Relationship to Revenue: How Conversational AI Can Supercharge Customer Success

More than just a chatbot, conversational AI can help nurture and grow customer relationships.
Headshot of Erica Hansen, senior director of customer success, Conversica
Erica Hansen
Expert Contributor
November 19, 2021
Updated: November 22, 2021
Headshot of Erica Hansen, senior director of customer success, Conversica
Erica Hansen
Expert Contributor
November 19, 2021
Updated: November 22, 2021

Your success is our success.

Today’s organizations have taken this truism to heart, understanding that the success of a business is inherently intertwined with the success of its customer. If customers find value in a product and see results, they’ll continue using it and stick around for more.

At its core, that’s what customer success (CS) is all about: ensuring customers achieve their desired outcome and thrive — all while building relationships, learning their interests, and anticipating their needs. Whereas customer support and customer service teams react to inbound customer communication, CS teams proactively eliminate customer problems before they rise to the level of a customer support touchpoint. These proactive engagements enable CS teams to contribute to the bottom line and nurture customer lifetime value in several ways:

3 Ways Customer Success Teams Add Value

  • Driving upsell and cross-sell revenue. CS teams can meet customers’ evolving needs by offering features or services they need to achieve their goals.
  • Reducing churn. CS teams can combine the relationships they’re already building with customer health data to identify and prevent churn –– resolving problems customers didn’t even know they had.
  • Facilitating the renewal process: CS provides the insight, organization, and team necessary to have the most productive, meaningful, and successful renewal exchanges, enabling businesses to see faster growth for less capital.

Focused on relationship building, maintenance, and improvement, CS teams become the quarterback of your business. They can become real revenue powerhouses — but only when provided with the right tools. 

Read More on Customer Success on Built In’s Expert Contributors NetworkWhat Do You Do When Product and Customer Success Won’t Play Nice?

 

The Capacity Challenge

One of the biggest challenges for CS teams is high customer-to-account manager ratios. A Gainsight survey found that, on average, a single customer success manager (CSM) is responsible for managing 50+ accounts and over $2 million in revenue. When spread this thin, CS teams can’t provide high-quality, high-touch, and consistent assistance needed for customer relationships to flourish and are forced to prioritize some accounts over others. Unfortunately, the result of these capacity issues is fragmented customer experiences, poor renewal rates, missed revenue expansion, and ultimately, unexpected churn. 

Moreover, an organization’s need to demonstrate a strong return on investment often translates into pressures to perform and acquire new revenue for CS teams –– only intensifying the capacity challenge. In this situation, CS teams tend only to focus on gaining new customers, so much that they fail to effectively address the need to retain current ones. Unfortunately, losing customers comes at a cost. According to Harvard Business Review, acquiring a new customer is anywhere between five and 25 times more expensive than keeping a current customer. When you combine revenue left on the table with the cost of acquiring a new customer, there’s too much on the line for CS teams not to be successful. 

Read More on Churn on BuiltIn.comEffective Customer Churn Prediction Requires Careful Planning

 

Conversational AI Can Boost Your CS Team’s Bandwidth

If organizations want to keep customers, they need solutions that can provide greater visibility into customer health, deliver a consistent customer experience across accounts, and drive customers towards the next best action — all while expanding team capacity.

This is where AI comes in. Specifically, conversational AI.

Conversational AI, which uses a combination of natural language processing (NLP) and machine learning technology, engages customers in two-way, human-like conversations across multiple channels. These intelligent solutions craft and deliver personalized messages at scale that help with onboarding new customers, collecting customer feedback, driving customer health, expanding product usage, and motivating interest in expansion opportunities.

What does this mean for CS teams? By automating these interactions, conversational AI helps CS teams alleviate capacity bottlenecks and deliver a more personalized touch to every customer. More proactive and personal attention means happier customers — and happier customers mean more revenue retained and more expansion opportunities. It’s a win-win for both parties.

The example in the next section illustrates how conversational AI can successfully expand CS team capacity and drive revenue growth — and offers lessons for implementation.

Read More on Churn on BuiltIn.comHow to Prevent Customer Churn, According to Experts

 

Reducing Customer Churn

A multinational database management company was looking to grow revenue through existing customers and boost loyalty by providing high-quality service from its CS team. However, the CS team struggled to service and meet the needs of the company’s 1,000+ customers. The company was risking poor, inconsistent customer experiences and customer churn.

To overcome its capacity challenges, the company leveraged AI assistants, powered by conversational AI, to automate the communication processes, specifically for long-tail customers. Even though these customers accounted for a much smaller portion of the company’s overall ARR (annual recurring revenue), they represented a significant portion of its customer base. AI assistants were deployed to proactively communicate and engage with these customers, allowing the CS team to optimize capacity and effectively scale communication to these long-tail accounts.

The company created a content repository with various resources, including webinars, case studies, and guides to drive customer engagement. As the extended arm of the CS team, they used the AI assistants to effectively deliver content to customers that would be relevant to them and their stage in the journey to reinforce company value.

To mitigate churn, the company focused on short-, medium-, and long-term strategies that evaluated customer data, trends, and patterns to determine how to trigger conversations or timely action by an AI assistant, such as understanding why there’s been a reduction in product usage. The company has found conversational AI hugely beneficial in this respect — bringing lower-value customers into a dialogue, which the CSMs weren’t able to do before.

One of the biggest benefits the company saw was being able to scale the relationships they were already nurturing. Facing such a high number of customers, the company initially assigned one CSM to each higher-value account. They quickly realized that neglecting to serve every customer led to high churn and lower renewal rates. The problem was that the CSM’s inability to scale impacted their ability to engage and communicate with customers. When the CS team didn’t hear any negative feedback, they assumed customers were happy with their experience, but it was actually the opposite

After implementing conversational AI to automate communications, the company could drive customer engagement throughout the lifecycle. While the AI assistants provided personalized communications, gathered product feedback, and conducted customer health checks, the CSMs could analyze the data to identify areas for improvement. Care increased and improved for more customers, allowing the company to scale those accounts more effectively.

Conversational AI works wonders for CS teams looking to solve capacity challenges, allowing technology and people to work in tandem to proactively deliver the best customer experience, greater team productivity, and greater customer retention. It is set to be another important milestone in the CS industry that will aid more businesses in a multitude of ways. Be it automating routine follow-up, increasing visibility into customer relationships, or delivering highly customized experiences, when Conversational AI is adopted into customer-facing teams, like customer success, organizations have a direct impact on revenue growth.

Read More on Built In’s Expert Contributor NetworkCustomer Feedback Is the Key to Predicting the Future

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