Conversion value up 47%,while the costof a conversion fell.
Jakdojade plans public transport journeys in almost 50 cities across Poland and sells mobile tickets in selected ones. It started in 2006 as a student project in Poznań. The campaigns behind it were being judged on app installs, a number that goes up whether or not anyone buys a ticket. Below is what changed when the conversion goals started counting revenue instead.
- +47%
- growth in conversion value
- +6.02%
- growth in total sales value
- -5.83%
- lower cost per conversion
- -7%
- lower cost on the client side
The tracking counted installs while the target was ticket sales.
A budget that did not grow with the target
Selling more tickets month after month on a limited budget puts the whole result on cost control. The study is blunt about the trap: without the right balance between promotion and return, campaigns still generate sales, they do it at the expense of profitability.
The tracking was counting installs
Conversion tracking leaned on the number of app installs and the analytics data underneath it was thin. An install is a cheap thing to buy and a flattering thing to report, and a media mix chosen against it looks efficient while saying nothing about whether a ticket was ever sold.
Ticket sales sat apart from the ads
The purchase feature and the advertising ran as two separate systems. Until sales data and budget decisions meet in one place, no campaign can be judged on the thing it exists for, and nobody can say which part of the spend earned the ticket.
Point the goal at revenue, then let the buying follow it.
Two objectives, kept apart
One set of campaigns went after new users and app installs. A second went after ticket purchases among people who already had the app. Running both against a single goal is how an account pays twice for the same person and files it as growth. The monthly budget stayed where it was. The media mix did not: the previous one had no remarketing in it at all.
The conversion goals were pointed at revenue
Install counts stopped being the target. Conversion goals were redefined around the business indicators that mattered, ticket purchases and revenue, and the list of campaign objectives was narrowed so the Google Ads algorithms stopped receiving signals that pulled against each other. Acquisition and re-engagement were split at the same time, so each could be spoken to differently.
Acquisition was scaled back, engagement was segmented
Spend on new-user campaigns came down so the budget could do more elsewhere. Audiences were segmented by how engaged they already were and the message followed the behaviour, which the study credits with a significant increase in click-through rate and in conversions. That is also what reaches the people who installed the app once and then barely opened it. New ad formats came in alongside.
The data was wired together before it was reported on
Sheets and Looker were integrated and the main Looker dashboard grew new reports. GA4 was reconfigured across the app and the site so transitions into the app could be tracked properly in GTM and through UTM parameters, and traffic sources were verified rather than trusted. The study is careful about the limits here: on the company lead platform the work was education, reporting and minor configuration fixes, not a rebuild.
Value went up, cost went down. That is two pictures, not one.
The study reports the change over what it calls the analysed period and never names the dates, so neither does this page. Conversion value grew 47% and total sales value grew 6.02%. The three figures charted below are the ones that point the same way: every one of them is a cost, and every one of them fell.
Only costs are on that chart, and that is deliberate. This account moved in two directions at once, and a bar chart draws exactly one thing: length. A long bar for +47% and a long bar for -28.8% would sit next to each other meaning opposite things, which is a picture that flatters rather than informs. The two growth figures are not two views of one number either. Conversion value is what the campaigns were credited with. Total sales value is everything the business sold. The study prints 47% and 6.02% side by side and never says how they relate, so each keeps its own label among the headline figures. One thing to carry into the original before you click: its headline compresses the two into sales up 47%, and the body of that same study does not support the reading. Two further figures are off the chart on purpose. Ad visibility rose 253.94% and Viewable CTR rose 777.45%, both credited to starting remarketing, which means the base they grew from was close to nothing. They describe how often an ad was seen and clicked in visible placements, not what came back from it, and set beside a 5.83% change they would squash everything else into a line.
What changed first was the definition, not the budget.
Your campaigns will get very good at whatever your conversion goal counts. Point that goal at app installs and you will buy cheap installs. Point it at purchases and revenue and the same budget goes looking for a different person. That is the whole case, and it is why the counting was rewired before anything was scaled. The study holds back the targeting detail and the budget schedule as sensitive, so what you get here is the mechanism rather than the recipe.
The second half is quieter and costs you nothing to check. Count how many conversion actions your campaigns currently optimise towards. If that list grew by accretion, with an install, a lead form, a newsletter signup and a purchase all marked primary, the system is being handed goals that pull against each other and it will settle the argument by buying whichever is cheapest. Narrowing the list is a settings change, not a project.
Then ask whether your reporting can even see the thing you just started counting. Here that meant GA4 reconfigured across app and site, transitions into the app tracked in GTM and through UTM parameters, and traffic sources verified instead of assumed. A conversion goal your analytics cannot confirm is still a guess, and it will read as a win for months before anybody notices.
This work was delivered by MTA Group, which Zero Fluff Digital is part of, by the same specialists who would work on your account. Every figure here comes from the case study MTA published, republished here with their consent. The reviews behind it are public and verified on Clutch, where clients rate the work rather than the agency describing itself.
Your conversion goal decides what the budget goes looking for.
30 minutes, no deck. You will see what your campaigns are optimising towards right now, and which of your conversion actions is quietly absorbing the budget.
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