Time to trust AI
Why AI will enhance CX delivery, not replace it
Who could predict that declining world oil prices could pose a threat to English church buildings?
Artificial intelligence could – and did.
It was analysis using artificial intelligence (AI) that made the connection between oil prices and lead theft.
When crude oil prices go down, investment in infrastructure tends to go up. That intensifies the global demand for lead, pushing the price up. This inflates the value of scrap lead, driving theft from church roofs.
This may seem an obscure connection. But if you specialise in insuring church buildings, it’s business-critical information. When the price of oil is low, monitoring infrastructure policy in places like China and the UAE can help predict future claims patterns.
This is just one of the myriad ways in which AI is transforming what organisations can do with data.
Paradigm shift
For decades, firms have relied on business intelligence (BI) to inform their strategies. They’ve made their decisions by analysing the past, and by measuring whatever metrics they judged important.
But now they have the potential to see the future, by finding trends they haven’t even looked for (like the impact of world oil prices on insurance claims by churches). Analysing the volumes of data required to find such hidden connections demands artificial intelligence.
AI enables organisations to work out what will happen next, and therefore what metrics they should measure. It does this by exploring, refining and testing vast amounts of data, in real time, and finding patterns for itself.
As such, AI represents a complete paradigm shift in how firms understand their customers and markets. BI’s has its limitations: it’s retrospective and subjective. AI is forward-looking and completely objective.
What’s more, AI is many times more powerful than the data analytics capabilities organisations have been used to. Pioneering computer scientist and AI entrepreneur Sebastian Thrun estimates that AI will make us 10-50 times better at our jobs.
A new world of possibilities
As in many spheres, there’s a great deal of uncertainty over what AI will mean for customer experience (CX).
In our view, the impact is likely to be enormously positive. AI will greatly enhance the experiences that CX teams can deliver.
In the digital era, we generate vast quantities of data as we interact with brands. Without the help of intelligent machines, it’s impossible for human beings to gather, process and analyse information on that scale; let alone use it to produce valuable business insight and strategies.
That’s where AI comes in.
Imagine a world in which you know not just your customers’ demographics, but also their personalities: their tastes and preferences, needs and motivations, beliefs and ethics.
Imagine that you can reach each one of them personally. You can offer them nuanced communications and dynamic experiences, in tailored designs and language that resonate with them as individuals.
And imagine that you can do all that to target their precise needs at any given time.
This isn’t the customer experience of the future. It’s already possible thanks to AI.
Barriers to adoption
But if AI can take CX to new heights, why are so few organisations yet embracing it?
Firstly, because its CX applications are brand new. Many businesses are yet to realise what it can achieve, or understand how to harness its power.
At the same time, exploiting AI demands a complex set of systems and capabilities:
Data science: the ability to understand data sources, and make them consistent so that machines can analyse them; and the algorithms required to analyse data and search for patterns within in it.
Connectivity: the technology to link the disparate platforms on which customer data sits. These include call-centre and other internal databases; the company’s website and social platforms; and external sources such as customers’ social media accounts and set-top boxes.
Automation: the software to process and analyse vast quantities of data, and generate genuine insights and recommendations from it.
Visualisation: the tools to distil the results of data analysis into meaningful displays.
Strategy: the ability to understand what the data is saying about the experiences customers want.
Personalisation: the ability to glean insights from behaviour science into individuals’ motivational triggers; and to use those triggers to design contextually relevant customer experiences.
In addition, organisations may find their efforts to implement this infrastructure being thwarted from within. Fears over the impact of AI on jobs may stoke internal resistance. Meanwhile, legacy systems and silo mentalities can prevent the all-important linking and sharing of data.
Information, information, information
When it comes to unleashing the potential of AI, everything starts with data.
The deeper and more connected your customer data is, the more effectively you can use AI to mine it. And the more transformative the results will be.
You’ll need to collect data in every area of the business; and just as importantly, from every external source of information you can access. That will mean:
identifying all relevant data sources.
automatically extracting them in a consistent format.
obtaining and storing them in line with data protection rules (which will be much harder to do under GDPR).
consolidating them to allow AI applications to see the whole picture.
Be prepared to deal with massive amounts of information – potentially thousands of data points on each customer. Then to create the personalised customer experiences AI can enable – and today’s customers expect – you’ll need to be able to ascertain:
who is engaging with you, and buying from you, over which channels.
why each individual calls your service centre, visits your website, downloads your app, checks your social media platforms, etc.
what pain points each customer encounters during their journey with you, why, and what to do about it.
What your customers are doing, and what their needs are, even when they’re not engaging with your business.
You may also find that deploying AI in your customer experiences means having to democratise your data. You’ll need to break down technology silos, and foster a culture where employees are willing and able to share their data with other parts of the business.
Data strategy
Using AI to transform CX demands a different kind of data strategy: one that opens up your data to the whole organisation, and tracks the impact on customer behaviour.
This strategy should be underpinned by three key dimensions:
Collection – automated process to find the information you need, and collect and consolidate it for machines to analyse.
Integration – solutions that seamlessly integrate the data sets you’re collecting with essential tools like your CRM platform or sentiment analysis programme.
Evaluation – a framework to measure vital customer behaviour KPIs:
Effort: how much easier have you made it for customers to complete the tasks you want them to complete?
Completion – how many more customers are now completing those tasks?
Experience – how much better do they feel while carrying the tasks out?
Conversion – how many more actually get to the point of buying from you?
At The Unit, we help the best-known brands to create effective AI strategies and solutions for their CX teams. We know how to bring the power of AI to your customer experiences.
Get in touch to find out more.
