When 96% of the market isn't ready to buy
As I’ve been thinking about decision makers learning about B2B software from AI chatbots instead of web search, I keep coming back to the question: how much of an impact can you actually have (on leads, demos, sales, etc.) by trying to manage what the chatbots say? To try to answer this, I want to sketch out a model of the typical B2B SaaS buyer's journey. So that’s what I’m going to do this week, based on my own past experience as a B2B SaaS buyer.
In this post, I’ll explain the model, then in the next few posts I’ll explore the implications. But I think the model is useful whether or not you’re worried about AI.
The first thing we need to consider is that most of the people who might eventually want to buy your SaaS aren't actually looking right now. Fast paced startups might replace a major piece of their software infrastructure once every 18 months. For larger companies (a.k.a. the ones with real budgets) it’s much longer. But to make things simple, let’s say that your average prospect will be open to purchasing your software once every two years.
Of course, there are also really early startups that are starting from scratch rather than replacing an existing system. But they’re much harder to model, and more importantly they have even less budget, so let’s not worry about them now.
Within that two year timespan, there are basically four phases:
Phase 1: Both the decision maker and the team that uses the current software are generally happy with it. The decision maker will look for information about how to understand and solve their big looming problems, but they’re not looking for software. They may passively come across your software, or reach out out of curiosity. But even if they determine that your solution is 10x better than what they currently have, the best response you’ll get is “Too bad we can’t change.” (Yes, this really happens.)
Phase 2: The decision maker starts to notice the their current software isn’t meeting the company’s needs. Maybe it’s because something has changed - they’ve gotten bigger or gone on a new direction. Or maybe they’ve just finally gotten frustrated with problems that were always there. But it’s not enough for the decision maker to decide it’s time - they need to convince the rest of their stakeholders. So while they’re building up the political will to make a major change, they may start paying more attention to what software is out there, but officially they’re still not looking.
Phase 3: The organization finally decides to replace the software that you’re 10x better than. But if things are bad enough that they’re willing to suffer the pain of migrating a major system, then finding the replacement is going to be urgent. They may do a few Google searches or ask ChatGPT for suggestions, but they’ll want to get to a short list as fast as possible - let’s call it a month. So they’re going to lean heavily on any options that they remember from Phases 1 and 2.
Phase 4: Once they have a short list of options to evaluate, it either switches to a sales process where you’re communicating directly with the decision maker, or you’re not on the short list and you have to wait for your next chance in two years.
So this is the thing that makes B2B SaaS marketing so frustrating: The decision maker isn’t in the market for your software for 23 out of 24 months. (That’s 95.8% of the time, which I rounded up to 96% in the title.) Your window to make it onto the shortlist is that one remaining month. But your chances of making that short list are mostly determined by whether or not you got their attention during Phases 1 and 2, which make up most of the 23 months.
So, that’s my model for the customer journey. It has lots of interesting implications to unpack. But as I said at the beginning, that will have to wait for the next few posts.
Thanks for reading Viral Esoterica! If you want a free Report Card evaluating how AI chatbots answer questions about your B2B SaaS, click here.