Gainsight’s Impact Analyzer Levels Up CS With Machine Learning Image

Gainsight’s Impact Analyzer Levels Up CS With Machine Learning

By Gainsight Team

Artificial intelligence (AI) seems to be everywhere these days.

From Siri and Alexa to TikTok’s For You page, AI is having a huge impact on how people interact with technology. And most of that impact is being driven by machine learning, the most important and popular subfield within AI. So whether your data set is voice commands or NPS scores, it’s likely that AI is going to be disrupting your workflows sooner rather than later. 

At Gainsight, we’re excited by the potential for this powerful tool to revolutionize the practice of customer success. We also believe that, as the definitive leaders in the field, it’s our responsibility to raise the standard for customer success software so that our customers can reach their goals more quickly and efficiently than ever before.

That’s why we wanted to take a second to focus on Impact Analyzer, powered by Horizon AI, the AI technology built by Gainsight. Impact Analyzer, part of the Gainsight CX Center, uses the power of AI to help Customer Success teams connect customer insights to business impact. 

Customer Success and Machine Learning: A Perfect Match

AI is an umbrella term for the ability of computers to learn and act like humans (thus the intelligence). Machine learning, on the other hand, is a particular technique for making the computer become intelligent. With machine learning, computers “learn” by reading data, then use what they’ve learned to complete tasks using an algorithm. 

For example, say you wanted to teach a computer to recognize the difference between a dog and cat. The computer would need to first process as many images as possible of dogs and cats. (The images would have to be tagged as such, of course.) After a while, the computer would no longer need the tags; it will have learned to recognize the animal on its own.

Now imagine how this plays out with customer success. With Impact Analyzer, the Gainsight platform learns how various drivers relevant to your business, like your customers’ survey results, impact key metrics like NPS and CSAT. And the more data it receives about your customers, the smarter Impact Analyzer becomes. 

Cut Through the Complexity

Customer success is a complex discipline, and in today’s complex business environments the solutions are by no means one-size-fits-all. And because there are so many processes and so much data, it can be difficult to analyze everything in a timely manner. One of the top priorities for Gainsight Impact Analyzer is to cut through the complexity of customer success so you have a clear picture of how your strategies are affecting outcomes. 

To accomplish this simplicity, Impact Analyzer processes data points like survey responses, scorecards, and company attributes stored in Gainsight’s Company object. Simultaneously, it identifies underlying factors that affect the key customer experience metrics such as NPS and CSAT, by classifying them as strengths and opportunities. Basically, simplification is built into the platform.

Identify Effective CS Strategies

After mining this rich set of unified customer data, Impact Analyzer then translates that information into insights you can use to make critical decisions about your business. Which is more important, engagement or adoption? Is the quality of customer support hurting retention? What adoption patterns should I drive during onboarding to maximize my chances of long-term adoption?

In short, Impact Analyzer will tell you what is working, and what isn’t. Once you understand how different drivers like healthscores and sentiment metrics impact business goals like NPS, renewals, and NRR, you can identify which customer success strategies are effective, and which ones need to change. This contextual data helps you prioritize efforts in order to meet your goals. 

Speed Up Decision-Making

With a clear vision, driven by real insights, Impact Analyzer will ultimately speed up your ability to make decisions about customer success. The tool plots data points on a grid-based on two axes: importance and performance. 

  • Importance: Identifies the strength of a relationship between a potential driver and an outcome; the stronger the relationship, the higher the Importance rating. 
  • Performance: Performance refers to how prevalent a driver is. The higher the value, the more likely it is that the driver is distributed in areas where the outcome’s value is high.

The data analysis for Impact Analyzer is updated daily, so you can be ready to make a decision about customer success strategy in real time.

Demonstrate the Impact of Customer Success

An underappreciated aspect of customer success is the need to demonstrate the impact of customer success strategies to other stakeholders within the organization, including leadership. This becomes even more important as companies grow, because the situation on the ground can become quite opaque. 

Because of this need, we wanted Impact Analyzer to have a built-in ability to present data in a clear and engaging way. With our reporting features, we made the results simple to understand the impact of key customer success activities on metrics such as NPS and NRR. The result is more than just simple reporting. Teams can feel confident in their CS strategies, their direct impact on time-to-value, and other key performance indicators, because they have the right data to confirm what they’re seeing every day as CS professionals. 

See How Gainsight Is Evolving

The features discussed here are just the tip of the iceberg for what Gainsight AI can do for you. You can learn more by watching our Evolve event on-demand

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