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Document & Reporting Automation

Client under NDA

The first ten days of the month stopped going into client reports

An EU digital agency runs SEO, PPC and SMM for several retainer clients. Each of them gets a personal monthly report at the start of the month, assembled by hand from ad platforms and analytics.

Published: 2026-08-24 · updated: 2026-08-24

Printed charts and a calculator on a desk, someone reconciling the figures
Illustrative photo of the working context, not a screenshot of the client's system

  • Time to prepare a monthly report

    10 days → 5 minutes

  • Projects handled by the same team

    +30%

  • Monthly saving on manual work

    ≈$5,000

In short

  • Problem: reporting was assembled by hand and consumed the first 8–10 days of the month, delaying both delivery and payment.
  • Solution: automatic data collection, a single definition of every figure, a draft report from the client's template, and a checklist review.
  • Result: a report takes minutes instead of days, and the agency runs 30% more projects with the same team.
  • Systems: ad platforms, analytics, report templates, e-mail.

Context

  • A full-service digital agency: SEO, PPC and SMM on retainer; name under NDA.
  • Region: EU.
  • Process volume: a monthly report for every client, personalised by the mix of services.
  • Team: channel specialists plus account managers, who were the ones assembling the reports.
  • Systems: ad platforms, analytics tools, report templates; some integrations under NDA.
  • The constraint became visible as the client list grew: reporting time grew linearly, and nobody paid for it — this work is not billed to the client.

Baseline

Baseline metrics with their sources. Without them, any later result has nothing to be compared against.
Losses≈$5,000 a month

The agency's own estimate from their rates

  • 8–10 days a month go into reports instead of projects
  • Approvals drag, and payments move with them
  • Every new client means overtime or a hire
  • Figures in the report disagree between sources
  • Before the work started we fixed: the time to prepare one report, the number of working days at the start of the month spent on reporting, and the number of projects the current team carried.
  • Data source: the agency's own records.
  • Separately we fixed which figures go into a report: until then the same figure was computed differently for different clients, and with no single definition there was nothing to automate.
  • There are no measurement dates or calculation formula behind the numbers, so they are published as reported results.

Diagnosis

Which hypotheses were considered, why this one was chosen, what was assumed, and the condition under which we would have stopped.
  • Three hypotheses were on the table: hire another account manager, buy an off-the-shelf BI tool, or remove the manual assembly.
  • The third was chosen: measurement showed the time went not into commentary but into copying numbers between tabs — work that needs no human.
  • The assumption: a figure that goes into a report can be defined unambiguously for every client. It was tested against past reports — and partly failed: two figures had to be redefined by hand.
  • Stop criterion: if the draft report still needs more than half of it rewritten after data assembly, the automation does not pay for itself and the work stops.

What we implemented

  • Data sources: the ad platform for each channel, analytics tools, internal work records.
  • Business rules: a metric dictionary — one definition across all reports, each with its source named.
  • AI components: a draft commentary on the change, and assembly of the report from the client's template.
  • Integrations: ad platforms, analytics, e-mail.
  • Human checkpoints: a report only reaches the client after a checklist review. Findings and recommendations are signed by the account manager — a person is accountable for them, not a template.
  • Monitoring: the share of reports needing edits is tracked separately. Its rise means a data source has changed and the metric dictionary needs revisiting.

How the process changed

Before

7 steps
  1. Open each channel's platform
  2. Copy the figures into a spreadsheet
  3. Merge and recalculate by hand
  4. Assemble the report from last month's copy
  5. Write the commentary
  6. Get it approved inside the team
  7. Send it to the client

After

5 steps
  1. Data is collected from the sources automatically
  2. Figures are computed from the dictionary — identically for everyone
  3. A draft report from the client's template
  4. A checklist review; the account manager signs the findings
  5. Delivery to the client together with the plan of work

What was stuck

For the first 8–10 days of the month the team assembled reports instead of doing project work. Approvals dragged, payments moved with them, and every new client meant either overtime or a hire.

  1. 1Data is collected from the sources automatically
  2. 2Figures are computed from the dictionary — identically for everyone
  3. 3A draft report from the client's template
  4. 4A checklist review; the account manager signs the findings
  5. 5Delivery to the client together with the plan of work
  6. Measured result

Results

Time to prepare a monthly report

10 days → 5 minutes

Reported by: Agency figures: a before-and-after measurement of the process

Projects handled by the same team

+30%

Reported by: Agency figures: project count compared at unchanged headcount

Monthly saving on manual work

≈$5,000

Reported by: The agency's own estimate from their rates: we saw neither the timesheet nor the calculation, so this is an estimate rather than a measurement

Economic impact

  • The effect is freed account-manager and specialist time that previously went into unbilled work.
  • The saving figure is the agency's own calculation from their rates. We did not verify it: we were shown neither timesheets nor rates, and presenting it as measured would be untrue.
  • Cash cycle sped up as a side effect: the report goes out on the first working day rather than the tenth, and approval and payment move with it.
  • Cost of ownership: the metric dictionary needs maintenance — ad platforms change the metrics they expose, and the report is the first thing to break.

Adoption

  • Reporting stopped being a start-of-month scramble and became an ordinary operation.
  • Clients get a report in a stable format on a predictable date — which mattered more than speed.
  • The solution owner is the agency principal, who also owns the metric dictionary.
«The first 8–10 days of the month used to go into reporting. Now reports assemble in minutes, everything is standardised and transparent, and the team spends its time on client results rather than manual assembly.»

Client under NDA — Agency principal (NDA)

What's next

  • Scaling: the same loop for quarterly and annual reports.
  • Next initiative: proposal preparation — the same data, a different document at the end.
  • What we decided against: letting the system own the findings and recommendations. It drafts the commentary, but a person signs it — a recommendation with no one accountable is worth nothing.

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