Connecting EZLynx to Meta Conversions API

Architecture

How EZLynx and Meta actually connect

Two systems that know nothing about each other. Everything below exists to give them one shared reference.

1. Step 1

   EZLynx holds the truth

   Comparative raters make quoting cheap and abundant. That makes the quote-to-bind rate the only interesting number, and it differs enormously by traffic source.

2. Step 2

   Meta Conversions API needs a click to match

   Meta matches server events to people using whatever identifiers you send, hashed with SHA-256 where required. There is no single mandatory key, which is why quality varies so much between implementations — a poorly matched event is accepted, reported, and worth much less than it appears.

3. Step 3

   The identifier is the bridge

   The fbc and fbp values, captured at the visit and carried into the EZLynx quote. Without it there is nothing to join on and no tool fixes that.

4. Step 4

   The event source decides reliability

   Send bound policies at first-year commission. Quote requests are a stage event, not revenue.

5. Step 5

   Deduplication at the destination

   Meta deduplicates on the pair of event_name and event_id. The browser pixel and the server event must send the same event_id for the same conversion, within the deduplication window. Get this wrong and every purchase counts twice — which is by far the most common Conversions API failure and it inflates reported ROAS rather than reducing it.

Diagnose it honestly

Working vs. broken, side by side

Both states look identical from the Meta dashboard, which is why this runs for months before anyone notices.

Diagnostic sequence

Diagnostic order

Each step rules out a class of cause. Run them in order and the last one usually has a single explanation standing.

1. 1

   Count policys carrying the fbc and fbp values

   The ceiling on everything else. Do this before debugging anything downstream.

2. 2

   Follow one real conversion end to end

   From the ad click through EZLynx and into Meta.

3. 3

   Measure quote-to-bind rate by traffic source

   It is the number that separates shoppers who will switch from shoppers who are checking their renewal price.

4. 4

   Read Event Match Quality and the deduplication indicator

   In Events Manager, open the event and check both. A low match quality means weak identifiers; a missing deduplication indicator means your event_id pairing is broken.

5. 5

   Read the match rate, not the success message

   Events Manager shows received events, the deduplication state and an Event Match Quality score per event. Events arriving is not the test — deduplicated, well-matched events arriving is. Compare Meta's reported purchases against your store's order count for the same window.

Source-of-truth validation

How it gets proven

Against EZLynx's own records, not against either platform's dashboard.

• The fbc and fbp values confirmed present on a live policy.
• A real conversion followed from click through EZLynx to Meta.
• Deduplication confirmed in Events Manager on a real purchase, with the browser and server events visibly paired rather than counted twice.
• Bound policies reconciled at commission against imported conversions, with quote volume reported as a cost.
• Reconciled over a fully closed window, matched per record rather than on totals.
• Re-checked 30 days later.

Straight talk

When you don't need this

Worth reading before paying anyone, including us.

• If Meta already reports conversions that reconcile against EZLynx's records within a few percent, this join is working and there is nothing to buy.
• Measure identifier coverage yourself first — pull your last hundred policys and count how many carry the fbc and fbp values. Ten minutes, free, and it tells you whether any of this is worth doing.
• If your bind rate is uniform across sources, optimising on quotes is defensible and learns much faster — but report on bound policies regardless.
• If you are not running Meta ads at meaningful spend, the Conversions API is effort without payoff. It earns its cost when the optimization signal is worth improving.