One new notification: Is AI driving the next generation of CRM?

According to research firm Gartner, a whopping 85% of all customer service interactions could be handled with no human involvement by as early as 2020. While that may sound a tad overoptimistic for some, especially if you’ve ever found yourself going around in circles fruitlessly trying to communicate with a customer services ‘robot’, the inexorable march towards full automation is in full swing.

For businesses of all shapes and sizes, AI-driven communication combined with machine learning is transforming how they engage with their customers in a more efficient and emotionally intelligent manner via the individual’s preferred channels.

Today, marketers have more customer data than ever before at their fingertips, and an ever-increasing number of channels through which to reach out to and engage with them. Behemoths like Amazon, eBay and Netflix have been the trailblazers when it comes to AI-powered CRM, whereby customer data, including browsing and purchase history, is harvested to better tailor marketing communications.

It’s a similar story for the likes of Sky Betting & Gaming in the egaming sphere. “Automation and real-time communications are a big area of focus for us – we have explored automating areas of self-help, marketing says Lucy Kenworthy, the Leeds-based operator’s CRM innovation manager.

“We use computer-aided decision logic to trigger onsite and offsite campaigns and to populate content.” In fact, she emphasises that, these days, “automation and computer-aided personalisation is a 100% necessity” as opposed to blanket communications with players.

“There is certainly a place for a more one-size-fits-all-communication – site-wide service messaging or major new campaign launches, for example – but these should be less frequent with more communications being nearer the one-to-one side of the scale. Technology making this possible is a massive help.”

New operators are also cognizant of the opportunities and benefits provided by machine learning within CRM. In August, Sam Hobcraft, founder of the newly minted Omnia Casino, explained to EGR Intel how he and the team are working towards implementing entirely AI-led CRM to help with marketing and player communications.

He suggested that six to 12 months after rolling out a self-learning algorithm, it typically outperforms human CRM managers in almost aspects, including awarding bonuses and identifying problem gambling.

“You want to get the program to the point where it is largely working by itself, but it is certainly more accurate than humans in spotting problems and trends in consumer behaviour,” he said.

AI’s role in retention

One of the gambling industry’s main costs is acquiring new players. And since there tends to be a high churn rate as promiscuous users flit from one brand to the next, operators need to provide a strong value proposition to each player.

The way to do so is through a deep understanding of every player, and communicating to their needs and expectations, suggests Pini Yakuel, CEO of AI CRM specialists Optimove. “This emotionally intelligent communication leads to relationship building, which is possible only thanks to AI.”

He adds: “AI can help determine which elements of customer behaviour are having the biggest impacts on value and which type of campaign will produce the strongest uplift for each customer. AI-driven player retention is helping increase profitability.”

A report published this year by Narrative Science and the National Business Institute discovered that 61% of businesses that were quizzed as part of a survey had deployed AI, compared with 38% in 2016.

This underlines how more and more companies are appreciating the benefits of AI, even if it isn’t cheap to roll out properly (a fairly rudimentary chatbot can cost upwards of five figures), and while it can certainly streamline labour-intensive and repetitive tasks, businesses shouldn’t leave AI to its own devices; it still requires a human element, of course.

“Manual sends mean manual quality control, [so] several human eyes looking over a campaign can spot issues and correct it before something goes out to a customer,” says SBG’s Kenworthy. [But] automating communication has the potential to automate a problem.

In order to mitigate this, it means upfront checks need to be much more stringent and all potential issues ironed out before something is live. Once live, it also can’t just be forgotten about; regular human checks still need to be in place.

“With an ever-changing compliance landscape in the gambling industry, this means human intervention is needed more so than other industries; content needs to be regularly reviewed to ensure it meets any new standards.”

Indeed, a major issue for the gambling industry involves ensuring complying with the codes of practice set out by regulators like the Gambling Commission and the Advertising Standards

Authority in the UK. “These systems rely on huge repositories of data from CRM campaigns combined with the use of emotive language in order to improve open rates, click outs and conversions by personalising the email to the individual, which is great in theory, but it has to be delivered in a compliant way,” says Allan Turner, CMO of BGO Group.

“So, maintaining the control of the messaging is key.” The rise of AI means companies have sprouted up promising to automate businesses’ CRM processes. One such company, Phrasee, claims that its deep learning engine, which analyses human language, outperforms humans 98% of the time.

To a layman this may seem mightily impressive, although Turner says: “It seems perfectly logical that the AI CRM systems can produce better results than humans because it’s much easier for the machine to analyse large numbers of data points.”

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One obvious area of where AI is being put to good use is customer support, with more and more businesses installing AI-powered chatbots to deal with routine customer queries on instant messenger platforms. And with the AI becoming smarter, customers are now more accepting of the concept.

A study earlier this year found that 69% of consumers prefer chatbots for those instances when they require quick communication with brands. AI will soon properly extend to voice (we’ve probably all received those cold calls from machines with terribly robotic voices) once the machines are able to hold a proper conversation.

This is inching closer and closer. Google’s machine-learning voice technology has achieved 95% accuracy, while the tech giant’s CEO, Sundar Pichai, recently unveiled a feature in which you can ask Google Assistant to make a lifelike call to a business on your behalf.

As part of the demo at its annual I/0 conference, Google autonomously called a hairdresser to book an appointment and a restaurant to make a table reservation on a preferred day. With a human-like voice, including sentence fillers like “um” and “uh huh”, the person on the other end of the line had no idea they were conversing with a machine.

Pichai’s audience was suitably impressed by the product – dubbed Google Duplex – although some company employees may be uncomfortable to discover they were fooled into thinking they were chatting to a human.

“The reason behind continuing to use humans rather than machines for customer services previously was that it was always deemed that the personalisation a human can provide outweighs the cost efficiencies of using automated platforms,” Turner says.

“But with improvements in recent years in AI technology, the ability of these systems to also be personalised means that the pendulum is now swinging towards the automated approach.”

Allan Turner, CMO of BGO Group, says maintaining the control of the message being put across is key

Embracing change

Global Gaming – the company behind Ninja Casino – is one operator poised to harness AI for CRM and marketing purposes, as head of CRM Shireen Haddadeen explains. “We intend to fully optimise our machine learning capabilities to support the exploration of new marketing environments using a wide range of variables to test, learn and iterate.

This structure of agile machine learning will assist in guiding the creative process whilst stimulating innovation across the business.” One potential challenge, though, is fi nding the right talent to lay the foundations for machine learning,” she says.

“With so many decision statements to consider, reliable knowledge and experience is required from experts in their fields ranging from data science, CRM, BI, marketing, UX, UI, customer operations, compliance, developers, product – virtually every aspect of the business – to work in collaboration, which can prove challenging for businesses from both a project and resource point of view.

“It’s one thing getting businesses and their employees to fully understand and adhere to regulatory requirements, but it’s another to provide QA that your AI operates in such a way.” For some, the prospect of machines supplanting much – or all – of their duties is a disconcerting thought.

A two-year study by McKinsey Global Institute forecasts than AI could eliminate as much as 30% of the global labour force by 2030. In real numbers, it means up to 800 million people could find their roles eventually replaced by machines.

In the near term, however, customer service appears to be the area AI will have the most impact, potentially turning call centre representatives into endangered species, or even making them practically extinct altogether.

And as for AI within CRM, isn’t the clinical and precise nature of the technology, knowing that a machine has communicated with a player to award a bonus or sent out a personalised piece of email marketing, all a bit depressing?

“I don’t find that prospect depressing at all to be honest,” Turner remarks. “I actually find it very interesting and potentially exciting to be able to deliver bespoke messaging to someone that they are more engaged with.

“In terms of jobs, it really just adds a layer to the process rather than putting people out of a job.” These sentiments are echoed by Global Gaming’s Haddadeen: “Rather than being perceived as a threat, AI is pushing boundaries and getting people out of their comfort zones, and really take accountability for their areas of expertise in exchange for monetary value.

“AI ecosystems need configuration from humans who are experts in their fields of knowledge, thus giving humans more time to dedicate to creativity, strategy, vision and other areas of passion and interest that often get underdeveloped because of necessary repetitive tasks.”

Besides this, she underlines how machine learning can optimise repetitive task management, which prioritises innovative ways of working and delivering while consistently improving the customer experience. “I believe AI will empower exciting shifts in productivity and innovation,” she notes.

Indeed, besides Gartner’s aforementioned prediction that 85% of all customer service interactions will be fully automated by 2020, the research company also anticipates AI to be worth an eye-watering $1.2trn to businesses this year alone – a 70% rise over 2017. Meanwhile, the value derived from AI is expected to rocket to $3.9trn by 2022.

In essence, AI is probably the biggest game-changer since the inception of the internet. And CRM is just one area to feel this effect.