You don’t have to look far in science fiction, be it in books, TV, or film, to find dystopian depictions of artificial intelligence, commonly abbreviated as AI.
Whether it’s antagonistic androids, intelligent personal assistants, or corpses reanimated with electricity, there’s always been something otherworldly and intriguing about the rise of artificial intelligence.
Yet, for all the far-fetched fictitious representations, artificial intelligence is making genuine waves in the business world. Using highly-intelligent computer software, business functions can replicate what were traditional human functions en masse.
But what does this mean for customer success professionals – and how can artificial intelligence revolutionize the industry?
In this article, we’re going to answer key questions, including:
- What is artificial intelligence?
- What is customer success?
- How will machine learning transform customer success?
- What our experts think of AI in CS
What is artificial intelligence?
Artificial intelligence (AI) is a subset of science that creates super-smart computers that can perform a variety of tasks that would otherwise require human intelligence. It was Alan Turing, the father of the modern computer, who once hypothesized, ‘Can machines think?’, provoking decades of debate on the definition and parameters of consciousness.
The capability of AI at present is in equal parts astonishing, convenient, and perplexing – without even beginning to predict how it’ll manifest itself in the future. Over the last decade, we’re seeing AI crop up more and more in our daily lives. From the likes of Siri and Alexa found in the average home, to search algorithms, speech recognition, and automated chatbots.
AI’s making fascinating, groundbreaking developments that impact all manners of vocations. Even when it comes to traditionally ‘human’ jobs, like teaching and writing, which always seemed impossible for a computer to replicate, their future is looking more likely to be integrated with AI.
According to the automation aces at AI Accelerator Institute (a little alliteration never hurt anyone, right?):
“AI systems work by receiving large amounts of training data, analyzing that data for patterns and correlations, and using these patterns to make predictions. AI programming focuses on three main cognitive skills: learning, reasoning, and self-correction.”
The umbrella term ‘artificial intelligence incorporates a number of more specific strands that are used on a day-to-day basis. An important thing to note is that AI isn't a substitute for human activity; it augments human activity.
Its popularity and rapid integration into organizations can be attested by these stats:
- 97.2% of organizations are now investing in AI and Big Tech (NewVantage Partners)
- AI tech investment will reach $232 billion by 2025 (KPMG)
- AI will contribute $15.7 trillion to the world economy by 2030 (PwC)
What is machine learning?
Machine learning is probably the most recognizable branch of AI; this uses data and algorithms to mimic the way humans learn without human intervention.
Machine learning is unique because it continually improves its understanding with time, and learns new behaviors to improve its results. IBM defines this as “algorithms [that] are trained to make classifications or predictions, uncovering key insights within data mining projects”.
Examples of machine learning include speech recognition software, image recognition, query-based websites like Quora, and recommendation systems like Netflix uses.
What is deep learning?
Deep learning, on the other hand, is a more specific subset of machine learning, using algorithms to analyze data with a logical structure, simulating the intelligence of humans.
Whilst machine learning uses predictive analytics to learn and simulate human behavior, deep learning is slightly more complicated. It involves newly-developed neural networks called ‘nodes’ which try to replicate the workings of the human brain by combining weights, data inputs, and bias.
What is customer success?
Customer success is one of the more customer-centric, human-led disciplines within modern-day businesses.
It already observes a delicate balance between its dependence on technology and its human-like characteristics, like empathy and strong communication skills. Customer success was born out of the technology boom of the last 20 years that saw the development of Software-as-a-Service (SaaS).
In its essence, CS helps customers of (largely) subscription-based businesses to reach their intended goals with the product and/or service they’ve purchased. Technological advancements already aid customer success’ mission, so it isn’t a surprise that we’re increasingly seeing cross-overs between CS and AI.
How can AI benefit customer success?
At Customer Success Collective, we believe CS professionals are modern-day superheroes – and nothing’s gonna change that! However, sometimes superheroes need a little technological help.
Off the bat, investing in AI sounds incredibly futuristic and expensive to the everyday person. But in fact, purchasing automation software is integral to keeping on top of your customer base. Buying AI technology for your newly-formed team might not make economic sense, to begin with, but should be considered when you begin to scale up.
Automate time-consuming tasks
Answering your customers' queries is a fundamental part of customer success, and without fast, clear communication, you can end up alienating a portion of your customer base.
The responsibility of answering every single question (see: “Where can I find ‘X, Y & Z’”) can be virtually impossible for large-scale companies.
This is where chatbots enter the game. Chatbots, or chat robots, are used in customer success to impersonate human employees with conversational styles of customer representatives by using natural language processing (NLP). These chatbots can answer questions that need very detailed answers and even learn from bad reviews for maximum efficiency. By utilizing bots, you can speed up the time that you can respond to customers.
Automate customer onboarding
Recent studies reveal that the finance industry has seen a 15-20% increase in overall onboarding costs due to manual onboarding, challenges like revenue loss, high operational costs, and a protracted onboarding process.
Welcoming new low-touch customers to the product with chatbots is an instant way to kick-start the onboarding process and introduce your company’s brand values to the new customer. A simple message like, “Hey, there, welcome to [company name]. Would you like to see a [product name] tour?”
AI systems provide seamless, fast customer experiences that go beyond the amount a CSM is capable of on an ordinary day. AI-powered customer onboarding is flexible and suitable for the ever-changing and bespoke needs of your many types of global customers. If your business is based in the US, but you have a European customer needing onboarding out of hours, AI can solve this problem.
We’ve got to remember that employees are human, after all, and businesses need to reflect on this all-important factor. Between staff shortages, annual leave, and collating customer data, there’s only so much humans can do themselves. If parts of the onboarding process become fragmented and lengthened due to these unavoidable human reasons, then you might find customers take their money elsewhere due to slow processes.
According to a report by InfoSys, 35% of bank customers move to competitors due to poor onboarding experiences.
Predict when customers might leave
Machine-learning software records customer behavior as data. AI’s ability to learn and predict behavior using analytics allows CSMs to study the customer’s purchasing habits and inclinations.
Is the customer not engaging with the product? Have they not used the product since the purchase date? Customer success professionals can leverage this information to keep an eye on at-risk customers and monitor their overall health to prevent them from churning.
Provide a personalized service
Where a CSM’s capability has its limits – whether it’s a human experience as fundamental as fatigue or having a social life – AI assistants do not have these issues. An AI system learns on a rapid scale and continually becomes smarter, which enables it to perform and manage more tasks.
With each customer interaction, AI becomes increasingly adept at understanding the customer’s needs and responding to them the right way. Over time, they can be trained to handle more complex tasks and save a company time and money.
The future of customer success tools
When conducting our survey for our 2022 Tools of Choice Report, we asked our respondents what impact they think AI will have on customer success over the next 12 months and beyond.
Here’s what some of them had to say: 👇
“[AI will be] massive in terms of removing administration needs and assisting with human interaction more efficiently. It’ll help when spotting trends to support learning.”
– Ed Allen, VP of Customer Success at Papirfly:
“[AI will have a] significant impact on analyzing data and providing inputs to client engagement and individual strategies for clients.”
– Jane Austin, Customer Success Principal - Manufacturing at BT:
“At Kaizan, we're building an AI assistant for CS.”
– Glen Calvert, CEO at Kaizan:
“For companies with a large volume of data [AI] will be an asset because it will help them build predictive models for important KPIs such as churn and customer retention.”
– Irina Cismas, Head of Marketing at Custify
“AI could help increase control and retention for low-touch CS teams but have a limited impact for enterprise businesses or high-touch accounts.”
– Adèle Dugré, Head of Customer Success (EMEA) at Front
“For B2C companies with large customer volumes [AI] will have a big impact.”
– Chad Estes, Head of Customer Success at SaaSOptics
“I think a small percentage over the next 12 months, but [AI will] definitely have a growing impact in the years to come.”
– Abby Grip, Manager of Customer Success (Americas) at Integrate
“AI will lead the way in empowering CS professionals to scale and grow effectively and efficiently. It will become impossible to run effective CS without AI.”
– Kate Neal, Director of Customer Success at Staircase AI
“AI has the potential to increase the degree to which CS teams can proactively engage with customers by leaps and bounds by exposing unanticipated relationships between actions and events.”
– Colin Luther, Manager of Commercial Accounts & Success Operations at Komprise:
“I believe that [with AI], companies with longer tails will be able to scale more efficiently, as they'll require fewer CSMs to manage their accounts.”
– Bryant McCombs, Manager of Customer Success at MongoDB:
“It all depends on how it's being used but in principle, [AI] is going to help CSM's scale their time and focus on what's most important to them."
– Paddy McGill, Head of Ecosystem at eWebinar
“If we can predict through analyzing trends when customer engagement dips and when to proactively reach out I think [AI] will be incredibly effective.”
– David O’Brien, Director of Customer Support, AgriWebb
“Automation will permit businesses to reduce churn by removing the manual tasks of CS to focus on rescue recovery and service.”
– Michael Provencher, Manager of Customer Success at Brizo FoodMetrics
“It'd be great to automate some of the repetitive conversations and to identify issues earlier.”
– Lauren Scholtz, Learning & Development Manager at intelliHR
“[AI will have a] big impact. If you need to scale, it will have a huge impact on the workload of CSMs. AI will help to take some of that workload off and make things more efficient.”
– Stephen So, Senior Customer Success Manager at Indio Technologies Inc.
“Hopefully AI will be able to detect the customer sentiment from support, sales, and success emails i.e. whether they’re happy, satisfied, or angry, etc.”
– Nik Wekwerth, VP of Customer Success at Buildkite
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