Your Lead List Is Already Dead: Why Timing Beats Targeting in B2B Sales

You bought a lead list last month. Five thousand businesses, nicely segmented by industry and postcode. Your sales team started calling on Monday.

By Friday, 300 numbers were disconnected. 200 contacts had changed jobs. And of the people you did reach, most said the same thing: “Not interested right now.”

That last part is the killer. Not “never.” Not “wrong person.” Just not right now.

The list told you who these businesses were. It said nothing about when they’d need you.

The Decay Problem Nobody Talks About

Lead lists start dying the moment they’re created. Contact details go stale. People move on. Companies close, merge, or rebrand. Industry benchmarks put B2B data accuracy at 60-70% on the day of purchase. Three months later, you’re below 50%.

But accuracy is the smaller problem. The bigger one is relevance.

A traditional lead list is a snapshot of who a business is. Their industry. Their size. Their location. Static facts. None of it tells you whether they need your service today, next month, or never.

So you spray messages at thousands of companies, hoping to catch the 2-3% who happen to be in-market. The other 97%? You’ve just annoyed them.

What If You Only Contacted Businesses That Needed You This Week?

That’s signal-based selling. Instead of starting with a list of companies and hoping some need you, you start with the event that creates the need and work backwards to the company.

A signal is a real-world event, recorded in public data, that tells you a specific business needs a specific service right now. Not eventually. Not theoretically. Right now.

Three examples from the UK:

• A restaurant fails its food hygiene inspection. The FSA publishes the result within days. That restaurant now has a regulatory deadline to fix structural problems, clean the premises, and deal with pest issues. Pest controllers and deep cleaning companies have a window of weeks, not months, to reach them.
• A new care home registers with the CQC. Before they can open, they need to recruit nurses, buy medical equipment, contract laundry services, and find insurance. Recruitment agencies and medical suppliers who reach them first win the contract.
• A company files new directors at Companies House. Leadership changes often trigger reviews of existing supplier contracts. Accountants, insurers, and legal firms have a narrow window to introduce themselves before decisions are made.

Each of these events is publicly recorded. The data is free. And each one creates a specific, time-bound need.

The Numbers: Spray vs. Sniper

Here’s what changes when you swap volume for timing:

Same number of opportunities. One-tenth the volume. And the quality of those conversations is completely different, because you’re contacting someone about a problem they already know they have.

Why This Isn’t “Intent Data”

You might be thinking this sounds like the intent data that companies like Bombora or 6sense sell. It isn’t.

Intent data tracks online behaviour: who’s reading articles about your category, visiting competitor websites, or searching for related terms. It’s probabilistic. Someone reading about CRM software might be in-market. Or they might be a student writing an essay.

Signal data tracks real-world events. A restaurant didn’t probably fail its hygiene inspection. It did. A care home didn’t maybe register with the CQC. It’s on the public register with a date stamp.

Intent data guesses what someone might need. Signal data confirms what they definitely need.

That’s a meaningful difference when you’re deciding who to spend your sales team’s time on.

The First-Mover Window

Signals create something traditional lead generation can’t: a first-mover advantage.

When a restaurant gets rated 0 for food hygiene, most pest controllers won’t find out for weeks or months, if ever. They’re waiting for the phone to ring, or relying on Google Ads to catch the owner when they eventually search for help.

The pest controller who calls within days of the inspection result being published has the conversation alone. No comparison shopping. No “let me get three quotes.” Just a business owner with an urgent problem and a professional who clearly understands it.

That window closes. Other suppliers catch on. The owner sorts the problem. But for those first few days, the signal gives you an edge that no amount of ad spend can replicate.

What Makes a Good Signal?

Not every public dataset contains useful commercial signals. The ones that work share four characteristics:

1. Public and free. The data comes from government registers, regulatory bodies, or official public records. No scraping grey areas. No data protection issues. It’s published specifically to be accessed.
2. Time-stamped. You can see exactly when the event happened. A food hygiene rating published three days ago is valuable. One from eight months ago isn’t.
3. Action-forcing. The event creates a need the business can’t ignore. A regulatory failure needs fixing. A new registration needs suppliers. A director change needs professional advisors. The business has to act.
4. Specific to a service. The signal maps directly to a type of provider. Not “this business might need some kind of help.” More like “this business needs pest control within the next four weeks.”

When all four conditions are met, you have a signal worth monitoring.

Is This Right for Your Business?

Signal-based selling works best when:

• You solve a specific, time-sensitive problem – not a vague “nice to have”
• Your sales cycle is short – days to weeks, not quarters
• You serve a defined territory – local, regional, or national within the UK
• Your competitors rely on directories and ads – so timing gives you a genuine edge

If that sounds like your business, there’s probably a public data source creating signals for you right now. The question is whether you’re monitoring it.