Case study · Tree services · Montgomery County, Maryland
Building AI visibility for a new tree-service brand
DEL Trees is a new division with almost no digital footprint. This study documents AI visibility from close to zero — what the starting point actually is, what gets changed, and whether any of it moves the measurement.
No baseline has been collected yet
There is no score on this page, no starting position and no result, because none has been measured. A baseline requires 240 recorded observations across 5 platforms, and that collection has not run.
The page exists now so the commitment is on record before the data arrives — including the possibility that the starting score is zero and stays there for a while.
Why a brand-new business is the interesting case
An established company that improves its AI visibility proves something ambiguous: the work may have caused it, or twenty years of accumulated reputation may have been catching up. A business that starts with nothing does not have that confound.
It starts near zero
A new division of an established landscaping company, trading under its own name with its own service line. Most case studies in this field begin with a business that already has a decade of citations behind it, which makes it impossible to tell what the work did and what history did.
The market is competitive and local
Tree work in Montgomery County has established competitors with long-standing directory presence, association membership and review histories. This is not an easy category to enter, which is the point.
The questions are high-intent
Nobody asks an assistant about tree removal idly. The questions are specific, urgent and commercial — the kind where an AI recommendation plausibly decides who gets the call.
Both mechanisms are visible
A brand this new is unlikely to exist in model training data at all. That separates the retrieval path from the recall path more cleanly than an established business ever could.
What this study will record
The same measurements any client receives, published rather than kept private. DEL Trees is a client of Greenbug’s, and that is stated plainly here rather than left for someone to discover.
| Measurement | What it captures | Status |
|---|---|---|
| Baseline AI Recommendation Score | The starting number, computed by the published formula. For a brand this new it may well be at or near zero — which is exactly why it is worth recording rather than skipping. | Baseline underway |
| Recommendation presence by platform | How often DEL Trees is named across the frozen buyer-question set, broken out by assistant, because the platforms disagree. | Baseline underway |
| Competitors named instead | Which tree companies the assistants recommend when DEL Trees is absent, and how consistently the same names recur. | Baseline underway |
| Cited sources | The domains the assistants actually relied on when answering. Over time this becomes the map of which sources hold authority in local tree services. | Baseline underway |
| Source gaps | Where the recurring competitors appear and DEL Trees does not — association registers, directories, review platforms, local coverage. | Baseline underway |
| Entity accuracy | Whether what the assistants say about the business is correct: services, service area, contact details, and whether it is confused with the parent landscaping brand. | Baseline underway |
| Changes implemented | Every change, dated — entity data, site structure, external listings, published content — so movement can be attributed rather than guessed at. | Baseline underway |
| Visibility change over time | Movement against the baseline, cycle by cycle, measured with a benchmark that does not change between cycles. | Baseline underway |
The conditions this study is published under
- The benchmark is frozen. The buyer questions are written once and not rewritten between cycles, so a later number can be compared with an earlier one.
- A zero is published as a zero. If DEL Trees is named in none of the answers, the page will say so for as long as that is true.
- No result is claimed without observations behind it. Every figure that eventually appears here traces to stored AI responses with dates and platforms attached.
- Being a Greenbug client has no effect on any public ranking or index. DEL Trees cannot be placed editorially because of that relationship.
- Work that fails is reported. If a change produces nothing, it is listed as having produced nothing.
- The relationship is disclosed on the page, not in a footnote.
Related
Building Greenbug.ai in public →
The same commitment applied to our own brand, under the same rules.
The methodology in full →
Weights, prompt freezing, platforms and everything the measurement cannot tell you.
What is AI visibility? →
The concepts this study is built on, explained from the beginning.
All case studies →
Every business being measured, with its honest current status.
Follow this study
Updates appear here as each measurement cycle completes. The first will be the baseline itself — the starting position, whatever it turns out to be.
Run the same measurement on your business
The methodology behind this study is the one every client gets. It starts by finding out where you actually stand.