Case Study / Moving & Storage
From invisible to AI systems to generating customers from them.
Mastodon Moving already had many of the signals associated with a strong digital presence. Established search visibility. An excellent reputation. More than a decade in business.
But when prospective customers turned to ChatGPT, Claude, Perplexity, and Google's emerging AI experiences for moving-company recommendations, Mastodon was largely absent.
Its competitors weren't.
Why were AI systems overlooking a business that traditional search already understood?
- Client
- Mastodon Moving
- Industry
- Moving & Storage
- Location
- Westborough, Massachusetts
- Engagement
- AI Search & Digital Ecosystem Optimization
- Started
- December 2025
- Status
- Ongoing
Primary results
From no measurable AI visibility to measurable AI traffic, leads, and sales.
0
AI mentions & citations
At baseline
276
AI-referred visits
Q2 2026
28
Leads generated
4
Sales generated
AI referral traffic shown for Q2 2026. Visibility and citation measurements reflect monitored AI search performance during the active engagement.
The starting point
Nothing appeared to be broken.
By conventional digital measures, Mastodon Moving had built a healthy presence.
The company had been operating since 2011. Its domain authority was 25. Its Google reputation stood at 4.9 stars across 145 reviews. Its traditional SEO presence was established.
This was not a business struggling to establish credibility online.
But Mastodon had begun noticing something else. When the company searched for moving recommendations using emerging AI tools, competitors appeared. Mastodon didn't.
25
Domain Authority
4.9 ★
Google Rating
145
Google Reviews
2011
Established
The disconnect was difficult to ignore.
Traditional search signals suggested Mastodon was healthy.
AI discovery told a different story.
Observe
Search visibility was no longer the whole picture.
Mastodon began testing how it appeared across AI-driven discovery experiences. Darby expanded that investigation by studying Mastodon alongside competing moving companies using AI search and competitive visibility data.
At baseline, Mastodon had no measurable mentions or citations across the AI environments being evaluated:
- ChatGPT
- Claude
- Perplexity
- Google AI experiences
Meanwhile, competing firms were appearing in the answers.
Mastodon could be found. But a new generation of discovery systems wasn't understanding and surfacing it.
That changed the question.
The problem was no longer simply: “How well does Mastodon rank?”
It became: “What does the wider digital ecosystem understand about Mastodon?”
Understand
Before changing anything, we needed to understand why.
Darby approached the problem as a diagnostic exercise rather than immediately prescribing a new marketing tactic.
We conducted three interconnected audits:
- 01
Website audit
Examining how Mastodon's website represented the company, its services, expertise, and supporting information.
- 02
SEO audit
Evaluating the traditional search foundation already supporting Mastodon's digital presence.
- 03
AI search audit
Examining how Mastodon appeared — or failed to appear — across emerging AI discovery environments.
The same analysis was performed against competing moving companies.
That comparison mattered.
The objective was not simply to identify whether Mastodon was absent. It was to understand what the digital ecosystem could see and interpret about competitors that it was not yet seeing clearly enough about Mastodon.
What the audits revealed
Detailed findings from this engagement are being prepared for publication.
Improve
Improve the signals, not just the ranking.
The objective was not to chase individual AI platforms or attempt to manufacture mentions. The objective was to improve how Mastodon was represented and understood across the digital information environment those systems were interpreting.
The work was guided by what the website, SEO, AI search, and competitive audits revealed.
We weren't optimizing for a chatbot. We were improving the information environment AI systems were using to understand Mastodon.
The work
The specific optimization initiatives from this engagement are being documented and will be published here.
Measure
AI systems began to see Mastodon differently.
As the work progressed, Mastodon began appearing inside the discovery environments where it had previously been absent.
Current AI visibility
These are visibility measurements recorded across monitored AI discovery environments. They are not percentages, and they do not represent traffic.
- Total AI Visibility30
- ChatGPT35
- Google AI Overview14
- Google AI Mode35
- Gemini35
AI visibility over time
Visibility arrived in stages.
Late 2025
Limited to absent visibility across important AI environments.
Early 2026
ChatGPT visibility rises significantly.
Spring 2026
Google AI Overview visibility emerges.
Summer 2026
Measurable visibility maintained across multiple AI discovery environments.
A conceptual milestone view. Points reflect observed states during the engagement rather than interpolated measurements.
Citation
Mastodon didn't just begin appearing. Its website began becoming a source.
AI visibility means more when the underlying organization is being used as part of the information environment itself.
16
Cited pages
- 01Homepage
- 02Services
- 03About
- 04Company Story
- 05Team
- 06Specialty Moving content
- 07Commercial Moving content
- 08Moving Advice content
The shift was no longer simply: “AI knows Mastodon exists.”
Mastodon's own information was becoming part of the answer.
Topical visibility
Visibility expanded beyond the company name.
9
Performing topics
27
Tracked prompts
Also measurable around
- Moving & Storage Services in Westborough, MA
- Shrewsbury Moving Services
Strongest topic
Mastodon Moving Services
88
Visibility
15
Mentions
From visibility to business outcome
Being cited is useful. Being chosen is better.
The change eventually became visible somewhere more important than an AI monitoring dashboard: actual website traffic.
276
AI-referred visits
Q2 2026
- ChatGPT132
- Claude67
- Google AI54
- Perplexity23
276
AI-referred visits
28
Leads
4
Sales
What began as a visibility problem had become a measurable source of customer acquisition.
Engagement
A continuing engagement.
December 2025
Engagement begins
Website, SEO, AI search, and competitive analysis.
Early 2026
AI visibility begins expanding
Spring 2026
Visibility emerges across additional AI discovery environments
Q2 2026
Measurable business outcomes
- 276 AI-referred visits
- 28 leads
- 4 sales
August 2026
Optimization remains active
Status: Ongoing
What we learned
The lesson wasn't that SEO stopped working.
Mastodon's traditional search presence was one of the reasons this case was so revealing. The company had authority. It had reputation. It had history. It had customers willing to recommend it.
What it lacked was visibility inside a new layer of digital discovery.
The solution wasn't to abandon SEO and chase AI algorithms. It was to understand the signals shaping how Mastodon was represented, identify where that representation could be improved, and systematically make the digital ecosystem easier to interpret.
- The result was not simply greater AI visibility.
- AI systems began surfacing Mastodon.
- Mastodon's website began being cited.
- People began arriving through AI platforms.
- Some became leads.
- Some became customers.
Visibility without understanding is incomplete.
This is what optimization looks like when the discovery environment changes.
How Darby thinks
Observe. Understand. Improve. Measure.
Observe
Mastodon was performing well in traditional search but absent from emerging AI discovery.
Understand
Website, SEO, AI search, and competitor audits exposed the disconnect between traditional visibility and AI visibility.
Improve
Darby used the findings to improve how Mastodon was represented and understood across the digital ecosystem.
Measure
AI visibility became citations. Citations became traffic. Traffic became leads. Leads became sales.
What are you trying to improve?
The problem isn't always where you expect it to be.
You don't need to know which service you need. Tell us what you're trying to accomplish, what isn't working the way you think it should, or what you're trying to understand. We'll start there.