MH Physique App
Voice of Customer
Report
Report
256
Total responses
+26
NPS score
170
Open-text responses
6
Survey types
Scores
Net Promoter Score
Detractors 0–6
Passives 7–8
Promoters 9–10
Promoters: 48 · Passives: 34 · Detractors: 21 · n=103
+26
NPS score
H&F category median approx +30
Most detractor feedback clusters on bugs and UX. However, a separate signal exists: approximately 7 respondents expressed dissatisfaction with the training prescriptions specifically — citing volume, exercise selection, or feeling guided off track. These are not UX complaints. Worth monitoring as the user base grows.
Satisfaction Scores (Likert)
n=69 · current users + churn cohort · scale −2 to +2
Intake process0.74
Training program0.57
Nutrition program0.36
Ease of use0.13
Ease of use nearly flat — the single biggest drag on conversion and retention.
Why they signed up
Reasons for choosing MH
Coded from n=32 open-text responses · read-verified
Verbatim buying language
"Biggest reason for choosing MH" survey · n=32
"Menno seems to know his shit. I do too much random and inconsistent crap so I thought some structure would help."credibility
"I trust Menno's focus on scientific principles."science
"MH is a trusted science based expert in the field."credibility
"His approach makes so much sense and his knowledge and interpretation of studies for evidence based training is outstanding."science
"I want consistent progress without thinking about details myself. I'm busy with work and family."convenience
What's working
What satisfied users say
NPS 9–10 open text + "biggest improvement" survey · n=11 improvement responses · read-verified counts
10+ mentions
3–4 mentions
1–2 mentions
n=13
Menno credibility as primary trust driver
"Menno is a smart man." "His approach makes so much sense." "Solid scientific training methodology."
n=4
Autoregulation removes decision fatigue
"It thinks for me and progressively overloads automatically. Previously I would need to do it and could not." "Saving lots of time, I had to autoregulate myself before."
n=3
Automatic rescheduling praised
"Rescheduling training days, which here is so awesome, basically automatic."
n=3
Re-engagement, excited about training again
"Got me excited about training again instead of just going through the motions."
n=2
Simplicity, no fluff
"Simplicity." "Love how responsive it is. No fluff. Love it."
n=1
Better muscle balance vs previous split
"More balanced than upper/lower split when lower workouts were grueling."
Friction and churn signals
Problem themes
Across all 170 open-text responses · read-verified · one respondent can contribute to multiple themes
UX (24) and bugs (14) dominate. Everything else is secondary. These two categories overlap — several respondents cite both in the same response.
Sharpest churn quotes
Exit survey + email churn Likert · n=13 churn responses · verbatim
"The app is not ready for prime time. Very buggy. It auto-suggests chili for breakfast. I can't change the time for 'meal 2', it just bounces instead of letting me save."bugs
"UX is a pain in the ass. Can't change meal timing, menus force you to scroll. Yesterday's meals auto-populate. Good idea, poor implementation."UX
"I didn't understand how the app should be used. It wasn't clear to me, especially the workout feature."onboarding
"The AI is very strict and doesn't do well outside its recommendations. Not a fan of not choosing my rep range."flexibility
"Another session making me late from work just trying to sort it and I'm unsubscribing."friction
n=13 is small. Direction is clear but treat individual sub-reasons with caution.
Nutrition — three distinct signals
Do not conflate these
n=7
Switched to a dedicated nutrition competitor
MacroFactor (4), RP Diet (3). Reason: photo-based AI logging, cheaper. Several continue using MH for training — not full churns.
n=6
Nutrition UX is friction-heavy
"Too many clicks to mark a meal done." "Barcode barely works." "Yesterday's meals auto-populate." "Can't change meal timing."
n=1
Expected a prescriptive meal plan
"I thought the app would provide a plan to follow according to my goal, not that I would have to choose foods to track macros."
Flag — n=1, unresolved
The meal planning feature exists. Whether this user did not find it or expected something different cannot be determined from one response.Scheduling — same feature, two user experiences
Complaints (n=7)
n=3
Too rigid for irregular schedules
"Hard to manage workout schedule if you have irregular training days. App wants you to choose training days. I need sometimes to change my schedule."
n=2
Can't modify workouts mid-session
"Doesn't let you add sets mid-workout. Constrains how many reps you can enter."
n=2
Bug: workouts on non-workout days
"A workout is added on a non workout day or a weekly checkup added on a Saturday."
Praise (n=3)
n=3
Automatic rescheduling praised as standout
"Rescheduling training days, which here is so awesome, basically automatic."
Implication
Works for regular-schedule users. Breaks for shift workers and variable-week schedules. Two user types hitting the same feature differently.Competitive landscape
Competitors named by users
"Other app prefer" responses (n=26) + exit reasons · read-verified
Why users went to competitors
n=7
RP: simpler UX, pre-made templates, better demos
"RP Hypertrophy is much simpler with pre-made templates and easier/friendlier UI/UX." "Feels professional, excellent exercise demos, no AI slop images."
n=5
MacroFactor: photo-based food logging
"Take a picture and the AI analyzes the food and auto-completes kcals/macros/name/ingredients." "Food logger is superior."
n=4
MyoAdapt: features MH lacks
"Wanted guidance on injuries, ended up going with MyoAdapt." "MyoAdapt has the missing features."
n=2
Hevy: multiple routines for variable schedules
"My work schedule changes week to week, picking from different routines each day is a great benefit."
Messaging implications
What this data supports — survey-grounded only
Derived from survey data only · not from positioning assumptions · counts in brackets
Use in copy — confirmed by data
Investigate before acting
Low signal, do not act on yet
Not present in this dataset