The Mom Test (book)

The Mom Test (book)

Indie Hackers

How to talk to customers when everyone is lying to you

I was super bad at talking to customers, and then I went out of business. Once I figured out how to do it properly, I wanted to write it down.

Share card

Actual performance

15followers
$10,000MRR/mo
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

btw
btw

Delight your customers

BetaList
Id
Identifying, Segmenting and Contacting our Customers51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Identifying, Segmenting and Contacting our Customers

Hacker News11
Ou
Our first three featured customers57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Our first three featured customers

Hacker News3
I
I built a tool that helps you talk with customers31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built a tool that helps you talk with customers

Hacker News1
Fi
Fibonacci in {lambda talk}49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Fibonacci in {lambda talk}

Hacker News1
Be
Beehive – Talk 1:1 About Anything43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Beehive – Talk 1:1 About Anything

Hacker News11
Ta
Talk Out of λtank43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Talk Out of λtank

Hacker News2
Wh
What if your ghostwriter and readwise could talk to each other?43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

What if your ghostwriter and readwise could talk to each other?

Hacker News1
Sh
Shoutium – Talk with those around you.43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Shoutium – Talk with those around you.

Hacker News1
My
My first ever e-book, Hacking Obamacare65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My first ever e-book, Hacking Obamacare

Hacker News6