Your listings tool says every location is healthy. It cannot tell you which market is losing money.
Bluefrog treats local listings, citations and reviews as a data source, not a standalone service. We pull location-level visibility and review signal into the same model that holds your calls, leads, booked jobs and revenue — so a multi-location operator can see which markets' visibility problems are actually costing money, and which ones are cosmetic.
Listings tools measure listings.
Nobody measures what the listings did.
Every category in local marketing has good tooling. What almost nobody has is the join between that tooling and the operational system where revenue is recorded.
A listings platform is very good at one job: pushing consistent name, address, phone, hours and category data out to a network of directories and telling you when something drifts. That is real work and it is worth doing. But the output is a compliance score. It answers “are we published correctly?” It does not answer “is the Tucson market underperforming because our visibility there collapsed, or because two technicians quit?”
Those are different questions and they need different data. Listing accuracy, profile completeness, photo and post recency, review volume, review velocity and sentiment all live in marketing tools. Calls, booked jobs, average ticket and completed revenue live in the CRM or field service system. Between them sits a translation layer nobody owns — so the listings report gets read once a month, nodded at, and filed.
Bluefrog builds that translation layer. We ingest listing and reputation data per location, normalize it against your own location roster, and attach it to the record of what each market actually produced. That is the same thing we do with organic search data and paid channels in marketing intelligence — local visibility is just another input to the same connected model.
Where the local data comes from.
We integrate with the platforms you already use rather than replacing them. If your team likes its listings vendor, keep it — we read from it.
Google Business Profile
The heaviest signal in local. We integrate with Google's APIs to work with profile content, posts, questions and answers, reviews and profile performance data per location — then hold that history so change over time is visible, not just today's snapshot.
Yext
Where a client runs Yext as the distribution layer for listing data, we integrate with its API to read location records, publishing status and directory coverage, and bring that state into the platform alongside operational data.
BrightLocal
Citation tracking, audit results and local ranking data are useful inputs to a revenue model. We integrate with BrightLocal's API where a client subscribes, so audit findings can be scored against market performance instead of read in isolation.
Data Axle
Data Axle (formerly Infogroup) is one of the underlying business-data aggregators that feeds large parts of the local ecosystem. Where a client has access, we integrate with it to check how core business records propagate and where stale data keeps reappearing.
Apple Business Connect
Apple Maps is a quiet but real source of local discovery, especially for mobile and in-car navigation. We treat Apple Business Connect location data as another coverage surface to monitor for accuracy and completeness per market.
Review platforms
Google reviews, industry marketplaces and vertical review sites. We ingest review text, rating, date and response state, then run AI classification for theme, sentiment and severity so reputation becomes structured data rather than a wall of stars.
Bluefrog is an independent technology company. We integrate with these platforms' public APIs, exports and account interfaces — we are not affiliated with, endorsed by, a partner of, or a reseller for Google, Yext, BrightLocal, Data Axle or Apple. What can be read or written for any given source depends on that platform's own API and on the permissions of your account.
Join visibility to money, per location.
Listing health on one side, calls and booked revenue on the other, resolved to the same location key — that join is the entire product.
- Profile fields & categories
- Hours, service areas, attributes
- Posts, photos, Q&A
- Reviews & responses
- Citation and directory records
- Profile performance data
- Location roster mapping
- Tracking number to profile
- Business unit & market grouping
- Duplicate profile detection
- Franchise / brand hierarchy
- Review theme & sentiment
- Severity and escalation triage
- Listing health scoring
- Market-over-market comparison
- Visibility change vs. call volume
- Location scorecards
- Drafted profile posts
- Drafted review responses
- Operational alerts to the branch
- Rollups for ownership
The report a multi-location operator actually wants.
Listing health and review signal in the same row as calls and booked revenue, so the conversation moves from “fix the citations” to “fix the markets where it matters first.”
| Location | Listing Health | Citation Errors | Reviews (90d) | Avg Rating | Profile Calls (30d) | Booked Jobs | Booked Revenue | Signal |
|---|---|---|---|---|---|---|---|---|
| North Metro | 96 | 1 | 64 | 4.8 | 418 | 301 | $392K | Healthy |
| West Valley | 91 | 2 | 51 | 4.7 | 356 | 248 | $318K | Healthy |
| East Metro | 72 | 3 | 19 | 4.2 | 184 | 112 | $131K | Visibility-linked |
| South Corridor | 88 | 0 | 47 | 4.6 | 331 | 196 | $204K | Conversion gap |
| Lakeside | 64 | 7 | 12 | 4.0 | 96 | 61 | $74K | Priority |
| Airport District | 69 | 5 | 28 | 4.4 | 142 | 108 | $149K | Watch |
Illustrative data. Figures show report structure only and are not client results. Available columns depend on which platforms are connected and what each platform's API exposes for your account.
Read across a row and the decisions get obvious. North Metro is healthy and does not need attention. South Corridor has clean listings and strong call volume but weak booking — that is a call handling problem, not a listings problem, and sending a citation cleanup crew at it would waste a month. Lakeside has broken citations, almost no review flow and revenue to match; that is where visibility work pays for itself. Without the join, all three locations look the same on a listings dashboard.
Profiles go stale because publishing is manual at every location.
Fifty locations means fifty profiles that need posts, answered questions and responded reviews. That is a systems problem, and systems problems have systems answers.
Google Business Profile content automation
The same engine behind automation intelligence drafts location-specific profile posts, service descriptions and answers to common questions — built from your real service mix, your seasonal demand and the language your own customers use on calls, not generic boilerplate rewritten fifty ways.
Publishing behavior is your call. Some clients want drafts queued for a marketing manager to approve; some want scheduled publishing per market with review by exception. Either way the history is retained, so post cadence becomes a measurable variable next to call volume rather than a task somebody forgot.
Review-response intelligence
Every review is classified for theme, sentiment and severity, then routed. A one-star review naming a technician and a scheduling failure is not the same object as a three-star review about price, and it should not get the same treatment. Severe items alert the branch manager; routine items get a drafted response in your brand voice for approval.
The more valuable output is the aggregate. When arrival windows are the top negative theme in three markets and nowhere else, that is an operations finding that arrived through the reputation channel — and it belongs in the same brief as your revenue reporting.
Content automation → · AI search optimization → · Local & organic search →
Operators running more markets than one person can watch.
This work is built for multi-location service brands, franchise groups, regional rollups and private-equity portfolios — anywhere the number of locations has outgrown the ability to keep a mental model of each one. At three locations an owner knows which market is soft. At thirty, the only way to know is to instrument it.
We do not sell listings management as a standalone service and we do not ask you to leave your current vendor. Local data enters the Bluefrog Intelligence Platform the same way ad platforms, call tracking and field service data do, and it lands in the same location-level reporting your leadership already reads. For home services operators specifically, this is one of the inputs behind marketing built on operational data.
If the platform already covers what you need, implementation is configuration. If your location hierarchy is unusual, your brands are split across entities, or you have a homegrown location database that has to stay authoritative, we build the connector. That is ordinary work here — see integrations and API integration.
Technology development since 1997 · AI integration platforms since 2001
AI is easy to access. Making it useful is hard.
Bluefrog makes AI useful by integrating it with the way your business actually works — your software, your calls, your customers, your marketing and your revenue.
Technology development since 1997 · AI integration platforms since 2001