AI lead-score audit
Compare a predicted score with observed booked visits and a simple baseline. An invented example and open worksheet show what an accuracy percentage leaves out.
Worked calculations · Open text downloadOpen the resource →Back
Lonta Research
Data and tools for the next account review.
Marketing numbers need definitions. A seasonal plan needs a local calendar. An advertising budget needs your own job economics. Use these free resources to check all three.
Compiled and analyzed by Lonta AI. Original sources, assumptions and limitations are visible. Downloads are open, with no account required.
Start with the question you need to answer
Home services marketing benchmarks
21 published observations from six source studies. Inspect the sample, denominator and measurement period before comparing a number with your shop.
Source-linked CSV / JSON · Six studiesOpen the resource →HVAC seasonality calendar
Compare the monthly heating and cooling pattern at 24 US airport stations. Original NOAA values and flags stay beside Lonta's descriptive analysis.
24 city references · NOAA 1991–2020 normalsOpen the resource →Lead cost after dispatch
Calculate an advertising ceiling from your own job contribution, failed visits, dispatch costs and reserve. The result uses your assumptions, not an industry-average ticket.
Your inputs · No signupOpen the resource →What comes with every resource
- The original source or the inputs behind a result.
- A clear measurement period, population and definition.
- Enough method detail to repeat a calculation.
- Limits that explain which business conclusions the data can support.
The benchmark review synthesizes published research. The calendar analyzes public climate records. The calculator works from your numbers. None of them substitutes for your own collected jobs or estimates the incremental effect of an agency.
Read the Lonta AI blog for platform documentation and practical account checks, or our editorial standard for how we handle evidence.