More B2B tech companies in Europe are advancing digital customer success (CS) to grow operations and boost outcomes, according to research by Gainsight, with 58% prioritising expansion revenue - revenue that is generated beyond a customer’s initial purchasing price or contract - compared with 28% in North America. To achieve their expansion revenue goals, many of these firms must level up their growth and customer-retention strategies. One way to do this is by using AI-powered CS platforms.
“There’s a lot of guesswork in CS about how accounts should be managed and where the focus should be with AI. We can finally see if there is a correlation between activities and outcomes,” says Ori Entis, senior vice-president of product, CS and AI at Gainsight, a customer success and product experience platform that helps businesses retain customers, reduce churn and drive expansion revenue.
Of course, adopting AI-powered tools won’t magically unlock more revenue. To achieve tangible results and strong ROI, chief revenue and customer officers must adopt the right framework for integrating AI into existing workflows.
At the heart of this approach are several key pillars, including effortless automation — ensuring AI enhances productivity without adding complexity.
“Assessment of customer health has traditionally involved a lot of human reporting and manual note-taking, which AI is automating through tools like call transcriptions and summarisation,” says Entis.
“It can also analyse multiple data sources simultaneously – emails, tickets, calls – to understand your overall interactions with a customer and provide key insights.”
This ability to consume huge amounts of data and turn it into actionable insights and alerts supports another key pillar of a strong AI framework: immediate tangible benefits.
For example, “AI can look at product usage, telemetry and financial data to find correlations with outcomes like renewals. This would be challenging or time-consuming for a person to do,” explains Entis.
By providing instant access to meeting summaries, past customer interactions and key action points, AI can improve account handovers.
“With every handover you miss a lot of history,” Entis explains. “But with AI, you can get a clear view of all the incidents – the good and the bad – that have happened before and when you need to be more closely tuned into what’s happening.”
AI is also a useful tool to validate educated guesses about customer health, allowing CS managers to make data-backed decisions.
“For example, if you sense that there is value in an activity, by shadowing a client right after onboarding to make sure that they’re using the platform correctly, you can use AI to look at the data and reaffirm that instinct.”
Delivering impact
To measure the ROI of AI deployment, consider, for instance, the time saved by automating routine tasks like note-taking and report generation.
“If you turn that note-taking over to automation tools, you’ve saved a significant amount of an account manager’s or CSM’s time, which you can correlate to a dollar amount based on their salary,” says Entis.
CSMs can also use conversational AI chat tools to analyse data, extract insights and construct reports. “On a preparation level, we’re seeing anywhere from 50% to 75% of that time cut,” says Entis.
Automating these routine tasks ultimately allows CS teams to focus on higher-value activities, boosting overall productivity.
“It frees people to do more strategic thinking about how to deliver value to an account, versus just firefighting a problem,” says Entis.
“It also enables them to look at activities and behaviours that they might be able to borrow from one successful account to fuel another.”
AI tools can draw on the entire history of customer interactions to deliver true personalisation at scale
Conversational AI’s ability to provide instant customer details, insights and recommendations can also help unlock the kind of deeper customer relationships that drive expansion revenue, retention and growth.
“When you have a personal relationship with a customer, the overall customer experience is higher, and there’s a correlation between customer experience and retention,” Entis explains.
Building these personal relationships at scale has always been challenging. “As a human being, you can probably write around 100 correspondences a day, which is a lot, but how do you serve 500 or 1,000 customers? The solution has historically been templates, but as we know, they’re not personal, so they don’t enhance the relationship.”
AI tools, on the other hand, can draw on the entire history of customer interactions, pull out events and other information from these communications, and embed them into correspondence to deliver true personalisation at scale.
By helping to summarise information and draft emails, a job that might have taken a CSM 10 or 15 minutes may take them just three to five.
“That means you can triple the number of correspondences while continuing to serve the customer on a personal level,” says Entis.
Driving adoption
Spotting the best cross-selling and upselling opportunities used to mean sifting through endless CRM data or relying on customer-success managers for insights.
Those days are over — AI can help instantly identify these opportunities, giving sellers the information they need without the extra legwork.
“If you have an AI-based health score and sentiment score and relationships, you can go into a system – for example Gainsight’s Staircase AI product – and see, as a seller, the state of the customer and how happy they are with their current solution, and then prioritise and fine-tune your list of potential leads in a much more crafted way.”
Gainsight includes robust security measures and protocols, meaning companies can place their full trust in the solution and the results it generates.
Moreover, firms can directly embed AI into existing workflows and the everyday tools that teams rely on, thereby enhancing productivity without disrupting familiar processes.
More than half (52%) of companies are already integrating AI into their workflows, according to Gainsight’s State of AI in CS survey.
“If AI is already integrated into an existing product, there’s a high chance that it’s going to be adopted,” says Entis.
“And it has to help solve a problem, because as with anything in life, people will use it if it helps them.”
The frictionless integration into workflows, along with the appropriate selection of tools that deliver immediate value, trust and effortless automation, is essential for a successful framework for AI adoption.
By prioritising these areas, companies can ensure measurable returns from their digital-transformation investments, driving stronger revenue, sustained growth and a smarter approach to customer success.
For more information please visit gainsight.com
More B2B tech companies in Europe are advancing digital customer success (CS) to grow operations and boost outcomes, according to research by Gainsight, with 58% prioritising expansion revenue - revenue that is generated beyond a customer's initial purchasing price or contract - compared with 28% in North America. To achieve their expansion revenue goals, many of these firms must level up their growth and customer-retention strategies. One way to do this is by using AI-powered CS platforms.
“There's a lot of guesswork in CS about how accounts should be managed and where the focus should be with AI. We can finally see if there is a correlation between activities and outcomes,” says Ori Entis, senior vice-president of product, CS and AI at Gainsight, a customer success and product experience platform that helps businesses retain customers, reduce churn and drive expansion revenue.
Of course, adopting AI-powered tools won’t magically unlock more revenue. To achieve tangible results and strong ROI, chief revenue and customer officers must adopt the right framework for integrating AI into existing workflows.
