Welcome to a brand-new EdTech Mentor interview featuring Justin Menard, the CEO and founder of ListEdTech! In this insightful discussion, Justin shares the secrets behind ListEdTech's success, including their unique growth strategy and the crucial role of team dynamics. Dive into the fascinating world of EdTech with Justin as he reveals the intricacies of predicting institutional behavior and the key factors driving product selection, particularly in the Student Information System (SIS) category. Discover how ListEdTech's innovative approach to marketing and sales, focusing on referrals and a dynamic newsletter, has propelled their growth in the competitive EdTech market. Don't miss this exclusive interview—your gateway to the latest trends and strategies in educational technology!
I'm Justin Menard. I'm from Ottawa, Ontario, Canada. I’m married, I have two grown kids, and I love traveling and reading—maybe a bit too much. Those are the two big passions I have.
Maybe the best description is curiosity. I studied for seven years full-time to earn a bachelor's degree because I had no clue what to do with my life. I love studying and learning, so I just kept going. At one point, the university got tired of just seeing me there, so they offered me a job, probably because it was cheaper for them. I've been working in EdTech ever since. I went from managing websites to managing an IT team for a faculty to head of IT for the registrar's office. It was a progression fueled by curiosity and a desire to learn.
That started right from this work. About 12 years ago, we were looking to change our student information system at the university, one of the systems I was managing. I went to EDUCAUSE , a great association that conducts an annual survey. I looked into it to understand the market and figure out which systems to consider. However, I found that some of the information was outdated and not comprehensive. Even though around 600 people filled out the survey, the data wasn’t always accurate. For example, at our university, the information was wrong because the CIO's assistant filled out the survey without full knowledge. This made me realize there might be a better way to gather this information. I started compiling data manually from university sites to find out which student information systems they were using. Despite being a horrible writer, I began posting blog entries about my findings. Eventually, I had so much information that companies and institutions started reaching out to me, asking if I could share what I had. That was the start of the company.
At the core, we track what software universities, colleges, and school districts use. Based on this data, we help answer multiple questions for both companies and institutions. For companies, we identify trends and potential clients based on tech stacks. If a specific product is being used by a group of institutions, we can identify other potential clients. For institutions, we provide insights into what their peers are doing and selecting. If an institution is looking for a new CRM, we can suggest products that fit their current tech stack based on peer usage. We don't recommend one product over another; we simply provide data showing what similar institutions are using. These are the two main value propositions.
The way we find information is by gathering anything that's public. That's the first step. We scrape university sites, company sites, RFPs, contracts—anything public. There's a lot of information out there from board approvals, senates, and students on social media who say, "I hate this specific product." We have a bunch of scrapers that go out every day, grabbing information—about 25,000 alerts per day.
We use machine learning to filter out a lot of wrong information. Then, a team of 16 employees manually go through the info and update our database. It's not because students say they hate a specific product that we add it to our database. It's just a clue. Sometimes, it hints that a product might be in use, so we dig into the specific institution. For instance, we might find an FAQ or an easy example like ‘universityofottawa.blackboard.com’. Once we confirm it’s working, that's the ultimate find. We're able to cover almost 80% of the market once we figure out how to do it. We ramp up quickly to 60%, but the next 20% requires more effort. However, we cover a vast amount of the market.
We started with North America, which includes the US and Canada, simply because I understand it better. Then we expanded. Depending on the products, in North America, we cover all higher ed and K-12 school districts. In North America, we cover about 7,000 higher ed institutions and nearly 40,000 K-12 school districts. Next, we moved to Oceania, including Australia and New Zealand, followed by Europe and the Middle East. Then, we continued with South America, Africa, and Asia. The coverage can be spotty in some areas. For example, in Africa, we have very good data for South Africa and Maghreb, but less data for Central Africa. Overall, we try to get information on around 25,000 higher ed institutions worldwide.
It's a learning curve. We're always amazed at what companies do with the data, and we're starting to learn how institutions use it too. When I first started, I was excited about creating dashboards in Tableau, thinking they were the best thing ever. But companies come back with questions I've never thought of, digging into very specific details. You quickly learn that these companies know the data inside out. They don’t see our dashboards and think, "Wow, I didn't know that." Often, they know the trends because they talk to their clients. They know some products are being switched from product A to product B, and they come to us to confirm it. We analyze the data and show it to them, and they often say, "I knew it." This confirms what they already suspected.
The more companies we get, the better the data becomes. At the beginning, we had a lot of data. I remember one company coming to us and asking different questions. I sent them the entire data set we had because we just wanted to confirm that the data was good. Working with these partners, they confirm the data and often ask, "But have you considered this?" or "Are you sure this product is actually an LMS?" We then have these great discussions, realizing that maybe it's not an LMS but a subcategory. They always help us refine our data, and these ongoing conversations are invaluable.
Sometimes, you do need to push back or draw a line. A good example is CRMs. You can basically do anything with a CRM—define it as a retention tool, a communication tool, an email tool, an SIS. It can cover many categories. We focus on classifying it in one product category based on its main goal. Even though we sometimes get pushback, once we explain the logic behind it, companies understand. They appreciate that one product is in one category, not 15.
If you're out there, we usually have you in our database. If we don't, we get excited because there's something new. Very often, these companies are already in our database but aren't the top clients we often show. They might appear in other products because we have to group the fine end. There's no fee or anything like that. If you're a new product and we follow that group, we really want to include you.
Even though reaching institutions was the actual goal of the company when we started, I remember saying, "We're going to help institutions with all this data. It's what I know." Of course, like any good small company, you follow where the money comes in. Companies started knocking on our door, so we pivoted and started working with them. But we always wanted to do the institution part. A few years ago, we opened up the portal to institutions to get feedback and see how they would use it. At one point, it went totally free to encourage more people to use it and help us build out the portal.
We officially launched the institution portal last fall. We got a few clients, and right away, we had these conversations. Institutions were using our portal, and we were trying to figure out why they kept looking at specific graphs. After talking with them, we built out features based on their needs. For example, Carleton University (from Ottawa, Canada) pointed out that institutions often look for RFPs (Requests for Proposals) to see which selection criteria their peers are considering. We had around 2,000 RFPs just sitting there, so we built a feature allowing institutions to search and download RFPs quickly.
Similarly, a company asked if we had pricing information. Initially, I said no, but then I realized we had 15,000 contracts. We started drilling into this data and built a view showing the average price paid for systems per student. Conversations with clients often reveal these simple yet valuable insights.
It's evolving rapidly. One thing that helps us is that we only include products in our database that have an educational client, which automatically removes a lot of products. For example, if you search for CRMs on Google, you'll find tons of information, but many of those CRMs aren't used in the educational sector, so we don't include them.
We track many edtech startups, often using sources like EDUCAUSE , which showcases 50 promising startups each year. We go through these lists, add relevant startups to our database, and then check if any educational institutions are using their products. If they aren't being used, they get dismissed from our database.
While it's a constant struggle to stay on top of things, our selection criteria help us manage the influx of new products.
I sought help from people with great knowledge to back me up. We were able to hire James Wiley, who joined us last year. He has over 25 years of experience in EdTech consulting and was a consultant at another great company. Bringing him on board opened up many possibilities. When clients or institutions have questions, especially about things like CRMs or the roadmaps of different companies, he can dig in with his wealth of experience. He won't tell you to select one product over another, but will provide insights based on what he's heard from clients and his extensive knowledge. For example, with AI, which is a hot topic right now, James understands how AI is integrated into current products much better than I do.
A few months after I started to amass information on system implementations, I took a year off to travel with my wife and kids. Despite being away, I continued posting and getting feedback. When I returned, I met with Simon Tokai, also co-founder of ListEdTech, and realized there was potential. This wasn't my first company, and from previous experiences, I knew we needed manual work alongside automation. We found a team in Asia to help us with the data.
Our first step was proving the concept: would anyone pay for this data? We put a PayPal button on our website for $250, offering all the info we had. Initially, we got a few people asking questions and paying for the data. Two big aha moments happened: first, Campus Management (now Anthology) asked for all our CRM data, which we negotiated for $2,000. Second, Phil Hill, who was at a UK conference, asked for LMS data and said we weren't charging enough after paying the $250. Phil has been a great partner, validating much information for us.
We bootstrapped everything from the beginning. I worked full-time at the University of Ottawa until last year. Now, I'm fully invested in the company, as is my wife, who has been working with us for about five years. We've grown steadily without investors, relying on our hard work and some luck.
Everything related to institutions is brand new and growing faster than anticipated, which presents some challenges but is very exciting. We've been working on predictions for two to three years. Initially, we published predictions for LMS selections on our website, achieving between 60-85% accuracy. Though it was surprising, it confirmed we were on the right track.
We've now shifted to using regressions based on tech stacks. We can now predict the top 5 products that similar institutions are selecting or using. This approach works well and is something both institutions and companies find valuable.
Companies have pushed us to go in this direction, and while we initially doubted our capabilities, the data has shown promise. While predictions will never be perfect, they can help identify potential clients based on factors like enrollment size, location, and tech stack. Understanding the ecosystems of major products like SIS and LMS also helps, as these products often come with affiliated partners. This approach helps us identify the perfect client profiles and their likely technology needs.
Yes, there is a certain sweet spot or timeframe where institutions might start considering a change, but it's only one variable. Contracts, especially for big ERPs or SISs, are usually negotiated for five or ten years. When a system changes, institutions don't switch after just a few years. Contract duration plays a big role, and they often change; for example, a 10-year contract might include an option for an additional five years. There are always details like this in the contracts. Additionally, if institutions start switching other systems in their tech stack, it can indicate that they might be considering a new ERP or another system.
I've always been interested in the SIS because it was my focus at the University of Ottawa. Even though trends in SIS systems are fairly flat, with institutions not changing them every year due to long-term commitments, there's a lot of movement within the category. Many systems are transitioning to the cloud, and new cloud-based players are entering the market. This puts pressure on institutions to modernize their systems, as many see the cloud as the way forward for reasons like security and reallocating staff. While the overall trends may not change much, there's a lot happening beneath the surface. Previously, big companies would bundle additional products with their SIS, like a portal, to entice buyers. Now, these additional products have evolved into standalone offerings, creating choices for institutions. AI is also a significant pressure point for these systems. Initially, many companies considered building their own LLMs, but most realized this was too ambitious and opted to partner with major companies like Google and Microsoft instead. It's interesting to see how even big systems like SISs are constantly under pressure to evolve.
I think the challenge with SISs is that many existing systems have been around for a long time. While this proves their reliability and effectiveness, they are often built on very old code bases, some dating back 20 or 30 years. So, when a new player like Workday enters the market, for example, they face a long process of development and refinement. Oracle is also building a new system, but this isn't something that can be done in just a couple of years. It takes time to build up the system, have clients try it out, and address any pain points. It might take a decade or more to fully develop and refine a new system. So, when you hear announcements about a new SIS being ready in two years, it's important to consider the complexity of the process. Despite this, many companies are introducing new SISs, and there's also a trend of some universities moving away from these big products and building their own, especially transitioning from proprietary systems to homegrown ones. This is an interesting shift in the market.
A lot of it is about fit, I think. You have to get along with people. You don't necessarily need to always share the same vision because I really appreciate people with different perspectives. We take a lot of time to discuss things. For example, someone might think we should go in one direction, while another team member might suggest another. We debate these ideas, and I enjoy that. But having a fit, having similar views on different things, is very important. One thing to note is many team members speak French, so our passion often comes out when discussing visions or ideas. We might start speaking French and get really animated, which might be a factor in how we connect with others.
Marketing and sales aren't our strong suits, and we don't really have a formal strategy. We do have a newsletter, which is a way for us to communicate what we do. People often reach out to us to discuss what we've shared in our newsletter. We intentionally create blog posts to share new data or discoveries and invite feedback. Companies sometimes reach out to correct or discuss our findings, which I appreciate. Referrals have played a big role for us. Even though EdTech companies are competitors, they also want good data. They refer us to others, and it's amazing to see how this has contributed to our growth.
Over the years, we've adjusted the frequency and content of our newsletter. We'll continue with our regular newsletter every two weeks, but every other week, we'll include news from university IT departments. We scrape university sites for this information, and it includes news like the launch of a new LMS or warnings about phishing scams. Institutions have expressed interest in knowing what others are doing, so this will be a valuable addition to our newsletter to help institutions stay informed about what their peers are up to.
