If you’ve read any of my writing, it won’t surprise you that I’ve been questioning just about every aspect of traditional B2B marketing in recent months (and not just because I like to be contrarian). It’s an interesting time to be a marketer, as just about every best practice or tactic of yore has been pronounced “dead.” While I’m not one for hyperbole, I do agree that we’re at a point of meaningful change – and opportunity. Today’s musings touch on the marketing qualified lead, signal-based marketing, and why defining your ICP with rigor and specificity is more important than ever.

I was recently chatting with some B2B marketers, and the topic of marketing qualified leads came up. Specifically, how to define an MQL, how to ensure alignment between marketing and sales, and how to operationalize the scoring and outreach workflows. It’s a good time to rethink definitions and processes that once seemed obvious, especially as many of us rebuild with the help of AI tooling.  

While drafting my contribution to the conversation, I had this thought that marketing qualified might… not mean anything anymore? Or perhaps the issue is that it means something different to everyone, rendering the concept entirely useless. I don’t think the solution is to standardize it, because this misalignment is a symptom of something larger: the concept of marketing qualified was built for a world that no longer exists. A world where marketing’s job is to manufacture readiness. 

The original intent of the marketing-qualified definition was to identify prospects who were ready to be sold to. It was a solution for something that couldn’t easily be observed – it’s impossible to know that someone is fed up with their existing provider or that they got a new budget line item approved, both signs that they may be “ready” to buy your product. So, instead, we created proxies and assigned points to behaviors that correlated with readiness: downloading a report, attending a webinar, or opening an email.  

This entire framework assumes readiness is something marketing manufactures. (Side note: I think a lot about the term demand gen. Is demand something that marketing should need to generate? Shouldn’t demand exist for a product to be built in the first place?! Anyway, I digress.) 

This approach works (ish) for traditional SaaS, but it breaks down when applied to usage and transaction-based models. These businesses are becoming increasingly common in a world dominated by AI, but they existed well before and continue to exist well beyond AI. With these products – which I often refer to as “painkillers not vitamins” – buyers don’t move through a linear funnel just once, and they are often not in market at all. They enter and exit the market repeatedly and unpredictably, driven by their own circumstances. Readiness is an inconsistent and fluid state, not a one-time event. And it's mostly exogenous, created by the buyer’s unique set of circumstances, not your nurture sequence. 

Plenty of companies have begun to shift their GTM motions to better fit usage models. This most commonly shows up in pricing: tons of AI companies have adopted usage-based pricing rather than a subscription model, which allows them to cover costs, optimize revenue, and meet the buyer where they are when they need it. 

GTM teams are also eagerly adopting signal-based marketing, where you engage a prospective buyer based on an observation that they are ready to buy, such as the announcement of a new hire or round of funding. With the explosion of signal-based marketing, it’s important to remember that observed signals only matter if they’re rooted in a deep understanding of your ICP. Does the fact that a company hired a new salesperson actually impact whether they’d get value out of your software? Why? Beware of copying signal-based playbooks from other companies whose product and/or target customer looks nothing like yours. I understand the temptation to track every possible signal as first- and third-party data becomes more accessible than ever before, but this leads to lazy marketing. 

Marketers should learn to document key signals with as much precision and rigor as they do any other part of the ICP definition, like tech stack or media diet. Just as we used to care exactly which publications our ICP read and why, we should care to understand what signals growth or change within the organization.  Otherwise, we’ll end up with an explosion of data points and very little signal (pun intended) in the noise. 

Here are a few examples of what this looks like in practice: company name, signal mapped to ICP definition, and outreach tactics that leverage those signals:

The funnel approach was more permissive of lazy marketing. You could skimp on knowing your buyer and defining your ICP because outreach was based on the idea that marketing could manufacture buying readiness. When you are selling a recurring subscription, the majority of buyers are always in market. As software companies continue to shift towards usage-based models, funnel-based marketing breaks down in favor of signal-based marketing, and signal-based marketing doesn’t allow us to be as lazy. In this new reality, the competitive advantage lies with marketers who are willing to do the specific, sometimes boring work of deeply understanding the people they sell to and the world those people inhabit.