How John Collins of LivePerson operates as a data-driven CFO

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John Collins is the CFO at LivePerson and the very definition of a modern CFO in every way. His career journey spans a job at the New York stock exchange, grad school at MIT, inventing a fully automated trading platform that he wrote from scratch, managing the portfolio for a 10 billion AUM fund, co-founding his own company, and joining LivePerson. As CFO at LivePerson, John is passionate about the role of data in the CFO world, the possibilities of “conversational commerce,” and the vision of combining algorithms and social justice.

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Key Takeaways

John’s journey to LivePerson

After getting introduced to LivePerson’s CEO Rob by chance, the compelling encounter led John to join the LivePerson team.

“After I met Rob, he gave me his vision for LivePerson and how the company’s innovations are changing the way that we communicate and do business. And the value proposition really resonated with me on a deep personal and professional level. I mean, who hasn't experienced frustration waiting on hold or dialing 1-800 numbers to get some intent, some need resolved with the brand? So being able to send a message and then go about your day and feel confident that your need would be taken care of without putting you on the brand or the agent’s schedule is super compelling. And then leveling that up into what we call conversational AI and specifically conversational commerce was a really compelling vision that I was pretty sold on from the beginning.”

Navigating data constraints

John describes how the data that most companies collect is inherently messy.

“I distinguish data from information. Data needs to be transformed in some way. It needs to be normalized. It needs to be cleaned in order to produce some kind of useful information for decision-making purposes. Many companies have a lot of data, but they have trouble accessing it. They have trouble reconciling. It's not clean, it's not reliable. I call these data constraints. And so there are many constraints you need to overcome in order to leverage data effectively.”

Conversational commerce

The future of commerce is conversational: two-way engagement that takes place on the customer’s terms.

“LivePerson is really a cloud-based platform that the largest brands in the world use to converse with their customers through messaging...You can, let's say, change your flight, order a burrito, arrange contactless, commerce services, like curbside pickup, all from the convenience of iMessage or WhatsApp or Facebook or any other channel that we prefer to use today. And messaging-based transactions like these I think represent a modern engagement model for brands and consumers that we call conversational commerce. The company has really evolved from synchronous web chat for customer care applications to asynchronous communications for a wide range of use cases, including two-way proactive notifications. So, no longer do you get this email that says “do not reply.” The LivePerson ethos and the essence of conversational commerce is that it's always two-way.”

LivePerson’s vision

The ability to converse with a brand in real-time will be a game changer, supplanting historical physical sales interactions.

“The vision of the company is that conversational commerce will really supplant the types of commerce that we've seen: historically brick-and-mortar, sort of physical retail sales, e-commerce where you're pointing and clicking on a website. The ability to converse with a brand to get questions answered increases confidence, increases the satisfaction of the experience. And ultimately, as the results show, it drives more sales for it for brands.”

CFO as a data scientist

John sees data transformation as the primary goal of the modern CFO - a departure from previous perceptions of the CFO as purely a financial professional.

“The CFO operates at the intersection of all the company's data flows, whether it's sales, product usage, finance. That's a vast sea of data. And fundamentally the role is to transform that data into useful information, right? As we mentioned for strategic decision making purposes, spreadsheets and traditional financial analysts are simply not capable of effectively utilizing the volume of data that's available in our increasingly quantified world. And from this perspective, the CFO sounds, I think, more like a job for a data scientist than a classically-trained finance professional.”

Navigating information silos

When information systems are fragmented, the entire company suffers. Creating efficient workflows is what allows companies to truly succeed.

“Most large companies’ internal operations run on a fragmented network of siloed spreadsheets and enterprise software where humans actually perform the equivalent of ETL jobs - that is, they manually extract data from one system. They transform it in a spreadsheet combining with other data or whatever the case may be. Then they load it into another system. And that creates the link, the connection between systems to make, you know, to make workflows happen; to complete processes is incredibly inefficient...the result of all this is severely constrained flow of reliable data that renders even the simplest automations very hard to deploy. So in order to move faster, in order to be smarter and take on the kinds of challenges and opportunities that were presented to us by the pandemic, you have to solve these data constraints.”

Statistically Sound Decisions

As humans and companies, we are predisposed to do things the way they’ve always been done. Analyzing data can help reveal whether or not those patterns are valuable.

“When you can bring to bear hard evidence that is statistically sound, it can change the way that we might be predisposed to think about a problem or an opportunity. You know, as humans, we have many innate biases, some of the most profound being availability bias. You know, what have we seen most recently that works? Well, let me just apply that same tool to this problem, which may not be the appropriate way or the optimal way to solve the problem. And so I think being more quote-unquote “data-driven” has allowed us to make more objective, higher quality, in other words more predictive decisions that ultimately lead to higher ROI.”

The importance of empathy

2020 was a year of stress. John says that recognizing that stress and supporting team members on an emotional level is a necessary task.

“Empathy is a clear trait that is needed in times of great uncertainty and in times of emotional stress. And certainly many people in the world were experiencing uncertainty and emotional stress. And so I think that putting yourself in the shoes of your employees and empathizing with them in a genuine way to find solutions to their problems, not just the company's problems, is essential for any leader to come through a unique challenge like the one we experienced in 2020.”

Giving employees ownership

As a CFO, it can be easy to dictate from the top down. But John believes that motivated employees are the best employees.

“I've always been a strong proponent of ownership. And I don't mean that in the way of, “just delegate everything.” I mean, people should feel excited about what they do. And in most cases you're excited about your work if you have a lot of control and you can kind of steer the ship to an extent, and take pride in what ultimately results from your decision-making. And if you're just having people execute on decisions that have already been made, I think that's a work mode that can be useful in some contexts, but from a leadership position I think it's a little bit suboptimal. And you know, you end up with people who are just working 9-5, right. They're just collecting a paycheck. Whereas if they're bought in, if they're a part of devising the solution and they're steering the ship, then I think they wake up in the morning thinking about that problem.”

Combating machine-learning bias

By pioneering programs like Equal AI, LivePerson hopes to ensure that algorithms are free of harmful bias.

“LivePerson has helped to found an organization called Equal AI whose sole mission is to eliminate bias in algorithms. And the classic scenario here is where let's say biased, legacy practices have collected data...There's just a broader need to question the way that we're building and training these algorithms, especially considering the extent to which they permeate our everyday lives and the extent to which virtually all digital brands today are leveraging some form of machine learning to bring value to the consumer.”

Banking love

Need proof that LivePerson wants the world to be a better place? Look no further than Bella, the new banking concept that combines cash with karma.

“We've launched a new brand. We call it Bella. You may have seen some of the buzz on social media. It's a bit of a test and learn scenario right now for LivePerson, but it's essentially a bank that literally loves its customers. Bella offers its members a beautiful, conversational experience that covers all of your traditional banking needs, but there's a lot more to it. For example, customers are randomly rewarded with up to 200% cash back just for using their Bella cards. And random acts of kindness are also a staple of the experience. For example, if you buy a coffee or your lunch, Bella may pick up the tab for you.”

The digital transformation

The world was already going digital before the pandemic. Now, there’s no going back.

“There was obviously kind of a forcing function for this digital transformation. And I think that has a lot of implications for our future strategy...once you have built a machine, right, just to solve a problem, you'll never put that problem back in the hands of less efficient, more expensive human labor. And so all of this in my mind comes together in a way that spells out an investment strategy and a product development roadmap and a go-to-market strategy that's very cohesive and aligned. And so that's how we're currently thinking about making decisions this year.”

Leveraging data advantages

The bottom line is that leveraging data is a full time job. To that end, John has hired a dedicated team to analyze data and put it to work within the company flywheel.

“There's a need to leverage more data to stay competitive, to lean in on what I call data advantages, which are distinct from leading with engineering or leading with business relationships. Data advantages I think are some of the most powerful forces you can bring to bear to solve business problems and unlock new opportunities...I've created a team that I call DMD: Data Models & Decisions, where I've hired a large team of scientists and engineers instead of the typical financial analysts and business analysts that are often found in the back office. And the central idea behind DMD is that, like my example with Alibaba, leveraging data appropriately, can create flywheel effects.”

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