Track your KPIs against target — straight from a spreadsheet.

What KPI tracking software should do

Every team has a handful of numbers that decide whether the month went well — revenue, conversion, churn, utilisation, lead time, NPS. KPI tracking is the discipline of watching those numbers against where they should be, and noticing fast when they move.

The trouble is that most teams "track" KPIs in a spreadsheet that someone updates by hand and a chat message that says "we're a bit behind on pipeline." Dedicated KPI tools fix that, but many of them want you to wire up connectors, model the data, and learn a new interface before a single number appears.

DataHub Pro keeps the spreadsheet as the source of truth and does the tracking on top of it. Upload your metrics and it builds KPI tiles, compares actuals to targets, charts the trend, projects the forecast and flags the anomalies. You get a living KPI dashboard without giving up the spreadsheet your data already lives in.

What you get out of the box

Six things that turn a metrics spreadsheet into proper KPI tracking.

How to start tracking KPIs in three steps

Step 1 — Upload your metrics

Drag in an Excel or CSV file with your KPIs — ideally with a target column alongside each actual. Or connect a live source so the data keeps flowing. The platform reads the columns and infers what's a metric, a date and a target.

Step 2 — Set targets and thresholds

Confirm the auto-selected KPIs, point each one at its target, and set any alert thresholds. The dashboard immediately shows actual-vs-target, variance and trend for every metric.

Step 3 — Watch, get alerted, share

From here it runs itself: scheduled refresh keeps it current, anomaly detection flags drift, and you share the dashboard or schedule a KPI report. You move from manually updating a sheet to being told when a number needs attention.

Who tracks KPIs here

KPI tracking earns its place wherever a team is accountable to a number:

• Founders and operators watching the company scorecard — growth, burn, retention — without standing up a data stack. See the startup workflow.
• Finance teams tracking budget vs actual, cash and margin against plan, with variance and anomaly flags. More in the finance teams guide.
• Sales and marketing leads tracking pipeline, conversion, CAC and channel performance against quarterly targets.
• Operations managers tracking throughput, cycle time, SLA and utilisation against thresholds, with alerts when they slip.

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KPIs teams track on day one

The best way to picture KPI tracking is to look at the scorecards teams actually build. Each of these starts from a spreadsheet the team already maintains and becomes a living dashboard that watches itself.

The company scorecard

Founders and leadership track a short list of numbers that define the business — monthly recurring revenue, new customers, churn, cash runway, gross margin. Upload them with their targets and the dashboard shows each one against goal, the trend, and a forecast to period-end. Anomaly detection flags the month something broke from the pattern, so leadership reacts to a dip while it's still small rather than explaining it in the next board meeting.

Sales targets

Sales leaders track pipeline value, win rate, average deal size and quota attainment against quarterly targets. With a target column alongside each actual, every rep and region shows percentage-to-goal and pace, and the forecast tells you mid-quarter whether the number is on track. The weekly sales review opens one shared dashboard instead of reconciling competing spreadsheets.

Budget vs actual for finance

Finance tracks spend and revenue against budget line by line, with variance tiles surfacing the biggest gaps and anomaly flags catching the unexpected. Because every figure carries an auditable trace, the variance you present is one you can defend. The finance teams workflow goes deeper into the month-end loop.

Marketing performance

Marketing leads track CAC, conversion rate, channel ROI and pipeline contribution against plan. Connect the ad-platform or analytics export, set thresholds, and the dashboard alerts when a channel's cost-per-acquisition drifts above target — early enough to reallocate budget before the quarter is spent.

Operational SLAs

Operations teams track throughput, cycle time, SLA compliance and utilisation against thresholds. The dashboard's anomaly detection and target-vs-actual tiles turn a wall of operational numbers into a short list of "things that need attention today." Instead of poring over a report, the manager is told where to look.

In each case the shift is the same: the team stops manually updating a tracking sheet and refreshing it from memory, and starts running a dashboard that pulls the latest data on a schedule, compares it to target, and raises its hand when a number moves. KPI tracking becomes something the software does, not a task on someone's list.

Why DataHub Pro for KPI tracking

Plenty of KPI dashboards exist. Two things make DataHub Pro the practical choice for a team that lives in spreadsheets.

Your data stays where it is. You don't migrate your metrics into a proprietary system or wire up a dozen connectors before you see a number. The spreadsheet — or a connected source like Google Sheets — remains the source of truth, and the KPI dashboard builds on top of it. Setup is minutes, not a project.

And the numbers are trustworthy. When you ask the AI a question about a KPI, the platform runs real operations on your file and shows the trace behind the answer, so the figure on the tile is auditable, not generated. That auditability is the same engine behind our BI and automated reporting features.

Pricing is published, flat and cheap — and you can start free. Comparing the incumbents for KPI work? See Power BI, Tableau and Looker Studio.

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