The synthesis logic behind the tool, the regional datasets it draws from, why a national cleaning protocol does not exist, and the four use-case overlays that translate the regional reading into the work you are actually doing. The protocol I would write for any homeowner in any zip code, in software.
What the Regional Protocol Generator does, in five points:
The honest reason this tool exists: most cleaning advice on the internet assumes a national average that does not exist. The work in San Antonio in August is not the same work as the work in Burlington in January, and a protocol that ignores that produces customers who think their cleaner does not know what they are doing. This tool is the protocol the regional editorial team would write for you, made on demand.
There is a phrase I see in cleaning-product marketing that I have been quietly annoyed by for fifteen years. It is some variant of "the right way to clean windows." Singular article, definite noun, no qualifier. As though there were one right way, applicable everywhere, and the consumer's only remaining decision was which brand of cleaner to put in the spray bottle.
There is not one right way. There are at least fifty right ways, and arguably closer to two hundred — each of them shaped by the water that comes out of the tap, the climate the house sits in, the contaminants that the local weather deposits on the glass, and the housing stock you are actually cleaning. The work in Burlington, Vermont in January is not the work in Austin, Texas in August. A protocol that ignores the regional context produces a customer who thinks their cleaner is incompetent and a homeowner who thinks the product they bought is defective. Neither party is wrong; the protocol is.
The Regional Protocol Generator is the tool we built to produce the right protocol for the region you are actually working in. You pick your state, optionally your city, and the kind of work you are doing. The tool reads the structured regional data we have been compiling for two years, runs a deterministic synthesis, and emits a seven-section document customized to your situation. The synthesis logic is what this methodology piece is about.
There is no national cleaning protocol. There is regional cleaning protocol, applied to a national grid of fifty states, each with its own water chemistry, climate, and contaminant calendar. The cleaning advice that travels well across regions is precisely the advice that is least specific — and least useful.
If you have read any of the regional field notes on this site, this will not be news. Linnea Jorgensen's upper-Midwest piece makes the case for a genuinely interior-only winter and a percarbonate-citric ice-dam-residue protocol that is not in any national cleaning literature. Jerry Davenport's Texas piece makes the case for a sleeve-application protocol on south-facing glass at 130°F and a separate well-water protocol for the Edwards Plateau households. Elly Giordano's Mid-South piece divides Tennessee into three water-chemistry zones with three separate protocols, none of which is the one a national chain would write. None of those protocols travels. None of them needs to. The cleaner in Minneapolis is not trying to clean windows in San Antonio at the same time.
What this tool does is the synthesis a regional contributor would do for you if they were standing in your driveway: read the water, read the climate, read the seasonal contaminants, look at the house, ask what kind of work you are doing, and tell you the protocol that fits. The data we have built into the regional state records is rich enough to do that synthesis in software, which is what the tool is. The methodology is what follows.
The tool asks three questions before it generates anything. State, city, and use case. The order matters and the omissions matter.
State is the foundational regional record. Every state in the dataset carries a water-profile summary (hardness range, dominant source, dominant tier), a climate profile (zone, summer, winter, humidity, extremes), an ordered list of regional contaminants (with seasons and severity ratings), a housing-stock summary, a four-season cleaning calendar, and an assigned author from the editorial roster. The state is what produces the bulk of the protocol's content.
City is an optional refinement. Where a state has more than one major metropolitan supply district — California has six, Texas has at least four, New York has the city-versus-upstate split — the city pick narrows the hardness reading from a statewide range to a specific municipal value. For users in single-supply-district states, or users who do not know their city's hardness profile, the tool falls back to the state's dominant-tier reading and labels the result as the state default. The city pick is not necessary for the tool to produce a useful protocol; it is necessary for the tool to produce the most precise one.
Use case is the question the regional contributor would not need to ask because they would be looking at the work, but the software does need to ask because it cannot see you. There are four use cases — DIY homeowner, working residential cleaner, commercial property work, and heritage residential — and they do not change the chemistry call. The chemistry is the chemistry; the water and the contaminants don't care who you are. What the use case does change is the scheduling, the labor structure, the equipment investment guidance, and (for the heritage case) the special-handling protocol on top of the chemistry. A homeowner in Charlotte and a commercial route operator in Charlotte get the same chemistry call but different protocols on top of it.
What the tool deliberately does not ask is zip code. The decision to skip zip-code-level granularity was made on the grounds that the Hard Water Scorer already exists for that, and it is the right tool for the precise-hardness question. Layering a zip-code lookup into this tool would either duplicate the scorer or fragment the protocol into per-zip variants that the regional data does not support. The right division of labor is: scorer for the precise hardness reading on a specific address; protocol generator for the regional synthesis the customer or the cleaner actually works inside.
The synthesis function in the tool's source code is a single deterministic mapping: structured inputs in, structured protocol document out. The same state plus the same city plus the same use case always produces the same protocol. There is no randomness, no machine-learning inference, no language-model generation. The protocol is composed from a small number of source-data fields and a small number of decision rules.
The decision rules are these:
The chemistry recommendation is selected from the hardness tier. If the city is picked, the chemistry is selected from the city's hardness reading; if no city is picked, the chemistry is selected from the midpoint of the state's hardness range. The five tiers — soft, moderate, hard, very hard, extremely hard — are the USGS classification, used identically across this tool and the Hard Water Scorer so the readings stay in lockstep. The chemistry text for each tier is hand-written, peer-reviewed against the cleaning-supply chemistry literature, and routed through editorial review before it ships.
The climate context is composed from the four climate sub-fields in the state record — summer, winter, humidity profile, and extremes. These are written for each state by the assigned regional author or the editorial team, are reviewed against the NOAA regional climate normals, and are not synthesized from any external API. The tool does not call a weather service; the data is in the regional dataset, by design, because regional patterns are stable enough that real-time weather is not the level of granularity that matters here.
The seasonal contaminant list is taken from the state record and sorted by severity descending, with alphabetical-by-name as the tiebreaker so the display is deterministic. Severity is hand-rated for each contaminant against the editorial-team rubric — severe means "drives a separate scheduling decision," moderate means "a documented but manageable pattern," mild means "a known background pattern most cleaners handle without adjustment." The severity rating is reviewed alongside the contributor's regional beat coverage.
The use-case notes are selected from a fixed library of four overlays, one per use case. Each overlay carries two to four protocol-shaping notes that ride on top of the chemistry recommendation. The DIY overlay focuses on equipment and cadence; the working-cleaner overlay focuses on quoting frequency and pure-water capacity; the commercial overlay focuses on contract structure and interior-winter buffering; the heritage overlay focuses on the no-ammonia / no-acid / no-razor handling envelope and the glazing-putty caution.
The current-season calendar entry is selected from the state's four-season cleaningCalendar field by reading today's date in the user's browser and mapping it to spring, summer, fall, or winter using meteorological boundaries. The other three seasons are shown as a small contextual grid so the year is visible at a glance.
That is the whole synthesis. Five rules, deterministic mapping, no surprises.
The use-case overlay is the part of the synthesis that does the most work to translate a regional reading into a usable protocol. Each overlay is short — two to four notes — because the overlay's job is not to repeat the chemistry but to translate it.
The DIY homeowner overlay is the lightest of the four. It assumes the user is cleaning their own house, owns or can buy a basic squeegee-and-strip-washer kit, has access to a distilled-water gallon from a grocery store, and does not need to think about quoting or labor structure. The protocol-shaping notes here focus on equipment investment proportionality (a DIY user should not be buying a pure-water pole) and on cadence flexibility (most DIY users find quarterly comfortable; monthly is overkill except in extreme-hardness markets). The DIY overlay is the only one of the four that explicitly addresses the question of when to call a pro instead — and the threshold is roughly "extremely hard water plus a multi-story house plus more than thirty exterior windows," at which point the math turns against the DIY approach.
The working residential cleaner overlay is the operational one. It assumes the user is running a route, quoting customers, managing seasonal volume, and amortizing equipment. The protocol-shaping notes focus on quoting the frequency rather than the cleaning (which is how route-based residential work actually monetizes), on planning around the regional contaminant calendar (the highest-volume booking weeks of the year are pollen-driven in most regions), and on pure-water capacity investment economics (a pure-water pole pays back in a season in very-hard or extremely-hard markets; it does not pay back as quickly in soft or moderate markets).
The commercial overlay is the contract-structured one. It assumes the user is doing storefront, office building, or property-management work. The protocol-shaping notes focus on fixed-frequency contract structure (commercial work runs on a service-level agreement rather than per-job pricing), on the labor structure shift to per-pane time targets and route density rather than per-house custom work, and on the interior-winter buffer for seasonally-constrained markets. The chemistry is identical to residential; the operational structure is not.
The heritage residential overlay is the special-handling one and the one that most needs to be on top of the chemistry, not in place of it. It assumes the user is working on pre-1925 stock — single-pane wood-sash glazing with original putty, often hand-glazed glass that is not the same surface as modern float glass. The overlay's protocol-shaping notes are mostly the things not to do: no ammonia, no acid, no razor work, no pressure-washing within six inches of putty, no soaking the wood sash. The conservation-grade special-handling notes come from the IWCA pre-1945 glazing reference set and from the conversations with historic-preservation contractors that have shaped my editorial beat over the past two years. The heritage overlay is the longest of the four — four protocol notes rather than two or three — because the failure modes here are the most expensive and the least obvious.
The tool does not include a price quote. Pricing for residential and commercial cleaning is regional and market-segment-specific to a degree that the tool's input set cannot resolve well. The Cost Estimator is the right tool for the pricing question; the Regional Protocol Generator stops at the protocol.
The tool does not include a real-time weather adjustment. A summer protocol generated on a 65-degree day in central Texas is still the summer protocol; the tool assumes the user can apply common sense around an individual weather event. Coupling the tool to a real-time weather API was considered and rejected on the grounds that regional climate patterns are more stable than the daily weather, and the protocol the tool produces is meant to be a planning document, not a day-of advisory.
The tool does not include a contractor referral. The Find a Cleaner page is where that lives, and the protocol generator is built to coexist with that page rather than to overlap with it. A homeowner who reads the protocol and decides they would rather hire someone clicks to the referral page from the cross-link grid at the bottom of the output.
The tool does not include user input for a non-listed city. If a user's town is not in the state's topCities array, the tool falls back to the state default and clearly labels the result as such. We considered allowing the user to type a city name and resolve it through a fuzzy lookup; we did not implement it because the resulting city would not carry the hardness, utility, sourceType, and neighborhood data that makes the city-specific output useful. The right next step for an unlisted-city user is the Hard Water Scorer, which is keyed on zip code rather than city name and works for any zip in the dataset.
I am going to be honest about why this is tool nine of nine rather than tool one of nine. When we began building the toolkit two years ago, the assumption was that the most valuable tool was the simplest one — the Streak Diagnostic, with two questions and a verdict. The plan was to scale outward through chemistry routing (Tint and Frame Substrate Identifiers), diagnostic decision trees (IGU Self-Check), and only then attempt the regional-synthesis tool, because regional synthesis required the regional data to be built first.
Two years later, the regional data is built. There are fifty state records, each with water profile, climate, contaminants, housing stock, and cleaning calendar; there are several hundred city records with verified hardness readings, utility identifications, neighborhood-level detail, and contaminant notes. The regional contributors — Jerry, Linnea, Tony, Mara, and the editorial team — have written the long-form pieces that document the regional patterns the tool synthesizes. The dataset that makes this tool possible did not exist when the project started; it does now, and the tool is the surface that combines it.
The tool is, in a meaningful sense, what the regional editorial beat is for. The state pages and the city pages are the long-form home of the data; the field-notes articles are the contributor-bylined deep dives; the Regional Protocol Generator is the synthesized output a working cleaner or a homeowner can actually print and use. The first two surfaces are the encyclopedia; this one is the field manual.
It is also the answer to a question I get more often than any other in my own editorial work, which is some variant of "I am about to clean my windows / start a residential route / move to a new state — what do I actually need to know about this region?" The honest answer used to be a thirty-minute phone call or a long email. Now the honest answer is a tool that takes three clicks and produces a printable document. The phone call is still available — through the contact form, through reader correspondence — but the three-click version is the version most readers were always going to use.
Derek Giordano is part of the Giordano Inc. editorial team and covers the Northeast corridor editorial beat for Window Washing Guide. Editorial content is researched and reviewed in collaboration with the Giordano Inc. editorial team and informed by interviews with practicing window-washing operators in the region, plus published trade, IWCA, and historic-glazing references.
Derek Giordano is part of the Giordano Inc. editorial team and covers the Northeast corridor editorial beat for Window Washing Guide, with a particular focus on pre-war and pre-1945 glazing diagnostics and handling protocols. Editorial content is researched and reviewed in collaboration with the Giordano Inc. editorial team and informed by interviews with practicing window-washing operators in the region, plus published trade, IWCA, and historic-glazing references.