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Thoughts on (App PMF & Creation)

Maximise:
Output Metric
Customer Lifetime Value
# of transactions
Retention
DAU/MAU
D1, D3, D7, D30 Retention

(using)
Input Metrics
Time Spent on App
PDP Page Conversion (% of clicks on PDP / DAU)

Immediate Priority is to:
finding which sub-component of Time Spent on App correlates strongest with Retention & Transactions:
by sub-section: is it time spent on Home Feed, Profile Feed, Wishlist section, etc.?
by content type:
by format: live, short video, memes, etc.
by source: supplier videos, AI videos, standalone creator videos, YouTube scraped videos
by theme: storytelling video, product demo video, etc.
by UX experiences:
size of PDP, color, layout, etc.
can a re-designed wish-list section correlate well with our output metrics?
by growth loops:
notifications & gamified loops on:
re-targeting
wish-listed items
affinity:
category (you’re looking at Home Decor only)
gender (you’re looking at Men’s Apparel only)
sub-category (you’re looking at traditional women’s wear only)
etc.

Track 1: experiments on smaller optimisations
small, incremental changes
Track 2: re-imagining the core experience with changes in value prop
Track 3: re-examine the assumptions we have taken in Track 1 and Track 2

how do we fit in subjective feedback?
run experiments on a clearer, newly acquired user cohort

Things to do: (non-prioritised)

Hand-curation of Feed
In rule-based logic, put product-tagged content above non-product tagged
A/B experiments on Feed
DS & Personalization-related work
Consolidated Feed
Affinity Targeting
Wishlist Flywheel
Wishlist becoming something more than a standalone feature - but a core value prop of app
Wishlist as a way to know more than about the user, as a way for the user to showcase their taste, as a way for trending products to emerge
This has other benefits:
provides unique differentiation in user’s mind,
helps us target user better,
activates social growth loops,
wish-list and repeated targeting on it gradually wears down the barrier to purchase
Growth & Retention Loops
Share a post
Affiliate Model
Retention Loops - wishlist updates
Notifications Tab & In-App Notifications (use MoEngage built)
Modelling a particular product (Sensetime SDK etc)
Urgency/Persuasion Elements on PDP
Stand-alone PDP
Wishlist Tab or Section?
Price Drop on wishlisted products/posts
Keep everything organized in one place and open up rabbithole of further products
Widget Types that break the feed monotony
Bot: "Show me a quirky look" that leads to an LLM flow
Productizing the content formats that work
Automation of non-negotiable Ops work like Product Tagging
Streaming Infra
Rating + best look
Enabling some constructs (like affiliate product tagging) to enable US iOS app
L2 page for when you tap onto a video
Ability to tag multiple products


Some notes on how we’ll work:
Extreme Speed & Iteration Rate (especially for Track 1)
This pod will move very fast and break many things.
It will make many MVPs, release fast, and scrap many MVPs too.

Find new ways to prototype fast (especially for Track 2)
It will also try to release no-code variants:
We have figured a way to embed analytics onto Framer (a design prototyping tool).
This allows us to release hard-coded MVPs with no Engg effort.
We can release a Framer Web Page that showcases a brand-new experience
Run Facebook Ads to get 100 (some statistically significant number) users on the page
Assess feed depth, time spent, and PDP visits, on the page

Very manual version of the vision → figuring PMF signs → then automate/scale

Analytics
We will also study all correlations separately.(example: we expect that there might be content types that correlate strongly with Transactions but moderately with Retention - or vice versa).


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