Brokers blame the leads. Usually the leads are fine and the process is broken. The real reasons conversion stalls, in the order you should check them.
Figures in this article describe the wider market and are drawn from the third-party sources listed at the end. They are not Lead Foundry results, and nothing here is a projection of what any individual broker will achieve.
The complaint is always the same: the leads are rubbish. Sometimes that is true. More often the leads are the same as last month and something else moved, and because the something else is invisible, the supplier absorbs the blame.
Here is how to find out which it is, in order, starting with the cheapest thing to check.
Pull last month's leads and calculate the median minutes between arrival and first attempt. Then split them into two groups, those first attempted inside an hour and those first attempted after four hours, and compare contact rates.
If the fast group performs materially better, you have a capacity or process problem rather than a supply problem. Given that the MIT Sloan research found contact odds fall by a factor of 100 between five and thirty minutes, a large gap here is the expected result rather than a surprise.
Why this test is first: It is free, it takes ten minutes, and it explains more variance than every other check combined. Changing suppliers before running it is how brokers spend a quarter discovering their new supplier has the same problem.
Calculate average attempts per lead. If it is below four, the cadence is not being followed regardless of what the process document says.
The evidence on this is stark. Velocify research across close to 3.5 million leads found 93% of leads that convert are reached by the sixth call attempt, and that 50% of leads are never called a second time. Salesforce reports 44% of reps stop after one attempt while 80% of sales require five or more follow-ups.
| Converted leads reached by the 6th call | 93% |
|---|---|
| Leads never called a second time | 50% |
| Leads that never receive one email | 59% |
| Reps who stop after a single attempt | 44% |
The first bar is what is achievable. The other three are what usually happens. Three quarters of the gap between a good month and a bad one lives in this chart.
Source: Velocify contact-strategy research and Salesforce State of Sales
Contact rate and appointment rate fail for opposite reasons and need opposite responses. Diagnosing the wrong one wastes a month.
| Symptom | Most likely cause | What to do |
|---|---|---|
| Contact rate fell, speed unchanged | Data quality changed | Query the supplier, ask for source URLs, claim replacements |
| Contact rate fell, speed also slipped | Capacity exceeded | Reduce volume or add calling time before blaming supply |
| Contact rate held, appointments fell | The first call needs work | Fix the opening and the ask, keep buying |
| Appointments held, settlements fell | Qualification or the meeting itself | Look further down the funnel than the lead |
| Everything fell at once | Something structural changed | Check delivery is still working before anything else |
The last row catches a genuinely common failure. An integration that silently stopped, a notification rule that broke, or an adviser on leave with no cover produces a collapse across every metric at once, and it looks exactly like a supplier problem until somebody checks the plumbing.
This is the one check that genuinely does point at the supplier. On the calls that connect, listen for whether the person remembers submitting a form and whether what they thought they were asking for matches what you sell.
A consumer who says "I never enquired about that" is telling you something about the landing page rather than about your script. Ask the supplier for the live URL of the page. An operator who owns the consumer brand will send it; an operator reselling network traffic frequently cannot.
If contact rate is healthy and appointments are not, the problem is the first ninety seconds. The most common failure is opening with who you are rather than with why they are hearing from you.
Naming the specific brand the consumer enquired through does two jobs at once. It reminds them of their own action, which is the fastest route out of suspicion, and in New Zealand it goes toward the IPP 3A obligation to make a person aware you hold information collected from a source other than them.
Upstream first. A fix downstream is measured through a broken stage upstream and will look like it did not work.
Check response time first. Split last month's leads by how quickly you made the first attempt and compare contact rates. If the fast group performs much better, the problem is capacity or process rather than supply. Then check average attempts per lead: if it is below four, the cadence is not being followed, and research shows 93% of converted leads are reached by the sixth attempt.
Look at which number moved. A falling contact rate with unchanged response time points at data quality and is worth raising with your supplier. A falling contact rate alongside slower response times points at capacity. A steady contact rate with falling appointments points at your first call rather than at the lead.
Six attempts across roughly a fortnight. Research across close to 3.5 million leads found 93% of leads that convert are reached by the sixth call, and that leads needing more than seven calls are 45% less likely to convert. Stopping at one or two is far more common and far more expensive.
Not before running the response-time split and checking attempts per lead. Both take minutes and both explain more variance than supplier choice does. Changing supplier without ruling them out means repeating the same result with a new invoice.