Deon Nicholas of Forethought On How to Build Lasting Customer Relationships

An Interview with Rachel Kline

Better self-service & AI. Ironically to build better more personalized support at scale when it matters, it is very critical that the customer be able to self-serve on the simpler issues. This means investing in customer training, knowledge bases, and customer-facing AI agents. Oftentimes, these AI agents can even be trained on your proprietary data, in addition to your help center or public data, which can lead to extremely high-resolution rates. Of course, this is one of the most critical use cases we have at Forethought.

Building lasting customer relationships has many benefits, including increased revenue, positive word-of-mouth recommendations, and saving on acquisition costs. But how does one do this? In this interview series, we are talking to Product Managers, founders, and authors who can share their “Five Tips For Building Lasting Customer Relationships”. As a part of this series, we had the pleasure of interviewing Deon Nicholas.

Deon Nicholas is the Co-Founder & CEO of Forethought, the first AI platform for customer support automation. Previously, Deon built products and infrastructure at Facebook, Palantir, Dropbox, and Pure Storage. Deon is a sought-after futurist and expert on generative AI, with appearances on CNBC, Bloomberg, and Yahoo Finance. He has authored several machine learning publications and holds numerous infrastructure patents. Deon was a World Finalist at the ACM International Collegiate Programming Contest and was named to Forbes 30 under 30. Originally from Canada, He enjoys spending time with his wife and two children, playing basketball, and reading as many books as he can get his hands on.

Thank you for doing this with us! Before we begin, our readers would like to learn a bit more about you. Can you tell us the “backstory” about what brought you to this career path?

Before I founded Forethought, I held roles in building products at Facebook, Palantir, Dropbox, and Pure Storage.

I grew up in Toronto and learned how to code from my older brother’s friend. I built my first video game when I was seven years old using drag-and-drop tools. My first job in high school was in customer service, and next, I was an intern at the Alberta Machine Intelligence Institute (Amii), one of the top machine learning labs in Canada. One problem I was especially fascinated by was how AI could answer questions — essentially what GPT4 does today.

No one in my family had gone to college before, but after learning about machine learning at such a young age, I knew I wanted to attend The University of Waterloo. When I got there, I decided to compete on the school’s programming team. At first, I was pretty bad. We didn’t win, but I just kept going. I read all four years’ worth of algorithm textbooks in my first year. I just wanted to get better. In my final year, I was a World Finalist in the International Collegiate Programming Contest, which is like the Olympics of Computer Programming.

I’ve since repeated that process as an entrepreneur. Every problem I face, I go really hard after solving it. I team up with great people, understand that failure is a possibility, and then just keep trying until we win.

When the idea for Forethought was first forming, I applied to Y Combinator and was rejected. I spent the next six months getting clarity on the direction I wanted to go in and what exactly our product was going to be. I was still fascinated by artificial intelligence (AI) and its potential to answer questions. And I knew from my previous role in customer service that there was a huge opportunity there. So, Forethought became a company focused on using generative AI to transform the world of customer service — coming full circle to my idea that originated in high school.

Forethought has since raised over $90M in venture capital and we count brands like Upwork, Airtable, Fetch, and Thumbtack among our customers.

Can you share with our readers the most interesting or amusing story that has occurred to you in your career so far? Can you share the lesson or takeaway you took from that story?

One of my proudest moments in the early stages of the company was our launch at TechCrunch Disrupt Startup Battlefield in 2018, the world’s most prestigious startup pitch competition. It was an amazing lesson in teamwork, focus, and leaning into authenticity as a leader.

We had gotten the acceptance letter into Disrupt in May 2018 and learned that we would be launching on stage and pitching a panel of judges, competing against 24 other startups for the Battlefield Championship. At the time, we had just barely landed our first customer.

As a team (it was about four of us at the time), we agreed to ignore the “vanity” — the coolness factor and excitement from launching at TechCrunch Disrupt — and that nothing else matters except delivering value to our customers. We decided we would not launch unless we had five customers willing to put their logos on our slide.

This became our sole focus for the next three to four months. In the beginning, we had one pilot customer. By the time we got to Disrupt, we had six. At the end of the day, nothing else matters if you’re not delivering value to your customers, and we were able to lean into extreme focus and make this happen. We also focused heavily on storytelling and knowing our business cold. Sami Ghoche, my co-founder, and I spent hours in a room thinking through the possible questions people could ask about the business and how we would answer them.

In the end, after all of that preparation and focus, not only did we launch on stage, but we won the Battlefield Championship! It was like this crazy dream come true. We raised our $9M Series A shortly after that, and after celebrating, we got right back to work. That focus on customer obsession has been with us ever since.

Are you working on any exciting new projects now? How do you think that will help people?

In addition to Forethought, I am also an angel investor in several Generative AI companies including Cognition (Devin) and Anthropic. I’ve invested in companies building AI agents for robotic process automation (RPA), AI agents for sales, and even AI for accounting. I fundamentally believe Gen AI is going to impact every area of business.

Staying up to date with what emerging startups in the field are doing also helps me stay sharp and know what’s coming next. I also enjoy getting to mentor these stellar gen AI founders and helping them launch their companies. More than 60% of the companies I back are run by female or under-represented CEOs. Diverse minds and voices are going to be critical to building AI that meets the needs of the future.

For the benefit of our readers, can you tell us a bit about your experience with building lasting customer relationships? Can you share an anecdote or two that illustrates your experience in this area?

You build good customer relationships by delivering and doing great work and forming strong personal connections with people. Customers who have a great experience with you or your product will come back again and again — especially if you have established a personal connection with them.

One of our earliest customers at Forethought had moved on to another company right before the COVID-19 pandemic hit. His new company was a food delivery company that saw a massive spike in demand for customer service due to the pandemic, and I was his first call because he knew Forethought could help them handle the surge. It was really an honor to receive that call from a previous customer who remembered me personally and thought of Forethought in such a moment. We’re still good friends to this day, and we even hang out outside of work.

In today’s fast-paced and constantly evolving landscape, what strategies do you employ to maintain a strong connection with your customers and anticipate their changing needs?

The most important thing to do is listen to your customers. You’re never too big of a company to jump on calls with your customer. You need to start by making sure your customers feel heard and understood. Empathize with them, and deeply understand their problems. As a customer myself, I know there’s nothing more frustrating than going in circles with a chatbot or a call center agent who doesn’t really understand the issue!

More broadly, whether through surveys, feedback forms, or leveraging Generative AI like Forethought to proactively discover trends and insights, analyzing CX data can help you identify opportunities to improve your products and services, or offer new products or features that your customers want. The data housed in customer support conversations is truly valuable in that way.

Can you discuss the strategies that companies can employ to strike a balance between driving revenue and profitability, and focusing on building customer relationships and loyalty?

Driving revenue and building customer relationships are not mutually exclusive. Stronger customer relationships lead to better retention, referrals, and expanded relationships over time that all ultimately add up to more revenue.

It’s easier to keep a dollar than to lose it to get a new one. When you take that to heart, you can build a customer-obsessed culture. Obsessing over your customers’ needs helps you build better products, and deliver those products more effectively. It helps you cut out the fluff and noise that ultimately does not delight your customer.

This is where AI and automation can help, by identifying trends and helping you focus on the right things. For example, most customer support tickets (55%) are “simple”, and more than a quarter (27%) are “moderate difficulty”. This represents a significant opportunity to reduce the cost of customer support without negatively impacting the customer experience. With the right tools, AI, automation, and self-service can effectively resolve most basic issues. This frees up your customer service team’s time up to focus on complex customer situations or problems. That means when your customers really need that one-on-one help, they can access it quickly and resolve their issues faster.

Could you describe the metrics and measures you use to evaluate the success of your customer relationship-building efforts, and how you identify areas for improvement?

NPS (Net Promoter Score) and CSAT (customer satisfaction) are the two most important metrics to understand your customer relationships. You should also understand gross and net retention (the inverse of churn: how many customers are staying with you). Another key metric should be your total touchpoints with a customer. How often are you talking to them, whether that’s through support tickets, customer success check-ins, or even taking them to dinner?

When it comes to customer service, the resolution rate is king. Are your customers getting their questions or concerns resolved? This is another area AI can help, by providing you with insights that help you improve your resolution rate.

Regarding customer-facing teams, what steps do you take to ensure they can deliver personalized, proactive, and efficient support, tailored to the needs of each individual customer?

Customer-facing teams must have the right tools to get the job done quickly and effectively. Speed to resolution is a huge factor in customer satisfaction, so clunky, outdated systems that require agents to spend hours resolving issues can really drag down your CX as a whole. For example, we see a lot of decision trees in customer service that force agents down specific paths based on what a customer says. But decision trees are often too rigid and don’t provide agents with the autonomy and flexibility to go above and beyond for a customer. Tools that allow agents to use natural language and conversationally address customer issues are much more effective and empowering.

What tips do you have for responding to negative feedback from customers, and what steps can be taken to turn those experiences into positive outcomes?

Negative feedback from customers should be addressed as quickly as possible. Most complaints are something fixable, and if one customer is experiencing an issue, it’s likely that other customers are, too. AI can help you quickly identify common issues in your customers’ feedback so you can start to identify root causes. Taking a growth mindset and a problem-solving approach to customer feedback will pay dividends going forward. In that sense, negative feedback should be taken as a gift.

Lastly, how do you use technology or AI to enhance your customer relationships, and what tools have you found to be most effective in building and maintaining them?

Sixty percent of people are afraid AI will make it harder to reach a human agent, and 42% worry it will provide incorrect information. But when done right, AI can enhance customer relationships.

We’ve seen this directly with customers using Forethought for customer support. Our suite of AI-powered tools help CX teams work smarter and faster, so they can improve resolution rates and customer satisfaction. There are four ways AI makes customer service better:

• Proactively providing intelligent, actionable recommendations and analytics about your CX so you can focus on priority issues.
• AI agents trained on your company’s historical data and connected to your knowledge base can quickly solve repetitive tickets and automate issue resolution.
• AI can also triage more complex tickets and hand them off to the right agents to accelerate response times and prioritize urgent issues. For example, AI can now understand sentence structure, tone, and nuance to accurately tag tickets and use historical knowledge and intent analysis to route tickets to the right team.
• Lastly, AI can serve as a copilot to agents, making them more productive than ever before. When AI is integrated into helpdesks, agents can view AI-generated ticket summaries, use AI-guided responses to customers, and search a knowledge hub to quickly find materials needed to resolve customer issues.

Here is the main question of our interview. In your experience, what are five key components of building lasting customer relationships? If you can, please share a story or example for each.

1. Listening and understanding. Every customer wants to feel like you understand them, and that you’re listening to them. The easiest way to do this is by validating what they need or what issue they are having, and making sure you have it right. Don’t rush into solving an issue before you truly try to understand the core of it. Empathy goes a long way.
2. Data and intelligent insights. Getting to know your customers also means knowing everything about your customers. You should maintain historical data on customer conversations that provide more context, understand what trends and issues they’re having, and know what recent touchpoints you’ve had with them, so they don’t have to answer the same questions over and over again. You can do this at an individual level, but also in aggregate. By seeing the overarching trends, you can likely give proactive help to a new user who might be likely to encounter an issue that many others have. This helps you know where to prioritize, and how to personalize. At Forethought, we built a tool called Discover, that helps customer experience leaders do this at scale.
3. Better self-service & AI. Ironically to build better more personalized support at scale when it matters, it is very critical that the customer be able to self-serve on the simpler issues. This means investing in customer training, knowledge bases, and customer-facing AI agents. Oftentimes, these AI agents can even be trained on your proprietary data, in addition to your help center or public data, which can lead to extremely high-resolution rates. Of course, this is one of the most critical use cases we have at Forethought.
4. Feedback and escalation mechanisms. Once you are armed with the right data and have put in place AI agents or other tools to help scale self-service, you need to ensure there is some feedback loop and escalation mechanism. Customers should be able to say when the self-service tools aren’t working and when they need to connect with a human. Or better yet, your systems should be able to pick up when this kind of “escalation” is likely to happen. Once you have these in place, you will know exactly where, when, and how to engage your customers with a personal touch, so these high-priority items are given the most care from your most experienced agents.
5. Giving a sh**. And finally, it comes back to customer obsession. Armed with all of the tools you need, the most important aspect is “doing something about it”. When an issue is escalated or brought to your attention, you need to treat it with urgency. Customer relationships and customer service are everyone’s job, whether you are a software engineer, an account manager, or the CEO. Resolving issues quickly and with high quality will then earn you the right to continue the relationship with the customer going forward. When things are going well, celebrate your customers, check in with them regularly, and ask them how things are going in their world — outside of your core offering. This is the key component to building a lasting relationship with your customers.

How do you ensure that these ideas are implemented throughout the customer journey?

It’s important to collect feedback from customers to see how they are really feeling about the interactions they have with your brand. You can do this by triggering brief surveys at key points in conversations and ensuring prompt action to address negative responses. If you are only looking at metrics like efficiency, productivity, and ticket deflection rates, you are missing the most important aspect of how your customer service is performing: how humans feel about it.

We are nearly done. You are a person of enormous influence. If you could inspire a movement that would bring the most amount of good to the greatest amount of people, what would that be? You never know what your idea can trigger. :-)

I want everyone to have access to a career in technology and AI, especially those who are underrepresented or underprivileged. This is really important to me. I grew up pretty poor in inner-city Toronto. Back then, I could not imagine the life I have now as the CEO of a leading venture-backed AI company. But I honestly got super lucky being introduced to computers and getting to chase this passion for technology and eventually AI. While I’m super proud of where I’ve come and where I am today, this shouldn’t be an anomaly. I think careers in tech are going to become more common, and I think AI is actually making it so that “everyone can be an engineer”. You don’t have to learn a complicated computer programming language to instruct a computer anymore, or to build a video game or a web app. With AI, you will be able to talk to the machine, much like talking to a teammate. That means the sky’s the limit for anyone who wants to build software or start a software company. And I want to see many many more people taking part in the economic mobility that comes with that.

How can our readers further follow your work online?

To learn more about Forethought, please check out forethought.ai! Or follow me personally on LinkedIn, X, or Instagram.

Thank you for the interview. We wish you only continued success!