For Indian consumer brands
Make your next call with the market in front of you.
Peers, consumer reviews, household demand and your own unit economics, in one place. Try the free tools without an account.
Built for Indian brands in Food & Beverage
- ✓ No sign-in to try
- ✓ Sample data is always labelled
- ✓ Built on public data
Built on
- Your Amazon and Flipkart stores
- Marketplace reviews
- Indian business news
- Household Consumption Expenditure Survey, MoSPI
- Peers in your product families
Three jobs, one place
Aisha sells a sunscreen on two marketplaces. Here is her Tuesday.
An illustrative story, not a customer. Every product view carries the Example data tag; paid and locked parts say so.
Aisha's Tuesday, in three jobs
Watch Aisha's Tuesday in 81 seconds
Read the film as text
- A distributor wants a price on Aisha's sunscreen.
- Today.
- She could guess.
- Or she could check.
- First, who she's up against.
- Four brands share her product family.
- Then, what shoppers want.
- Review themes, counted, with thin data flagged.
- And where households spend,
- state by state, from the national survey.
- Now the question that decides it.
- At five hundred rupees an ad,
- she keeps thirty thousand per hundred orders.
- At twelve hundred, she loses eleven thousand.
- She signs up free.
- One email, no card.
- Then links her stores.
- Now the SWOT:
- where her reviews beat the category,
- and what the news points to.
- She keeps the evidence,
- and composes a report a second analyst checks.
- The take: price against pack size.
- Claim only what she can show.
- Every source cited.
- Aisha replies with a number she can defend.
- Try the numbers yourself.
- No sign-in.
- Make your next call with the market in front of you.
01
Who am I up against?
Aisha links her two stores. Sylvr reads her catalog and finds the brands that sell in her product families.
In testing
sylvr.io/founder/peersExample data
02
Read what consumers want
Review themes, counted by how many consumers say it, with a plain flag when a number is thin. Then where households spend on her category, by state.
In testingLive
sylvr.io/founder/reviewsExample data
sylvr.io/founder/demandExample dataPaid plan
03
Test how it makes money
Price, cost, ads and repeat purchase in one place: profit per 100 orders, LTV to CAC and payback.
Live
sylvr.io/economicsExample data
Pick your door
Start with the job you have.
Pick your door
- See who you compete with, and what consumers say about them
- Find the states where your category sells
- Test price, cost and ads before you commit
What is inside
Six things inside, by the job they do.
What is inside
Who am I up against?In testing
Product-family peers
The brands that sell in your product families.
Read what consumers wantIn testing
Review themes
What consumers praise and complain about, feature by feature.
Read what consumers wantLocked · sign in
Price against rating
Where every brand sits, so you see the gap you can own.
Read what consumers wantLive
Regional Demand
What households spent on your category, by state, as surveyed. The forecast needs an account.
Test how it makes moneyLive
Unit Economics
Profit after ads, LTV to CAC and payback.
Support from analysts
Analyst reports
Sourced reports from analysts, to read beside your own numbers.
For analysts, beside the founder
Help founders decide with sourced work.
Explore the data, run a framework, publish a report that founders read for their category. Delivery straight to a founder is planned.
Not open yetApplications for the Programme are not open yet.
Read a published reportReports are public to read. The Programme is how an analyst starts: apply, a 15-day trial, a briefing, then access while your pass is active.
Know your category
before you decide.
Try Unit Economics now. No sign-in, no card.