Enterprising Insights, Episode 16: Mid-Market SaaS Applications

Enterprising Insights, Episode 16: Mid-Market SaaS Applications

In this episode of Enterprising Insights, The Futurum Group’s Enterprise Applications Research Director Keith Kirkpatrick discusses the opportunities for SaaS vendors in the mid-market space, delving into key market trends, differences between the enterprise, SMB, and mid-market, and opportunities for vendors seeking to participate in this market. Then, Kirkpatrick will close the show with the Rant or Rave segment.

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Listen to the audio below:

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Keith Kirkpatrick: Hello, everybody. I’m Keith Kirkpatrick, Research Director with The Futurum Group and I’d like to welcome you to Enterprising Insights. It’s our weekly podcast that explores the latest developments in the enterprise software market and the technologies that underpin these platforms, applications, and tools. This week, I’d like to delve into the mid-market SaaS platform market and discuss some of the key market trends, differences between the enterprise, SMB, and mid-market, and the opportunities for vendors seeking to participate in this market. Then as always, I’ll close out the show with the Rant or Rave segment where I’ll pick one item in the enterprise software market and either champion it or criticize it. So, let’s get right into it.

What we’re going to talk about today is the mid-market. Really, what we’re getting at here is obviously, if you think about the potential market for software, you have the very small SMB market. That would be everything from your one-person shop all the way up to about 50 or 100 seats. That is certainly a market that some vendors have done very well with, typically smaller vendors because they’re going to provide some software with some pretty basic functionality at a relatively affordable price. There, the business play is of course, trying to get as many companies as possible to sign up for the product, which of course is going to have certain good features that may not be as powerful or full-functioned as enterprise software. The name of the game is obviously, to try to convince these small companies that they need to have the same sort of functionality, or if not the same functionality, something that approximates it compared with a larger enterprise software package.

Then of course, you have the enterprise software packages out there. Those are quite large, usually full-featured, tends to be more expensive, but of course they tend to get some of the newest innovations a little bit more quickly. They’ll also get more handholding, perhaps more specialized integration services, some additional consulting services and so forth. Obviously, the idea is to try to go out and land as many large logos as possible. Now of course, that comes at, obviously at a cost. It is more expensive to sell to, and service these types of customers, which tend to be the more demanding. So, what we’re going to talk about today is the mid-market. Really, if you think about the evolution in the market, it used to be that you had to design software that was very, very focused on a particular segment in terms of it being deployed on a certain infrastructure. But really, the emergence of the cloud has really changed all of that. It’s allowed software to be delivered much more cheaply, much more efficiently, both in terms of delivery and the marketing.

As a result, what we have seen are the emergence of companies that are really targeting mid-market companies to really fuel their business. Companies like HubSpot, Zendesk, Zoho, the list really goes on and on, and there are obviously a lot of other companies I’m leaving out, but those are just a few representative names. The idea is that they’re going after, sort of an underserved market, one that where entry-level SMB software is really too small for them, or doesn’t have enough features, isn’t powerful enough, maybe there’s not enough support there, but an enterprise offering might be too much, both in terms of cost, or perhaps the feature set is so overwhelming that they realize they’ll never use it. So when we think about the mid-market, it’s really, the beauty of it is that it, kind of combines the best of both worlds. As we start to really see the use of artificial intelligence come into the market, that’s a new catalyst there that really will, I think, transform how these organizations, these mid-market organizations as well as the vendors that service them, how they interact with each other.

Okay, so why would a vendor want to target the mid-market? Well, there’s a few different reasons there. First of all, the mid-market really combines the best of both enterprise and SMB. So if you think about it, the mid-market actually, generally has shorter sales cycles. Why is that? Well, there are generally, fewer stakeholders. There are fewer hoops to jump through and of course, sometimes the needs are a little bit more pressing than they are at the enterprise level because they are taking on a shorter planning cycle. There’s usually lower customer acquisition costs because you’re not having to woo as many folks over such a long period of time. The other thing is that if you think about an enterprise customer, let’s say you go out and acquire a very large enterprise customer. If, after the contract period is up they decide not to renew, or they decide to defect to another vendor, that’s a pretty large hole to fill.

That can really negatively impact the financial health of a vendor by just solely relying on one or two large enterprise customers. For a vendor that is, kind of starting out or has been, kind of chugging along in the market, the mid-market tends to be, A, a little bit more stable. And if you lose one particular customer, it’s usually not the end of the world because the average contract value would not be the same as a large enterprise customer. Speaking of that, mid-market companies, generally are a little bit more stable than say very large enterprise customers in terms of growth, as well as SMBs. So in a sense, their revenue might be a little more predictable, and as a result it is easier to target them with an offering because they have a general idea of where they’re willing to be in a year, in terms of growth if we’re talking about things like seat licenses, that sort of thing. So, it’s a good target there because of the predictability.

Now, the other reason why it’s really an attractive market is that a lot of vendors tend to focus in on either SMBs because it’s a volume play, or they’re tempted by the large enterprise segment. If you think about the market buying trends, if you look at SMBs, they tend to just focus on narrow, or point solutions, although that is starting to change a little bit, and you have enterprises that are going to be looking at large, big, dedicated, broad platform solutions to meet the varied needs of their different stakeholders. Now, mid-sized businesses as a result, usually are left choosing between a large enterprise solution, or kind of combining a bunch of smaller point solutions.

So, there’s a real opportunity for mid-market vendors to really focus in on those needs of companies that are, sort of too big for SMB-type software and a little too small for enterprise. Now, I had mentioned before that if you think about what’s going on in the market, you have AI, and particularly generative AI. This is going to become a really interesting catalyst in the market simply because you’re going to have much more functionality available at a relatively lower cost. If you would think about having to go out and build in some of the capabilities that generative AI can now provide fairly easily, these solutions, particularly those at the SMB and mid-market level, you would never be able to do that and recoup your cost. Generative AI is changing that pretty significantly.

The other thing that, I believe is going to be really interesting is, as the market starts to mature and evolve, we are going to start seeing again, as I mentioned in previous podcasts, the shift to more usage-based pricing. How is that going to impact the mid-market? Well, for one thing, as I mentioned before, mid-market businesses tend to be a little more predictable in terms of how they go about doing their business. They may not be growing as quickly as a small business. They may not have the scale in terms of number of users using a particular feature set. So as a result, they’ll have a very, very clear idea, or be able to forecast exactly how much usage of generative AI that they’ll need in any given period. As a result, they’ll be able to quickly tie their actual cost to the benefits that they’re getting. So I think generative AI, in particular can be a real game changer for that market.

Another thing of course, is that if you think about the mid-market and the way that they look at software, they just want it to work without a lot of hassle in terms of integration, they don’t want to have to have a lot of customization, and they want to make it so their workers can quickly get value out of the software. Generative AI is going to go a long way to helping that. Instead of having to worry about training people on how to use a full new platform, a lot of the functionalities will eventually work their way into a very basic, sort of natural language-based chat interface.

So, instead of having to figure out how these menus work or which boxes to select, by using generative AI you’ll be able to very easily create almost a non-interface through generative AI. It will also allow them to quickly connect with other software, other applications out there as long as there are APIs being built to pull in data or features from other platforms out there. So, I think it’s going to have a massive impact particularly in this mid-market segment, where they’re looking for that, sort of enterprise-level functionality, but they don’t, or they’re not able to necessarily manage the cost of doing that.

Now, I think one of the other things that it’s important to understand, it’s again, the most important thing for these buyers tend to be about simplicity and friendliness to these users because they just don’t have the technical support resources out there that the enterprises do. They may have a little bit more than SMBs, but ultimately they’re not going to be looking to implement a solution that’s going to take many, many, many quarters to implement because ultimately, they may not have that need for that level of complexity. So, that’s where there’s a real opportunity for vendors to really offer a solution that touches that enterprise level of functionality in the things that matter to these businesses, while perhaps not offering as many features, but doing that in a way where it is right-sized for these smaller or these medium-sized businesses.

The other thing is that some of these mid-market companies may actually be willing to, I don’t want to say overpay, but perhaps pay fair value for some of these features as long as they’re ready, out of the box because again, they’re not looking to necessarily have things that are going to take a lot of time to customize. They may be happy with things that are able to deliver value very quickly. I think that’s where it’s important to make sure that in engaging with these customers, that they have a firm idea on the level of customization that they’re going to be seeking because if it starts to creep up further and further, that’s where the actual implementation costs may start to run up and they wind up, essentially competing against enterprise-grade software.

Now, I think perhaps the most important thing to remember here is that if we look at the enterprise market or look at the SMB market, there’s a pretty clear line. You understand that an SMB is going to be way smaller than an enterprise and vice versa. The mid-market is, sort of straddling that middle ground, and I think the segment will continue to evolve. Certainly, like every other class of buyer, they are going to be looking for more functionality over time driven by the advances in generative AI. But ultimately, the most important thing, of course is making sure that functionality is delivered in a very easy, seamless way without a lot of implementation hurdles, without a lot of complexity with pricing, because ultimately that’s really where you’re starting to get up to that enterprise level in terms of an offering, and you wind up competing against the very large enterprise vendors.

So I think the key takeaway here is, for the vendors that are doing this, that are approaching this market, I think there’s a real opportunity right now because of the fact that enterprise solutions, everyone is talking about implementing the latest and greatest feature sets, particularly around generative AI, and automation, and that sort of thing. That’s great, but I think there’s a real opportunity to target these companies that may not have as rigid in terms of requirements or in terms of functionality. They may not be looking for everything in the kitchen sink, but they’re looking beyond just, kind of cobbling together point solutions, like sometimes happens at the SMB segment. So, just food for thought as the market rolls on here in 2024 and we continue to see the implementation of generative AI and how that really impacts the market moving forward.

So now, as always, I wanted to talk a little bit about … I’d like to move to the Rant and Rave section. Today, I actually have … Again, it’s sort of a bit of a rant, but it turns into a rave. So, last week we talked a bit about Google’s Gemini’s issue in terms of the text to image generator not returning historically correct images as a result of prompts that went in. We’ve recently learned this past week that there was a machine learning engineer over at Microsoft, who basically said that he had let his bosses know that there was some serious safety concerns around Microsoft Copilot’s text to image tool. He basically, said that he went to Microsoft, and raised issues and said, “This stuff shouldn’t be out there in the market.” Microsoft, I believe talked to OpenAI, and this engineer said that nothing was done.

So, the engineer then wrote a letter to the FTC, and of course this went public last week. It was picked up by all of the major news organizations. Really, a couple of other things that he mentioned, really were around users being able to type, or he would be able to type in prompts like pro-choice and it would return, as what I think he termed was insensitive or outright alarming imagery. The rant part is that when this initially came out, Microsoft really didn’t say anything about it, which is really in contrast to what Google did. As soon as these issues came up, Google immediately shut down Gemini and said, “We’re going to focus on this. We’re going to fix this.” However, by Friday, Microsoft had come out and said that basically, the Copilot service wound up blocking these image generation requests for sensitive topics like pro-life, pro-choice, teen assassins with rifles, things like that. I think now Copilot will actually say, “I’m sorry, I can’t generate an image because it’s against my principles, or Microsoft policies,” or something like that.

So, this is where they think they might have been a little bit slow to address this problem. They’ve done the right thing and now they’ve essentially, decided to tackle this head-on and say, “Look, we realize that this is not what we want the tool to be doing,” and they’ve put in these guardrails to prevent some of this controversial stuff from coming up. Like with Google, I think Microsoft, and really a lot of these other folks out there that are making their tools available, there are going to be some hard lessons out there in terms of whether it’s red teamers putting stuff out there, or just random people trying to essentially, trick the chatbot into generating imagery that could be considered offensive or super controversial. That stuff’s going to continue to happen. This is not easy work, particularly if we’re talking about operating in a society where quite honestly, sometimes there are different definitions on what constitutes acceptable versus not acceptable responses.

I think Microsoft, they obviously have invested and continue to invest a ton of money into this. It is a tool that organizations, particularly large enterprises are utilizing with good results. Obviously, there’s a lot of really great enterprise value in Copilot, and I just think it’s a question of growing pains. The industry itself, we sometimes forget the generative AI, at least in terms of the general public’s consciousness, it’s not that old in terms of usage. Really, if you think back even a year, a little over a year ago, let’s just say to January of 2023, a few people had heard of generative AI outside of the teams working on it. So, I think that ultimately, I’m pleased to see that when there are issues that come up, whether we’re talking Microsoft or whether we’re talking Google, it does seem that they are doing the right thing, and are responding, and are working hard to address some of these issues with respect to controversial content.

Again, it is going to be, sort of a … I don’t think it’s going to be a one and done thing. The key is really, continuous testing. It’s making sure that the teams that are involved with overseeing the guardrails that, they are made up of diverse viewpoints and voices to make sure that, that actually just have one worldview being judge, jury, and executioner with this stuff. Of course, making sure that there’s ongoing monitoring, because you can have stuff like model drift and all of that stuff over time. So long story short, I think we are … Hopefully, the industry as a whole will be learning from these snafus, and we’ll have to see how things play out over time.

Well, that’s all the time I have today, so I want to thank everyone for joining me here on Enterprising Insights again. I’ll be back again next week with another episode focused on the happenings within the enterprise application market. Thanks again, for tuning in and be sure to subscribe, rate, and review this podcast on your preferred platform. Thanks, and we’ll see you next time.

Author Information

Keith has over 25 years of experience in research, marketing, and consulting-based fields.

He has authored in-depth reports and market forecast studies covering artificial intelligence, biometrics, data analytics, robotics, high performance computing, and quantum computing, with a specific focus on the use of these technologies within large enterprise organizations and SMBs. He has also established strong working relationships with the international technology vendor community and is a frequent speaker at industry conferences and events.

In his career as a financial and technology journalist he has written for national and trade publications, including BusinessWeek,, Investment Dealers’ Digest, The Red Herring, The Communications of the ACM, and Mobile Computing & Communications, among others.

He is a member of the Association of Independent Information Professionals (AIIP).

Keith holds dual Bachelor of Arts degrees in Magazine Journalism and Sociology from Syracuse University.


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