How to automate client reporting.

Most agencies describe the job as building a dashboard. That is the last step and it is the easy one. What takes the time is everything before it: logging into each platform, exporting, pasting into a master sheet, reconciling the names and the currencies and the date grains by hand, then building the report and sending it.

Then next month, doing all of it again. The work is not hard. It is repetitive, it happens on a deadline, and it is the reason reporting is the first thing that slips when a roster grows.

There is no single tool and no single hire. Getting from platforms to a number you can trust breaks into five separate kinds of work, and each one is a different specialism.

• Collecting

  Connector maintenance, auth flows, API quirks and backfills. Bought as a connector product, or hired as a data engineer.

• Storing

  A warehouse, a region, access control and cost control. Cloud spend, plus somebody to own it.

• Cleaning up

  Modelling raw exports into consistent tables. This is the step everything after it depends on, and it is an analytics engineer's job.

• Reporting

  Dashboards people actually open, per client. A template library, or a BI developer.

• Watching it

  Knowing when a number moved or a sync never arrived. An alerting tool, or somebody opening dashboards every morning.

Cleaning up is the one that gets left out, because connecting a platform produces a table immediately and it looks like the job is done. It is not. The same metric arrives from three platforms under three names, in three types, at three different grains, in three currencies.

Put two of those in one report without reconciling them and the totals disagree. Ask an AI about them and it answers confidently and wrongly, because nothing in the data tells it that two columns are the same thing. Every hour spent on dashboards before this step is done is an hour spent on a report somebody will later stop trusting.

Two questions settle most of it. How many clients do you report on, and how many platforms does each one run? Below about five clients on two or three platforms each, a careful spreadsheet and a monthly afternoon is genuinely the right answer, and any tool is overhead.

Above that, the cost stops being the hours and starts being the inconsistency: two people producing the same number differently, and a client noticing before you do. That is the point at which it is worth buying or building the five pieces above, and the order to do them in is the order they are listed.

SightShark runs all five, into a data warehouse you own rather than one we hold. It ingests from 200+ platforms on a daily schedule, models the data inside your own cloud project, builds the reports from templates assigned per client, and watches every client for a threshold, a change, or data that never arrived. Each client sees only their own data, whether they log in to your portal or open a dashboard you share with them.

If you would rather assemble the five yourself, the list above is the honest shape of it. If you would rather not, that is what this is.