What's actually causing the drops

DQ reason inferred from the setter's free-text notes per lead (multi-label, so totals can exceed the lead count). Status comes from the spreadsheet column.

DQ reasons surfaced in setter notes

Status breakdown

Ad creative → cancelled bookings → cancel rate

For each ad / source: how many of the cancelled-list leads originated there, total bookings Mitch received from the same source in the period, and the resulting cancel rate. Off-DM = booked direct via Calendly; the agent has no record of the lead before the call.

Buyer persona, demographic and financial qualifier

Custom properties extracted by the agent during qualification on the 77 matched conversations. Empty rows mean the agent never asked or never set the property in this cohort.

Buyer persona

Demographic segment

Financially qualified

Recommendations — ranked by leverage

1. 01
   Top DQ reasons surfaced from setter notes

   The leading drop reasons across the period were No answer (called 2x) (26), Rebooked / kept warm (16), Indian / language-barrier DQ (8), Not interested anymore (8). Most of these are catchable before the call: country of residence, age (≥ 21), employment status, and minimum savings can all be set as boolean custom properties the agent populates during the qualification turn. Calendly link only fires if all four resolve to true.
2. 02
   "No answer (called 2x)" and "rebooked / kept warm" are symptoms, not causes

   26 notes were tagged 'called 2x NA' and 16 tagged 'rebooked / kept warm' (combined: 42 of 153 leads, 27%). These describe what the setter did — they don't explain why the lead disappeared. Likely upstream causes worth A/B-ing in the agent prompt and ad copy:
     • Booking-to-call lag too long — if the slot is 3+ days out, intent decays. Prompt the agent to lock in same-day or next-day slots first.
     • No commitment ladder — the agent sends the link without re-confirming why they want the call (income goal, current pain, time horizon). Add a 'why this matters to you?' beat before the link.
     • Ad copy promises a low-friction touch — if the creative says 'free strategy chat' the lead expects 5 mins, not a 30-min sales call. Audit creative-to-promise alignment in the riskiest ads (table below).
3. 03
   Geo / language filter at the targeting and the agent layer

   8 leads were flagged as 'Indian' or 'language barrier' in the setter notes. If the ad targeting nominally is Australia-only, this volume implies leakage from interest-graph spillover. Action: tighten Meta Ads exclusions on country and language. In parallel, give the agent a country probe ('quick context — based in Aus or somewhere else?') before the link. If the lead self-identifies outside the ICP, agent sends free course instead of Calendly.
4. 04
   Age qualifier before the Calendly link

   2 no-shows were below the minimum age. Add a boolean custom property age_qualified. The agent asks once, sets the flag, and the link is gated on that flag. The under-21s get a content-only path (free course) instead of a sales call.
5. 05
   Financial pre-qualifier in DM

   6 leads disqualified post-call on income/savings/visa status. Two short questions in DM before the link: "Quick context: working full-time, casually, or between jobs right now?" and "Roughly what's saved up to put toward the trading runway?". Map the answers to a financially_qualified property. If false, the agent routes to the free course; if true, the link goes out. This converts a setter call into a 30-second DM exchange.
6. 06
   Ad creatives with ≥ 50% no-show rate

     • Spear hour V2 — 3/4 no-show (75%)
     • Kids think i am_Group_1 — 3/4 no-show (75%)
     • So glad its monday_Group_1 — 4/7 no-show (57%)
     • Maz — 4/8 no-show (50%)
   
   Pause or re-creative. Cross-reference these against the ads that brought buyers (different cohort): if a creative has high booking volume but low show-up rate, it's pulling tire-kickers — likely a hook that overpromises ease or under-qualifies on commitment.
7. 07
   76 of 153 leads (50%) booked without ever DM-ing the agent

   They went straight from IG bio link → Calendly → call. The agent never qualified them, never warmed them, never sent a reminder. Today the human setter inherits the no-show. Action: route the bio Calendly link through a DM-trigger landing page (or a single-question Typeform) so every booking touches the agent at least once. Even one qualifying turn (country + age + employment) should drop this cohort's no-show rate materially.
8. 08
   Automated pre-call agent (intake + reminder + reschedule)

   Stand up a second agent that owns everything between booking and call: a confirmation DM the moment Calendly fires the webhook ('locked in for {slot} — see you then'), a pre-call reminder 1h before with the join link, a no-show recovery DM the minute the call doesn't connect ('saw you missed the call — want me to lock in a new slot?'), and a 24h + 48h follow-up if there's no reply. This replaces the manual setter retention loop (Adrian / Sam / Baylee dialing 2× and texting) with a deterministic workflow and frees their time for the warm conversations that actually need a human voice.

Lead-by-lead detail · 153 leads

Sorted by booking date. Each card shows status, ad attribution (if traceable), opener (first inbound message captured by the agent), and the setter's free-text note classified into DQ tags.