Reporting time fellfrom 30 hours a monthto around seven.
GetResponse sells marketing automation software to more than 350,000 customers in 183 countries. Its paid search ran on 11 Google Ads accounts, the global one alone held 201 campaigns, and 10 teams inside the company each expected a report built for them. The study behind this page measures the work in hours and account counts. It reports no revenue figure, and this page does not invent one.
- 11 → 3
- Google Ads accounts after the consolidation
- 201 → 114
- campaigns on the global advertising account
- 30 → 7 h
- monthly reporting time, from the worst month to a typical one
- 10
- client teams reading one reporting tool in place of separate reports
Eleven accounts, ten teams, and a report owed to each.
Two hundred campaigns with no shared logic
More than 200 campaigns ran in Google Ads, grouped by theme, with nothing tying a budget to what a customer from that market was worth. Working out the goal of any single campaign took time, and a consistent view of the whole account took longer.
Reporting ate the strategy time
Ten teams on the client side each expected a tailored report. Building them grew into a standing workload that pulled attention away from the decisions those reports were meant to support.
Every channel measured itself
Each advertising platform ran its own tracking, and the landing pages were not connected to one another. With no shared reporting model, comparing channels meant reconciling numbers that were never built to match.
Name everything the same way, then rebuild what the names describe.
One naming convention across every account
Campaign names were standardised, along with the method for managing and analysing PPC work. Consistent names are what let a single dashboard read every account, and they made the client’s rebilling simpler as a side effect.
One reporting tool in place of many reports
The separate team reports were replaced by one tool covering all activity, with dashboards every team could read. A second dashboard tracked spend by channel. Reporting in real time let the specialists react faster and gave the client one view of performance.
Non-brand search split by what a customer is worth
The old non-brand structure was split mainly by geography. English-language campaigns moved into seven tiers by target customer acquisition cost, estimated from average revenue per country and a standard conversion rate, with a tCPA set in each. Keywords were grouped by the feature people searched for, such as email marketing or automation, because each feature can carry a different lifetime value.
Tracking unified across the paid channels
Landing pages were rebuilt as one shared system with event and conversion tracking on top. Measurement for Google Ads and Facebook Ads, with LinkedIn Ads alongside, was brought into one environment. Older Facebook campaigns were audited and given only the adjustments they needed.
The study counts hours and accounts. It never counts revenue.
The chart shows monthly reporting time at its heaviest and after the change. Accounts and campaigns sit in the strip above, because a count of campaigns and a count of hours do not share a scale.
Read the gap with its limits. The first bar is the worst month and the second is a typical one, so the fall is larger than the change in an average month would be. The source page also shows reporting time month by month, with no scale on the hours axis. In it, the share of time spent on reports climbs for several months before it drops, which fits a rebuild that cost time before it saved any. The study says the changes led to stronger campaign performance and gives no number for that, so this page makes no such claim. The hours are the result on record.
Ten teams asking for ten reports is a cost you already pay.
A naming convention looks like housekeeping, and here it carried the rest of the work. Once every campaign in every account followed one pattern, one dashboard could read all of them and each team could filter its own view. If your account structure needs a specific person to explain it, every report you build on top of it needs that person too.
The structural lesson is about what a campaign split is for. Splitting non-brand search by country tells you where a click came from. Splitting it by the acquisition cost a market can carry, and by the feature someone searched for, tells your bidding what that click is worth to you. You need revenue per market and a conversion rate you trust to set those tiers, so your measurement has to be unified before your structure can follow it.
Count the hours your team spends assembling reports for one month. That figure is the first thing a cleaner account pays back, and it is the one most teams have never written down.
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.
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