Operator guide
Compare lead counts, attempts, response times, bookings and attendance with consistent definitions. Investigate differences before assigning causes.
Short answer
Pull five numbers for each location over the same month: leads received, leads with at least one attempt, median time to first attempt, leads that booked, and booked leads that attended. Use written definitions everywhere. Read left to right; the first column where a location falls behind comparable locations shows where to investigate, not what caused the gap.
Revenue alone cannot show whether a gap occurred before contact, booking or attendance. Review the intermediate records too. This guide is for operators comparing their own locations; franchise corporate teams building a support queue can use the guide to supporting underperforming franchise locations.
One row per location, one month, pulled the same way everywhere.
| Number | How to get it | What it tells you |
|---|---|---|
| Leads received | Count of lead records created in the month | The size of the opportunity |
| Leads with at least one attempt | Count with any outbound call or text logged | Whether the work is happening at all |
| Median time to first attempt | Median of first attempt time minus arrival time | How fast the work happens |
| Leads that booked | Count with an appointment on the schedule | Whether the work converts |
| Booked leads that showed | Count of those appointments attended | Whether the booking was kept |
Two rules make the comparison fair. Use the same definitions at every location, written down, including what counts as an attempt. And use the same month, because seasons can affect locations differently and comparing July with September can mislead. The lead response time guide sets out the timing definitions and why the median is reported instead of the average.
Read the table left to right to locate differences worth checking against individual records.
| Location | Leads | Attempted | Median time | Booked | Showed |
|---|---|---|---|---|---|
| North | 62 | 61 | 8 min | 24 | 19 |
| East | 58 | 34 | 4 hr | 11 | 9 |
| South | 71 | 68 | 12 min | 27 | 14 |
| West | 24 | 23 | 9 min | 9 | 7 |
These are placeholder numbers, written to show how to read the shape.
East attempted 34 of 58 leads, about 59%, compared with North's 61 of 62. Review the unattempted records and timing before attributing the gap to staffing or process.
South recorded 14 attendances from 27 bookings, about 52%. Check cancellations, appointment dates, source mix and confirmation records before choosing a response.
West has 24 leads compared with North's 62, about 39% of the volume, and a similar observed booking rate. That alone does not establish a demand problem or rule out leakage.
North can be a comparison point, provided its service, maturity, source mix and observation window are comparable.
Counting leads without a logged attempt can expose a follow-up or recording gap that revenue totals do not explain. Check existing activity before classifying a lead as unworked.
An attempted rate of 55% is a prompt to inspect eligibility, coverage, duplicates and logging. It does not establish the cheapest fix.
Go in with the table and four questions, in this order. All four are about the system, not the person.
If staff cannot reconstruct a lead's history, investigate the recording and access gap before relying on aggregate comparisons.
One thing, at one location, for one month. Take the location with the lowest attempted rate, not the lowest revenue, and give it a single written rule: every lead gets a first attempt the same day it arrives.
Do not change three things at four locations at once. When the number moves, you will not know which change moved it.
Then sample by hand, once, and decide afterwards whether the reporting gap is worth fixing.
Start with a random sample from the same period at each location and record its size. Thirty records can be an exploratory exercise, but it is not a universal reliability threshold or a guarantee of an afternoon's work. Use a larger or complete dataset before drawing close comparisons.
Use the sample to check record quality too: missing timestamps, duplicate attempts and ineligible leads can distort comparisons.
A sample can identify records to investigate. Similar percentages in a small sample do not establish that locations perform equally.
Check whether the source systems can export the required fields and whether definitions match. Automate a reconciled export where possible, while keeping someone responsible for reviewing exceptions.
Keep the core table readable and add context where it changes interpretation. Avoid ranking managers on raw rates without accounting for source mix and volume. If you need to follow leads past the booking to collected payment, the lead-to-cash guide defines each stage.
Repeat the comparison and inspect the underlying records. An attempted rate rising while response time worsens may reflect coverage, timing or logging changes; it does not prove staff logged bulk attempts.
What it does not do is tell you which location to visit. That is still the job of whoever reads the table.
When follow-up runs through Fynso, the work is done the same way at each location that uses it. Lead follow-up is live in supported configurations: a text or call when a lead arrives, within the contact hours and cadence each location approves, booking against the location's real availability, and handoff to a named person, with each location keeping its own rules. Each attempt, reply, handoff and booking is recorded in one format, with bookings checked against the booking system, so several of these columns come from the record rather than from a spreadsheet. Confirm which fields and reports are available for your systems before you rely on them. How Fynso shows which locations followed up describes the intended view.
Write down what counts as a lead, an attempt, a booking, and an attendance. One page, dated, used at every location.
Leads received, leads with at least one attempt, median time to first attempt, leads that booked, and booked leads that showed.
Compare like for like. Seasons can affect locations differently, so a July compared with a September can mislead.
Stop at the first column where a location falls behind comparable locations, and investigate those records first.
Give the location with the lowest attempted rate a single written rule for a month, then re-run the same five columns.
We will walk through your follow-up, your systems and what Fynso would do, on a discovery call.
Start with the share of leads with at least one logged attempt and the median time to that attempt. A location with normal lead volume and a low attempted rate may be losing leads before booking has a chance, or may not be logging attempts. Check the records to tell which.
Sample by hand once from the same period at each location and record the sample size. Use it to check missing timestamps, duplicates and ineligible leads, then decide whether fixing the reporting gap is worth it. Small samples can point to records to investigate, not prove locations perform equally.
Compare rates and counts, not totals. Lower volume can reflect market size, tracking, lead source or unlogged leads. Check the lead feed and source mix before deciding whether the location needs marketing support or follow-up support.
Monthly for the table and weekly for the count of leads with no attempt at all. The monthly table is for deciding things. The weekly count is an alarm that anyone can read in five seconds.
Eight numbers, the same definitions everywhere, and a fifteen-minute review. A weekly scorecard for multi-location appointment businesses, with what public franchisors track.
At one location, the owner is the system. At three, the system has to work without you in the room. What changes in people, follow-up, numbers and cash, with the research behind each.
This scenario shows a follow-up need your team can review. Fynso can discuss the workflow, available data and connections for your business before agreeing on scope.
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