AI is presently used by 52% of customer success teams. However, instead of radically reinventing how they provide customer success, the majority of CS leaders are stuck experimenting with simple tools.
Here’s a real-world look at how AI tools for customer success is currently changing customer success, going beyond the jargon and simple note-taking tools. Most CS leaders are unaware of how exciting (and accessible) the possibilities are.
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Table of Contents
How AI is Transforming Customer Success?
AI is already being used informally by CSMs to edit emails, take notes automatically during calls, and come up with solutions for challenging client scenarios.
Here are some things to be aware of:
- Segments with little touch become completely touchless. CS teams may thus handle accounts much more economically without sacrificing quality, saving human interaction for problems that require a more individualized approach.
- Intelligent self-service solutions are provided to high-touch segments. Without the help of a CSM, customers might find more value inadvertently and on their own schedule, increasing product adoption and accelerating time to value.
- CSMs become strategic consultants. Your team has the mental space and ability to think more strategically when AI takes care of repetitive duties. Naturally, CS becomes a growth driver when more time is spent on revenue-generating tasks like expansion planning and EBRs.
- Experiences for customers become genuinely smooth. AI keeps track of every action and statement a consumer makes in every department. This eliminates the need for clients to repeat themselves when speaking with various team members. The dialogue continues exactly where it left off, regardless of whether they are interacting with sales, customer service, or their CSM. Instead of dealing with disparate teams that don’t communicate with one another, customers feel as though they are interacting with a single, helpful company.
Best AI Tools for Customer Success
The most effective CS teams are using AI techniques incrementally, beginning with particular problems, tracking results, and then growing from there. Here are the best AI tools for customer success.
Dock
The steady stream of calls, emails, and meetings can be difficult for customer success teams to handle. Relationship-building time is lost when these exchanges are transformed into helpful tools for clients.
In your client workspace, Dock AI makes it simple to turn your customer chats into helpful resources. Meeting summaries, customer success strategies, project checklists, and more may be produced instantaneously by uploading a Gong recording, document, or client call transcript.
ChatGPT and Other LLMs
Many customer success teams are aware that they ought to use AI, but they are unsure of how to get started. It can be difficult to determine which tools would genuinely save time versus add to the workload, and the variety of possibilities can be overwhelming.
Trying out user-friendly generative AI tools like ChatGPT and Claude is a straightforward way to get started. Additional benefits come with a ChatGPT Team subscription, which enables you to create personalized ChatGPT versions and distribute them to your team to maintain team cohesion.
These can be useful for creating reports, crafting better communications, or rapidly locating basic information. Platforms like Copy.ai come with built-in capabilities made specially to maintain the writing style of your business.
Conversation Intelligence
Good conversations are essential to customer success, but it’s impossible to recall every detail from every call. Teams lose out on chances to assist customers and early warning indicators when these insights are not recorded.
In order to identify possible concerns before they become significant ones, Gong assists by recording and examining client talks. It assists teams in customizing their strategy for every client, concentrating on the most crucial duties, and developing detailed instructions for managing typical circumstances.
Similar methods are used by UpdateAI, which is designed more especially for CS teams and includes features like VoC topic tracking. Also, conversation intelligence technologies tailored to particular niches are becoming more and more popular.
For instance, Strada offers agentic AI for insurance that automates workflows and follow-up in response to client calls. It helps teams save time while making sure nothing falls between the cracks by taking care of things like insurance claims, renewals, and servicing requests immediately.
Customer discussions can be captured and summarized with the aid of Avoma, Fathom, Grain, Otter, and Fireflies.
AI Customer Success Platforms
It used to take countless spreadsheets and human labor to monitor the health of hundreds or even thousands of accounts. Problems were frequently overlooked until it was too late to address them. This dynamic is being altered by tools such as ChurnZero.
AI can be used to examine communications, health scores, account history, and customer engagement patterns to provide a comprehensive picture of each connection rather than depending solely on intuition.
For instance, you may evaluate sentiment analysis, track significant subjects, generate summaries automatically, visualize relationship maps, and obtain prompt answers concerning accounts—all without having to do any manual labor. Similar AI-powered customer success products are available from Totango and Gainsight.
Documentation and Knowledge Management
It is common for customer knowledge to become dispersed throughout several platforms, such as chat threads, shared drives, and emails, or to become stuck in the minds of particular team members. All parties suffer as a result: new team members find it difficult to catch up, and consumers receive inconsistent responses.
Guru and other AI knowledge management technologies address this by centralizing all important data in a single location and enabling smart search.
During customer encounters, agents may now swiftly locate what they need without having to put clients on hold or move them around. Knowmax and Bloomfire offer different approaches to knowledge management driven by AI.
AI Agents for CS
CS teams are being pushed to accomplish more with the same resources as customer expectations rise. Burnout, erratic service, and lost opportunities may result from this. AI bots assist by managing repetitive activities and offering astute support.
With the ability to investigate clients, recommend next steps, execute them with a single click, extract insights from discussions, update records automatically, and correct contact information, agents enable CS managers to concentrate on more critical tasks while efficiently assisting a greater number of customers.
AI agents are given the ability to manage low-touch client outreach and discussions independently by Cust.co. These same AI agents can serve as CSMs’ backstage copilots for high-touch parts. Relevance AI and Conversica both provide distinctive approaches to AI assistants for customer success teams.
Research and Consumer Insights
Traditional methods, which frequently overlook significant patterns and fail to integrate input across numerous channels, make it nearly impossible to understand what customers genuinely think across thousands of contacts.
This problem is addressed by Dovetail, a customer insights portal, which uses AI to examine all customer interactions, including recorded calls, NPS surveys, and support issues.
It identifies key points in discussions, extracts insightful information without requiring hours of manual examination, and links relevant comments from these many sources to present the whole picture. Similar features are available in Insight7 for market research and customer interview analysis.
Conclusion: AI Tools for Customer Success
The majority of customer success teams are only beginning to explore the potential of AI. AI tools for customer success can anticipate problems before they happen, customize every customer engagement, and relieve your CSMs of administrative duties that take away from their strategic potential.
The best part is that they are available now rather than in the future. Keep in mind that you can get results without entirely overhauling your CS team. As you develop confidence, scale from a single use case that solves your biggest pain point.
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