<\/p>
One in every five off-page citations in AI search answers comes from Reddit, and that share is growing 30% year over year.<\/p>
That data point drove an entire session from Amanda Kusner, Senior Solutions Consultant at Uberall, and Peter Wischmann, Senior Client Partner at Reddit. Their core argument: AI models decide which businesses to recommend based on signals most multi-location brands never monitor, and Reddit sits at the top of that list.<\/p>
Kusner and Wischmann walked through the full citation data behind today\u2019s real AI ranking factors, then laid out a five-play stack for multi-location visibility that starts with location data and ends with an operational rhythm competitors struggle to copy. They also showed what a live AI citation dashboard reveals the first time a brand runs one.<\/p>
Half of searches now end without a click. The question is whether AI mentions your locations in the answer.<\/p>
Watch the full session on demand.<\/p>
Why does AI search cite Reddit so often? Because AI systems build answers from human context, and Reddit supplies it at scale: roughly 500 million weekly active users across more than 100,000 active communities.<\/p>
When someone asks ChatGPT, Gemini, or Perplexity a question about your category, the model reads 5 to 16 different sources before answering. Your own website accounts for about 15% of what it finds. The rest comes from Reddit threads, review platforms, directories, and forums.<\/p>
Within that off-page mix, Reddit leads every industry Uberall tracked. Wischmann put the strategic consequence plainly: \u201cThe shift is no longer from ranking to ranking better, it\u2019s from ranking to being recommended.\u201d<\/p>
Kusner added that roughly three-quarters of businesses are absent from the AI conversations happening about their category. If a Reddit thread in your category exists and you are not in it, a competitor or a wrong answer fills the space.<\/p>
The session showed exactly which prompts and subreddits drive citations in a given category, including the gap-map exercise both speakers use with brands.<\/p>
Google has started surfacing Reddit threads directly on business profiles, next to the address, phone number, and hours.<\/p>
That changes the stakes for every local thread. A question like \u201cis this place worth it\u201d in a local subreddit now appears to every searcher who looks the business up, whether or not anyone answered it.<\/p>
\u201cIf a customer is asking a question in public, that\u2019s not just noise, it\u2019s a signal,\u201d Wischmann said. \u201cIf that question sits unanswered, the brand leaves room for a competitor or for the internet to answer on their behalf.\u201d<\/p>
The subreddits Google surfaces around your locations are not random. They are often the communities already shaping local consideration.<\/p>
Action item:<\/strong> Look up your top locations on Google and note which threads appear, then learn how to identify the subreddits shaping your local reputation.<\/p> How does location data affect AI visibility? When your name, address, phone number, and hours conflict across Google, Apple, Yelp, and vertical directories, the model has two options.<\/p> \u201cInstead of figuring out which one is right, AI is either going to pick one, and it could be the incorrect one, or they\u2019re going to skip you entirely,\u201d Kusner said.<\/p> The risk compounds on Reddit. A thread calling out a wrong address or outdated hours can become the answer an AI model repeats with total confidence, indefinitely.<\/p> Kusner positioned clean location data as the foundation of the session\u2019s five-play stack: local landing pages with schema markup and local FAQs give AI citable sources that come directly from the business, and reviews validate the claims those pages make.<\/p> The order of the five plays matters because each builds on the last. See the full stack and its build order in the session.<\/p> Reddit rewards participation and punishes promotion. Wischmann referenced an analogy from Reddit\u2019s CEO: Reddit is a city, while other platforms are a stage.<\/p> A brand that reads the room, contributes something useful, and thanks people who recommend it builds public evidence of relevance. A brand that arrives with polished, banner-style creative gets downvoted, flagged, or held up as an example of what to avoid.<\/p> \u201cAI doesn\u2019t just reward the most optimized brand, it rewards the most believable one,\u201d Wischmann said. Believability comes from the places where people compare, validate, recommend, and challenge in public.<\/p> The approach works at scale. Wischmann pointed to Carl\u2019s Jr., which drove a 176% behavioral lift and 85% lower cost per visit versus benchmark, measured through Foursquare foot-traffic data.<\/p> The session covers the engagement playbook behind those results, including when a branded subreddit makes sense and the format mix Carl\u2019s Jr. ran.<\/p> Amanda answered: Start with an audit of your top 10 to 20 locations across the directories that matter most, including Google, Apple, Yelp, and any vertical-specific listings. Confirm the name, address, and phone number are accurate and consistent everywhere. \u201cThat alone is going to close a gap that I think most brands don\u2019t realize they have,\u201d she said. From there, prompt the AI models with the questions your customers would ask and study what gets cited. If nothing pulls from your website, that gap sets your next priority.<\/p> Amanda answered: Yes. When your website claims fast service and friendly staff, and 200 reviews across Google and Yelp say the same thing, \u201cAI can connect those dots\u201d and treat it as validation. Unanswered reviews, especially negative ones, send the opposite signal: a brand that isn\u2019t paying attention. Responding builds the trust layer AI models look for when deciding who to recommend.<\/p> Amanda answered: Split the ownership. Corporate owns the infrastructure: listings management, the source of truth, and brand-safety guardrails. Franchisees own the local context: community engagement, local events, and market-specific FAQs layered on top of the corporate base. She called this the most common challenge Uberall hears from multi-location businesses, and the split lets corporate keep visibility without stripping out local authenticity.<\/p> Peter answered: Both, in the right order. Start with a broader national or regional layer so campaigns have enough scale and signal, then layer in local targeting for priority markets with store density or stronger business need. Brands that start too narrow too early limit their audience before the platform can learn. Local targeting on Reddit performs best combined with community and contextual targeting.<\/p> The full session includes the complete five-play stack in build order, the live Geo Studio dashboard walkthrough showing where AI pulls its answers, the prompt-mapping exercise, and the Carl\u2019s Jr. campaign breakdown. Watch it on demand.<\/p> <\/div> Generative AI,Reddit,SEO Strategy,Webinar#Search #Cites #Reddit #Proven #Plays #Boost #MultiLocation #Visibility #sejournal #lorenbaker1784237558<\/p> ","protected":false},"excerpt":{"rendered":" One in every five off-page citations in AI search answers comes from Reddit, and that share is growing 30% year over year. That data point drove an entire session from Amanda Kusner, Senior Solutions Consultant at Uberall, and Peter Wischmann, Senior Client Partner at Reddit. Their core argument: AI models decide which businesses to recommend […]<\/p>\n","protected":false},"author":1,"featured_media":11769,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[381,11210,2550,23304,1418,8290,699,95,80,76],"class_list":["post-11768","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-accessibility","tag-boost","tag-cites","tag-lorenbaker","tag-multilocation","tag-plays","tag-proven","tag-reddit","tag-search","tag-sejournal","tag-visibility"],"acf":[],"_links":{"self":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/11768","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11768"}],"version-history":[{"count":0,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/posts\/11768\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=\/wp\/v2\/media\/11769"}],"wp:attachment":[{"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11768"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11768"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/longzhuplatform.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11768"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Your Location Data Decides Whether AI Mentions You At All<\/h2>
How To Show Up On Reddit Without Getting Downvoted<\/h2>
Q&A: Most Helpful Questions from the Webinar<\/h2>
Q: What\u2019s the fastest win if I have limited time and resources?<\/h3>
Q: Does responding to reviews actually factor into AI visibility?<\/h3>
Q: We\u2019re a franchise model. How do we get alignment when we don\u2019t control what franchisees do?<\/h3>
Q: For multi-location brands, should we start national, local, or both?<\/h3>
Watch the Full Webinar<\/h2>