Introducing BuyerCue - B2B SaaS Leads Backed by Real Buying Signals

Today I'm launching BuyerCue, AP2's newest site. It's a lead list for people selling to small software companies, and every company on it comes with evidence.

If you sell anything to SaaS founders (a dev tool, a marketing service, an ad slot, a newsletter sponsorship), you know how the usual lead list goes. You filter a big database by job title and company size, export a few hundred rows, and then find out most of them have never paid for anything like what you sell.

BuyerCue starts from the other end: companies that have already paid a stranger on the internet to help them grow.

🤔 Why We Built BuyerCue

Running AP2 means I spend a lot of time on the other side of this. Every time we ship something like Idea Launch, FindMyBnB or BarGPT, we go through the same launch routine: directories, launch boards, featured listings, promoted slots. Some of those cost money.

It made me realize that all those paid placements are public. A company that paid to be featured on a launch board has proven something a job title never will: it will spend money on distribution. If it did that more than once, it's a repeat buyer.

That's the thesis behind BuyerCue:

• Past spending beats a job title. A paid placement actually happened. It isn't a guess based on someone visiting a pricing page.
• Repeat spending is the strongest signal. Companies that buy distribution once tend to buy it again.
• A lead you can't reach isn't a lead. Every company we qualify has at least one public business contact route.

⚙️ How It Works

1. Find the paid placements. We scan public directories, launch boards, marketplaces and listing pages for signs that a business paid to grow: paid placements, promoted slots, high-effort submissions and ad tech. We only use public pages. No logins, no paywalls, no leaked data.
2. Check the business. From each company's own site we pull the product, audience, pricing, maturity and public business contact routes, then score how strong the buying signal is. Every fact links to the page it came from and the date we saw it. If we don't know something, we leave it blank.
3. You search and pick. Filter by category, signal strength, maturity and whether a business email is published. Every row shows why the company qualified, so you can judge fit before you spend anything.
4. You reach out. Use the company's published email, contact form or brand account. BuyerCue never sends email for you. Your outreach, your voice.

🔍 Free to Search, Pay Only for What You Unlock

Searching needs no account. For free you can see how many companies match your filters, their signal strength, the evidence behind it, and which contact routes exist.

When you find companies worth contacting, you spend 1 token to unlock 1 company. That shows the name, domain, business contact routes and the full paid-placement evidence, and the company stays yours for good, CSV export included. New accounts start with a free token, so you can try it before paying.

If you're not sure where to start, the prospect segments are ready-made lists, like developer-tool companies investing in growth. Each one states exactly how its companies were selected.

🧾 Receipts First, Guessing Never

I wanted BuyerCue to be honest about what its data can and can't tell you:

• Every fact is sourced and dated. You can check a row before you send anything, and anything we haven't re-confirmed in 90 days is flagged as stale.
• Detected tools are clues, not proof. An ad pixel on a site shows what's installed, not how much they spend.
• The score tells you who to look at first, not who will buy. Your own sense of fit still matters.
• Companies, not people. Contact routes are business channels like a company inbox or contact form, never personal addresses, and companies that opt out are never shown or exported.

We've also started writing guides on the thinking behind it, starting with how to find SaaS companies paying for distribution and buying signals vs. purchase intent.

🛠️ Built the AP2 Way

Behind BuyerCue is a data pipeline we call SaaS-Opedia. It's TypeScript from end to end: Node workers find listings, pull details from company sites, and score each company, and a Next.js app serves the search. As with everything we ship lately, AI coding agents did a lot of the building, and I focused on the rules: public pages only, a source for every fact, blank instead of guessed.

It's the same approach behind our marketing automation and programmatic SEO work: let AI do the tedious parts and keep the judgment for yourself.

🚀 Try It

If you sell to SaaS founders, stop guessing who has a budget. Start with the companies already spending.

👉 Search BuyerCue for free, or see what an unlocked company looks like in the free sample profile.

We'd love your feedback. Find us on Twitter/X and tell us what segment you'd want next.