Stop paying for leads that were never real.
Every inbound lead scored against eleven checks before it reaches a rep, and only the real ones sent back to Meta, so your budget optimises for buyers instead of form-fillers.
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MetaGmailHubSpotOutlookMicrosoft TeamsMetaGmailHubSpotOutlookMicrosoft TeamsMetaGmailHubSpotOutlookMicrosoft TeamsMetaYou hit the lead target. Sales still says the leads are bad.
“Why is sales ignoring these?”
You delivered the number. A third of the phones never connect, and plenty of the rest never asked for anything. The target was met and nobody is happy.
“Which campaign actually worked?”
The ad account reports 240 conversions. The CRM shows 31 real conversations. Both numbers end up in the same deck and neither one survives a follow-up question.
“Why is cost per lead climbing?”
Because the algorithm optimises for whoever fills a form fastest, and nobody has ever told it which of those people turned into revenue.
From more leads to real leads.
What changes when your CRM tells Meta which ones were real.
Questions you can’t answer
- Is this lead even real?
- Which form is working?
- Did Meta learn anything?
- What’s the real cost per lead?
- Who followed up, and when?
- Where is the funnel leaking?
- Can we prove any of it?
Questions LIO answers
- Scored on arrival
- Per-form performance
- Conversions sent back
- Cost per qualified lead
- Assigned and timestamped
- Funnel visible end to end
- Audit trail, seven years
Marketing that gets judged on revenue, not volume.
Lead quality, on arrival
Every lead is scored 0 to 100 against up to eleven checks as it arrives. Fake numbers, dead domains, disposable email and duplicates route straight to junk or to a review queue.
Your ads learn who buys
Qualifying leads go back to Meta as offline conversions with hashed data, so the algorithm stops chasing form-fillers. An events log shows match quality and why anything was suppressed.
One funnel, end to end
Captured, scored, approved, replied, closed. Broken down per campaign and per form, with suppression reasons shown, so the number you present is the number sales recognises.
How growth teams actually use LIO
Bad leads get filtered, not forwarded.
Set your thresholds once. Obvious junk is binned on arrival, the uncertain middle lands in a review queue, and only real people reach a rep or a nurture sequence.
Your ad spend gets smarter every week.
Approved leads are sent back to Meta as offline conversions, hashed. Match quality, suppression reasons and retries are all visible, so you can see the loop working rather than hope it is.
You report a number sales recognises.
Per-campaign and per-form performance sits beside the junk rate, so the weak placements are obvious. LIO flags what to pause before the spend is gone.
You don’t need a bigger budget. You need cleaner data going in.
Checks per lead
0
Fake numbers, dead domains, disposable email, duplicates and geography, all run on arrival.
Every lead scored
0–100
Scored before it reaches a rep, a nurture sequence, or your conversion reporting.
Capture latency
0 min
Real-time webhook with a five-minute polling fallback, so no submission is ever missed.
Audit retention
0 yrs
Append-only trail of every lead event, consent action and deletion request.
Selling looks different depending on where you sit.
Sales Teams
One shared pipeline, so no prospect is worked twice and no context is lost.
Account Executives
Your own call list, ranked, with two minutes of prep before every dial.
Outbound Teams
ICP fit and intent signals that tell you who to target before you dial.
Sales Leaders
A weighted commit you can defend, with at-risk deals surfaced early.
Stop paying for leads that were never real.
Score every inbound lead on arrival, send only the real ones back to Meta, and report a number sales recognises.