By Scott Logie, MD, Insight at REaD Group
We are living in the age of machines. What used to be thought of as science fiction is now simply taken as fact. Electric cars, payment by watch and tv on the go are all being used by everyone every day. In addition, thought controlled bionic arms, space travel and waste blasting toilets without the need for a sewer are all being trialled right now. Surely teleportation isn’t too far away and we can all go Back to the Future.
Technology on the rise
In the world that we inhabit – the world of marketing and building customer engagement – machines are already common place. Machine learning models, chatbots and AR/VR based content are being used, and are being well received, by the end customer. In fact, there are areas, such as gamification, where consumer demand is greater than the usage at present. As a Fitbit obsessive, if someone ties my daily step count with rewards in exchange for data then I would sign up immediately.
One of the many debates this creates is around whether it is necessary to inform the end customer that they are engaging with a machine. From a personal point of view, I’m not sure this is needed. For me, the bigger issue is ensuring that the right combination of person and machine is in place.
Research shows, for example, that people really want to talk to people when the request is complex or where there is a need for a complaint to be made. Making sure that the conversation can be identified as moving in a particular direction and the right intervention is in place feels more vital than the end individual knowing if the operative is real or not.
74% of consumers admit they would sooner complain about a product or service to a human rather than a chatbot [DMA Customer Engagement 2019 – Facing the future: how consumers and brands view new technology]
Rage against the machine!
Certain AI platforms, such as the financial assistant, Plum, are now being programmed to deal with abusive messages such as those containing swearing, rudeness and sexism. This has seen a positive impact from a customer perspective, as witty and humorous responses from the AI have often helped to defuse a situation and reassure the consumer that they are dealing with an intelligent entity.
And in reality, it isn’t too long until we allow our own machines, home assistants or phones or even our fridge, to engage with the brands machines and make decisions for us making the identification moot.
Data is vital
Of course, at the end of the day, there are some constants that always need to be in place. The first is identifying who the customer or prospect is and being confident that you have the right person and the second is having enough data of interest to make the interaction relevant. In amongst all the chat about AI, VR, AR and machine learning it is vital to remember that it’s the data that fuels the success – or otherwise – of these technologies.
At REaD Group we often talk about giving brands the right to be personal. That is never more real than when there is a combination of machine and person doing the engagement. Not having the data infrastructure, or indeed the base data, in place means that the discussion about machine v person is irrelevant. Ultimately, having a clean, up to date, enriched dataset is vital to the success of any AI, chatbot or other technology-based pilot.
By Scott Logie, Chair of the DMA Customer Engagement Committee and MD, Insight at REaD Group
I recently had the privilege to chair the DMA’s Future of Customer Engagement event in Bristol. I lived in Bristol for nearly 10 years, loved the city and still do. It’s a vibrant, cultural hub with great art galleries, restaurants and gig venues. It also has a very active marketing community and that was evident both in terms of the 60 plus people who came along and also the wide range of speakers at the event itself.
The event was built around some research we have done as the Customer Engagement Committee. We’ve done a lot of research over the last few years and in all the studies have taken some time to focus on what the likely future trends are in terms of areas that consumers would like to use to engage with brands. Tim Bond, from the DMA research team picked out 4 key trends:
Chatbots – those virtual assistants who help you on-line. One of the key stats that Tim shared was that men were more likely to want to engage with chatbots than women (36% v 26%). As a middle-aged man, this didn’t surprise me, anything to avoid talking to real people. The sooner these are used to replace doctors, customer support teams and dental nurses the better!
Voice – generally seen as Alexa or Siri but really any voice activated device at home or on the move. The key reason given for using voice commands was convenience which makes sense. My worry here is how freedom of choice is retained as more and more decisions are left to devices to make.
Virtual Reality or Augmented Reality – using devices to bring locations or products alive. This is clearly one of the most exciting aspects to consider when looking at any future trends. Something we all (‘we’ two thirds of us) express interest in but the challenge here is how you move from something that is a gimmick to something that adds value.
Gamification – using competition, goals and targets to incentivise customers to change behaviour. As a Fitbit obsessive I really get this but haven’t linked any of my goals to a product yet. There are insurance companies, and banks as well, giving rewards to customers who can prove behaviour change – live healthy and pay less for insurance – why not!
In addition to the research we had a panel discussion around these four topics that drew out lots of areas for discussion, but for me the key point was that while tech is maybe driving some of the change we are seeing, tech alone is not the answer. This then brought us back to one of the main principles of the whole Customer Engagement campaign – to show that the brands that will win in terms of building long term loyal relationships will combine tech, data and creativity to achieve this.
The next three sessions were really testament to this. First of all, Ian Hughes from Consumer Intelligence showed how insurance companies from around the world are, right now, breaking down barriers and allowing consumers to buy insurance in ways that suit them. The main driver for this is putting the customer in control – so no more need to buy a large one-off insurance policy for your car when you only use it 3 hours a week; or using life insurance to purchase policies that can provide a real-life event for those left behind rather than just paying for the funeral. Interestingly, most of the innovation was being driven from outside of Europe and North America.
Neil Mackin from Amazon Web Services then presented on two topics. The first centred around how AI and Machine learning are impacting on lots of areas within Amazon – from distribution and warehousing to recommendation engines and next best offers. The second was what Amazon are doing to make a lot of the algorithms they develop available for use by brands, universities and just ordinary people. They are often derided as being the example of all that is bad with online retailing, killing our high street. However, the impression I was left with was one of a book retailer becoming a tech giant and using the work they do responsibly and sharing the learning.
The fun and informative final presentation was from Lovehoney, the UK’s largest on-line retailer for sex toys and lingerie. They are a real South West success story and grew out of observations made by marketers on what products were going to sell in the future and, guess what, sex sells! In addition to being probably the only presentation I have sat through where a full range of wild and unmentionable *ahem* toys were discussed repeatedly, the thrust of the session was really how well structured Lovehoney are around the customer – from staff training, product reviews, product testing, email comms and on-line interaction they showed how the customer is key to everything that they do.
In many ways that summed up for me the key takeaway from the really excellent afternoon, which is that all the tech in the world is useless unless you know the customer, know what they are like, what they want and then provide that to them in the most convenient way possible. As the world changes and what we see as traditional marketing dies away, the winners will be the brands, and the suppliers and agencies that support them, who really take that lesson to heart. Being personal is knowing the end customer, and ensuring the engagement matches their preferences using whatever technology and content that is available to do so.
By Scott Logie, MD, Insight at REaD Group
The robots are coming! Well, not quite, but the ever growing trend for implementing AI and automated systems to aid in our everyday lives seems to be showing no signs of slowing.
Recent research conducted by advisor company, Gartner, suggests that by the year 2020 a quarter of all customer service and support will incorporate chatbots or a similar form of virtual customer assistant technology. This seems like an astonishing figure, and one that has both positive and negative connotations.
The last decade has seen a huge jump in the proportion of people engaging on digital channels, and it is therefore hardly surprising that companies are investing more and more in these virtual customer assistants. Purely from a resource point of view such a transition makes a lot of sense; artificial intelligence (at least at this stage!) doesn’t ask for a pay cheque.
There is also a distinct advantage to the consumer – these automated systems are capable of functioning 24/7, without the need for sleep or coffee breaks. Furthermore, the prospect of a future free from hours spent on hold listening to Justin Bieber might not be the worst thing in the world.
However, when it comes to customer service, can human contact ever truly be replaced or replicated? According to research we conducted last year, 62% of consumers rated high quality customer service as the largest factor influencing brand trust and loyalty in the retail sector (Retail Trend Report 2017: New World, New Consumer).
While these virtual customer assistants are undeniably becoming more sophisticated all the time, it is the warmth of human interaction that creates this customer engagement. Some of these systems are capable of detecting frustration and anger in a customer’s voice and will transfer the call to a person in a call centre at a certain point. I find shouting down the phone helps. But by and large there is no doubt that they are still worlds away from being able to react and alter their response or attitude based on things like sarcasm and emotion.
There also comes a stage when we have to ask – where does this end? Do we eventually reach a point where human contact has been phased out entirely and we find ourselves reliant on machine to machine relationships? Say, for example, my bank bot detects that I’m overdrawn and applies for an overdraft on my behalf, and this instigates another chatbot which then decides whether to grant me said overdraft. The possibilities are dizzying, and somewhat terrifying – just one short leap to Skynet!
The question of trust and customer experience is not one to be overlooked lightly. The majority of consumers taking part in Gartner’s survey said that they find it difficult to trust VA’s to assist them with more complex tasks, such as handling their banking, insurance or utility issues (29%, 16% and 35% respectively). Therefore, brands will need to demonstrate to customers that they will still receive the same high levels of customer service once these technologies have been incorporated.
Perhaps if this predicted future comes to pass a balance will need to be struck between convenience and functionality. A system whereby technology and human work in tandem may be considered as an initial compromise – HAVA’s (Human Assisted Virtual Assistants). The idea being that when a VA is faced with a situation it cannot handle or a question it cannot answer, a human agent will then take over the conversation. The growing development of machine learning will also theoretically mean that VA’s are able to learn from these instances and adapt to resolve these situations themselves in future.
Essentially, it will remain to be seen how effective these VA’s are in maintaining the high levels of customer service that consumers have come to expect. Advancements in technology such as natural language-processing and machine learning are perhaps bridging the gap between the soulless and robotic automated systems that we’ve come to know, but can they ever truly hope to encourage the same level of engagement and replace human interaction? The next few years will certainly be interesting, but brands must be sure to put customer experience first, or risk dealing with the consequences.
2nd February 2017
By Scott Logie, MD, Insight at REaD Group
During the recent, and really rather excellent, DMA event on the Future of Customer Engagement there was a throw away remark made by one of the speakers that really stood out for me. In amongst all the Dystopian nightmare futures; predictions of millions of job losses and the creation of new ones we can’t even imagine as yet; the replacement of call centres with chatbots and the running of our homes handed over to tiny lovable robots was the statement “one aspect of customer engagement we need to consider is that much of it will be between machine and machine”.
When we think about customer engagement, at least when I do, we tend to think about computers, or even Artificial Intelligence on the company side – creating triggers when someone drops onto a website or automating outbound comms, responding to live chat on-line or in a call centre. However, there is also the automation, or computerisation, of the customer side of things. With things like Siri, Cortana, Amazon’s Echo and Dot functionality and Google Now already common place there are times when the decision to engage with a website or brand may not be made by the end consumer but could well be made by a “machine”. As such, who – or indeed what – is the customer in this instance?
From a data perspective, this makes how we gather, hold, manage and then present data and information in the future very interesting. In the past a Single Customer View (SCV) was centred around a person, or maybe a household, based at a physical address. Over time this evolved to take into account e-mail address where we would often know an individual by an email address, and start to gather a lot of data against that email address without knowing who the person was, or where they lived. In many cases it might even be that we never actually find out what that person’s full name is but through e-mail we can build up a decent amount of knowledge and information about them and start to create a meaningful relationship.
In recent times that has evolved again. From the first time an individual drops onto a website we now tend to capture the IP address and/or the device ID of the device being used. If that doesn’t connect to one we already know we then create a new record in the SCV. Over time this device connects hopefully to an email address as we get initial registration and then, if needed, to a name and address as a transaction takes place. This does mean that we do already centre our SCV developments on machines.
To a certain extent it is about ensuring that we capture the most relevant data as early as possible and then connecting that data to a “person” as we learn more. So in many ways we have the technology capability already in place to deal with building a database, or single customer view, that creates customer engagement strategies between two devices. On one side are automated triggers and engagement streams already in place, on the other side devices that may or may not be operated by a human.
Back to the recent event. During an inspiring presentation by Jeremy Waite from IBM, he introduced us to Jibo, the next generation of home help style AI. Jibo responds to human instructions but also has enough intelligence to collate data and make decisions on its own behalf. As an example, Jeremy, who has been testing it out, recently got told by Jibo that he was running late for a meeting and didn’t have time to walk so Jibo had ordered him an Uber. While this is amusing and shows how AI is developing, it also raises quite an important question: Who are we marketing to here? The person who owns the robot or the robot itself? Does Jibo decide to use an Uber because the owner has trained it to select Uber as their taxi firm of choice or does Jibo select Uber because it recognises Uber from marketing messages received? To a certain extent it doesn’t matter, as AI develops the robots will increasingly make decisions on our behalf, marketing will need to also develop to “sell” to machines.
While we might be set to market machine to machine at the moment, and be able to gather and host the data required to do so, I suspect where we currently do fall short is in our ability to distinguish between machine and person in terms of how we are trying to influence and why. This will provide a real challenge for the future and one that might need to be solved quicker than we think.
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