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Anomalies

Data gone quiet: a stream stopped

Spots a data stream (site events, CRM leads, ad spend) that used to arrive steadily and has now been silent longer than its usual pauses, or dropped sharply in the last full week, while other sources of the project keep sending data. Without this check, a metric that fell to zero looks like a real business drop in reports.

Anomalies

Data gone quiet: a stream stopped

The “Contact form submissions” stream has brought no data since 2026-09-14. That is 14 days in a row, while it normally pauses for about 2 days.

Next step: Check the “GA4 · nordicclean.fi” connection: whether the source changed its export structure, whether access is still valid and whether these events are still being sent.

An example of an insight card. The numbers are made up: in the product, the card shows the numbers of your project. What is inside an insight ↓

When you see this card

  • A data stream (website events, CRM leads or ad spend) has been silent for longer than usual
  • Or the stream still runs but brings clearly less than usual
  • Then the cards where a metric dropped name the data break as the likely cause, not a business failure

What it needs

  • At least one connected stream: a CRM, an ad account or site events
  • Stream history with a steady rhythm

Result type

  • Broken measurement data or tagging does not let you measure the result

Questions it works on

The same idea elsewhere

  • Control charts (SPC) · W. Shewhart

Each data stream has its normal rhythm. Silence longer than usual is a special cause: you look for it, not mistake it for a business drop.

How it works in KO

  • How a KO report works

    A report is a list of sections of fixed types, and the whole team shares one copy of it. This gives the main property: one metric for one period shows the same number in every section and for every person.

What is inside an insight

The card is a short conclusion. A click opens the breakdown: what the conclusion stands on and how far you can trust it.

  • What we know

    Facts with numbers and their source: what changed, by how much, compared with what.

  • Where exactly

    The channels, campaigns, managers or stages where the change is strongest, with a link to the report.

  • Cross-check

    The conclusion is checked against a second signal: confirmed, not confirmed or cannot be checked. Plus what else changed on the same days.

  • We assume

    Likely causes. A hypothesis is labelled as one and never passed off as a fact.

  • We forecast

    Where the period ends if nothing changes.

  • What to do

    The step, what it gives, how to check the result, and the cost of doing nothing.

  • For

    Owner, analyst or agency client: each role sees the cards in its own order.

  • More than one condition behind a card

    To raise one card, KO goes through the slices of your project, including the fields of your CRM, and compares them with the norm of your own project, adjusted for season, holidays and working days. The conclusion is checked against a second signal. When KO finds the root cause, its effects do not show up as separate cards: you see the cause, not ten symptoms.

Demo

Imagine your project is already in KO

The demo is the project of a made-up company, with ads, website and CRM already connected. Open “What to do now” to see what your insights would look like: each with its breakdown, result type and who it is for.

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See what to cut, fix, and scale — using your real data.

Vitaly, co-founder of KO
Vitaly Product & sales
Azat, co-founder of KO
Azat Engineering

You'll meet the founders, not a sales rep — we built KO after years of running growth on broken numbers.

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