Newvoicemedia whitepaper dawn of ai powered customer engagement uk

The dawn of AI-powered customer engagement

By Martin Hill-Wilson for NewVoiceMedia

Introduction If Frank Eliason has become the recognised founding father of social customer service, then Alan Turing deserves the same accolade for the next generation of self-service we are now witnessing.

The film title for ‘The Imitation Game’ came from a chapter heading in a book that Turing wrote which explored the criteria for an ‘intelligent machine’. He argued that if someone could not tell the difference between how a human answered questions and those from a machine, then that machine could be considered intelligent.

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Fast forward sixty years from when Alan Turing first proposed this test and we are now at the dawn of intelligent assistance becoming mainstream. In reality, we are further on than that. The latest generation of capability powered by artificial intelligence already allows us to successfully interact with an intelligent assistant by voice or text.

Crucially, intelligent assistance can understand both the context and intent of our enquiry. Even better, it can become smarter over time at both understanding and responding once machine-to-machine learning is plugged in as a background activity.

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If you want to bring this to life, try a new game that Google has recently launched. It’s called Quick, Draw!

As you draw on the screen, the system tries to guess the shape based on the previous doodles it has already stored on its neural network. It’s a fun way of discovering what machine-to-machine learning does and starts to help you realise its potential in customer engagement.

The things that matter Humans are very competent at recognising patterns.

We constantly look for them in life, it is something hardcoded into our DNA. For example, think how readily we respond to a sudden change in our field-of-vision or a loud noise. If the anticipated patterns are inconsistent, we notice immediately.

We do this as we have to make sense of things and recognise events before they happen. But, we become overwhelmed when the amount of data we are scanning becomes too great to absorb and process. This is where computing excels. Especially when it is run as a cloud service, such as a neural network, which is where machine-to-machine algorithms are typically housed.

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With this massively expanded capability, we can discover patterns that lie beyond human observation.

What is the most likely best answer to this customer’s question based on all previous ones?

Of all the deals in the pipeline, which are the priorities based on their match against the ideal characteristics of a customer?

In a world where the amount of data we are all exposed to keeps growing and growing, we are clearly at a point where we need some help to see the wood from the trees.

Assuming you are someone who has eagerly adopted smart living, you risk being overwhelmed with the sheer volume of feedback from your smart home, Fitbit device and other forms of real-time feedback. Instead wouldn’t it make life easier if your own digital assistant could help you find a better value utility provider? Or keep tabs on your monthly cash flow? In other words, root out what really matters in that data lake.

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Acting digital is about being real-time This kind of proactive help is clearly relevant in a world where reducing customer effort remains a major customer service objective. Here are some of the obvious uses of this capability many organisations will want to leverage: 1

Based on your interest in these products/services, are you interested in...?

2

Based on how you are using this product/service, are you interested in...?

3

Since you asked about these features, you might also want to know...

4

Based on your previous interest, this item is now in our summer sales

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In the old world, these instances would remain buried in management information reports and certainly would not be surfaced in time to be relevant from the customers’ perspective.

A similar approach can be taken in customer service to anticipate customer need and therefore transform a live inbound enquiry into either a self service or proactive service experience:

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1

Is this safe/allowed/possible?

2

When/where/how - will it/they - arrive/be collected/be fixed?

3

How do I do xx with my new yy?

4

What will happen next once this has finished?

Self-service finally arrives Sometimes reducing effort simply means not having to wait to talk to a person. Contact centres inevitably have busy periods. Talking to someone is not always going be an option late at night or at certain times over a weekend. Moreover, I may be someone who does not like live assistance. Indeed 31% of UK smart phone users make no traditional voice calls in a given week. That’s because smart phone culture tends towards autonomous self-management.

We can see this in our purchasing behaviour. Customer reviews, community experts, trusted friends and families that can be tapped into via a messaging app now empower us to find out what we need to know. All at our convenience.

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This form of behaviour has inevitably affected businessto-business purchasing behaviour as well. Reliance on a sales person for information and advice is gradually being reduced, especially in the early phases of the buying journey. 2016 Forrester research into this evolving behaviour discovered that 59% of US based B2B buyers agreed with the following statement:

I do my own research online and prefer not to interact with a sales representative as my primary source of research

Forrester’s insight into this behaviour illustrates the world we are moving into.

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In the not-too-distant future, when B2B buyers engaged with a virtual assistant are ready to speak with a human, the VA will schedule the meeting and provide the sales rep with all the context they need to pick up the thread without missing a beat.

Earlier in 2016, Kate Leggett, also from Forrester, reported that US customer adoption of intelligent assistant in contact centres grew from 28% in 2012 to 52% in 2015. Another sign of the appetite for selfservice.

In turn, Gartner are predicting that customers will manage 85% of their relationships with an enterprise without interacting with a human.

We have already seen this trend in our own contact centres. We can see the impact in terms of the increase in average talk time when customers do want to speak to someone. The simpler enquiry is now being dealt with through self-service.

Of itself, this is not breaking news. The intent to provide self-service has been a long standing customer service ambition. Until recently, this meant offering an IVR or online service portal. Unfortunately, both have attracted customer criticism for being hard to navigate and use with the result that many still revert to live assistance.

What has now changed is the way we can offer a superior customer experience that makes self-service a clearly better option.

Intelligent assistance can be positioned as a single gateway to any enterprise service. A conversational middleware that can access information and workflow housed in legacy systems. The impact can be transformative.

Think about the previous complexity of trying to shoehorn a desktop sized e-commerce site onto a smart phone sized screen. Even when made responsive, it is a tough challenge for retailers to balance simplicity against choice.

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Instead, an intelligent assistant can operate like a concierge or personal shopper, asking questions and finding what the customer is looking for. This can be anything across the customer lifecycle.

Some intelligent assistants can execute tasks as well as provide information. The following examples come from the makers of Bixby which is now a Samsung asset. They were originally showcased during 2016 from the same people who developed Siri which was acquired by Apple.

Make a reservation at Main Street Cafe for 8pm, but only if it’s not going to be raining when we’re there

Are there any concert tickets under $65 within 25 miles for any of my favourite bands?

Is this a good lawn mower to buy based on the reviews? Is this the best price I can get, and can I return it easily if I don’t like it?

If I book this vacation, will I still be within my quarterly budget, and if not, are there some better vacation deals that my family would enjoy?

This voice based intelligent assistance shows what is possible in a world in which speech recognition is now 90% accurate ‘out of the box’. Notice how the system is able to tap into both third party data and also develop a trusted relationship with the user in terms of knowing personal preferences.

Samsung were fast to recognise how Bixby could be made available across an entire product portfolio as an ever present support for customers. The reason why a customer would only shop for Samsung products?

We shall see.

But the underlying message is that information and workflow can be served up to customers in a conversational style that meets customers’ expectations for immediate access on their terms.

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Is live assistance dead?

Does this mean customer service is going to run on just algorithms? Are people going to become surplus to requirement? Will agents become redundant?

It does seem that more simple requests can now be offered as self-service. This is a win-win. Organisations enjoy a reduced cost to serve. Advisors can escape the tedium of these types of enquiry and customers gain immediate access to what they are looking for.

At the other end of the scale, human assisted service will remain for a number of reasons. When things become emotional or complex, live interaction remains the clear favourite. Equally when relationship building matters, it’s all about providing a human touch to make the right impact.

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In addition to this simple rule-of-thumb are some important engagement design principles that need to be considered: 1

Poorly designed customer journeys often require the compensation of human intervention. Even if the customer task could be self-served, it is unlikely to happen when the engagement becomes too complex or emotional. Therefore, simplify journeys before attempting to self-serve.

2

Self-service always needs to have escalation paths to live assistance built into the customer journey. There is no way of anticipating when a customer might suddenly require this.

3

Blended journeys which use both live assistance and self-service will become more common now that the hand-offs can be made without disruption.

Intelligent assistance will become woven into customer engagement. It is no coincidence that all major technology brands announced their AI engagement strategies during 2016. As Google observed this is now an AI first world. The technology is smart enough, the customers are ready.

Agile brands are already in full-swing.

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About the Author Martin Hill-Wilson is a long standing member of the UK customer service community. He currently works independently under the Brainfood brand with a range of clients focussing on customer related strategy assignments. He also participates as conference speaker, workshop facilitator and blogger in his role of passing on best practice and next generation thinking.

Current topics include social customer service and the broader issues involved in becoming a social business.

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