Quality & lead intelligence

Hyper Entrepreneur — Mia quality report

Rolling 14-day window · refreshed 2026-09-14 12:56 UTC · influencer cmrjtm9k0000mpokztq4gbyvp

Who is sending the messages

5,144
external (ManyChat / GHL)
913
Mia (the agent)
14%
share that is Mia
697
inbound from leads
Some of the channel burn traces back to Mia. She accounts for 3 of 45 opt-outs and 1 of 23 duplicate sends, 6% of the total. The rest followed an external broadcast. This is worth acting on inside the agent, not just upstream.

Duplicate sends (same text twice inside 30 min)

SourceDuplicate sendsLeads affected
external (ManyChat/GHL)2216
ninjo agent11

Contact addresses still being sent

AddressSent byMsgsLeadsLast sent
support@hyperentrepreneur.comexternal (ManyChat/GHL)20172026-09-14
support@hyperentrepreneur.comhuman operator222026-09-11

These are the addresses under watch. Every “email the team” deflection lands in one of them, so any that goes unanswered converts a decision-stage question into a lost lead.

The leads we actually held a conversation with — 31

4
blocked on money
25%
of stated objections
0
beginner, no offer yet
3
already run a business

Business maturity — do they already have an offer?

SegmentLeadsShareExample values
other or unclear667%
alone person seeking support; already doing all that and more; consulting business
has business or offer333%
Arabic-speaking entrepreneur; business owner; entrepreneur
Only 9 segmented lead(s) in this window, too few to read a mix from. Widen the window for the audience picture.

Main blocker (from the evaluator's main_objection)

BlockerLeadsShareExample values
other or unclear1062%
did not understand; doesn’t understand English; don't have capital for now
money425%
too expensive; needs money; price
tech or access212%
link not working; couldn't access page

The evaluator writes objections as free text: 16 leads produced 15 distinct phrasings, 14 of them one-offs. Shares are therefore of clustered objections, and the “other / unclear” row is a genuine long tail of individual wording rather than a gap in the data. Useful consequence: the per-lead objection text is high quality for reading a single conversation, even where it resists aggregation.

Why conversations stalled

ReasonLeadsShareExample values
other or unclear1467%
asked for a paid personal conversation; asked for the link; automated message from another system
money419%
asked about TikTok account issue and money transfer help; couldn't afford it; financial situation
tech or access210%
couldn't access page; link not working
fit15%
not interested in AI skills

What they say they want

Read this one carefully. Of 4 leads with a stated goal, 0 repeat our own marketing hook back to us (“get paid helping businesses with AI”) and only 4 said something independent. So we do not really know what they want yet, and asking a better qualifying question is the fix.

What leads are asking about

TopicLeads
other programs38
price or affordability7
payment plan5
schedule or dates5
time commitment2
guarantee or risk1
tier choice1

Coarse keyword buckets, directional volume rather than precise counts.

Errors, fails and complaints

Every item below is a candidate, not a verified finding: these are regex matches on what the lead wrote, shown with the verbatim quote and the conversation id so each one can be rechecked before it is acted on. Expect a meaningful share of false positives.

HIGH opt out · 45

HIGH broken link or page · 1

Generated by src/scripts/agent_quality_report.py · findings write-up in agents/hyper-closer/quality/