Billing says one thing, finance's spreadsheet says another, and the board pack says something else again. So before anyone can make a decision, someone has to work out which number is right, and that can take days.
The real cost isn't the time. It's the decisions made on figures that are slightly wrong: budget going to the wrong channels, forecasts that miss, and problems spotted months after they started.
Your best analysts shouldn't spend the first week of every month making the numbers match.
When revenue, refunds, failed payments and cancellations are recorded in different systems, they never quite line up. Every month end turns into a hunt for the missing £150,000.
OpenByte records every event once, in one place, so the numbers match from the start and month end becomes a formality.
"Which customers make us the most money?" shouldn't be a three-week project.
The questions leadership cares about most cut across teams: which channels bring profitable subscribers, which plans keep people longest, where revenue is leaking. Answering them usually means someone joining data from five systems by hand.
In OpenByte, your marketing, billing, payments and support data is already connected, so the answers are ready when you need them.
Most brands find out about a revenue problem at month end. By then it has already cost them a month.
A processor starts declining more cards. An affiliate starts sending fraud. A price change quietly pushes up cancellations. When data arrives late and in pieces, these problems show up weeks after they started.
OpenByte updates as things happen, so you can spot a change in payments, cancellations or fraud the same day.
Your analysts should be finding insights, not building pipelines.
Most data teams spend more time moving and cleaning data than analysing it. Every new question needs a new connection to another tool, and every connection is one more thing that can break.
OpenByte sends thousands of detailed data points on every subscriber, payment and support conversation into BigQuery, ready to use. Your team can build churn models, forecasts and revenue analysis in the tools they already know.
A forecast is only as good as the data behind it.
When forecasts are built on numbers that don't match, the board learns to add its own margin of error. Every miss makes the next forecast harder to believe.
With accurate, detailed data on every subscriber, you can forecast revenue, cancellations and risk with confidence, and show exactly where every number came from.
How accurate is OpenByte's data?
Can we build our own dashboards and models?
Will this replace our reporting tools?
How does it help finance and leadership?
How does pricing work?
