Generative AI can boost CS

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Guy Nirpaz is the founder of the leading customer success platform, totango. He wrote Farm Don’t Hunt – The Definitive Guide to Customer Success.

When I wrote Farm Don’t Hunt: The Definitive Guide to Customer Success ten years ago my focus was on how living in a digital-first world had changed the paradigm of how we do business. As the concept of “agriculture” of our customers has become a central tenet of customer success, I have also come to understand that the customer journey itself is a company’s most important product. It encompasses the holistic experience customers have with companies, from exposure to brand touchpoints to interactions with products or employees, meaning it needs to be repeated all the time so it’s always improving.

Now the rise of generative AI is forcing us to rethink the way we do things. After years of turbulence in technology and the economy, and amid the increased pressure of an always-connected hybrid workforce, I believe the accessibility of this groundbreaking technology offers a renewed promise of opportunity. Smarter, more flexible technology enables us all to become hyper-efficient.

What does this mean for customer success, which many associate with the human touch in business relationships, as we find ourselves storming into a new era?

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A shifting landscape

In an always-connected and always-on world, remote and hybrid workloads push many of us well beyond a 40-hour work week. We have too much to do and too little time to do it. However, we are now on the cusp of a groundbreaking shift in generative AI that I believe will change the world – not to mention customer success – in much the same way that industrialization changed the face of America: through our productivity and ultimately our working week.

Back in the early 1900s, a large proportion of Americans lived on farms and worked by hand for more than 70 hours a week without electricity or electrical equipment. By the 1950s, the tractor had replaced the bullock and, together with other mechanical equipment, provided three-quarters of the power needed in the field. In addition to new equipment to increase productivity, scientific knowledge and technology improved production methods, with iterations continuing today.

Just as technology once increased productivity on farms and brought the US back to a 40-hour work week, I believe AI is about to make taking care of our customers a whole lot more manageable.

Cherish our customers

To be successful today, companies need to maintain and expand their customer base. That means it’s never been more important to nurture our customers so they can achieve the business outcomes they want and grow no matter what the world is going on. While composable customer success practices and technologies allow us to adapt quickly to change, AI opens up new opportunities for companies to deliver great experiences and value – and do it at scale.

Especially when it comes to customer success, “scale” doesn’t mean “without personalization”. Instead, it’s about information and intelligence at scale. By allowing AI to augment our work by helping us automate customer journeys, monitor customer health, spot trends, friction, and opportunities, and more, we’re giving ourselves the bandwidth to get creative and strategic while delivering powerful and personalized automated develop practices.

With tools that automate our clients’ editing or reduce the effort required to water them for growth, we need to rethink the way we work. What does customer success with greatly increased productivity look like?

The power of people + technology

Having an AI assistant integrated into the platform your teams use certainly doesn’t mean you have to water your customers ten times as often. Instead, your trusty assistant can help you determine the best cadence, as well as identify clients that need extra attention. It can give your customer success managers (CSMs) more insight into roadblocks, churn risks or new opportunities by synthesizing a variety of data collected on a specific customer account – then drilling down to see how that compares to trends or anomalies in your wider customer portfolio.

Perhaps most importantly, all this critical information is now easily accessible. By using a natural chat interface, team members no longer need time to fully launch and train this new tool before it becomes effective. For example, they can simply ask the assistant how to spot the customer segments with low health scores or decrease in usage in the last 30 days and take action from there.

Instead of watering customers 10 times or drowning them in data sources and spreadsheets, your teams can dedicate their interactions with customers to more strategic discussions and activities, ensuring that customers are not only well watered, but also get the specific nutrients they need have to thrive.

Embrace this new era

None of us want to be disturbed; we want to be the disruptors shaping the next generation of customer success. Therefore, I believe now is the time to invest in learning how to use AI responsibly and properly.

Consider creating small, internal innovation pods dedicated to testing, experimenting, iterating, and integrating AI into your systems. With an agile mindset and composable technology for customer success, they can experiment with modular components or integrate sweeping changes. In addition to exploring the benefits of AI internally, it’s also important to stay involved in the bigger conversation by participating in discussions about how companies can responsibly and safely use AI to expand their work.

As more companies get comfortable with AI and integrate it into their systems, I think we’ll see an increase in margins, not just getting more accomplished, but doing it all better. With more bandwidth to focus on customers, you can nurture them well and deliver the results they need.

Whether you run a business or are one of the tens of thousands of tech workers affected by recent layoffs, now is not the time to sit on the sidelines. The next evolution is underway: are you ready to help lead the movement and shape the future of AI in customer success?


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