When ChatGPT, Gemini, Perplexity, or Google's AI Overviews give a homeowner wrong information about your foundation repair company, the fix is not to argue with the chatbot. The fix is to correct the underlying sources those systems pull from — your website, directory listings, and review platforms — and then publish clear, current facts that give the model a better answer to draw on next time. This takes days to weeks to resolve, not a single request.
Why AI sometimes states outdated or incorrect contractor details
Answer engines do not verify facts the way a person would; they summarize whatever text they can find across your website, directory profiles, and past reviews, then blend it into a single response. If your business changed its service area, dropped a warranty term, or updated pricing structure but an old blog post, outdated directory listing, or stale review still mentions the previous version, the AI may repeat the outdated version because it appears more frequently or more clearly stated across the web than your current information.
This is a sourcing problem, not a malicious one. Large language models (LLMs, the AI systems behind tools like ChatGPT) generate answers by predicting likely text based on patterns in training data and, for tools with live search, real-time web content. If three directories say you serve one metro area and your homepage says another, the model has no reliable way to know which is current. It picks whichever signal seems strongest or most repeated.
How wrong hours, service areas, or claims cost you calls
A homeowner searching for emergency foundation repair at night who is told your company is closed, or that you only serve a neighboring county, will simply call the next contractor listed. Wrong information does not just annoy a prospective customer; it removes you from consideration before you ever get the chance to speak with them. Every incorrect detail an AI repeats is a lost call you never see happen.
The cost compounds because these tools are often used at the exact moment someone has a cracked slab, a bowing wall, or a sinking porch and wants an answer immediately. If the AI states your company does not offer free inspections when you do, or lists a warranty length that no longer matches your current policy, the homeowner may choose a competitor whose listed terms sound better, even if your actual terms are just as strong or stronger. Wrong details do not just mislead; they actively steer business away from you.
Correcting the sources AI draws from
Answer engines rely on a patchwork of your Google Business Profile, website, industry directories, and review sites, so correcting one source rarely fixes the whole picture. Start with your Google Business Profile and website, since these tend to carry the most weight, then work through directories like Angi, HomeAdvisor, Yelp, and any foundation-repair-specific listing sites where your hours, service area, or pricing language might be outdated.
Consistency matters more than perfection on any single platform. If your website says you serve five counties but your Google Business Profile still lists three, that mismatch is itself a signal that confuses AI tools trying to determine which version is current. Go through every platform where your business appears and align the basic facts: service area, hours, phone number, financing or warranty terms, and the specific foundation repair methods you offer, whether that is push piers, helical piers, slab piers, or drainage correction. Treat this as a recurring audit, not a one-time cleanup, since directories update on their own schedules and can drift out of sync again.