Pepper. It is indeed a way to merge personalisation, simplicity and emotional to create an experience you will speak of for years to come.

Case Study 3: Connie, Hilton Hotel’s newest concierge

Meanwhile in the hotel industry, I shared already how hotels are aiming to provide a more personal and simple experience using concierge companions. And then there is Hilton. Hilton Hotel in Virginia has been piloting Connie, an AI powered robot designed to provide concierge advise to guests. The goal to reimagine the travel experience and wow guests in unexpected ways. Together Hilton Hotels, Wayblazer and IBM are doing just that, helping guests with questions on hotel amenities and services, and even local attractions and events outside the hotel. And throughout the exchange, constantly providing opportunities to provide feedback and an opportunity to engage with the guest in a meaningful way.

Case Study 4: Meet Rachel, Soul Machines AI enabled avator

One of the most common triggers of emotion, comes from equity or fairness. Yet how is it fair that online experiences are rarely designed for this with disabilities. Soul Machines aims to change this and ensure equity in online experiences.

Meet Rachel, a lifelike avator embodied with Artificial Intelligence – who can see and hear, engage in conversation, detect emotion and interpret reactions. It allow you to engage with companies on line without using a keyboard and in a connected experience which ensures you are being understood Rachel is currently learning how to recommend the best credit card for you – and there is more to come .

In Conclusion

Customer experiences designed with the audience segmented to a person of one, of which are designed to remove complexity from each moment of truth and of which create positive and memorial moments of truth, are experiences which will build the disruptive and powerful brands of the future. They are experiences which we remember, which we talk about with our friends, family and colleagues and they are experiences which we share on our social channels. But most importantly of all, they are experiences which provide us with the emotional reward needed to continue advocating and buying from brands in the future.

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