Why every scaling B2B SaaS company needs AI agents for their customers and teams?

The CX function is one of the forefront functions to embrace the change, validated by IDC’s projection that AI spending by CX teams is projected to exceed $15 billion by 2025.
Karthik Krishnapandi
Head of Solutions
July 11, 2024

Why every scaling B2B SaaS company needs AI agents for their customers and teams?

The CX function is one of the forefront functions to embrace the change, validated by IDC’s projection that AI spending by CX teams is projected to exceed $15 billion by 2025.
Karthik Krishnapandi
July 11, 2024

Why every scaling B2B SaaS company needs AI agents for their customers and teams?

The CX function is one of the forefront functions to embrace the change, validated by IDC’s projection that AI spending by CX teams is projected to exceed $15 billion by 2025.
Karthik Krishnapandi
July 11, 2024

Heading

Fascinating to see how fast things are changing in the AI tech solution space - ML > GenAI > RAG > AI Agents. But what about the problem space, i.e., the real-world application of AI, especially in the CX (support, CS, solutions, and onboarding) function? What's their expectation?

From our 100 of hours of calls with top CX leaders in the last few months, the signal is loud, clear, and consistent. They just want this -Enable their end users and internal teams with instant, accurate, reliable, and contextual information about the company's products/services using AI, which isn't possible with traditional simple rule-based bots/ intranet searches.

Listing top reasons why CX function in B2B SaaS companies should adopt AI now rather than wait for eternity,

Automated support

Almost 60% of customer queries are repetitive and simple “How to..” questions. Customers usually find it very difficult to find what they want in traditional help center knowledge bases. Any of these things happens while searching for what they want in knowledge bases: Rare-Zen-minded users find what they want after hours of search, Frustrated-with-life (cursing/abusing a bit) users drop off deciding to live with the problem or take a vow to find another vendor, Patient-and-forgiving users accept their poor searching skills and raise a support ticket. None of these outcomes are great for a business that promises kick-ass customer support. And, once a customer query comes into the ticket lifecycle, it takes an average of 1 business day to reply and even more to actually resolve it.

Here comes the AI Agent to the scene to rescue :) By training the AI agent on your company’s product knowledge that exists in the help center, internal documentation, Slack channels, etc., and deploying it on your websites/products, it can answer these questions instantly, aiding faster product adoption and significantly boosting customer experience.

Save time for your team

Support teams' productive time is generally wasted in answering these mundane and repetitive queries. By deploying intelligent and context-aware AI agents to answer these “L1-How to” queries, the support team can focus on solving more complex problems for the customer, engage in proactive customer value-adding work, or best case, make a 4-day work week for your hard-working support teams :)

Onboard new support agents faster

Let's accept reality and have some mental peace - B2B SaaS products are inherently complex. On average, every SaaS product has over 200 help articles, an equal number of internal docs, 1000s of past customer tickets, and zillions of internal Slack/MS team threads. It's humanly impossible to master this knowledge, even for your new, 200-IQ, and aspiring support agent. On the other hand, AI Agents can be effortlessly custom trained on 1000s of articles/millions of words, and most importantly, the right context can be retrieved and an AI-reply generated based on the query in just a few seconds. These custom-trained AI Agents can act as helpful and lovable product buddies to help your new support agents quickly master your product.

Where to find? What is right?

B2B company’s product knowledge and customer context are generally distributed across various data sources - public knowledge bases (Zendesk/Freshdesk), internal docs (Confluence/Notion), Slack/MS team threads, past customer tickets, CRMs, your kid's rough notes, local library, newspaper archives, etc. When your support rep wants to quickly reply to your customer query, they first have to do a Sherlock Holmes-like detective search to find the right source, then the right answer, and then finally reply, all while keeping the stop clock ticking (oh, SLA breaches topics are for another day, please). AI agents, unlike simple and traditional direct searches, can understand the intent and context of the question and customer, find the right content, and instantly suggest an accurate AI reply, which can be used by your support reps to reply quickly with just one click.

Standardize customer experience

The quality of support agent replies also hugely varies based on each one’s product knowledge and communication skills. Some of your agent’s replies are like Shakespearian sonnets, some like Washington Post articles, some like cryptic tweets, some are simple grinds, and finally, the rest are just as expected :)With AI agents, you can customize the brand tone (empathetic, friendly, and professional), have multi-lingual capabilities, and be great at explaining details clearly and instantly. Your support agents can run a quick check against their draft replies to quickly refine them for consistency without losing their individual style.

Rise of AI agents

Finally, the tech landscape has changed forever with the release of genAI models and agentic frameworks in the last 12 months, definitely earning a space along with other key tech moments in history like - Vacuum tubes, transistors, ICs, PCs, tele-communication, Internet, Smartphones, TikTok, Theranos, etc. The debate of AI being smoke without fire is definitely settled with companies first adding AI to their landing pages for fun to fully reimagining their workflows and products with AI. Unlike traditional, rule-based, and scripted bots, AI agents can now understand intents, break down tasks, carry out custom actions, interface with other tools, and most importantly, have human-like conversations.

Final Thoughts

The CX function is one of the forefront functions to embrace the change, validated by IDC’s projection that AI spending by CX teams is projected to exceed $15 billion by 2025. It's high time to turbo-power your CX function with AI not just to survive but to flourish in the new era of AI and to exceed your ever-growing customer demand for faster and better support.

Curious to know more on how to get started with AI agents in your CX function- Customer Support/Success/ Onboarding/Presales/ PS, Book A Demo with us to see you can implement AI quickly and reliably in company.

Fascinating to see how fast things are changing in the AI tech solution space - ML > GenAI > RAG > AI Agents. But what about the problem space, i.e., the real-world application of AI, especially in the CX (support, CS, solutions, and onboarding) function? What's their expectation?

From our 100 of hours of calls with top CX leaders in the last few months, the signal is loud, clear, and consistent. They just want this -Enable their end users and internal teams with instant, accurate, reliable, and contextual information about the company's products/services using AI, which isn't possible with traditional simple rule-based bots/ intranet searches.

Listing top reasons why CX function in B2B SaaS companies should adopt AI now rather than wait for eternity,

Automated support

Almost 60% of customer queries are repetitive and simple “How to..” questions. Customers usually find it very difficult to find what they want in traditional help center knowledge bases. Any of these things happens while searching for what they want in knowledge bases: Rare-Zen-minded users find what they want after hours of search, Frustrated-with-life (cursing/abusing a bit) users drop off deciding to live with the problem or take a vow to find another vendor, Patient-and-forgiving users accept their poor searching skills and raise a support ticket. None of these outcomes are great for a business that promises kick-ass customer support. And, once a customer query comes into the ticket lifecycle, it takes an average of 1 business day to reply and even more to actually resolve it.

Here comes the AI Agent to the scene to rescue :) By training the AI agent on your company’s product knowledge that exists in the help center, internal documentation, Slack channels, etc., and deploying it on your websites/products, it can answer these questions instantly, aiding faster product adoption and significantly boosting customer experience.

Save time for your team

Support teams' productive time is generally wasted in answering these mundane and repetitive queries. By deploying intelligent and context-aware AI agents to answer these “L1-How to” queries, the support team can focus on solving more complex problems for the customer, engage in proactive customer value-adding work, or best case, make a 4-day work week for your hard-working support teams :)

Onboard new support agents faster

Let's accept reality and have some mental peace - B2B SaaS products are inherently complex. On average, every SaaS product has over 200 help articles, an equal number of internal docs, 1000s of past customer tickets, and zillions of internal Slack/MS team threads. It's humanly impossible to master this knowledge, even for your new, 200-IQ, and aspiring support agent. On the other hand, AI Agents can be effortlessly custom trained on 1000s of articles/millions of words, and most importantly, the right context can be retrieved and an AI-reply generated based on the query in just a few seconds. These custom-trained AI Agents can act as helpful and lovable product buddies to help your new support agents quickly master your product.

Where to find? What is right?

B2B company’s product knowledge and customer context are generally distributed across various data sources - public knowledge bases (Zendesk/Freshdesk), internal docs (Confluence/Notion), Slack/MS team threads, past customer tickets, CRMs, your kid's rough notes, local library, newspaper archives, etc. When your support rep wants to quickly reply to your customer query, they first have to do a Sherlock Holmes-like detective search to find the right source, then the right answer, and then finally reply, all while keeping the stop clock ticking (oh, SLA breaches topics are for another day, please). AI agents, unlike simple and traditional direct searches, can understand the intent and context of the question and customer, find the right content, and instantly suggest an accurate AI reply, which can be used by your support reps to reply quickly with just one click.

Standardize customer experience

The quality of support agent replies also hugely varies based on each one’s product knowledge and communication skills. Some of your agent’s replies are like Shakespearian sonnets, some like Washington Post articles, some like cryptic tweets, some are simple grinds, and finally, the rest are just as expected :)With AI agents, you can customize the brand tone (empathetic, friendly, and professional), have multi-lingual capabilities, and be great at explaining details clearly and instantly. Your support agents can run a quick check against their draft replies to quickly refine them for consistency without losing their individual style.

Rise of AI agents

Finally, the tech landscape has changed forever with the release of genAI models and agentic frameworks in the last 12 months, definitely earning a space along with other key tech moments in history like - Vacuum tubes, transistors, ICs, PCs, tele-communication, Internet, Smartphones, TikTok, Theranos, etc. The debate of AI being smoke without fire is definitely settled with companies first adding AI to their landing pages for fun to fully reimagining their workflows and products with AI. Unlike traditional, rule-based, and scripted bots, AI agents can now understand intents, break down tasks, carry out custom actions, interface with other tools, and most importantly, have human-like conversations.

Final Thoughts

The CX function is one of the forefront functions to embrace the change, validated by IDC’s projection that AI spending by CX teams is projected to exceed $15 billion by 2025. It's high time to turbo-power your CX function with AI not just to survive but to flourish in the new era of AI and to exceed your ever-growing customer demand for faster and better support.

Curious to know more on how to get started with AI agents in your CX function- Customer Support/Success/ Onboarding/Presales/ PS, Book A Demo with us to see you can implement AI quickly and reliably in company.

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