Artificial intelligence is no longer an optional gadget when it comes to Customer Success Management (CSM). It's an indispensable ally that frees up precious time, boosts the impact of CS teams and reinforces their responsiveness, so that they can refocus on what's most important: people. Our customers.
But how do you integrate this "AI-Human" marriage into your daily CSM routine? What AI tools should be used, at every stage of the customer's life? And how can we place "value" at the heart of AI uses (for the better, and for ROI)?
AI, the indispensable assistant for CS teams
Far from being a threat, AI is an opportunity for Customer Success teams. Particularly for redundant tasks, such as :
- Information summaries: AI creates reports of e-mails or meetings, available in the company's CRM. Ideal, for information sharing and handovers (for example, between two CSMs or during a handover between sales reps and CSMs).
- Sentiment analysis: exchanges with a customer can be analyzed by tools integrating natural language processing (NLP), to better understand their expectations, desires, obstacles, level of satisfaction or dissatisfaction. A valuable complement to the human expertise of CS teams, offering rapid insights to better guide their actions.
- Task automation : whether it's writing templates for responses to customer emails, organizing a meeting and then writing its minutes, or assigning the most suitable CS profiles to certain accounts... AI manages.
- Data personalization: in a low-touch strategy, where contacts are few and far between, artificial intelligence tools help enrich and personalize customer data. Ideal for delivering the most coherent strategy possible.
For all these tasks (and more), 56% of CX managers are exploring new generative AI tools, according to Zendesk's CX Trends 2024 report. These tools are useful for CS teams at every stage of the B2B SaaS customer lifecycle. For example:
- Customer onboarding: onboarding chatbots fromHubspot, Mixpanel to collect and analyze data, Optimizely to provide personalized recommendations ...
- Upsell phase: software such as DBSCAN helps segment customers to personalize offers. Then, Gainsight, Totango or ChurnZero help track upsell performance.
- Day-to-day support, Julius.ai is a powerful data analysis tool (which reduces the number of hours spent on Excel...). Some B2B SaaS providers even go so far as to integrate ChatGPT into their live chat platform, to automate certain customer exchanges.
However, beware of falling into the trap of over-using tools: AI must reduce, optimize and better qualify human interventions, without replacing them, and always rely on a key foundation: value.
What's more, its implementation requires time, successive iterations and regular maintenance to guarantee its relevance and effectiveness.
Using AI in CS teams: a "value" challenge
Artificial intelligence tools can save time and focus on what really matters. Or rather, "those" who really matter: customers.
Today, B2B SaaS CSMs have a threefold challenge for the customers they support:
- Generate maximum real value for the customer: generative AIs don't just provide raw data, they can formulate concrete, personalized recommendations for each customer. Depending on the customer's profile and objectives, AI can suggest specific strategies to maximize product use, or support the customer's expansion. AI can also generate scenarios, based on customer behavior: forecasting AIs like Hubspot's Breeze simulate predictions that help to make informed decisions.
- Demonstrate your own added value, as a CSM : the more AI eases the day-to-day burden on CSMs, the more they can support -fully- customers. And demonstrate their added value. A billable CS strategy is essential if CS teams are to make the most of their valuable, proactive work. Antonin Bigot and Cécile Beaussant Le Gentil (co-founders of Customerz) discuss this with Damien Duval (Nomadia) and Céline Bocchi (ex-Head of CS at CoachHub and Cornerstone) in this episode of our podcast: "Can you bill your CS service?"
- Reinforce the perceived value of the product : the perceived value of your offering is a decisive lever for adoption, expansion and retention. The challenge for the CSM is therefore to increase perceived value, by becoming a strategic advisor capable of supporting customer development... And here again, AI proves very useful. Here are a few examples of how AI can be used, specifically to work on perceived value:
