Reporting & Analytics
AI referral traffic: measuring the visitor ChatGPT sends you
Spotting an assistant-driven visit inside your CRM is a separate job. Referrer patterns, hidden fields, the points where the attribution chain snaps, and double counting.
Custom dashboards: who should see which number?
Reps, managers, executives, marketing and finance each need a different screen. Here is how to decide what earns a tile, what belongs in a report and who sees which rows.
Shared report links: a safer way to send reports to clients
How to retire screenshots and PDF attachments in favour of a report link that carries a password, an expiry date, a view limit and a revoke button you control.
Asking for reports in plain language: getting data without SQL
How a single sentence turns into a query, which questions a plain-language layer answers well, and the three checks that keep a fast number honest in a meeting.
Scheduled reports: the summary that lands on Monday morning
A four-line summary at 8:00 on Monday reaches the desk before the week is planned. Metric selection, send time, recipient lists and alert thresholds, in order.
Report anomaly alerts: knowing when the numbers break
A Tuesday morning alert and a silently broken integration behind it: how to build anomaly alerting as an early warning system instead of another source of noise.
Churn risk score: seeing customers before they leave
An account silent for forty-one days with a renewal fifty-five days out: a field guide to building a churn risk score, from signal choice to thresholds and backtesting.
Call queue metrics: measuring the caller who is waiting
Turn the waiting queue from a gut feeling into a measurement: thresholds, abandonment, percentiles and shift planning, with the rule each number triggers.
Customer profitability analysis: who actually makes you money
The account at the top of your revenue list is rarely at the top of your profit list. Build a view that counts discounts, cost to serve and payment delay.
Variance analysis: the reason behind plan versus actual
Revenue under plan tells you nothing on its own. Split the gap into volume, price and mix, separate timing from permanence, and attach an owner to each cause.
Internal benchmarking: comparing against your own data
Stop measuring yourself against industry averages you cannot verify. Pick a reference point inside your own data, slice it properly, and act on the gap you find.
A metric dictionary: making everyone read the same number
Why one screen yields two numbers, and how to stop it: numerator, denominator, time window and filters, plus a two-week build for a working metric dictionary.
Inventory turnover and stock aging analysis
Inventory turnover and aging reports reveal the cash parked in your warehouse. Learn the formula, the age buckets, and how to clear slow-moving stock.
The GEO Dashboard: Which KPIs Matter for AI Visibility
Which KPIs really matter for AI visibility? Learn to read share of voice, citation rate, question coverage and the competitor gap, and skip vanity metrics.
Measuring AI Traffic: Seeing ChatGPT and Perplexity Visits in GA4
Visitors from AI search are hiding in your analytics. Learn to find AI traffic in GA4, split it into its own channel, and read the real limits of a click.
Building your own sales reports with a custom report builder
Choose dimensions, measures and filters to assemble your own sales report in minutes, then save, schedule and share it before anyone even asks.
How to build a sales report: KPIs and examples
Move from a wall of numbers nobody reads to a report that drives decisions. KPI selection, structure, cadence, audience and the mistakes to avoid.
Call center KPIs: AHT, occupancy and service level (SLA)
Service level, AHT, occupancy, abandonment, and first call resolution explained: what call center KPIs measure and why you balance them instead of maxing one.
Demand forecasting: aligning stock and sales on one dataset
Demand forecasting predicts how much you'll sell so stock, purchasing and cash stay aligned. How it differs from sales forecasting, and how to start simple.
What is RevOps (revenue operations)? Uniting sales, marketing and success
RevOps unites marketing, sales and customer success under one revenue engine. Here is what it is, why it matters and how a small team can build it — no silos.
Revenue intelligence: forecasting from conversation and pipeline data
Revenue intelligence turns conversation and pipeline data into a forward-looking forecast — how it differs from a dashboard, its signals, and where to start.
Forecast accuracy: how close are your sales predictions?
A practical way to measure the gap between your sales forecast and what actually happens, and the steps that close it over time.
Average deal size: how to measure and grow it
How to calculate average deal size correctly, why the average can mislead without the median, and how bundling, upsell, and ICP targeting grow it.
Customer concentration risk: when revenue leans on one client
Learn how to measure revenue concentration, spot the "one whale" problem early, and diversify before one client controls your business.