May 8, 2024

How to Successfully Add AI to Enterprise Support, with Informatica’s Geetha Gopalakrishnan

Last week’s TSIA webinar made one thing certain: As growing customer expectations and constrained budgets continue to hurt retention and renewals, companies are turning to the quality of their support operations to save the day. Great customer support is stopping revenue leakage by reducing escalations and keeping the customer trust required for long term customer relationships.

To scale the ability for CX to help business, the industry is turning to AI. But not all AI is created equal. Are business building their own? What are the focusing on first in the list of use cases? Last week’s TSIA webinar answered just that, explaining new research on where companies are investing in AI, and how large enterprises are dealing with the build versus buy debate. The webinar revolved around the theme of improving customer support quality by investing first in sentiment analysis and unified monitoring, the concept of automatically observing and prioritizing every customer interaction using AI. 

Here are five takeaways from a webinar in which John Ragsdale from TSIA, Judith Platz from SupportLogic, and Geetha Gopalakrishnan from Informatica laid out the case for partnering with an enterprise-grade vendor like SupportLogic to scale AI programs. 

1. CX is now the key driver of revenue growth

In today’s crowded software market, great CX has become the differentiator for companies successfully renewing and expanding their customer relationships. AI is allowing support teams to unlock the valuable customer data and insights needed by the entire organization to drive revenue growth and reduce churn. These insights are helping businesses understand the customer journey and identify potential friction points that could impact renewal rates. By analyzing customer interactions and predicting sentiment, support teams can address issues early and even prevent churn. This of course has a significant impact on key metrics such as net dollar retention, margins, customer lifetime value, and sales efficiency.

2. “Shift left” and listen to the voice of the customer

The concept of “shift left” in customer support involves addressing potential issues earlier in the customer journey before cases accumulate. By shifting the focus to the customer lens and actively listening to their voice, support teams can identify and resolve issues. Sentiment analysis provides the ability to monitor every support interaction at scale, allowing teams to address customer concerns and prevent escalations. This goes beyond using reactive metrics like CSAT, and helps teams root out what could potentially cause a bad CSAT before it occurs.

3. Support engineers are more important than ever

While AI is helping automate tasks and provide new insights, it’s not about deflecting the customer. Support engineers play a crucial role in providing empathetic, personalized support that builds long-term customer relationships. Companies still expect complex support issues to be solved by trained, quality support engineers. Where AI has an opportunity is in assisting engineers with automating tedious tasks and streamlining responses. This gives more time back for troubleshooting and working with the customer.

4. Partnering with the right AI vendor is key

Building your own AI solution can be costly and time-consuming. Partnering with the right AI vendor can help you integrate AI into your existing ecosystem, allowing you to deliver on business expectations faster. Look for a vendor that understands your business and can provide a turn-key solution that integrates with your existing tech stack. Rather than try to stretch an in-house data science team across multiple business cases, the right SaaS solution offers domain-specific expertise. This is the route Informatica took even with the success of their own sentiment detection tools. When it was time for the organization to scale to the cloud, they partnered with SupportLogic. Geetha expands on the speed and success of this partnership in the following clip:

Finding the Right Sentiment Solution

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The Impact on Informatica’s Customer Relationships

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Seeing Fast Time-to-Value with SupportLogic

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5. Start AI implementation with three key drivers

When implementing AI in your support operations, Geetha recommended identifying three key drivers. How will AI help you accelerate growth, improve productivity, and scale your operations? By focusing on these drivers and measuring the impact of AI on metrics like net dollar retention, margins, and customer lifetime value, you can demonstrate the value of your support team to the entire organization.

“SupportLogic has provided us with insight and clarity into what cases need the most attention and which customers are facing the most critical issues. As a result, we’ve resolved cases faster and better, while redirecting resources towards self-service content to improve the customer experience.”

– Geetha Gopalakrishnan, SVP, Customer Support, Informatica

Final Thoughts

AI is a present-day necessity for B2B companies looking to gain a competitive advantage through customer support. By embracing AI and partnering with the right vendor, customer support and success teams in B2B tech can gain a significant competitive advantage. With the ability to proactively address customer concerns, improve support quality, and drive revenue growth, AI is no longer a nice-to-have – it’s a must-have for any company looking to succeed in today’s fast-paced, customer-centric market. As the landscape continues to evolve, those who embrace AI will be well-positioned to thrive in the future of customer support.

For more on this session, including John Ragsdale’s support industry insights, check out the full recording over at SX Live Library

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