7 Questions Your Jobber Dashboard Can't Answer (But You Ask Every Monday)

Jobber's reporting scored 5 out of 10 in a 2026 independent review, with reviewers calling out no custom report builder, no revenue forecasting, and no technician performance dashboards. [fieldcamp review]

That is why every Monday you open Jobber Insights, stare at the dashboard, and still text your bookkeeper the same three questions.

You do not need another dashboard. You need the answers. Instead of building, maintaining, and logging into a report, you text Sully a question and get the answer in 10 seconds. It pulls from Jobber plus QuickBooks, Gmail, and your ad platforms at the same time.

Below are seven questions your Jobber dashboard cannot answer today, each paired with the Sully prompt that does.

1. What is my true profit per job, including labor burden and card fees?

Jobber's job costing shows price minus labor, materials, and expenses entered manually. It does not subtract payroll taxes, workers comp, insurance allocation, fuel burden, or the 2.9% plus 30 cents you pay Jobber Payments on every card swipe. [Jobber Help Center: Job Costing]

Labor burden alone typically adds 20 to 30 percent on top of base wages. On a $1,200 install with $400 in direct labor, that is another $80 to $120 you never see on the Jobber profit bar.

What you actually need: profit after all real costs, rolled up by service type, technician, and month. Jobber cannot give you that without an export to Excel and some manual math. Our breakdown on AI quoting and estimating for contractors walks through how operators build the full cost picture.

Text Sully: "Show me my real profit margin on every job last month after labor burden, card fees, and material markup. Group by service type."

2. Which lead source actually produced booked revenue last quarter?

Jobber's Insights Dashboard shows requests by source if you remember to tag them, and it shows revenue totals. It does not tie the two together. You cannot see "Angi sent 40 leads, 8 became jobs, totaling $24,000 in revenue" without exporting and joining data yourself. [Jobber community: Job Costing discussion]

That matters because Invoca's 2025 Home Services Call Conversion Report found the industry converts at a 46 percent rate across 60 million phone calls, but the range between top and bottom lead sources is massive. [Invoca 2025 report]

Without source-to-revenue attribution, you spend blind. You need booked revenue per source, cost per acquisition, and average job value per source, all in one view.

Text Sully: "How much booked revenue did each lead source produce in Q1? Show me cost per booked job and average ticket by source."

3. What is my CSR booking rate, and who is my worst booker this week?

Call-center KPIs are the core of operator culture at shops like Wilson Companies and A1 Garage Door. John Wilson on the Owned and Operated podcast puts it plainly: every role should have a number, and booking rate is the number for the office. [Owned and Operated: Call Center KPIs]

Jobber does not track booking rate. It tracks requests and quotes and jobs, but it has no concept of "rang, booked, or not booked" because it is not a call platform. If you route calls through a tracking number, that data lives somewhere else entirely.

The question you actually want answered every week: of the 180 calls we took this week, how many became jobs, and which CSR is dragging the team down? Jobber's dashboard has none of the inputs.

Text Sully: "What was our call booking rate by CSR last week? Flag anyone below 60 percent."

4. Which customers are likely to cancel their maintenance plan in the next 60 days?

Customer lifetime value and churn prediction are not features Jobber has ever shipped. Jobber's public feature list includes no churn model, no renewal risk flag, and no CLV view. [Jobber features]

A contractor on the Jobber community wrote that they wanted better profitability and revenue analytics and got "analytics are relatively shallow. If you need deep job costing, multi-location rollups, or custom dashboards, you may find it limiting." [getonecrew Jobber review]

For a $2M plumber with 600 plan members, spotting the 40 at risk of cancelling next month is the difference between a flat renewal year and a contracting one. That requires reading contract history, last visit date, payment status, and complaint notes together. Jobber stores all four but connects none of them.

Text Sully: "Give me the 20 maintenance plan customers most likely to cancel next quarter. Show last visit, payment history, and any unresolved complaints."

5. Why did revenue dip this month compared to last March?

Jobber Insights shows revenue over time. It does not tell you why. The dashboard cannot decompose a revenue drop into "fewer leads," "lower close rate," "smaller average ticket," or "a specific technician had a bad month."

Jobber has no revenue forecasting and no variance analysis. You get a line that goes down, and you are left to open seven tabs and figure out the cause yourself. [fieldcamp Jobber review]

Jack Carr on the Owned and Operated podcast talks about this as the dispatcher's dilemma: you need the diagnosis, not the chart. The chart is table stakes. This is the same pattern we cover in AI dispatcher build vs buy for home services.

Text Sully: "March revenue was down 14 percent versus last March. Break down the gap by leads, close rate, and average ticket. Identify the biggest single contributor."

6. Which of my unpaid invoices are actually collectible, and which are dead?

Jobber shows an aging invoice list. That is a flat table. It does not rank invoices by collectibility, does not suggest which customers have a history of paying after reminder 3 versus reminder 1, and does not surface invoices where the customer has already disputed.

Bad debt for home service businesses typically runs 1 to 3 percent of revenue. On $2M that is $20,000 to $60,000 a year. Jobber's dashboard cannot tell you which $40,000 worth of invoices will land in that bucket.

You want a ranked list: probability of collection, recommended action, and days outstanding. That requires reading Jobber plus your email thread history plus customer payment behavior. Jobber owns only the first.

Text Sully: "Rank my unpaid invoices by collection probability. For each, tell me the recommended next action and estimate how much I will actually recover."

7. Is my QuickBooks data actually matching my Jobber data, and where is it wrong?

This one is painful because the answer is usually no. Independent reviewers report that Jobber's QuickBooks integration drops roughly 2 percent of line items during sync, with auto-sync frequently breaking and users abandoning the integration entirely. [getonecrew Jobber review]

Two percent of line items sounds small until you are a $3M contractor and that is $60,000 of revenue your accountant has in one system and not the other.

Jobber's dashboard does not reconcile. It shows Jobber numbers. QuickBooks shows QuickBooks numbers. The gap between them is where your tax return breaks.

Our Jobber AI Receptionist review covers the broader pattern of Jobber features that are sharp inside Jobber and weak at the boundary. Reporting is the clearest example.

Text Sully: "Find every invoice in Jobber last month that did not match QuickBooks. Show me the dollar gap and which line items dropped."

The meta-issue: Jobber was built for one-off jobs, not operating data

Every limitation above traces back to the same design decision. Jobber was built to manage a job lifecycle: request, quote, schedule, invoice, get paid. It is excellent at that.

Business intelligence is a different product. BI needs rollups, joins, time-series decomposition, and cross-system reads. Jobber ships none of those because it was never meant to. A contractor on getonecrew summarized it: "If you need deep job costing, multi-location rollups, or custom dashboards, you may find it limiting." [getonecrew Jobber review]

Jobber's own response to this gap has been Insights Dashboard and 20-plus built-in reports. That is a real effort. It is also a thin layer on a system that does not have the underlying data model to support real operator questions.

The workaround most contractors land on is a spreadsheet, a VA, and a Monday ritual. That worked at $500K. It does not scale past $2M.

Why dashboards keep failing this job

Jobber's team is not asleep. They ship meaningful features and have 250,000 businesses on the platform. [Jobber pricing]

The ceiling is structural. Dashboards answer the questions you anticipated when you built them. They do not answer the question you have on Monday morning, which is always a little different from the question you had last Monday.

Adding a custom report builder solves part of this, but building a new report takes 20 minutes and the question has already moved on. The real fix is to stop building reports and just ask. That is the Sully pattern. You text a question, Sully reads Jobber plus QuickBooks plus your ad accounts plus your email, and you get a paragraph answer in 10 seconds.

You keep Jobber. You keep your workflow. You drop the Monday dashboard ritual.

For a typical $2M contractor running Jobber, the 7 questions above come up every single week. Building 7 dashboards that answer them costs roughly 40 hours of setup plus ongoing maintenance. Most shops never finish the project. The ones who do end up with dashboards that answered last year's question, not this week's.

Sully replaces that entire pattern. The questions above are asked and answered in text, in seconds, against live Jobber data plus every other tool you actually use to run the shop.

See Sully in action at sull.ai.