What end-to-end analytics reveals: real examples from practice
We collected real reports from different niches. Each block is a specific data slice and an insight that helped make a decision.
End-to-end analytics isn't just a dashboard. It's answers to questions that cost money.
Below is a selection of reports from different projects. Each shows a separate slice: by channel, product, hour, client type, refusal reason. Together they give a full picture of the business.
Each block below is a separate client, a separate niche, a separate period. The reports aren't connected to each other. We deliberately brought them together to show that end-to-end analytics works the same way in any business — construction, services, products, B2B, and B2C. All data is real; company names have been anonymized.
Where the money came from
We see revenue by every ad channel, campaign, and keyword — not clicks, but rubles in the register.
When it's more profitable to sell
Lead conversion changes by hour and day. Reallocating budget without increasing spend gives +20-40% more leads.
Who on the team earns the most
A ranking of specialists by conversion and revenue — not by call count, but by real contribution to profit.
Which product sells better
Conversion of different products differs several-fold. One product closes 69% of the time, another only 14%.
Business overview: visits, leads, sales, revenue
The first thing a manager sees is a summary panel for the period. One screen replaces dozens of tables.
Summary dashboard
The full funnel from first visit to revenue. You can see how metrics changed over time — where the peaks and dips were.
TOP ad channels by revenue
TOP websites by revenue
What time converts best?
Lead conversion varies 7x depending on the hour. This is a direct lever for managing the ad budget.
Lead conversion by hour of day
582 leads, 2,667 visits, 400,370 ₽ spend. Conversion is lower in the morning, higher during the day, and the most effective hour is 15:00-15:59.
Conversion by hour (top and outliers)
Which product sells best?
Conversion of different products differs 5x. This report changes priorities in advertising and scripts.
Sales and conversion by product
116 sales, 21,236,227 ₽ revenue. Overall conversion is 20%, but individual items range from 14% to 100%.
You can track anyone: site foreman, surveyor, manager, specialist
The system isn't limited to sales managers. Any role in the chain — foreman, tech specialist, surveyor — is linked to the deal and shows its own contribution to revenue. Below are two real examples from different niches.
Foreman efficiency: revenue and average check
8 sales, 107,700 ₽ revenue. Each foreman is linked to their deals — you can see who works fast and who has a long cycle.
Tech specialist efficiency: conversion and revenue
364 leads, 116 sales, 21,236,227 ₽. Same principle — different role, different niche, different scale. The analytics work the same way.
Whether it's a foreman on-site or a tech specialist on a call-out — the system records their involvement in the deal and shows their real contribution to revenue. This changes the culture of evaluation: not 'how many times they went out,' but 'how much they earned for the company.'
It works in sports too — take padel clubs
The same principle applies to sports projects. In jetypadel we track:
- 🏟️ Courts — booking load and conversion for every court and time slot
- 🧑🏫 Trainers — conversion and revenue per trainer: session bookings and membership renewals
- 🛍️ Product sales — sales of rackets, gear, and accessories — which items actually bring in revenue
New, repeat, outbound: who buys better?
Different client types have different conversion, average check, and deal cycle. This changes the strategy for working with the client base.
Inquiries by client type
3,446 inquiries, 776 sales, 163,758,487 ₽ revenue. Repeat clients are the main asset.
Leads by inquiry type over time
Repeat leads consistently dominate by volume, and all three channels dip sharply during a certain period and then recover.
Why don't clients buy?
This report is a direct signal for product and marketing improvements. Without it, 'refusals' are just lost money.
Refusal reasons — 415 deals
Almost every other refusal is 'changed their mind.' This is a signal not about price, but about nurturing: the client wasn't ready to buy.
What to do with each refusal type
Implement nurture emails, improve content before the lead
Automatic callbacks, SMS after a missed call
Cleaning up keywords and ad targeting
Set up deduplication in the CRM — saves managers' time
Which day of the week converts better?
Lead volume and conversion by day of week don't always match. Sunday brings in almost as many leads as Monday — but converts far worse.
Leads and sales by day of week
4,178 leads, 55 sales, 4,724,930 ₽ revenue. Weekdays and weekends show very different conversion.
How much does a target lead cost?
Regular CPL counts every lead in a row. Target CPL counts only those who are actually interested in the company's product — the difference between channels can be several-fold.
Why a low CPL doesn't mean profitable
Two channels, the same budget — completely different results once you look past the raw CPL.
Target CPL by channel group
442 target leads, 144 sales, 32,235,449 ₽ revenue. Target CPL varies several-fold between channel groups.
Full lead cost: ad budget vs. ad budget + team salary
The owner can view either number: the full cost with team salary, or just the ad budget. Each answers a different question.
Team salary behind the channels
Target CPL: ad budget vs. full cost
Comparing channels? Use 993 ₽. Assessing total spend? Use 1,921 ₽ — salary is fixed and not tied to a single channel.
How long does it take for a lead to become a sale?
A separate cut from the deal funnel: what share of sales closes on which day since the lead came in. This is a planning tool, not part of the main dashboard.
Cumulative conversion into sales by deal cycle
Shows what share of all sales has already closed by each day since the lead was created.
What you get from day one
End-to-end analytics isn't reports for the sake of reports. Every data slice answers a specific business question.
Revenue by channel and campaign
You see which ad ruble brought real money, not just clicks. Without this, optimizing budget is impossible.
Best time for advertising
Conversion changes 7x by hour. The right ad schedule lowers CPL without cutting reach.
Top products and weak items
One product sells at 69% conversion, another at 14%. Budget goes where the real return is.
The value of repeat clients
39% vs 12% conversion. The data proves retention is more profitable than new client acquisition.
Team ranking in money
Specialist conversion ranges from 27% to 48%. This data is for training, motivation, and lead distribution.
Why they don't buy
43% of refusals aren't about price or competitors, but 'changed their mind.' This is a task for content marketing and nurturing.
The best days for advertising
Monday and Tuesday convert several times better than the weekend. That's a direct lever for the ad schedule.
The real cost of a client
Target CPL shows which channel actually brings clients, not just cheap, irrelevant leads.