Franchise Decision Radar

Methodology

How this data is sourced, extracted, modeled, and presented — and why it looks different from what you’ll find elsewhere.

Data Source

Every data point on this site originates from Franchise Disclosure Documents (FDDs) filed with the Wisconsin Department of Financial Institutions. Wisconsin requires annual franchise registration with a complete FDD. These filings are public records.

We use regulator-filed PDFs — not franchisor-provided summaries, third-party databases, or marketing materials. The FDD is the legal disclosure document a franchisor is required to give prospective buyers before any money changes hands.

Why Wisconsin?
Wisconsin is one of a small number of states that requires franchise registration and makes filed FDDs publicly accessible. This gives us a single, consistent source for comparing brands that sell franchises in the same state under the same regulatory requirements.

What We Extract

From each FDD, we extract structured data from specific disclosure items:

FDD Item What It Contains What We Use It For
Item 5 Initial franchise fee Cost to enter comparison
Item 6 Other ongoing fees (royalty, marketing, technology, etc.) Fee burden modeling
Item 7 Estimated initial investment range Startup cost comparison
Item 19 Financial performance representations (optional) Decision Reports (paid)
Item 20 Outlet counts: openings, closings, transfers by year System health comparison

Every extracted value includes provenance: the filing year, source state, page number, and specific item or table reference. If a value cannot be cleanly extracted, it is recorded as unavailable with a note explaining why — we do not infer or fabricate data.

Three Layers of Data

We separate raw facts from derived metrics from editorial assessments. Each is tagged so you always know what you’re looking at.

Extracted Pulled directly from the FDD. Page-level provenance. Modeled Computed from FDD terms using stated assumptions. Editorial Evidence-based assessment. Always flagged.

Extracted data

Direct values from the disclosure document: franchise fees, investment ranges, outlet counts, royalty rates. These are facts as stated in the filing. No interpretation applied.

Modeled data

Computed values where the FDD provides the terms but not the total. The primary example is fee burden modeling: we take each brand’s royalty rate, marketing requirements, technology fees, and other mandatory costs, then compute total annual ongoing fees at standard revenue levels ($200K, $300K, $400K, $500K).

Fee model assumptions: Year 5 · Single territory · 1 owner + 1 technician · Even revenue distribution · All mandatory fees enforced

Included: Mandatory recurring fees — royalty, marketing/ad fund, technology, call center, convention, website, mandatory bookkeeping/sales center

Excluded: One-time fees, optional programs, business operating costs, variable per-sale charges

Where a fee has a range (e.g., bookkeeping $200–$500/month), we model at the low end and disclose the range. Modeled values are always tagged and the assumptions are stated on the page where they appear.

Editorial assessments

Qualitative judgments — watchouts, positive signals, disclosure quality ratings — are clearly labeled as editorial. They are evidence-based (citing specific FDD sections) but represent our assessment, not extracted facts.

What We Do Not Do

Category Selection

We cover recurring residential service franchises — territory-based, homeowner-facing businesses with recurring or seasonal revenue. Categories are selected based on:

We do not pursue breadth for its own sake. A category with 30 brands but high model drift is less useful than a category with 6 tightly comparable brands.

Decision Reports

The free comparison pages show what differs across brands. The paid Decision Reports ($99/brand) explain so what and what to ask about it. Each report is a self-contained, print-ready PDF covering 13 sections:

Report standards

Every Decision Report follows the same analytical standards as the free site:

Ready to compare franchise brands using regulator-source data?

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