Real estate & marketplaces
Find out why the leads moved.
Put what people do on your listings next to your enquiries, your clients and your ad spend, then ask in plain English. Which city, which app, which client? Did interest fall, or did something break? Crunch investigates across all of it — and shows exactly how every number was counted.
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Live — “Rental enquiries dipped — split by city, then Pune by app, then find when the Android ones stopped. Did Android users lose interest, or did the enquiry step stop working?”
Inside one investigation · a property marketplace
The enquiries that vanished
The data, joined
- Clickstream591,481 events — listing views, gallery views, contact clicks
- Enquiries from the apps11,401 records exported from MongoDB — enquiries, calls, viewings
- Listings1,665 — city, rent or sale, client
The questions
“How many rental enquiries did we get each month from January to March 2025?”
“Split that by city. Now split Pune by app — Android, iOS and web.”
“When did the last rental enquiry from Android in Pune come in? Did views of those listings drop after that?”
“So which fits better — Android users lost interest, or the Android enquiry step stopped working?”
What Crunch did
- Followed the person’s lead one small step at a time: the monthly trend, then the city, then the app.
- Found the slice that broke — Pune, Android — and the day it stopped: February 16.
- Checked the other side of the story in the clickstream: did people stop looking? They didn’t — and then weighed the two explanations without claiming more than the data shows.
The answer
Browsing held; enquiries vanished. The pattern fits a broken enquiry step on Android, not lost interest.
Sample data: a fictional property marketplace with Indian cities, built for demos. The video is speeded up — the full conversation took about 45 minutes.
Your listings, your leads, one conversation
Clickstream from your site and apps, enquiries from your own database, clients and ad spend from exports — joined without a pipeline.
Add the tag
Google Tag Manager on your site sends listing views, searches and contact clicks.
Bring your records
Sync enquiries from your own database with bb-connector, or upload clients, listings and ad-spend exports.
Ask across all of it
“Which client’s listings stopped getting leads? Which campaign brings viewings?” Crunch joins the datasets and shows its working.
Questions it answers
From listing views to leads
“Leads fell this month — was it our ads, or our listings?”
“Which city, app or listing type lost enquiries, and from when?”
“Which clients are getting the most leads for what they pay?”
“Where do people drop between viewing a listing and contacting the agent?”
“Which campaign brings viewings, not just clicks?”
“Which listings get viewed but never contacted?”
Watch it work
Investigations on a property marketplace
Each clip is one question — or one conversation — and the investigation behind it.
The founder's conversation
“Growth feels flat and I can't tell where we're losing people — I don't even know the right question to ask. Where should I focus?”
Three turns: Crunch turns a vague worry into first questions, lays out a plan before running anything — flagging that traffic-source data is empty — then runs the funnel and names the leak: 12,300 lost between viewing a listing and contacting an agent.
The leak under the flat line
“Walk me through our funnel, from searches to viewing a listing to contacting an agent. Which step loses the most people?”
Of 20,000 searchers, 16,000 view a listing but only 3,700 contact an agent. The leak isn't at the top — 12,300 are lost between the listing and the contact.
The north star, decomposed
“The median and 90th percentile of listing views per person, and the ratio between them — are a typical user and a heavy user close or far apart?”
Far apart: the median person views 4 listings, the 90th percentile views 19 — a 4.75× gap. A thin power core carries the metric.
The loudest channel isn't the best
“Which traffic source's visits turn into agent contacts most often — and is it the same source that sends us the most visits?”
Not the same source. Referral converts best at 36% (paid 18%, organic 9%), while organic sends the most visits — 19,000 of 42,500. Organic was just loud.
The enquiries that vanished
“Rental enquiries dipped — split by city, then Pune by app, then find when the Android ones stopped. Did Android users lose interest, or did the enquiry step stop working?”
Six short questions across the clickstream, the app's enquiry records and the listings: Pune's Android rental enquiries went 42 → 28 → 0 by March, the last on Feb 16 — while views held at about 85 a day. The pattern fits a broken enquiry step, not lost interest. Speeded up — the full conversation took about 45 minutes.
Point Crunch at your marketplace
Add the tag, bring your records, and ask your first question — no analyst, no dashboard, no wait.
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