The 3+1 ICP. It’s a pattern I’ve seen in tons of conversations the last couple months, especially last week at GTM 2024.
Nearly everyone in B2B has an ICP with the same 3 things:
1️⃣: 👥 Size
Proxy for buying power or complexity. Usually expressed as employee count or revenue. Segmentation usually start by bucketing companies by size.
2️⃣: 🌎 Geography
Proxy for laws, language, timezones and culture. This comes down to whether we’ve got the capacity to serve someone in a particular geo[1]
3️⃣: 🏭 Industry
Proxy for company groups of companies that do similar things. Usually expressed as some top-down classification like NAICS or SIC[2]. We usually try to find industries where we do better and target those.
However, there’s *always* a plus 1.
➕1️⃣: 🧩 The Missing Piece
This is the thing that’s unique to your business. Here are real examples I’ve heard recently: has a travel search use case, does SMB payroll, offers pharmacy services, visits consumer homes, depends on performance marketing, has resort properties, is a well-established local restaurant..
The first 3 are usually pretty easy to get—you can buy them off the shelf from any old data provider. The ➕1️⃣ is much harder.
RevOps teams are always on the hunt for proxies they can use to find their ➕1️⃣. However, because they’re so used to thinking about the world in terms of the “data points” they can buy for the first 3, they’re usually looking for some dataset that gives them a number (e.g. marketing spend, count of physical locations, etc). If it doesn’t exist, they give up.
So if you're saying something like “if we just had X, we could nail our ICP”. Try asking “What does that X tell me about the company that makes them a better customer?” and then drill down.
For example, take “We just need to know paid search spend” for a company that sells an AI landing page optimization service.
Q: “What does paid search spend tell us about the company?”
A: “That means they value paid traffic to landing pages and that’s what we help with”
Q: “Why would they value paid traffic?”
A: “It’s probably their major source of customers”
Q: “Why’s that?”
A: “They sell to consumers and that’s the best way to reach them”
➕1️⃣: “Maybe we could just classify some accounts as low-dollar consumer-facing and start there”[3]
It’s not perfect, but it gives you a new way of tackling the problem without just going ¯\_(ツ)_/¯ and telling the reps to go research it.
Would love to hear about your ➕1️⃣ and how you’re dealing with hit. Hit me up in a DM or in the comments.
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[1] I didn’t say state or zip. Laws, language and timezones (to some extent) matter. Don’t slice finer than that.
[2] This is broken. NAICS and SIC were built for government economists, not sales. I recommend bottoms-up clustering like Gradient Works Market Map.
[3] This is a good AI agent web scraping use case
