Scaling an organisation might appear straightforward, especially when there’s a high-demand product like AI involved. In reality, though, it’s both a science and an art — requiring someone who understands how these principles intersect and drive growth.
Phil Coady, Chief Revenue Officer of AI/ML firm Dataiku, brings a wealth of experience in scaling businesses at both the start-up and enterprise levels. He sat down with Frontier Enterprise to discuss his approach to business growth, his decision to join Dataiku, and the future direction of the AI revolution.
Can you share a bit about your experience in scaling companies?
There has to be product-market fit. Product-market fit is amorphous, and it’s always moving around, but you have to have an idea that there’s a market and a pain there, and there’s a product that can answer that pain. The trick is that your product has to then answer the pain more discreetly as you go along and as the market matures and as more competitors come in. When I’m scaling out sales organisations, I get very myopic very early. This wouldn’t necessarily be data, because they figured a lot of this out already, but I get very focused on my TAM, or total addressable market, and my SAM, or my serviceable addressable market, because they’re a little bit different.
The TAM is anybody I could sell to. My SAM is who do I want to sell to today, now? I’ll give you an example. I may do a TAM and decide that retail is a great market for me, but I may be a really small company, and my product might be kind of evolving, so yes, I can sell to retail, but it may not be Walmart right now, because I might not be able to manage something of that size and scale. So your SAM is about who you can service and what you can service today. Then that changes, as long as your TAM changes. Once I get through that, what I’m really focused on is, what’s the ideal customer profile (ICP)? What is the ICP persona, and what pain points are we targeting that would be important to them? Once we know that baseline, then it just becomes a talent issue of, ‘Am I hiring the right profile to do the right type of selling that we need to the right types of personas that we have?’ Is it an enterprise software sale? Is it an SMB? Is it transactional? Is it PLG-led?
Once we move from that, it becomes about building the scaffolding for a sales and revenue process, which traditionally has been MEDICC (metrics, economic buyer, decision criteria, decision process, identify pain, and champion). This scaffolding simplifies the process, but at its core, it’s about value-based selling. When you lose MEDICC, the only two things that really matter are: ‘Do we have pain?’ and ‘Can I solve a business problem?’ Pain can be personal, professional, latent, or actionable — and do I have a champion within the customer organisation to help me navigate?
Let’s say I was coming to your organisation. Someone there has to have a pain that I can associate with and attach to, that I can help them with, and it has to be significant enough for them to champion me inside your organisation. It’s really the classic level of enterprise-value selling. The problem is that a lot of organisations don’t value-sell but rather product-sell, leading with what their product can do, and by the way, that’s great. In some environments, like in security, that approach is perfect. A lot of tools are sold that way. But if you’re in an evangelical or early-adopter marketplace, which is what I usually focus on because I find them more interesting, the key is putting a process in place that is driven by value, pain, and solving problems.
What attracted you to your current role in Dataiku?
One of the reasons I’ve had some success in my career is that I’m okay at picking markets, as well as companies within those markets. I’m a pattern recognition person by nature, and I look at how things are adopted and why they are. For example, when I chose AppDynamics to go into the APM, I was convinced that the most valuable asset a corporate enterprise would have is its application. The application becomes your company. The reason why most companies lose resonance with the public is because they lose their brand. Their brand no longer resonates, and that’s a bit ethereal, but the application — that’s another thing. I started thinking about old-school businesses like Wells Fargo or Bank of America, which have been around for hundreds of years. They did an amazing job curating their brand through physical locations, and they could control that. Now, suddenly, they have an application on a phone, and someone can’t use it because they’re on the tube in London, and now your brand is terrible. That’s why I chose AppDynamics — I was firmly convinced with the app.
Why did I choose Dataiku? For one, there have only been three tectonic shifts in my time in tech. By tectonic shifts, I mean massive technology changes that reshape business. For me, there was the internet in 1995, the cloud around 2006, and now AI. These shifts collide and change the course of business and how we interact. Entire industries are born from these shifts. For example, when the internet took off in 1995 and started reaching large enterprises, it spawned things like cybersecurity, which is now a multi-trillion dollar market. Being involved in one of these three major shifts is what interests me.
In my opinion, OpenAI is what spurred AI from a user perspective — it created the user demand. My son is using OpenAI to write papers, and soon it will be on every phone. OpenAI made AI accessible and democratised for everyone. I saw this user explosion coming, and then I found this little company called Dataiku that, in my opinion, undermarkets itself. For 11 years, they’ve been obsessed with democratising AI. To truly get value out of something, you need to extend it to large groups of people. So, I’m going to promote a product with a user interface that’s simple enough for a large group of people to use in democratising AI within an organisation. When I’m building models and my value chain across AI, I can have direct interaction points all the way through. I love that idea because I thought the user community would be embedded.
With Dataiku being born in the pre-ChatGPT era, has there been a shift in business strategy since?
There’s been a shift, but I don’t think it’s because we’re running to a market. It’s a shift because we’re reacting to a market. What I mean by that is we would be foolish not to have a generative AI solution, conversation, and development. Interestingly, we’re actually just releasing what we call Dataiku Answers, which is a natural language way of asking questions of large data sets and getting responses.
However, we won’t give up on traditional AI and predictive AI. We love the generative AI players, and their models come into our platform pretty consistently, but we also believe that AI is bigger than just generative AI. Generative AI gets the hype because it’s the easiest to turn around and deliver quick, tangible results. We love it, we have a whole strategy for it, we’ve made some announcements, and we’ll make more to come. It will definitely be a big part of our development — but it won’t take us off the path of our predictive and traditional AI models.
For an enterprise tech company, how do you measure your brand success?
Ultimately, I think the way you judge your brand is by people’s ability to use your product, get value from it, and feel comfortable talking about it. What made Amazon, in my opinion, is their maniacal obsession with their customers, so for me, the focus is on driving customer satisfaction.
When a company signs up to buy COTS (commercial off-the-shelf) software from one of my companies, I’m dogged about the fact that they could choose anyone they wanted — especially the biggest companies in the world — but they’re deciding to trust us. Part of that is our ability to deliver value, but another part that isn’t discussed enough is that they’re really paying us to connect them to the future of the marketplace. We’re not going to give them a technology that, three years from now, they’ll need to replace because the market or technology stacks have moved on. I can’t talk about our roadmap, but we have a brilliant product team that identifies where the market is headed and ensures that if you sign on to Dataiku, you won’t get boxed out, to the best of our ability.
One of the big reasons I came here is that I know I won’t be leveraging my relationships and asking people to commit to me for multiple years, only to find myself unable to meet their future needs two years down the line.
