Franchisee Health, who is slipping and how to keep them

What Franchisee Health is

Franchisee Health is the HQ app that answers the retention question before it becomes a departure: which members of your network are slipping, why it looks that way, and what move is most likely to keep each one. Its promise, in the app's own words, is to "see which franchisees are at risk, and the intervention most likely to retain them."

Losing a location is the most expensive event in network economics, and it rarely arrives without a data trail: margin drifting for two quarters, engagement going quiet, contributions thinning out. The trouble is that the trail is spread across four different aggregate views, and nobody reads all four for every location every week. This app does exactly that in one run, and comes back with names, reasons, and a specific move for each.

Where to find it

The app lives on the Member Directory page, the roster home for association-style networks, and leads its Apps row: a dark album-cover tile with the subtitle "Which franchisees are slipping, and how to keep them," a breathing "Live" dot, and a Preview control. The tiles after it in the row are the section's standing tools: the Talk to your Network Analyst and Network Coverage pair, the roster import, and the dues reconcile.

Which networks see it follows which networks have the Member Directory itself: it is an association-side surface, so a franchise HQ, whose roster lives on the Network page, does not carry this section or its app. On the phone, the app appears in the Apps row on the HQ mobile home for association networks, under the same gating; see HQ apps on mobile.

What it reads

The specialist reads your network's franchisee aggregates: margin, activity, engagement, and coverage. These are the same pre-computed rollups the Member Directory and the Network page are built from, refreshed overnight, so the app and the pages always agree. In the app's own words, "it reads only network aggregates, never a franchisee's private data": no invoices, no jobs, no correspondence, nothing from inside a member's own IQ account. That boundary is enforced by the database role HQ runs under, not by instructions to the model; the full story is in what an HQ app can and cannot read.

Before your first run, the card shows a worked example, rows like one location flagged at risk, another steady, engagement marked watch, captioned "This is an example. Your franchisees fill in as locations contribute."

What comes back

A finished Franchisee Health run is a prose finding covering three things per flagged member:

• Who is at risk. The members whose aggregate trail reads like trouble, named the way your roster names them.
• Why it looks that way. The specific driver behind each flag, a margin slide, activity going quiet, engagement dropping off, coverage thinning, rather than a bare risk label. A flag you cannot explain is a flag you cannot act on.
• The retention move for each. The intervention most likely to keep that member, matched to the driver: a different conversation for a margin problem than for a disengagement problem.

The finding lands in the card, saves automatically to your network's history, and can be pinned, reopened for free, and exported as a PDF; see keeping, reopening, and exporting HQ findings. Running it is free, with no Intelligence Unit prompt.

Before your network is contributing

The app carries a standing cold-state line: "Works best once more of your network is contributing. Connect locations from the Members section, and franchisee health fills in." A member who has not connected is largely invisible to the aggregates this app reads, which cuts in a direction worth knowing: your quietest members in the data are often your quietest members in fact, and getting them contributing is itself the first retention read. The Network Coverage tile in the same row tracks exactly that number.

Best-practice example

Ahead of your quarterly member-success review, you run Franchisee Health. The finding names three members: one with margin sliding two quarters straight, one whose activity went quiet six weeks ago, and one flagged only for thinning coverage, likely a data problem rather than a business problem. Three different drivers, three different moves: a benchmarking conversation for the first, a check-in call for the second, and a reconnection nudge for the third. You pin the finding, and next quarter's run tells you which of the three moves worked.

Related articles

• HQ Apps overview
• Member directory overview
• What an HQ app can and cannot read
• Keeping, reopening, and exporting HQ findings

Data sources