If you’re in B2B sales or marketing and tired of chasing leads that never close, this one’s for you. AI analytics tools promise to help you find your “ideal customer profile” (ICP), but most of the advice out there is fluffy or just parrots vendor pitch decks. Here’s the real-world, step-by-step guide to using Leadspace to actually identify your ICP—what works, what doesn’t, and what to skip.
Why Bother With Ideal Customer Profiles?
Let’s be honest: most sales teams waste time on leads that were never going to buy. The point of building an ICP is to focus on the accounts that actually look like your best customers—so you can stop chasing dead ends.
Leadspace claims it can help you do this with AI. The good news is, it does a lot of the heavy lifting. The bad news? It’s not magic. You need to know what you’re doing, or you’ll drown in data and fluffy recommendations.
Step 1: Get Your House in Order
Before you fire up the AI, you need a decent foundation. If your CRM is a mess or your “closed-won” data is full of junk, any AI tool will just multiply your problems. Here’s what you need:
- Clean Customer Data: Start with a list of your best current customers. Scrub out duplicates, dead accounts, and anyone who didn’t actually buy.
- Accurate Outcomes: Make sure you know which deals were actually successful. Don’t include renewals, free trials, or one-off purchases unless they’re part of your true ICP.
- Firmographics & Demographics: Basic stuff like company size, industry, geography, revenue, and contact roles. If you don’t have this, AI will just guess—and not always well.
Pro tip: If your “best customer” list is tiny, it’s better to add more time upfront than to train an AI on a handful of examples. Garbage in, garbage out.
Step 2: Connect Leadspace to Your Data
Assuming you’ve got a Leadspace subscription, here’s what you do:
- Integrate your CRM or marketing automation platform. Leadspace connects with Salesforce, Marketo, HubSpot, and a few others out-of-the-box. Don’t try to upload CSVs unless you enjoy pain.
- Map your fields. AI only works if it knows what “Revenue” or “Industry” actually means in your system. Take the time to match up your CRM fields to Leadspace’s inputs.
- Sync regularly. Data gets stale fast. Set up regular syncs (daily or weekly) so you’re not making decisions on last quarter’s info.
What to ignore: Don’t get distracted by optional bells and whistles like social media data or “intent” signals unless you know they work for your industry. Start simple.
Step 3: Define (and Refine) Your ICP Criteria
Now comes the part where most people get lazy or overthink it.
- Start with what you know: What do your best customers have in common? Industry, size, tech stack, location, pain point? Write it down.
- Don’t get too granular: If you try to make an ICP with 20 attributes, you’ll end up with nobody. Keep it to 3-5 core characteristics.
- Talk to sales (and support): The best data is often in your salespeople’s heads. Ask them what patterns they see in deals that actually close and stick around.
Feed these criteria into Leadspace’s ICP modeling tool. The AI will use them as a starting point.
Watch out: If you just let the AI pick your ICP for you, it’ll often latch onto weird correlations (“all our best customers use Gmail!”) that don’t mean much. Always apply a sanity check.
Step 4: Let Leadspace Build and Score Your ICP
This is where the AI does its thing:
- Model building: Leadspace analyzes your customer data and tries to find patterns. It’ll suggest “lookalike” criteria—sometimes obvious, sometimes surprising.
- Scoring: The platform assigns an “ICP Fit Score” (or similar) to leads and accounts in your database. Higher scores mean closer matches to your ICP.
Here’s what actually matters:
- Top scoring accounts: Focus your sales and marketing efforts here.
- Edge cases: Look at a few low-scoring “good” customers and high-scoring “bad” ones. If the AI is missing the mark, tweak your inputs.
Ignore: Don’t obsess over small score differences (e.g., 87 vs. 85). The real world isn’t that precise.
Step 5: Pressure-Test Your ICP
Before you turn your team loose, check your work.
- Gut check: Does the list of top-scoring accounts actually look like your best customers?
- Field feedback: Have reps test outreach to these accounts. Are they engaging? Are you seeing better win rates?
- Iterate: If something looks off, adjust your model inputs and rerun. This isn’t a one-and-done thing.
Pro tip: Don’t just trust dashboards. Export a list and spot check the companies. If a bunch are obviously wrong, dig into why.
Step 6: Put It to Work—Without Overcomplicating
Here’s where most teams trip up: they over-engineer the process or create a dozen “micro-ICPs.” Resist the urge.
- Prioritize outreach: Focus on accounts with the highest ICP scores for sales and ABM campaigns.
- Refine targeting: Use your ICP to filter inbound leads, enrich contact lists, or suppress low-fit accounts from marketing.
- Keep it simple: Don’t try to build a separate model for every product or region unless you really have the data (and the patience).
What not to do: Don’t let the ICP become a gatekeeper that blocks reps from chasing promising outliers. It’s a tool, not a rulebook.
What Works, What Doesn’t
Let’s cut through some common myths:
- AI is only as good as your data. If you feed it garbage, you’ll get garbage back—faster.
- Leadspace is strong at firmographic matching and account scoring. If you sell to complex orgs, it’s way better than manual research.
- Intent data and “AI signals” are hit-or-miss. Sometimes they help, sometimes they’re just noise.
- No tool replaces talking to customers and sales. AI can spot patterns, but it can’t explain weird edge cases or sudden market shifts.
A Few Final Tips
- Start with a basic ICP. Don’t aim for perfection. Good enough beats “perfect and never launched.”
- Plan to revisit quarterly. Your best customers today might look different in six months.
- Document your logic. So you remember why you made certain decisions if you need to explain them later.
Keep it simple, keep it honest, and don’t let the hype distract you. AI analytics in Leadspace can save you a ton of time and guesswork, but only if you feed it good data and sanity-check the results. Iterate, trust your gut, and remember: no tool is a silver bullet, but you can make it work for you.