The GigaOm Pivot – rebuilding the analyst business for the digital enterprise

How do you transform and grow in these times? CEO Ben Book has taken GigaOm from a boutique analyst company to what is now recognized as a leading analyst firm, redefining the nature of analysis in the process. Here he looks at how the market for research has evolved, and how GigaOm has shifted to align with the needs of end-user organizations as they prepare for a data-driven, digital future. 

On identifying the market need – linking strategy to execution with technical content

Every company wants to be a data business. Look at the web-scale companies, a lot of the unicorns that came out of Silicon Valley, Uber, Lyft, Airbnb and Facebook. They’re data companies collecting and using data that’s driving the revenue model. Facebook is an advertising model. Airbnb is an e-commerce-type model. Different models, but at the root, they’re using data to provide digital experiences. 

Entrepreneurs can start a business so fast now with the cloud, with access to tooling, with all the pace of innovation. You can start a company in 30 days, you can build an MVP in 30 days, and you can get it to market in 90 days. You can get feedback and then you can build on that. You don’t even need funding, it’s pretty incredible how fast you can move. 

That’s driving the innovation on the enterprise side. Enterprises want more digital transformation. If they have a digital product and get better data, they can help their customers and make better planning and revenue decisions. In the past, companies had to buy hardware, build a data center, and hire a bunch of people to manage it. You don’t need to do that anymore; you just need a credit card and a developer. 

For a long time, technology was too hard to use, but we’re moving into a new phase. The big cloud providers have done a really good job of making technology easier so anyone can use it. That’s driving the huge boom in the analytics and data infrastructure space. For example, generative AI is a new AI technology that you don’t need to be a data scientist to use. That’s clearly a big deal – but how do you prepare and enable your staff? 

This should be where analysts come in, but the companies in our space, traditional research companies, are more like consulting businesses, people businesses. They focus on selling time with analysts. We also see strategy and execution research companies, but they won’t help you with the glue that connects strategy to engineering. 

Also, customers need to make decisions faster, be more agile, so they want to have information at their fingertips. If they have to wait to get on a call versus having information right there, it’s slowing them down. Whether an hour, a day, or a month. This was the starting point for our transformation at GigaOm. We asked, what percentage of conversations do you need versus consuming content? We realized we could build a better business model by putting that information into content versus hiring thousands of people to field those calls. That was the huge market opportunity we identified. 

On defining the product set, innovation and fail-fast, and MVP

We built to that market need based on digital products. At GigaOm, we start with a goal and then figure out – how do we get there quickly, with as few people as possible. With small groups working on a project, this is really about discovering innovation by testing and learning. You will likely fail at some things, and that’s great; you failed, let’s not do that again, but what did we learn from that? How can that help us find our next opportunity?

Some of the greatest opportunities we’ve come across, come from this approach. For example, we started building the Key Criteria/Radar product by figuring out what our customers wanted. After building it 4 times over a year with customers and trying to drive revenue, we repurposed it into two products; The Radar, which is a high-value product, and then the standalone Key Criteria report, which supports the Radar. 

The only way we were able to get to that product was because we tried a lot of things. Customers told us they didn’t like early versions. That gave us an opportunity to say, what would you like? That’s always the challenge – getting in front of the customer, collecting data, and then innovating on that. 

We’re constantly rethinking how we can build our organization to scale, and sometimes, we’re going to fail. But, we can leverage those experiences to understand how our business can run differently and operate in a more successful way. As a company trying to disrupt and do new things, you have to do things differently. We look at what the industry has done, and we look to do similar, but with a twist. 

This can be both product and organizationally-focused. We have a new type of community centered on technical expertise, which allows different parts of the ecosystem to come together and build the best products to support that ecosystem. So we asked them, what would you want to help you do your job? 

Based on that feedback, we built a product that filled a massive gap in the market. 

Then we looked at how to build an organization around that. Our practitioner analysts love being around other people like them, so how do we build this around technical leadership, bringing out the technical wisdom they can learn from each other? They all have their own experiences.

It all comes back to concepts such as fail-fast and MVP (Minimal Viable Product). When you have your MVP, you can then build a process and practice around it, which can take longer than finding your MVP. But you need the people and process to support it at scale. It took us 1 year to build the Key Criteria and Radar MVP, and 3 years to build to a scale of 120 reports.

On our community of practitioners, and the broader ecosystem 

We work with a really strong, experienced set of practitioners. To be a practitioner, to have that ‘technical wisdom’, you need a set of experiences as a CTO, a chief architect, or an engineer. Some of our analysts are in different parts of the ecosystem, whether they are channel, consulting, or a technology partner. 

As one of the leaders we have at GigaOm likes to say, “It’s different being in a car crash than watching a car crash”. In our business, you get a different picture deploying to cloud and watching it fail versus hearing it third-hand. It’s hard to take third-hand advice because they haven’t done it and can’t get into the details about how to be successful. They can’t tell you from experience what potholes to avoid and what challenges you’re going to have. 

Our experts go further and deeper to help customers try that next new thing, whether it is AI/ML, Observability, or AIOps, or Kubernetes, or Anti-Phishing, or XDR, or whatever comes after Edge. How do we stay in front of the market? We have people that have actually done it. If we haven’t, we find someone in the ecosystem who has. For example, Howard Holton has deployed RPA at Rheem Manufacturing, Ron Williams has deployed AIOps and Observability at American Airlines.

It’s not just technology, CIOs, engineers and architects, or CMOs and their marketing teams. It’s finance teams and investors. Just like with fail-fast, you learn a lot from your mistakes and also from other people who have had those mistakes. When you hear from these people, you’ll not just conceptualize, but internalize the lessons and take a successful action. We practice that a lot. How do we internalize the challenge or opportunity and come up with an action, versus a conceptual strategy that you have to figure out how to execute. 

There really is no substitute for experience. Our experts are actually consuming our reports to do their jobs, and with this model, they’re leveraging each other in a more scalable way. That’s been really important, that together we’re better. They all want to be a part of that, to build this next generation of research. 

The broader vision is around building a better industry. We have built a community around the different parts of the ecosystem by partnering with everyone. Everyone wants to forward that initiative – Distributors, VARs, customers, all want to work together to do better as an industry. If you can get them to collaborate with a common goal, that allows you to build something at a different scale. 

By using the channel and working with partners, that helps drive revenue. For example, we work with several media partners who use our content to make money. We work with VARs, who use our research to help customers learn about new technologies. Sometimes those customers might not buy our research the first time around, but the second or third time they do because it’s so different, focused on what actions to take to be successful.

On preparing for the future, for enterprises and GigaOm

Enterprise customers have wanted a product like ours for a long time, but their initiatives were held back, blocked by legal, political, budgets and other factors. COVID enabled digital projects to take off. Customers found they could be more proactive and use newer technologies to solve problems – where before, they might have been looking at keeping the lights on, a crisis like this allowed them to accelerate and think farther in advance.

In response, we also needed to look farther out. Our mantra is to provide the best research, so customers know what’s coming, so they can be proactive and make decisions they can implement with confidence, versus making a decision now and then having to figure out what to do when something new comes in. For example, we saw Observability and Kubernetes coming, and we’ve been following these ecosystems for years. We have visionary practitioners like Ron Williams (Ex Chief ITOps Architect), who have deployed these technologies at a global scale before the mainstream. 

AIOps is a hot topic too. Not many companies are doing it yet, but they want to. And there’s also a lot of change – we had to update our first report within six months after we published. It’s really hard to do from a business process and a technology perspective, but we have analysts who’ve actually done it. We have the hard-won expertise that can help customers move forward on their journey of maturity. Organizations will fail first, everyone does, but we can help them identify the potholes as we’ve been there already and can help them. 

As another good example: a lot of companies want to build a real-time data architecture to support the digital products they’re building, but don’t have the time or capacity to understand what’s going to happen in the next 2-3 years, let alone 3-5 years. We have products supporting those different elements of the market across near-, mid-, and long-term planning. So, when you’re deploying for the first time, you can know it will work with the next thing versus having to buy a bunch of technology and then rip and replace it. 

We produce hundreds of reports across these different categories, and how they interact. That’s the other challenge with technology. Look at cloud database and real-time streaming; how do they fit together, and how do you build a strategy? That’s really hard. That’s really what we’ve tried to focus on in our practices, how they knit together – you can see this in our GigaBrief on Cloud File Storage

Enterprises need to get stuff done, and we respond to that. But even now, we’re looking to the future, testing and learning, and driving our business models forward. If change is constant, we need to be constantly changing too. That’s how we’ll not only survive, but thrive in the new digital economy.