Envision a future where technology, particularly AI, accelerates your revenue growth and revolutionizes how you manage customer renewals. This is not just a promise, but a potential reality for technology companies, paving the way for a brighter, more profitable future.

In an episode of the TECHtonic Podcast, host Thomas Lah, Executive Director and Executive Vice President of TSIA sat down with Brent Grimes, CEO of Reef.ai, to explore how AI can be a game-changer in revenue growth, particularly in renewal management. 

This blog post will provide a comprehensive overview of the critical insights from their conversation, highlighting practical steps your company can take to leverage AI for sustainable growth. These actionable strategies are not just theoretical, but valuable and implementable, empowering you to take the next step in your business’s evolution.

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The Growing Importance of AI in Revenue Growth

In the past year, companies in the TSIA Cloud 40 index, a benchmarking index for cloud companies, have reduced their spending on selling, general, and administrative expenses (SG&A) by over 5%, primarily by reducing headcount. These companies are returning their focus to growth, but with a crucial difference—they want to grow without dramatically increasing sales and marketing spend. This is where AI, particularly machine learning, comes into play.

“Our research is showing that using AI to improve renewal rates is the first place companies are tending to start if they’re going to apply AI to help with revenue.”—Thomas Lah, Executive Director and Executive Vice President, TSIA

In this podcast conversation, Grimes and Lah explain that while there’s a lot of buzz around generative AI, the most immediate opportunities for revenue growth lie in the tried-and-true areas of AI, such as machine learning (ML). Companies find that using AI to improve renewal rates is one of the most effective ways to drive revenue. This is because machine learning models can help you predict churn risk, identify downgrade risk, and make more selective investments in your customers well in advance of the renewal cycle.

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Why Renewal Management Is the Perfect Starting Point

Renewal management is a critical area where AI can have a profound impact. Grimes shared that most organizations still rely on generalized health scores to manage renewals, and they often need more effectiveness. 

Health scores typically combine various fields of information about customers based on internal knowledge and assumptions. However, they can only go so far because they are designed to flag multiple issues, from risk to growth opportunities, making them less effective at predicting specific outcomes like churn. Health scores are a tool used to assess a customer account’s overall health, but their predictive capabilities can be limited.

 “The more things a score tries to do, the less things it can be really good at.”—Brent Grimes, CEO, Reef.ai

AI-driven models, on the other hand, offer a more sophisticated approach. By applying machine learning (ML) to customer data, you can build predictive models that go beyond educated guesses. They can identify the variables that genuinely matter based on real data science and probabilities rather than assumptions. This means you can start engaging with at-risk customers much earlier in the cycle, giving you more time to mitigate risks and improve renewal outcomes.

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The Power of Data in AI-Driven Renewal Management

AI’s most significant advantage is its ability to process and analyze vast data. However, as Grimes notes, many companies find their data too messy to be helpful. AI can make sense of your data, even if it’s imperfect. Reef.ai, for example, uses data generated through standard processes, such as sales history, support engagement, and marketing engagement data.

Machine-generated data, such as telemetry from software products, is particularly valuable because it often contains the most meaningful correlations, making it an essential component of any AI-driven renewal management strategy.

Related: How AI is Revolutionizing Revenue Growth with ML-Powered Risk Prediction

Operationalizing AI: From Data to Actionable Insights

Once you’ve built a predictive model using AI, the next step is to operationalize it. This means taking the insights from the model and turning them into actionable recommendations that your team can implement. As Grimes explains, more is needed to create and simply present a score to your team. You need to go a step further by providing clear, actionable recommendations based on the insights generated by the AI.

“Having a very proactive PR campaigner on the score makes a huge difference in terms of really getting people behind the scores.”—Brent Grimes, CEO, Reef.ai.

Reef.ai takes this a step further by incorporating feedback loops into the model. When a recommendation is made, the model tracks whether the team followed it and the outcome. This data is then fed back into the model, allowing it to continually improve and become more accurate over time. 

This process is crucial to AI-driven renewal management. It ensures that the model is not just a one-time solution but a continuously evolving tool that adapts to changing customer behaviors and market conditions. This continuous improvement process sets AI-driven renewal management apart from traditional approaches.

Related: Operationalizing AI: A Strategic Guide for Department Leaders

The ROI of AI-Driven Renewal Management

One of the most compelling reasons to invest in AI-driven renewal management is the clear return on investment (ROI) it can deliver. According to Grimes, companies that engage with Reef.ai typically see ROI within the first quarter when using the model. By the second quarter, the results become even more significant. 

The key to achieving this level of ROI is to start using AI well before the renewal cycle. By engaging with customers who are at risk six to nine months before their renewal date, you can take proactive steps to mitigate churn and improve retention rates. This helps you preserve revenue and build more robust, resilient customer relationships.

Related: Harnessing Technology and AI for Revenue Growth: Strategies and Insights

Beyond Renewal: Expanding the Use of AI Across Your Business

While renewal management is an excellent starting point for using AI, the potential applications are far broader. The same principles can be applied to other business areas, such as expansion and lead qualification. By building AI models focusing on these areas, you can identify new growth opportunities and make more informed decisions about where to invest your resources.

For example, AI can help you identify industries or customer segments where you have a higher likelihood of expansion and then provide recommendations for targeted marketing and sales efforts. This verticalization strategy allows you to tailor your approach to different industries’ specific needs and challenges, ultimately driving more significant growth.

The Future of AI in Revenue Growth

The conversation between Thomas Lah and Brent Grimes highlights AI’s transformative potential in driving revenue growth for technology companies. As AI models become more sophisticated and automated, the barriers to entry will continue to decrease, making it easier for companies of all sizes to leverage these powerful tools.

However, as Grimes emphasizes, it’s not just about the technology—it’s about changing your operations. By shifting from a reactive approach to renewal management to a proactive, data-driven strategy, you can uncover new levels of efficiency and effectiveness. And as AI continues to evolve, the companies that embrace these changes will be the ones that lead the way in the next era of business growth.

Lah ended the podcast with a warning to companies that haven’t caught on yet: “If you’re not operating this way three or four or five years from now, the way you’re managing renewals, and the way you’re deploying your employees is going to look incredibly dated.”

If your company wants to grow revenue more efficiently, now is the time to explore how AI can help you achieve that goal. By starting with AI-driven renewal management, you can begin to see the benefits within just a few months. As you expand your use of AI across other business areas, you’ll be well-positioned to stay ahead of the competition and drive sustainable growth for years to come.

Your Key Takeaways

• AI enhances revenue potential: By leveraging AI, particularly machine learning (ML), your company can accurately predict churn risk, identify growth opportunities, and strategically invest in customers well before renewal cycles. This proactive approach can significantly enhance revenue retention and growth.
• Data-driven decision-making: AI-driven models go beyond traditional health scores by using real data science to identify the key variables that impact customer retention. This allows you to engage with at-risk customers earlier, improving renewal outcomes and maximizing ROI.‍
• Transformative ROI with AI: Companies implementing AI-driven renewal management typically see a clear return on investment within the first quarter, with even more significant results by the second quarter. Starting with AI in renewal management sets the stage for broader applications across your business, leading to sustainable, long-term growth.