Navigating the EdTech Landscape:
Turning Market Intelligence into Strategic Insight
For nearly a quarter of a century, Phil Hill, Founder & Publisher of Phil Hill & Associates LLC, has tracked the technologies, trends, and market shifts shaping higher education—often spotting what’s next before it reaches the mainstream. From the early days of learning management systems (LMS) to today’s AI-driven transformation, Hill has combined market analysis with consulting expertise to help institutions find academic value in technology change.
That grounding in data first drew him to the work of Justin Ménard, CEO and Founder of ListEdTech. “When I first came across Justin’s work, I was impressed by how the data wasn’t just a snapshot of the market, but also showed the history, allowed you to categorize institutions more effectively, and provided a perspective I hadn’t seen elsewhere,” says Hill. “We started doing joint work on LMS market reports and now have been working together for ten years.”
The unique perspective Ménard’s data provides grew out of his own experience navigating higher ed technology firsthand. After 25 years working in higher education, he saw a need for better, more reliable data to help institutions make informed decisions. “I started ListEdTech while the university was going through a student information system selection,” says Ménard. “Being a data geek, I went to EDUCAUSE, downloaded everything I could find, and started going through the information. I quickly realized the data didn’t always tell the full story. That’s what started me down the path of compiling, validating, and sharing better market data.”
Moving from Awareness to Action
The need for that deeper context has only grown as the EdTech market has matured. Today, institutions are not just evaluating what a particular technology solution can do, they are evaluating the stability and long-term direction of the companies behind it. Blackboard’s recent financial restructuring has been a reminder that vendor risk extends beyond product roadmaps and market share. “Six to nine months ago, the biggest concern would have been that institutions were overlooking program-level accountability,” says Hill. “Now that these changes have received more attention, the challenge is shifting from awareness to understanding what they mean strategically. The two major areas are student loan limits, which are tied to academic programs, and the requirement to look at the economic outcomes of graduates after completing those programs. Together, those changes have implications that go well beyond individual programs.
“Universities operate through significant cross-subsidies, so if one program loses access to federal loans or faces new challenges, it can affect the broader portfolio. What institutions need to recognize is that this is not just a program-level decision—it’s a strategic one. Presidents and cabinets need to be looking at their portfolio of programs now, using the data available today to understand what could happen and determine how to respond. Waiting until the official data arrives in 2028 will be too late.”
The same type of market intelligence that helps institutions evaluate vendors is also highly valued by investors looking to understand the future of edtech companies. When private equity firms and other investors seek outside perspectives, they are often looking for data that can validate assumptions, challenge projections, and reveal trends that may not be immediately visible. “Investors are often looking for insights that are very specific to the company they’re evaluating,” explains Hill. “They’re usually coming in with a thesis and a model they’ve built internally, and they’re trying to test those assumptions.
“For example, in a turnaround situation, they may want to understand how quickly a company is losing customers year over year, what the attrition rate looks like, and whether the turnaround has enough time to work before the company faces additional financial pressure. They’re using the data to validate what they’re being told and determine whether there’s evidence behind the story. It’s not a general market question, but about understanding a very specific situation and determining whether the data supports their investment decision.”
Ménard sees a similar pattern. “Oftentimes they’re trying to understand the history and want to know how the market got here, what patterns have existed over time, and whether what they’re seeing is consistent with what has happened before. A snapshot can tell you where you are today, but it doesn’t tell you how you got there. The value of the data is being able to put today’s situation into context.”
“Oftentimes they’re trying to understand the history and want to know how the market got here, what patterns have existed over time, and whether what they’re seeing is consistent with what has happened before. A snapshot can tell you where you are today, but it doesn’t tell you how you got there. The value of the data is being able to put today’s situation into context.”
– Justin Menard
CEO & Founder
ListEdTech
Understanding the EdTech Landscape
The combination of Ménard’s data-driven view of market movement and Hill’s ability to interpret the forces behind those shifts provides a more complete picture of the EdTech landscape. “Justin’s adoption data is extremely valuable because it shows history and trends, which allows you to make projections. But adoption data always has a time lag. By the time a school implements a new technology solution, the decision was often made a year or more earlier. That’s not a divergence, it’s simply the nature of the data. You also need to consider sentiment: what institutions are discussing, what faculty are asking about, and how people are responding to changes like AI. That context adds another layer of insight alongside the adoption data.”
While Hill may focus on the broader strategic implications and potential risks, Ménard’s analysis can reveal another side of the story. “I’m clearly an optimist,” says Ménard. “Phil might look at how much a product is trending down or how much market share a vendor is losing, while I’ll explore how many institutions have moved to the new version of the product and think, ‘Wow, this is a massive shift.’ For example, with Blackboard, I was looking at how many institutions were moving from Learn to Ultra and seeing that they were confirming they were staying with the platform. It’s the same data; we’re just looking at it from different points of view. That’s what makes the conversation valuable.
“With the growth of online program management (OPM), everybody was talking about it—you couldn’t open a publication without seeing something about it, and the perception was that every university was moving in that direction. But when I looked at the data, what stood out was that, while OPM was a significant trend, it represented only a subset of institutions. It was influencing the conversation far more broadly than the actual adoption numbers suggested.”
Applying an Institutional Lens
As institutions evaluate technology partners, market rankings and industry quadrants can be a helpful starting point, but they should not replace deeper analysis. “Quadrants are a great tool because they simplify a complicated market,” explains Ménard. “If you’re looking at a market with 100 vendors, they help you understand who the major players are. The part I struggle with is when marketing gets involved—when you start looking closer, you sometimes find things that don’t quite add up. The bigger question is: How are those placements determined? What are the criteria, and how are they measured? Many times, there isn’t a clear formula. It may be based on interviews with a handful of institutions, sometimes selected by the vendors themselves, which creates another layer of filtering. That doesn’t mean companies are doing anything wrong, but it’s important to understand how objective the picture really is.
“When we created our own view of the market, we wanted it to be as transparent as possible. The data is based on factors like the number of institutions using a product and the number of new implementations over a specific period of time. Institutions can then apply filters based on their own characteristics because every vendor has a different target audience. The goal is to help institutions understand the market through their own lens and see which solutions their peers are choosing.”
The rise of artificial intelligence is also adding another layer of complexity to technology decisions. Rather than evaluating AI tools as standalone products, many institutions are beginning to see them as part of broader technology ecosystems, often tied to the major platforms already embedded across campus. “That’s a hard thing for us to track because AI is often part of a much bigger decision,” explains Ménard. “When an institution is evaluating a product, AI is one of the features they’re looking at, but it’s not always the reason they’re making the decision. We see institutions feeling pressure to move forward with AI but lacking the resources or funding to build everything themselves, so they’re looking to the larger companies and tools they already use to bring those capabilities in.
“The larger vendors aren’t necessarily trying to connect every system across campus, they’re focusing on targeted applications that can help review work, provide recommendations, or support a specific workflow where users decide whether to accept those suggestions. You can see what vendors believe the future looks like based on the tools they’re building: Are they focused on transforming everything with AI, or on helping learners, faculty, and administrators do specific things better? AI has become a window into a company’s long-term strategy: where they’re investing, what problems they’re trying to solve, and how they see their products evolving.”
“Justin’s adoption data is extremely valuable because it shows history and trends, which allows you to make projections. But adoption data always has a time lag. By the time a school implements a new technology solution, the decision was often made a year or more earlier. That’s not a divergence, it’s simply the nature of the data. You also need to consider sentiment: what institutions are discussing, what faculty are asking about, and how people are responding to changes like AI. That context adds another layer of insight alongside the adoption data.”
– Phil Hill
Founder & Publisher
Phil Hill & Associates, LLC
Grounding Decisions in Market Data
Whether the customer is a college, technology vendor, or private equity firm, Ménard’s goal is to reduce uncertainty by grounding decisions in reliable market data. “When someone asks for a broad data set, I immediately wonder what’s driving the request. If they want all the LMS data, I’m thinking, ‘There are probably a handful of companies they’re evaluating, which one is it?’ Ultimately, they’re trying to understand where the market is headed, who’s gaining or losing market share, and whether those trends will continue. You can have a theory, but when you support it with data, you have much more confidence in your decisions.”
“Private equity now owns much of the edtech market,” adds Hill. “Many universities still think about venture capital and startups, but much of the market—even for relatively small companies—is driven by private equity dynamics. Ten or fifteen years ago, venture capital was focused on vision and growth potential. Today, private equity is asking different questions: Can a company become profitable? Is there room to grow contract value? Is the business model sustainable? Around 2021, there was an enormous amount of interest in edtech because capital was plentiful. When interest rates increased, that changed almost overnight. Companies that had been counting on another funding round or an acquisition suddenly faced a very different environment.”
While investors use data to reduce uncertainty around acquisitions and market opportunities, institutions respond differently. “Institutions do not react that quickly to policy, they react to periods of change,” says Ménard. “When that happens, technology decisions tend to slow down. Institutions pause, ask more questions, and look for signals before moving forward. We can show what similar colleges are evaluating, what their technology stacks look like, and where they’re headed. When a school announces a new technology, they often reference other institutions that have made the same decision. They don’t want to feel like they’re making that decision alone.”
Creating a Foundation for Strategic Decisions
Market data and policy analysis each provide valuable insights, but together they give institutions a more objective foundation for making strategic decisions. “Ten years ago, decision-making was often driven by marketing claims,” says Hill. “Schools would talk to peer institutions, but were still reacting to what vendors were telling them. Justin’s data and policy analysis give institutions something objective to anchor those conversations. Instead of starting with a marketing claim, you can start with the data, the policy implications, and other measurable criteria. Ultimately, it empowers institutions to take a more active role in their own decision-making.”
“When we first started working together, I had all this data and was confident in what I was seeing,” adds Ménard. “Phil would look at the same trends and explain what was driving them from a completely different perspective. For example, when we saw Campus Management’s SIS market share decline by 5% or 10%, I wondered why they were losing so much ground. Then someone asked, ‘Did you look at school closures?’ I went back to the Integrated Postsecondary Education Data System (IPEDS) data and found that many of those institutions had simply closed. They weren’t switching products; they were no longer operating. Phil brings that extra layer of context that explains what’s really happening. The data tells you what happened, but understanding why it happened makes all the difference.”
Combining Insight with Market Intelligence
The strongest technology decisions come from combining strategic insight with market intelligence to better understand not only what solutions are available, but how they perform in real-world institutional environments. “Our role is to provide the evidence,” says Ménard. “We can show the technology stack, and if you change one product, we can show that there are very few institutions using that combination of systems. That doesn’t mean it’s a bad product; it just provides another data point to consider. We focus on the evidence, and Phil brings the context around that decision, including the strategy, the market dynamics, and the different perspectives that influence the outcome. He sees the story behind the data.”
“If an institution only works with us for advice on a vendor selection, but they’re not looking at implementation data and market trends, they’re missing a lot of the nuance that Justin’s data provides,” adds Hill. “A decision isn’t just about whether one system looks like the right fit, but also understanding how that system fits into the larger landscape. It’s important to ask questions like: What other institutions like yours are using this product? Are they using it alongside other systems you already have or are considering? Are there examples of these systems working together, or are you going to be the first one trying to make that connection? A holistic approach allows you to see those additional layers and make a more informed decision—one that considers not just the technology itself, but how it supports your institution’s goals, integrates with existing systems, and helps position you for what comes next.”