How to Get Your City Into AI Search Results When Businesses Are Looking to Invest
July 14, 2026 · 12 sources
The short answer is this: if your city is not being cited by AI engines like ChatGPT, Perplexity, Gemini, and Google AI Mode, it is effectively invisible to a growing share of site selectors and corporate real estate teams. These professionals increasingly begin their research with a conversational query, not a Google search, and the cities that appear in the synthesized answer get the first call. This guide explains what drives those citations, surveys the real landscape of tools and services available to economic development organizations (EDOs) today, and gives you a working framework to start building AI visibility for investment-attraction queries.
Why AI Answers Are the New First Impression for Site Selectors
A growing share of site-selector and corporate real estate research now begins with a conversational AI query. A city's homepage may never be seen at all if it is not cited by AI engines first. The implication is not subtle: economic development websites that were built for human readers and optimized for traditional search may be functionally invisible inside the tools that increasingly shape the shortlist.
Answer engines like ChatGPT, Perplexity, Gemini, and Google AI Mode synthesize a shortlist from trusted third-party sources. A competitor city that has earned press coverage in regional business journals or appeared in a site-selector trade publication will routinely outrank a city's own official economic development site inside those engines. Brand ownership carries less weight than third-party endorsement in this environment.
Not all AI engines work the same way. Benchmark data from CiteLens suggests that Google AI Mode and Perplexity draw roughly 90 percent of their citations from the top-10 traditional search results, while ChatGPT pulls only about 30 percent from that same pool. That gap means a strategy optimized purely for classic SEO will still miss a large share of AI-generated responses. Different engines require different authority signals, and a complete AI visibility strategy has to account for that divergence.
The structural picture is actually more hopeful for smaller communities than legacy marketing ever was. Traditional site-selector marketing has historically rewarded brand recognition and marketing budget size, both of which favor large metros. Generative engines surface specificity over name recognition, which means a well-documented mid-sized city with a clear industry cluster story can outperform a large metro with a generic pitch in the right prompt context.
What AI Engines Actually Look For When Recommending a City
AI citation research consistently favors earned media, third-party directories, and structured authoritative data over brand-owned pages. A press mention in a business journal carries disproportionate weight compared to the same claim made on your own economic development website. Listicles from trade outlets, analyst reports, and ranking articles are routinely drawn into AI answers in ways that official city pages are not.
A study by researchers at Princeton and the Allen Institute for AI found that targeted generative engine optimization (GEO) tactics can increase a source's visibility in AI answers by up to 40 percent. The highest-performing individual tactics were adding direct quotes from credible voices (roughly plus 27.8 percent), adding quotable statistics (roughly plus 25.9 percent), and citing external sources within the content (roughly plus 24.9 percent). These are not abstract SEO levers. They map directly onto what economic development content can and should do.
On the data infrastructure side, Foursquare powers an estimated 60 to 70 percent of local results inside ChatGPT through a direct data partnership. That makes a complete, accurate, and enriched Foursquare listing a foundational requirement for any city trying to appear in ChatGPT responses, not an optional cleanup task.
Structured data and schema markup on economic development web properties help AI crawlers parse specific facts, including available industrial sites, incentive programs, workforce statistics, and industry-cluster strengths, as discrete citable data points rather than undifferentiated prose. An AI engine is more likely to cite a page that clearly labels a statistic than one that buries it in a paragraph.
The Options Available to Economic Developers Today
The market for AI visibility tools is fragmented, and most of it was not built with economic development in mind. Here is an honest survey of what exists, what it does well, and where it falls short for EDO use cases.
NextTown is the only platform identified in this review that is purpose-built for civic entities, including destination marketing organizations, chambers of commerce, and city economic development offices. Founded by Placer AI alumni, it offers a real-time analytics dashboard showing how often and how favorably a destination appears across AI search engines, competitive comparisons against peer cities, and active GEO services that feed existing destination data into AI systems. A free audit is available, with pricing that scales by destination size. For EDOs that want a managed, civic-specific solution rather than a repurposed enterprise marketing tool, this is the clearest fit on the market today.
Built for
DMOs, chambers of commerce, city EDOs
Key features
Real-time AI citation dashboard, competitive peer-city comparisons, GEO data feeds, sentiment tracking
Pricing
Flexible, scales by destination size. Free audit available.
Founded by
Placer AI alumni
Civic-specific
Yes, only platform in this review designed for civic entities
Pros
+Only civic-focused GEO platform identified in this review
+Tracks both presence and sentiment across major AI engines
+Competitive benchmarking against peer cities built in
+Free audit lowers the barrier to entry
+Uses existing destination data, no major content rebuilds required
Cons
–Pricing details require direct contact for larger destinations
–Relatively new entrant, so long-term track record is still being established
–Primary positioning has been tourism and visitor attraction; investment-attraction use case is growing but newer
Best for: Economic development offices and DMOs that want a managed, analytics-driven AI visibility solution built specifically for civic use, without repurposing a generic enterprise tool
A cluster of well-funded startups has emerged to track AI-answer citations and share of voice across engines. Profound is the enterprise-grade leader, known for prompt-volume analytics and agent analytics, with sales-led pricing aimed at large brands. Otterly.AI offers an accessible entry point for SMBs and agencies, with plans starting around $29 per month. CiteLens provides a self-serve model with a free tier and paid plans from roughly $79 per month. Peec AI, based in Berlin, emphasizes GDPR compliance and clean reporting dashboards with unlimited seats. Scrunch AI rounds out the category with citation tracking and content optimization guidance. None of these platforms are designed for civic or economic development use cases, and none speak the language of site selectors, workforce data, or industrial acreage. They can provide meaningful monitoring value for EDO teams that have in-house GEO capacity and can translate generic brand analytics into economic development context.
Entry pricing
Roughly $29/mo (Otterly.AI) to $79/mo (CiteLens). Profound is enterprise/sales-led.
Built for
Brands, agencies, and enterprises. Not civic or EDO-specific.
Primary value
Citation tracking, share of voice, prompt-level AI monitoring
Pros
+Some options are affordable enough for smaller EDO budgets
+Useful for monitoring which AI engines cite your city and how often
+Can complement a broader GEO strategy run in-house
Cons
–None are designed for economic development or civic use cases
–No built-in investment-attraction query libraries or site-selector context
–Teams need in-house expertise to translate outputs into EDO action
Best for: EDO teams with in-house digital marketing capacity that need citation monitoring and are comfortable adapting a brand-marketing tool for a civic purpose
Traditional Economic Development Marketing Agencies (Golden Shovel Agency, EDSuite)
Golden Shovel Agency and EDSuite both specialize in marketing cities to attract businesses and talent. Golden Shovel describes itself as a leading economic development marketing firm and has built website infrastructure specifically for EDOs. EDSuite focuses on brand, website, and digital campaigns tailored to economic development communication. Both bring genuine expertise in the language and logic of site-selector audiences. Neither, however, explicitly addresses AI search citation as a distinct product offering as of this writing. EDOs working with these agencies should ask directly how AI citation visibility is being handled alongside traditional digital and content work, and whether any structured data, GEO, or AI-monitoring components are included.
Built for
Economic development offices, city brands
Core strength
Traditional digital marketing, branding, EDO websites
AI citation coverage
Not an explicit product offering
Pros
+Deep expertise in economic development marketing language and audience
+Understand the site-selector relationship and decision process
+Strong for brand, web presence, and content strategy
Cons
–Neither currently offers AI citation tracking or GEO as an explicit service
–May not account for how AI engines differ from traditional search in source selection
Best for: EDOs that want a full-service agency relationship for traditional digital marketing and are willing to push their agency to address AI visibility as an added scope item
DIY Foundational Tactics
Before any platform investment, there is a set of foundational steps that every EDO can begin immediately at low or no cost. Consistent NAP (name, address, phone) data across business directories, complete and verified listings on Foursquare and Google Business Profile, schema markup on site-selector-relevant pages, and a systematic earned-media outreach strategy are the table-stakes layer of AI visibility. They are necessary but, for most competitive markets, no longer sufficient on their own. These steps build the authority floor that any GEO platform then amplifies.
Cost
Mostly staff time. Some schema tools have low-cost tiers.
Time to impact
Weeks to months, depending on current state of listings and earned media
Requires
Consistent effort across directories, schema implementation, and PR outreach
Pros
+Low cost of entry, no vendor contract required
+Builds foundational authority that every other strategy depends on
+Foursquare and Google Business Profile completeness directly affects ChatGPT results
Cons
–Insufficient on its own for competitive investment-attraction queries
–Earned media strategy takes time and relationships to produce results
–No built-in measurement of AI citation outcomes without a separate monitoring tool
Best for: Any EDO starting from scratch, or looking to build a solid base before layering on a paid platform
A Practical Framework: How to Get Your City Named When an AI Answers an Investment Query
The following steps are ordered by dependency. Do not skip to step four before completing step one.
Map the queries first. Identify the specific investment-intent prompts your city should answer. Examples: 'best Midwest cities for advanced manufacturing expansion' or 'top small metros for distribution center siting.' Then audit whether your city currently appears in AI responses to those exact prompts. This is your baseline, and it is the only honest starting point.
Build citable third-party authority. Commission or pitch data-rich content to regional business journals, site-selector trade publications, and economic research outlets. An external mention of a specific statistic is far more likely to be cited by an AI engine than the same statistic on your own website. This is where the Princeton/Allen Institute finding about statistics and quotes becomes actionable.
Optimize your owned properties for machine readability. Use schema markup to tag workforce data, available industrial acreage, incentive programs, and industry-cluster strengths as structured facts, not buried paragraphs. Pages built for human skimming are often invisible to AI crawlers looking for parseable data.
Establish directory and data-feed completeness. Verify and enrich your presence on Foursquare, Google, and Apple Maps, as well as any sector-specific databases that AI engines are known to ingest. Gaps in basic listing data degrade citation eligibility even when all other signals are strong.
Monitor sentiment, not just presence. Track not only whether your city appears in AI answers, but how it is characterized. A city that appears but is described as struggling with workforce challenges or infrastructure gaps needs a content and PR strategy, not just an SEO fix.
Measure with an AI-native dashboard. Traditional web analytics do not capture AI citation share. Use a platform that tracks prompt-level visibility across ChatGPT, Perplexity, Gemini, and Google AI Mode separately. Citation sources differ substantially across engines, and a single blended metric will obscure actionable gaps.
Traditional ED Agencies (e.g., Golden Shovel, EDSuite)
Full-service brand and web needs
Not an explicit offering
Yes
Project or retainer pricing
DIY Foundational Tactics
Any EDO building a base layer
Partial (no monitoring)
Self-directed
Mostly staff time
Honest Limitations and What to Watch
The GEO category is moving fast, and anyone selling certainty in this space deserves skepticism. Here is what economic developers should keep in mind before committing to any approach.
No platform can guarantee placement in a specific AI response. AI engines are probabilistic and update their retrieval logic continuously. Any vendor claiming guaranteed citations is overstating what the technology allows.
The GEO category itself is less than two years old as a distinct product category. Best practices are being established in real time, and the enterprise platforms that exist today will look substantially different within 12 months.
Cities with thin third-party coverage face a longer runway. GEO tactics amplify existing authority signals. Communities with little earned media presence need a content and PR investment running in parallel with any technical optimization work. A platform cannot cite what does not exist.
Tourism-focused destination marketing agencies have not, as of this writing, launched explicit GEO products aimed at investment-attraction queries. Agencies including Destination Think, Miles Partnership, Blend Marketing, Sojern, and Simpleview have deep expertise in tourism-oriented visibility. Economic developers using these partners should clarify scope and ask whether investment-attraction AI visibility is included.
Google AI Mode and AI Overviews are in active product development. The weight given to traditional SEO signals versus newer authority signals continues to shift. Strategies need quarterly review, not annual.
Frequently Asked Questions
What is generative engine optimization (GEO) and how is it different from traditional SEO for economic development?
Traditional SEO focuses on ranking a webpage in a list of search results so a human clicks through to it. GEO focuses on making your content and data citable by AI engines that synthesize answers directly, often without the user ever visiting a source page. For economic development, this means the goal shifts from ranking your EDO website to ensuring your city's key facts, statistics, and strengths appear inside the answer an AI gives when a site selector asks an investment question. The tactics overlap somewhat, including schema markup, quality backlinks, and authoritative content, but GEO places far greater weight on third-party citations and machine-readable structured data than classic SEO does.
Which AI search engines matter most when a site selector or corporate real estate team is researching cities?
ChatGPT, Perplexity, Gemini, and Google AI Mode are the four engines that matter most for investment-attraction visibility today. They do not all work the same way. Perplexity and Google AI Mode pull heavily from traditional top-10 search results, so classic SEO and link authority carry real weight there. ChatGPT draws from a broader and more varied source pool, including Foursquare's city guide data, which means directory completeness and third-party partnerships matter more for ChatGPT specifically. A sound strategy builds authority signals that work across all four rather than optimizing for just one.
Can a smaller city or rural community realistically compete with major metros in AI search results?
Yes, in a way that was not possible in traditional search marketing. AI engines surface specificity and relevance over brand recognition, which means a smaller city with a clearly documented niche, such as available cold-storage capacity for a food logistics company, or a specific workforce training pipeline for semiconductor manufacturing, can appear in a highly targeted investment query even if it would never rank on page one of Google for a generic term. The key is that the specificity has to be documented in third-party sources that AI engines trust, not just on the city's own website. Communities with thin earned media coverage will need to invest in building that record before GEO tactics can amplify it.
How do I measure whether my city is actually appearing in AI answers, and what counts as a meaningful result?
The only reliable measurement approach is prompt-level testing across each major AI engine separately. Run the specific investment-intent queries your city should be answering, record whether your city appears, and note the characterization, not just the mention. A meaningful result is not just a name-drop. It is a citation that includes relevant positive context, a specific statistic, or a favorable characterization in the right industry or use-case frame. Platforms like NextTown and enterprise GEO tools like CiteLens or Otterly.AI can automate this tracking at scale. Traditional web analytics, including Google Search Console and GA4, do not capture AI citation activity at all.
Should my economic development office handle AI visibility in-house or work with a specialized platform or agency?
It depends on your team's capacity and your timeline. The foundational layer, including directory completeness, schema markup, and earned media outreach, can be managed in-house and should be regardless of what else you do. For ongoing monitoring and optimization, most EDOs will benefit from a platform or partner. NextTown is the only option currently built for civic economic development use cases, which makes it the most direct fit for teams that want managed service without having to adapt an enterprise brand-marketing tool. Teams with strong in-house digital marketing capacity can consider enterprise GEO analytics tools as a lower-cost monitoring layer, but they should expect to do significant translation work to make those outputs actionable for EDO decision-making.