Posts

October 2025 Digital Marketing Roundup: What Changed and What You Should Do About It

/0 Comments/in /by

October showed just how fast AI is reshaping how brands connect, convert, and stay visible. OpenAI turned chats into checkout experiences. Google tested AI-written snippets and agent-driven search. The line between platforms, ads, and transactions keeps disappearing.

Creators gained new credibility. Rebrands proved riskier than ever. Data-driven PR entered a new era.

Here’s what mattered most and how to stay ahead.

Key Takeaways

  • • AI is officially a channel, not a tool. Search, shopping, and PR are all happening inside AI environments now.
  • • Authenticity outperforms aspiration. Whether you’re selling luxury goods or refreshing your brand, identity, and connection drive growth.
  • • Visibility depends on AI citations and structure. The brands getting mentioned in AI results are building more trust and traffic everywhere.
  • • Automation is powerful, but it still needs control. As Google’s AI Max expands, you need to balance efficiency with oversight to protect budgets and brand safety.
  • • Every brand action is a public statement. From rebrands to creator partnerships, perception moves fast. Plan your narratives or risk losing control of them.

Search & AI Evolution 

Search has moved beyond discovery. October’s updates from OpenAI and Google show how AI is collapsing the gap between queries and actions. Visibility means something different now.

OpenAI launches in-chat purchases

OpenAI rolled out Instant Checkout in ChatGPT. U.S. users can now buy products directly inside the chat. Powered by Stripe, the feature starts with Etsy listings and will expand to more merchants soon. Sellers on Shopify are auto-enrolled. Others can join by connecting product feeds and enabling Stripe checkout.

An ad in ChatGPT.

Our POV: ChatGPT shopping changes product discovery completely. If your product data isn’t complete, detailed, and conversational, you won’t show up. The most visible listings will have rich attributes and language that reflects how users naturally describe what they want.

What to do next: Audit your product feeds. Fill every field. Use detailed, long-form descriptions that anticipate real-world queries. Give the e-commerce agent what it needs to surface your products.

<h3> Google tests AI-written meta descriptions <h3>

Google began testing AI-generated snippets powered by Gemini. Instead of pulling your written meta description, the model writes or summarizes one based on on-page content.

Our POV: Google’s been rewriting descriptions for years. AI just made it smarter and less predictable. Treat your page intros as the new meta description because that’s what AI will pull from.

What to do next: Front-load the first 150 words of each key page with a clear summary of what the page delivers and why it matters. Tighten headings and intros, monitor CTR shifts, and adjust language when AI summaries drift from your brand’s tone.

<h3> Google Search Labs adds Agentic AI <h3>

Google’s AI Mode now lets users book restaurants and other services directly from results. Search is moving from recommending to acting.

Our POV: This isn’t a traffic killer. But signals are shifting. AI will handle the click path. The brands that win will have structured, verified, action-ready data.

What to do next: Audit structured data, integrate local feeds, and make sure your listings are up to date across booking platforms. When the search agent starts acting on your behalf, data hygiene becomes your conversion strategy.

Paid Media & Automation

AI is taking over ad delivery. Control is the new currency. You have to balance efficiency with visibility to keep performance from becoming unpredictable.

Google doubles down on AI Max

Google refreshed its AI Max ad pitch. The system is fully automated: it matches intent, rewrites copy, and routes users to brand assets. Powerful, but still a black box.

Google AI Max.

Our POV: Automation doesn’t replace strategy. Advertisers need visibility, not just results. Without strict guardrails, budgets can leak into low-value placements or off-brand creative.

What to do next: Run low-risk tests first. Add negative keyword lists, set URL exclusions, and manually review creative. Monitor performance closely until you can prove control before scaling.

Apple launches dedicated Games app

Apple introduced a standalone Games app with iOS 26, bridging Game Center and the App Store. Developers can now feature their games, run dual search visibility, and analyze engagement with new metrics later this year.

Apple's Games app.

Our POV: This isn’t a small tweak, Apple’s essentially building a second storefront. Game publishers who adapt early will own discoverability.

What to do next: Refresh creatives, optimize In-App Events, and plan for dual indexing between the Games app and App Store. When analytics arrive, use them to refine ASO and campaign timing.

Social & Content Trends

Creators and consumers are rewriting the rules. Authenticity, identity, and emotional connection drive engagement across platforms that once ran on aspiration and polish.

TikTok reframes luxury branding

TikTok’s new research shows luxury audiences care more about self-expression than status. It’s about showing who you are, not showing off.

TikTok's 4 Ls of Luxury concept.

Our POV: That shift goes way beyond luxury. Audiences in every category now expect brands to reflect their identity. Connection beats aspiration. Authenticity beats polish.

What to do next: Reevaluate your brand’s emotional identity. Work with creators who reinterpret your message through their lens. Build content that feels participatory, not performative.

UK YouTubers contribute £2.2B to the economy

YouTube creators generated £2.2 billion for the UK economy last year, supporting over 45,000 jobs. Parliament even launched a cross-party group to represent them.

Our POV: Creators aren’t influencers anymore. They’re small businesses with real economic weight. Partnering with them means investing in industries, not individuals.

What to do next: Build collaborations that help creators grow beyond campaigns. Shared education, joint products, or community-driven initiatives create deeper, longer-term value.

PR, Reputation & Brand Risk

Reputation management has become real-time and AI-measurable. From LLM citation tracking to brand backlash, every communication choice now echoes faster and louder.

Notified + Profound launch AI-driven PR monitoring

A first-of-its-kind industry partnership between these two companies now offers a tool that tracks how often press releases are cited by LLMs like ChatGPT and Gemini. It finally gives brands visibility into their “AI footprint.”

Our POV: PR just gained a measurable seat in AI discoverability. Knowing when AI cites your releases helps you shape future narratives.

What to do next: Integrate AI citation metrics into your analytics stack. Identify which stories get surfaced and refine future language to match the tone that earns citations.

Rebrands are riskier than ever

Cracker Barrel’s attempted rebrand backfired almost instantly. Modest design updates triggered outrage and political backlash—proof that brand refreshes now carry reputational stakes.

Our POV: Rebrands still matter, but they demand foresight. A design tweak is a message, whether you mean it or not.

What to do next: Before launching a new look, test reactions across audience segments and scenario-plan your communication strategy. Shape the story before the internet does.

Olivia Brown automates PR outreach

A new AI platform called Olivia Brown is automating nearly every part of digital PR, from writing press releases to pitching journalists and sending aggressive follow-ups. It promises to “democratize publicity,” but its bulk-send approach is flooding inboxes and straining relationships between brands and reporters who value relevance and trust.

The Olivia Brown interface.

Our POV: Rebrands still matter, but they demand foresight. A design tweak is a message, whether you mean it or not.

What to do next: Before launching a new look, test reactions across audience segments and scenario-plan your communication strategy. Shape the story before the internet does.

SEO 2.0: The New Search Game

Traditional rankings are giving way to AI visibility. The brands that master structure, credibility, and omnichannel authority are the ones AI systems will learn to trust and users will keep choosing.

Rankings + AI Citations

Traditional SEO metrics can’t capture how visible you are inside AI systems. NP Digital’s SEO 2.0 approach tracks AI citations alongside rankings to see how content performs in generative search.

Our POV: Rankings aren’t the endgame anymore. Visibility inside AI summaries is. The brands that get cited are the ones shaping what users read next.

What to do next: Create original, data-backed content that builds authority across multiple platforms: YouTube, Reddit, TikTok, and forums. These are the signals AI models use to decide who to trust.

<America’s favorite new query: “Is it good or bad?”

SEMrush found that U.S. users are now searching in binary terms. Tens of millions of queries every month ask if something is “good” or “bad.”

A graphic showing the main topics behind "Good/Bad" searches from SEMrush.

Source

Our POV: AI Overviews have trained users to expect clear answers. If your content hedges or buries the lead, you’ll lose clicks and credibility.

What to do next: Structure pages for speed and certainty. Use FAQ blocks, schema markup, and straightforward intros that deliver the verdict early. This is how you earn trust in zero-click environments.

Conclusion

AI is rewriting the rules of visibility, discovery, and trust. Success no longer depends on who publishes most. It depends on who provides the clearest data, most credible voice, and strongest structure. The brands investing in AI-ready content, authentic storytelling, and measurable strategy will own the next wave of search, social, and PR.

Need help applying these insights? Talk to the NP Digital team. We’re already helping brands adapt as things develop.

Read more at Read More

SEO vs. AI search: 101 questions that keep me up at night

/0 Comments/in , /by
SEO AI optimization GEO AEO LLMO

Look, I get it. Every time a new search technology appears, we try to map it to what we already know.

  • When mobile search exploded, we called it “mobile SEO.”
  • When voice assistants arrived, we coined “voice search optimization” and told everyone this would be the new hype.

I’ve been doing SEO for years.

I know how Google works – or at least I thought I did.

Then I started digging into how ChatGPT picks citations, how Perplexity ranks sources, and how Google’s AI Overviews select content.

I’m not here to declare that SEO is dead or to state that everything has changed. I’m here to share the questions that keep me up at night – questions that suggest we might be dealing with fundamentally different systems that require fundamentally different thinking.

The questions I can’t stop asking 

After months of analyzing AI search systems, documenting ChatGPT’s behavior, and reverse-engineering Perplexity’s ranking factors, these are the questions that challenge most of the things I thought I knew about search optimization.

When math stops making sense

I understand PageRank. I understand link equity. But when I discovered Reciprocal Rank Fusion in ChatGPT’s code, I realized I don’t understand this:

  • Why does RRF mathematically reward mediocre consistency over single-query excellence? Is ranking #4 across 10 queries really better than ranking #1 for one?
  • How do vector embeddings determine semantic distance differently from keyword matching? Are we optimizing for meaning or words?
  • Why does temperature=0.7 create non-reproducible rankings? Should we test everything 10 times over now?
  • How do cross-encoder rerankers evaluate query-document pairs differently than PageRank? Is real-time relevance replacing pre-computed authority?

These are also SEO concepts. However, they appear to be entirely different mathematical frameworks within LLMs. Or are they?

When scale becomes impossible

Google indexes trillions of pages. ChatGPT retrieves 38-65. This isn’t a small difference – it’s a 99.999% reduction, resulting in questions that haunt me:

  • Why do LLMs retrieve 38-65 results while Google indexes billions? Is this temporary or fundamental?
  • How do token limits establish rigid boundaries that don’t exist in traditional searches? When did search results become limited in size?
  • How does the k=60 constant in RRF create a mathematical ceiling for visibility? Is position 61 the new page 2?

Maybe they’re just current limitations. Or maybe, they represent a different information retrieval paradigm.

The 101 questions that haunt me:

  1. Is OpenAI also using CTR for citation rankings?
  2. Does AI read our page layout the way Google does, or only the text?
  3. Should we write short paragraphs to help AI chunk content better?
  4. Can scroll depth or mouse movement affect AI ranking signals?
  5. How do low bounce rates impact our chances of being cited?
  6. Can AI models use session patterns (like reading order) to rerank pages?
  7. How can a new brand be included in offline training data and become visible?
  8. How do you optimize a web/product page for a probabilistic system?
  9. Why are citations continuously changing?
  10. Should we run multiple tests to see the variance?
  11. Can we use long-form questions with the “blue links” on Google to find the exact answer?
  12. Are LLMs using the same reranking process?
  13. Is web_search a switch or a chance to trigger?
  14. Are we chasing ranks or citations?
  15. Is reranking fixed or stochastic?
  16. Are Google & LLMs using the same embedding model? If so, what’s the corpus difference?
  17. Which pages are most requested by LLMs and most visited by humans?
  18. Do we track drift after model updates?
  19. Why is EEAT easily manipulated in LLMs but not in Google’s traditional search?
  20. How many of us drove at least 10x traffic increases after Google’s algorithm leak?
  21. Why does the answer structure always change even when asking the same question within a day’s difference? (If there is no cache)
  22. Does post-click dwell on our site improve future inclusion?
  23. Does session memory bias citations toward earlier sources?
  24. Why are LLMs more biased than Google?
  25. Does offering a downloadable dataset make a claim more citeable?
  26. Why do we still have very outdated information in Turkish, even though we ask very up-to-date questions? (For example, when asking what’s the best e-commerce website in Turkiye, we still see brands from the late 2010s)
  27. How do vector embeddings determine semantic distance differently from keyword matching?
  28. Do we now find ourselves in need to understand the “temperature” value in LLMs?
  29. How can a small website appear inside ChatGPT or Perplexity answers?
  30. What happens if we optimize our entire website solely for LLMs?
  31. Can AI systems read/evaluate images in webpages instantly, or only the text around them?
  32. How can we track whether AI tools use our content?
  33. Can a single sentence from a blog post be quoted by an AI model?
  34. How can we ensure that AI understands what our company does?
  35. Why do some pages show up in Perplexity or ChatGPT, but not in Google?
  36. Does AI favor fresh pages over stable, older sources?
  37. How does AI re-rank pages once it has already fetched them?
  38. Can we train LLMs to remember our brand voice in their answers?
  39. Is there any way to make AI summaries link directly to our pages?
  40. Can we track when our content is quoted but not linked?
  41. How can we know which prompts or topics bring us more citations? What’s the volume?
  42. What would happen if we were to change our monthly client SEO reports by just renaming them to “AI Visibility AEO/GEO Report”?
  43. Is there a way to track how many times our brand is named in AI answers? (Like brand search volumes)
  44. Can we use Cloudflare logs to see if AI bots are visiting our site?
  45. Do schema changes result in measurable differences in AI mentions?
  46. Will AI agents remember our brand after their first visit?
  47. How can we make a local business with a map result more visible in LLMs?
  48. Will Google AI Overviews and ChatGPT web answers use the same signals?
  49. Can AI build a trust score for our domain over time?
  50. Why do we need to be visible in query fanouts? For multiple queries at the same time? Why is there synthetic answer generation by AI models/LLMs even when users are only asking a question?
  51. How often do AI systems refresh their understanding of our site? Do they also have search algorithm updates?
  52. Is the freshness signal sitewide or page-level for LLMs?
  53. Can form submissions or downloads act as quality signals?
  54. Are internal links making it easier for bots to move through our sites?
  55. How does the semantic relevance between our content and a prompt affect ranking?
  56. Can two very similar pages compete inside the same embedding cluster?
  57. Do internal links help strengthen a page’s ranking signals for AI?
  58. What makes a passage “high-confidence” during reranking?
  59. Does freshness outrank trust when signals conflict?
  60. How many rerank layers occur before the model picks its citations?
  61. Can a heavily cited paragraph lift the rest of the site’s trust score?
  62. Do model updates reset past re-ranking preferences, or do they retain some memory?
  63. Why can we find better results by 10 blue links without any hallucination? (mostly)
  64. Which part of the system actually chooses the final citations?
  65. Do human feedback loops change how LLMs rank sources over time?
  66. When does an AI decide to search again mid-answer? Why do we see more/multiple automatic LLM searches during a single chat window?
  67. Does being cited once make it more likely for our brand to be cited again? If we rank in the top 10 on Google, we can remain visible while staying in the top 10. Is it the same with LLMs?
  68. Can frequent citations raise a domain’s retrieval priority automatically?
  69. Are user clicks on cited links stored as part of feedback signals?
  70. Are Google and LLMs using the same deduplication process?
  71. Can citation velocity (growth speed) be measured like link velocity in SEO?
  72. Will LLMs eventually build a permanent “citation graph” like Google’s link graph?
  73. Do LLMs connect brands that appear in similar topics or question clusters?
  74. How long does it take for repeated exposure to become persistent brand memory in LLMs?
  75. Why doesn’t Google show 404 links in results but LLMs in answers?
  76. Why do LLMs fabricate citations while Google only links to existing URLs?
  77. Do LLMs retraining cycles give us a reset chance after losing visibility?
  78. How do we build a recovery plan when AI models misinterpret information about us?
  79. Why do some LLMs cite us while others completely ignore us?
  80. Are ChatGPT and Perplexity using the same web data sources?
  81. Do OpenAI and Anthropic rank trust and freshness the same way?
  82. Are per-source limits (max citations per answer) different for LLMs?
  83. How can we determine if AI tools cite us following a change in our content?
  84. What’s the easiest way to track prompt-level visibility over time?
  85. How can we make sure LLMs assert our facts as facts?
  86. Does linking a video to the same topic page strengthen multi-format grounding?
  87. Can the same question suggest different brands to different users?
  88. Will LLMs remember previous interactions with our brand?
  89. Does past click behavior influence future LLM recommendations?
  90. How do retrieval and reasoning jointly decide which citation deserves attribution?
  91. Why do LLMs retrieve 38-65 results per search while Google indexes billions?
  92. How do cross-encoder rerankers evaluate query-document pairs differently than PageRank?
  93. Why can a site with zero backlinks outrank authority sites in LLM responses?
  94. How do token limits create hard boundaries that don’t exist in traditional search?
  95. Why does temperature setting in LLMs create non-deterministic rankings?
  96. Does OpenAI allocate a crawl budget for websites?
  97. How does Knowledge Graph entity recognition differ from LLM token embeddings?
  98. How does crawl-index-serve differ from retrieve-rerank-generate?
  99. How does temperature=0.7 create non-reproducible rankings?
  100. Why is a tokenizer important?
  101. How does knowledge cutoff create blind spots that real-time crawling doesn’t have?

When trust becomes probabilistic

This one really gets me. Google links to URLs that exist, whereas AI systems can completely make things up:

  • Why can LLMs fabricate citations while Google only links to existing URLs?
  • How does a 3-27% hallucination rate compare to Google’s 404 error rate?
  • Why do identical queries produce contradictory “facts” in AI but not in search indices?
  • Why do we still have outdated information in Turkish even though we ask up-to-date questions?

Are we optimizing for systems that might lie to users? How do we handle that?

Where this leaves us

I’m not saying AI search optimization/AEO/GEO is completely different from SEO. I’m just saying that I have 100+ questions that my SEO knowledge can’t answer well, yet.

Maybe you have the answers. Maybe nobody does (yet). But as of now, I don’t have the answers to these questions.

What I do know, however, is this: These questions aren’t going anywhere. And, there will be new ones.

The systems that generate these questions aren’t going anywhere either. We need to engage with them, test against them, and maybe – just maybe – develop new frameworks to understand them.

The winners in this new field won’t be those who have all the answers. There’ll be those asking the right questions and testing relentlessly to find out what works.

This article was originally published on metehan.ai (as 100+ Questions That Show AEO/GEO Is Different Than SEO) and is republished with permission.

Read more at Read More

Tim Berners-Lee warns AI may collapse the ad-funded web

/0 Comments/in , /by

Sir Tim Berners-Lee, who invented the World Wide Web, is worried that the ad-supported web will collapse due to AI. In a new interview with Nilay Patel on Decoder, Berners-Lee said:

  • “I do worry about the infrastructure of the web when it comes to the stack of all the flow of data, which is produced by people who make their money from advertising. If nobody is actually following through the links, if people are not using search engines, they’re not actually using their websites, then we lose that flow of ad revenue. That whole model crumbles. I do worry about that.”

Why we care. There is a split in our industry, where one side thinks “it’s just SEO” and the other sees a near future where visibility in AI platforms has replaced rankings, clicks, and traffic. We know SEO still isn’t dead and people are still using search engines, but the writing is still on the wall (Google execs have said as much in private). Berners-Lee seems to envision the same future, warning that if people stop following links and visiting websites, the entire web model “crumbles,” leaving AI platforms with value while the ad-supported web and SEO fade.

On monopolies. In the same interview, Berners-Lee said a centralized provider or monopoly isn’t good for the web:

  • “When you have a market and a network, then you end up with monopolies. That’s the way markets work.
  • “There was a time before Google Chrome was totally dominant, when there was a reasonable market for different browsers. Now Chrome is dominant.
  • “There was a time before Google Search came along, there were a number of search engines and so on, but now we have basically one search engine.
  • “We have basically one social network. We have basically one marketplace, which is a real problem for people.”

On the semantic web. Berners-Lee worked on the Semantic Web for decades (a web that machines can read as easily as humans). As for where it’s heading next: data by AI, for AI (and also people, but especially AI):

  • “The Semantic Web has succeeded to the extent that there’s the linked open data world of public databases of all kinds of things, about proteins, about geography, the OpenStreetMap, and so on. To a certain extent, the Semantic Web has succeeded in two ways: all of that, and because of Schema.org.
  • “Schema.org is this project of Google. If you have a website and you want it to be recognized by the search engine, then you put metadata in Semantic Web data, you put machine-readable data on your website. And then the Google search engine will build a mental model of your band or your music, whatever it is you’re selling.
  • “In those ways, with the link to the data group and product database, the Semantic Web has been a success. But then we never built the things that would extract semantic data from non-semantic data. Now AI will do that.
  • “Now we’ve got another wave of the Semantic Web with AI. You have a possibility where AIs use the Semantic Web to communicate between one and two possibilities and they communicate with each other. There is a web of data that is generated by AIs and used by AIs and used by people, but also mainly used by AIs.”

On blocking AI crawlers. Discussion turned to Cloudflare and their attempt to block crawlers and its pay per crawl initiative. Berners-Lee was asked whether the web’s architecture could be redesigned so websites and database owners could bake a “not unless you pay me” rule into open standards, forcing AI crawlers and other clients across the ecosystem to honor payment requirements by default. His response:

  • “You could write the protocols. One, in fact, is micropayments. We’ve had micropayments projects in W3C every now and again over the decades. There have been projects at MIT, for example, for micropayments and so on. So, suddenly there’s a “payment required” error code in HTTP. The idea that people would pay for information on the web; that’s always been there. But of course whether you’re an AI crawler or whether you are an individual person, it’s the way you want to pay for things that’s going to be very different.”

The interview. Sir Tim Berners-Lee doesn’t think AI will destroy the web

Read more at Read More

Google expands image search ads with mobile carousel format

/0 Comments/in , /by

Google rolled out AI-powered ad carousels in the Images tab on mobile, now appearing across all categories — not just shopping-related ones.

Why we care. Ads are now showing directly within image search results, giving brands a new, highly visual placement to grab attention where users are actively browsing and comparing visuals. With users often browsing images to explore ideas or compare options, these AI-powered carousels give brands a chance to influence discovery earlier in the journey.

The details:

  • The new format features horizontally scrollable carousels with images, headlines, and links.
  • These carousels are powered by AI-driven ad matching, pulling in visuals relevant to the user’s query — even in non-commerce categories like law or insurance.
  • The feature was first spotted by ADSQUIRE founder Anthony Higman, who shared screenshots of the new layout on X.

The big picture. By integrating ads more seamlessly into visual search, Google is blurring the line between organic and paid discovery a continued shift toward immersive, image-based ad experiences that go beyond traditional text and product listings.

Read more at Read More

With negative review extortion scams on the rise, use Google’s report form

/0 Comments/in , /by

Google Business Profiles has a form where you can report negative review extortion scams, the form launched a month ago. You can find access to the form in this help document and I believe you need to be logged into your Google account with access to the Business Profile you want to report.

Review extortion scams. This negative review extortion scams are on the rise and a huge concern for local SEOs and businesses. A scammer will message you, likely over WhatsApp or email, and tell you that they left a one-star negative review and the only way to remove it is to pay them.

Google wrote in its help document, “These scams may involve a sudden increase in 1-star and 2-star reviews on your Google Business Profile, followed by someone demanding money, goods, or services in exchange for removing the negative reviews.”

The form. The form can be accessed while logged into your Google account by clicking here. The form asks for your information, the affected Google Business Profile details, more details on the extortion review, and additional evidence.

Do not engage. Google posted four tips when you are confronted with these scams:

  • Do not engage with or pay the malicious individuals. This can encourage further attempts and doesn’t guarantee the removal of reviews.
  • Do not try to resolve it yourself by offering money or services.
  • Gather all evidence immediately. The sooner you collect proof, the better.
  • Report all relevant communication you receive in the form.

Give it a try. There are some who are doubtful that this form actually does anything. But one local SEO tried it out over the weekend and within a few days, the review in question was removed. So it is worth giving it a shot.

Why we care. Reviews on your local listing, especially on Google Maps and Google Search, can have a huge impact on your business. Negative reviews will encourage customers to look for other businesses, even if those reviews are fraudulent. So, being on top of your reviews and removing the fake and fraudulent reviews is an important task most businesses should do on an ongoing basis.

This form will help you manage some of those fake reviews.

Read more at Read More

Google tightens rules on fraud-linked phone numbers in ads

/0 Comments/in , /by
Google Ads tactics to drop

Google Ads is updating its Destination requirements policy to block phone numbers tied to fraud or prior policy violations, part of the company’s ongoing effort to curb deceptive advertising practices.

The timeline:

  • Policy update effective: December 10, 2025
  • Enforcement ramp-up: Over roughly 8 weeks after rollout

What’s changing. Phone numbers flagged as fraudulent or with a history of violations will now be deemed unacceptable under the Destination requirements policy, leading to ad disapprovals.

Why we care. The change targets bad actors who use legitimate-looking phone numbers to mislead users or bypass enforcement, a recurring issue in sectors like tech support scams and lead generation. It’s a reminder to audit contact information across campaigns and ensure all numbers are verified and legitimate. Failing to do so could disrupt ad delivery, delay approvals, and hurt campaign performance during the enforcement rollout.

For advertisers. Those impacted will receive disapproval notices and can refer to Google’s help center for guidance on fixing disapproved ads or assets.

First seen. This update was shared by ADSQUIRE founder, Anthony Higman on X.

Between the lines. Google continues tightening ad verification and destination standards amid growing scrutiny over scams and consumer trust — showing that accountability for ad content now extends beyond just the landing page.

Read more at Read More

Why AI availability is the new battleground for brands

/0 Comments/in , /by
AI availability concept

GEO, AI SEO, AEO – call it what you like.

The label doesn’t matter nearly as much as understanding the shift behind it.

At the center of that shift lies one idea that explains everything: AI availability – and here’s why it matters.

What is AI availability?

The three pillars of brand availability

The idea of AI availability comes from Byron Sharp, research professor at the Ehrenberg-Bass Institute, who introduced it in a comment on one of my LinkedIn posts.

Sharp’s work underpins modern brand science and shows that growth depends on availability.

Brands grow through sales, and sales grow through two kinds of availability: mental and physical.

  • Mental availability refers to the likelihood of being considered in a purchasing situation.
  • Physical availability refers to the ease and convenience with which an item can be bought.

For years, these two principles have guided brand strategy.

They explain why Coca-Cola invests in constant visibility and why Amazon makes every click lead to a checkout.

But in the era of generative search, there’s now a third kind of availability marketers need to understand – the likelihood that your brand or product will be recommended by an AI system when a user is ready to buy.

That is AI availability – and it changes everything.

AI as the new influencer

If you are still thinking of AI as a technology, you are already behind.

Think of it instead as the world’s most powerful influencer.

ChatGPT alone is used by about 10% of the global adult population, according to recent research from OpenAI, Harvard, and Duke. 

That makes it far more pervasive than any social media platform at a similar stage in its life cycle.

Most people do not use it to code or write poetry – they use it to make decisions. 

Nearly 80% of ChatGPT conversations, the same study found, fall into three categories: 

  • Practical guidance.
  • Seeking information.
  • Writing.

In other words, people are asking AI to help them decide what to do, buy, and believe. 

The study also shows that these conversations are increasingly focused on everyday decisions rather than work. 

The distinction between search, research, and conversation is collapsing.

Source- “How People Use ChatGPT,” OpenAI, Harvard University, and Duke University
Source: “How People Use ChatGPT,” OpenAI, Harvard University, and Duke University

The result is simple.

AI systems are now the gatekeepers of modern discovery. They decide what information to surface and which businesses appear in front of consumers.

Forget the Kardashians. Forget influencer marketing.

If you’re invisible to AI, you’re invisible to the market.

AI is the new influencer.

From keywords to fitness signals

The SEO industry has spent two decades optimizing for how humans search with keywords – but that is changing.

Large language models (LLMs) infer meaning from context, probability, and performance.

They are scanning for what we can call fitness signals – a term from network science.

Fitness describes a product or service’s inherent ability to outcompete rivals, allowing one business to dominate a market even if others started earlier or invested more.

Think of how Google overtook Yahoo. 

It wasn’t just about better search algorithms – it was a better business model built on a stronger performance attribute: relevance.

These performance attributes are what make a business fit for survival. They are the qualities that define how well you solve a problem for a customer.

AI deploys search strategies to identify which businesses solve which problems most effectively. 

Because it exists to serve human needs, those same signals determine your AI availability.

Yes, AI uses search strings, fan-out queries, and reciprocal rank fusion, among many other strategies and tactics. 

It doesn’t search like humans because it isn’t bound by the same cognitive and speed limitations.

Humans search by “satisficing.” Keywords + Page 1 rankings = good enough.

Machines operate on an industrial scale – searching, gathering, assessing, and recommending.

Dig deeper: Fame engineering: The key to generative engine optimization

The psychology of performance

To understand why this works, we turn to evolutionary psychology.

Geoffrey Miller, author of “Spent,” explained that humans have always been driven by two fundamental needs. 

  • We seek to display fitness indicators that enhance our status.
  • We chase fitness cues that increase our chances of survival or pleasure.

Consumer products have evolved to meet those needs. Luxury goods signal success. 

Convenience products signal control. Both deliver psychological reassurance.

AI works in a similar way. Its goal is to satisfy human intent. 

When someone types a complex prompt into an LLM, the AI interprets it not as a string of keywords but as a statement of need. 

It then searches its training data and live information to find the most relevant and trustworthy performance attributes that match that need.

That is why context matters so much more than content. 

You are no longer competing for blue links – you are competing for cognitive inclusion in an AI’s mental model of your category. 

Your job is to make your brand’s fitness and performance attributes unmissable to that model.

Get the newsletter search marketers rely on.

See terms.

Category entry points and the new SEO

Category entry points are the situations, needs, and triggers that put someone in the market to buy.

In the world of GEO, these are your new keywords.

They are what users express in prompts rather than in search terms. 

“Where can I find sustainable running shoes for flat feet?” is not a keyword query – it is a buying situation.

Your strategy is to:

  • Understand those buying situations.
  • Map them to your own performance attributes.
  • Create enough context that AI can confidently associate your brand with the solution.

That means describing not only what you do, but how you do it, who you do it for, and why you are distinctive.

This isn’t new. It’s the same foundational brand positioning marketers have always needed.

What’s changed is that it now feeds the world’s most sophisticated recommender system.

Dig deeper: AI search is booming, but SEO is still not dead

A local example: The sandwich shop in Stoke

Imagine a small sandwich shop in Stoke. It’s not glamorous, serving sausage sandwiches, bacon rolls, and coffee. 

The owners don’t want to be influencers. They just want customers.

How does a business like this make itself visible to AI?

Turn everyday details into data signals

The first step is to make its performance attributes explicit.

  • What ingredients are used?
  • Where do they come from?
  • What makes the sandwiches good value?
  • How long has the business served the local community?
  • Where is it located?
  • What is the hygiene rating?

All these details are small signals of trust and quality. 

A strong website should describe them in clear, human language. 

Every piece of information tells AI that:

  • This business exists.
  • It serves specific needs.
  • It performs well in doing so.

Build reputation where AI listens

Next, build local reputation. 

  • Encourage reviews on Google, TripAdvisor, and social media. 
  • Invite local bloggers to taste and review the food. 
  • Issue a press release about an anniversary or charity event. 

Every third-party mention adds more mutual information between your brand and the market – and that’s what AI learns from.

GEO is where good brand marketing meets intelligent technology.

Embrace both SEO and GEO

And for the “GEO is just SEO” crowd, yes, ranking on Google and in the local pack might be the best bet for increasing AI availability for this shop. 

However, it might also be hosting a relaunch event and inviting 30 local bloggers and press members to secure coverage.

Both are valid tactics with multiple benefits – and you can do both.

Until Google decides what it’s doing with the 10 blue links and AI Mode, bothism is the best plan – SEO and GEO, not just one.

From PR to performance

Larger businesses apply the same logic at scale. The recent wave of acquisitions in the SEO and analytics sector is a testament to this. 

These are deliberate attempts to control information ecosystems.

Owning media outlets, communities, and data platforms increases a company’s visibility in the information that AIs learn from. 

It creates an abundance of references that confirm expertise, authoritativeness, and relevance.

In traditional SEO, this is referred to as off-page optimization. 

In GEO, it is strategic distribution – where performance attributes and PR meet.

Your goal is to describe what you do, while making sure others also describe it.

Fame, distinctive assets, and consistency still matter. But the audience is no longer just human.

Dig deeper: AI search relies on brand-controlled sources, not Reddit: Report

Building AI availability

To make your brand visible to machines that now mediate discovery, you need to understand how and where that visibility is built.

Start with a visibility audit

Diagnose your current presence. 

Identify the category entry points most relevant to your products, and ask what prompts a user might type when they are ready to buy. 

Tools such as Semrush’s AI Enterprise platform can simulate these scenarios and show where your brand appears.

Get listed where AI looks

Identify the sources that AI models reference. 

Many LLMs use a mix of training data and live search, with listicles, directories, and “best of” articles among the most common data sources.

Being included in those lists is a sensible marketing strategy. 

Just as supermarkets stock their own shelves with their best products, you should position your brand among the best available options.

Expand your owned ecosystem

Over time, you’ll find saturation points where every competitor appears in the same lists. 

At that stage, innovation and owned media become essential. 

Start your own publication, commission original research, and contribute to conversations in your category.

Create context that earns recommendations

Digital shelf space isn’t the problem. Credible context amplifies your fitness signals.

Efficient, data-led, and creative, this is GEO’s manufactured style. But its success depends entirely on having a brand worth recommending. 

That’s why GEO is the outcome of proper marketing. 

Still, it’s proper marketing with a specific focus: increasing the likelihood of being recommended by AI.

The future of visibility

SEO has always been about optimization. 

GEO is about promotion – building and distributing enough credible, distinctive information about your business that an AI can recognize it as a trusted source.

The techniques look familiar: PR, branding, copywriting, partnerships, directories, and reviews. 

The difference lies in intent. You’re not feeding a search engine – you’re training an intelligence.

This requires a new mindset. 

  • You’re no longer optimizing for human users who type short queries into Google. You’re optimizing for a probabilistic model that interprets human intent across millions of contexts. 
  • It doesn’t care about your title tags. It cares about whether you look like the right answer to a real problem.

GEO is both exciting and humbling. 

It reconnects brand marketing and search after years of false division, and reminds us that while the tools evolve, the fundamentals endure.

You still need to be known, available, and distinctive. 

And now your audience includes machines that think like humans but learn on their own terms.

Back to fundamentals, forward with AI

GEO is a return to marketing fundamentals seen through a new lens. 

Businesses still grow by increasing availability. 

Consumers still buy from the brands they notice and can easily access. 

What has changed is the mediator: AI has become the primary distributor of attention.

Your task as a marketer is to make your brand’s performance attributes, category entry points, and distinctive assets visible in the data that AI consumes. 

The goal hasn’t changed – to be chosen. Only the mechanics are new.

Because in the age of AI, the only brands that matter are the ones the machines remember.

Read more at Read More

Web Design and Development San Diego

Search Central Live is back in Zurich!

/0 Comments/in , /by

We’re thrilled to announce our upcoming Search Central Live Zurich on December 9th!
This is a fantastic opportunity for SEO and digital marketing professionals to connect, learn and engage with each other and the Google Search teams.

Read more at Read More

7 local SEO wins you get from keyword-rich Google reviews

/0 Comments/in , /by
Google reviews local SEO

Keywords in reviews are generally believed to help local rankings, although their impact is still actively debated within the local SEO community.

Regardless of where the truth on ranking impact ultimately lands, keyword-rich reviews can still provide meaningful value for local SEO beyond pure rankings.

Below are seven reasons why you should still encourage keyword-rich reviews.

1. Review justifications

If your reviews consistently mention a keyword related to your business, the likelihood that your Profile will get a Review justification in search increases.

This visibility can boost click-through rates. Higher engagement may lead to a secondary improvement in search engine rankings.

Plumbing Google review justifications

2. Place Topics

Google creates clickable Place Topics from keywords in your reviews. These topics:

  • Highlight your specialties.
  • Filter reviews for customers.
  • Can boost your Profile’s engagement.
Google place topics

3. Review snippets

Google bolds frequently mentioned terms in three review snippets on the Business Profile. This draws users searching for those terms to your Profile, hopefully increasing click-through rates.

Google review snippets

4. Menu Highlights (restaurants)

The Menu Highlights are generated from customer reviews and photos, similar to Place Topics.

Maestro Pasta menu

Recent analysis from Claudia Tomina showed that:

  • The menu highlights section impacts rankings.
  • Keywords in reviews impact the Menu Highlights section.
  • Therefore, when you get a menu highlight for a term mentioned in your reviews, you should rank better for that term.

5. AI editorial summaries

Google’s AI-generated business summaries pull concepts from reviews (e.g., “cozy”) to describe your business.

While Google’s AI summaries aren’t something you can edit, encouraging customers to include specific keywords in their reviews could influence the AI to emphasize aspects most beneficial to your business.

Basta Pesta AI summary

6. AI review summaries

Google’s AI generates review summaries by analyzing common sentiments and tips from customer feedback.

If your customers mention the right keywords in their reviews, your review summary will appear more compelling.

Google AI review summaries

7. Ask Maps about this place feature

Google is phasing out the old Q&A section and replacing it with an AI-powered feature that pulls answers from customer reviews.

This means reviews with detailed info (and the right keywords) are more valuable than ever.

Skyway Roofing Ask Maps about this place

How do you get keywords in your reviews?

It does not make sense to directly ask your customers, “Can you please add [keyword] to your review?” It’s unnatural and weird and will leave the customer wondering what your deal is.

But that doesn’t mean you have no options.

To encourage customers to naturally include relevant keywords in their reviews, begin by upgrading your review request templates.

Miriam Ellis recently wrote a helpful guide all about how to get keyword-rich reviews, which also includes three review request templates to make it extra easy for every business owner.

These templates guide customers on what to say, encouraging longer, more detailed, keyword-rich reviews — and can even prompt them to add photos to their reviews.

Here are three of those templates:

Scenario 1: Requesting reviews of specific products

Hi [customer name],
I’m [your name and job title] from [company name], and I’m writing to check in with you on your purchase of [product]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? 
I’m enclosing a photo of [product] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with:
– The features of this product that stand out most to you– What you like or dislike about it– How you’ve been using the product since you purchased it   
If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.
[review us here link or button]
Sincerely,[name, job title, business]

Scenario 2: Requesting reviews of specific services

Hello [customer name],
This is [your name and job title] from [company name], and we were so happy to [service provided]. It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? 
I’m enclosing a photo of [the service that was provided] for your use in your review if you don’t have your own photo, and I’d be so grateful if you could review your experience with:
– Whether the service met your expectations– What you like/dislike about the service– How we did with our customer service 
If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied, and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.
[review us here link or button]
Sincerely,[name, job title, business]

Scenario 3: Requesting reviews when you’re not sure what a customer purchased

Email template
Hello [customer name],
Thank you for being our customer. I’m [your name and job title] from [company name], It’s my job to be sure you’re satisfied, and I wondered if you would be willing to provide your feedback in a review at [link]? 
I’m enclosing a photo of [the business premises] for your use in your review if you don’t have your own photo, and I’d love it if you could review:
– Whether you found our customer service helpful– What you like/dislike about our store– Why you chose our store 
If there’s anything we could have done better for you, please feel free to contact us directly at [phone number or feedback form link]. I want to be sure you’re fully satisfied and we’re so grateful for your business. Thank you very much if you can take the time to tell us about your personal experience in your review.
[review us here link or button]
Sincerely,[name, job title, business]

Now, make it work for you

By implementing a few simple improvements in your review requests, you will receive more detailed reviews from your customers, and their enhanced feedback will provide numerous benefits.

You may even increase your Google rankings for additional keywords, but I can’t guarantee anything. With all the other benefits, rankings shouldn’t be your primary goal anyway.

Read more at Read More

Home Services Digital Marketing Strategies

/0 Comments/in /by

Over 2.5 million home services businesses operate in the U.S., from HVAC companies and plumbers to pest control specialists and landscapers. Most compete within a 10-15 mile radius, fighting for the same local customers.

Here’s the problem: your potential customers need help right now. A burst pipe. A broken AC in July. A wasp nest over the front door. They’re Googling “emergency plumber near me,” asking ChatGPT for recommendations, or searching through Google’s AI Overviews for “same-day HVAC repair.” They’re calling the first business that looks trustworthy.

If you don’t show up in those searches, either traditional Google results or AI-generated answers, with strong reviews and clear contact info, you’ve already lost the job.

Home services marketing gets you in front of customers at the exact moment they need you, across every platform they’re using. This guide breaks down the specific tactics that work for local service businesses.

Key Takeaways

  • Home services marketing drives visibility when customers search during emergencies or urgent needs in your local area.
  • Reviews and your Google Business Profile directly impact whether customers call you or scroll to the next listing.
  • Effective home services marketing combines local SEO, paid search for high-intent keywords, and reputation management.
  • Mobile-optimized websites with click-to-call functionality are critical since most home services searches happen on phones.
  • AI search tools like ChatGPT and Google’s AI Overviews now influence how customers find local service providers.
  • Tracking call volume, form submissions, and cost per lead helps you invest in what actually brings customers through the door.

Why Do Home Services Businesses Need Marketing?

Referrals and repeat customers built your business. But what happens when your best referral source retires? Or when a new competitor opens two miles away and starts undercutting your prices?

Marketing creates a predictable lead pipeline that doesn’t depend on word-of-mouth alone.

Here’s what effective marketing does for home services businesses:

  • Generates leads during slow seasons. HVAC companies can’t survive on summer AC calls alone. Marketing keeps your calendar full with maintenance appointments, system upgrades, and off-season work.
  • Captures customers before they call your competitor. When someone searches “24-hour electrician,” three businesses appear in Google’s map pack. Marketing gets you in that top three instead of buried on page two.
    • Look at the example below. These three electricians dominate the local map pack for emergency searches. Notice how each has over 100 reviews, clear phone numbers, and “Open 24 hours” indicators. The businesses below this fold get far fewer calls.
Google results for "24 hour electrician Phoenix."
  • Builds pricing power through reputation. When you have 200+ five-star reviews and your competitor has 15, customers stop shopping on price alone. They’ll pay more for the business that looks trustworthy and established.
  • Lets you choose your customers. Good marketing attracts the right jobs at the right price points. You’re not just taking whatever walks through the door.

Without marketing, you’re reacting. With it, you’re in control of your growth.

What Makes Home Services Marketing Unique?

Home services marketing operates differently than retail, ecommerce, or B2B software. You’re selling an in-person service that requires customers to let strangers into their homes, often during stressful situations.

That creates three unique challenges:

Hyper-local competition. You’re not competing nationally. You’re fighting for visibility against 15-30 other plumbers, electricians, or HVAC companies within a 10-mile radius. Your customer in Austin doesn’t care about the best roofer in Dallas.

Trust is the primary buying factor. Customers research your business before opening their door. They check if you’re licensed, read what other homeowners say about you, and look for proof you won’t rip them off or do shoddy work.

Look below for an example of what customers see when researching a home services business. This HVAC company’s Google Business Profile displays detailed reviews mentioning specific technicians and response times. These trust signals matter more than flashy branding.

A Google Business Profile from an HVAC company.

Speed matters more than polish. Most home services searches are urgent. Customers need someone today, not next week. They’ll call the first business that answers the phone and can schedule them quickly. A beautiful website means nothing if your contact info is buried or your phone goes to voicemail.

This means your marketing needs to prioritize:

  • Mobile-first design since 70% of home services searches happen on phones.
  • Click-to-call buttons on every page, above the fold.
  • Service area pages for each city or neighborhood you cover.
  • Real customer photos showing your team, trucks, and completed work.
  • Fast page load times because impatient customers bounce quickly.

Digital Marketing Strategies For Home Services

Winning in local home services marketing requires a mix of visibility tactics and trust-building. You need customers to find you when they search, trust you enough to call, and remember you for future jobs.

The strategies below work specifically for home services businesses. Each section covers what the tactic does, why it matters for local service companies, and how to implement it without wasting money on tactics built for other industries.

Home Services LLM Marketing

Large Language Model (LLM) marketing optimizes your content to appear in AI-generated search results from tools like ChatGPT, Claude, Perplexity, and Google’s AI Overviews.

When someone asks ChatGPT “Who’s the best emergency plumber in Austin?” or uses AI Overviews to search “how to choose an HVAC company,” you want your business cited in those responses.

How to optimize for LLMs:

Answer specific questions clearly. Create content that directly answers common home services questions: “How much does furnace replacement cost in Chicago?” or “What causes low water pressure?” AI tools favor content that gets straight to the answer in the first paragraph.

Use structured data markup. Add schema markup (LocalBusiness, FAQPage, HowTo) to help AI understand your services, location, and expertise. This increases your chances of being cited as a source.

Build authority with detailed guides. Publish comprehensive resources like “Complete Guide to Emergency Plumbing Repairs” or “HVAC Maintenance Checklist for Homeowners.” AI models pull from authoritative, in-depth content when generating recommendations.

Check out this Google’s AI Overview for landscaping companies near Seattle. These businesses earned placement by creating structured, authoritative content that AI can parse and reference.

An AI Overview for landscaping companies near Seattle.

Claim and optimize your Google Business Profile. AI tools often reference Google’s local business data when making recommendations for service providers.

Home Services Content Marketing

Content marketing for home services means creating blog posts, videos, and guides that answer customer questions, build trust, and improve your local SEO rankings.

Customers research before calling. They want to know what the job costs, how long it takes, and whether they can trust you. Content answers those questions and positions you as the expert.

What works for home services:

Location-specific service pages. Create dedicated local landing pages for each service in each city you cover: “Emergency Plumbing in Austin, TX” or “AC Repair in Round Rock.” Include local details like average response times, areas served, and city-specific regulations.

Educational blog posts targeting search queries. Answer questions customers actually ask: “How do I know if my water heater needs replacing?” or “Why is my AC blowing warm air?” These posts drive organic traffic and demonstrate expertise.

Video content showing your work. Film your technicians diagnosing problems, completing repairs, or explaining maintenance tips. Video builds trust faster than text. The River Pools YouTube channel is a good example, showing repair tutorials and walkthroughs..

The River Pools YouTube channel.

FAQs on every service page. Add 3-5 frequently asked questions at the bottom of each service page. This helps with SEO and reduces pre-call questions.

Paid Media for Home Services

Paid search (PPC) puts your business at the top of Google instantly, above the map pack and organic results. For urgent home services searches, paid ads capture customers who need help now and will call the first number they see.

Home services keywords are expensive. “Emergency plumber” or “AC repair near me” can cost $15-$75 per click in competitive markets. That’s why your campaigns need tight targeting and strong conversion tracking.

Here are some best practices for home services PPC:

Target hyper-local, high-intent keywords. Bid on “emergency electrician in [neighborhood]” or “same-day HVAC repair [city].” Skip broad terms like “plumbing tips” that attract researchers, not buyers.

Use call extensions and location extensions. Make your phone number and address visible in every ad. Most home services customers call directly rather than visiting your website first.

Run call-only campaigns for mobile. Over 70% of home services searches happen on phones. Call-only ads display just your phone number and business info with a tap-to-call button.

In the paid ads for “emergency plumber NYC,” you can see book buttons, star ratings, and location info. Notice how these ads dominate the top of results before any organic listings appear.

Sponsored listings for "Emergency Plumber NYC."

Track phone calls, not just clicks. Use call tracking software like CallRail to measure which keywords drive actual phone inquiries and booked jobs.

Home Services SEO

SEO (search engine optimization) helps your business rank organically in Google without paying for every click. For home services, local SEO drives the most valuable traffic because customers search for providers in their immediate area.

Local SEO focuses on appearing in the map pack (the top three businesses with pins) and ranking for city-specific keywords. Getting into that map pack means more calls.

How to optimize local SEO for home services: 

Optimize your Google Business Profile completely. Fill out every section: business description, service areas, hours, attributes (veteran-owned, emergency services, etc.), and upload at least 10 photos. Add posts weekly to stay active.

Create dedicated pages for each service and location. If you serve five cities, create five separate pages for “AC Repair in [City].” Include local landmarks, neighborhoods, and zip codes in your content.

Build local citations. Get your business listed on Yelp, Angi, BBB, Chamber of Commerce, and industry directories. Consistent NAP (Name, Address, Phone) across all sites signals legitimacy to Google.

The example below shows a location-specific service page optimized for local SEO. Notice how the plumbing company includes the city name in the H1, mentions specific neighborhoods served, references local weather patterns, and includes a map showing their service area.

A location-specific page for a plumbing company.

Optimize for mobile speed. Run your site through Google PageSpeed Insights and fix any issues slowing load times. Slow sites lose impatient mobile customers.

Social Media For Home Services

Social media for home services builds local recognition and trust. You’re not trying to go viral. You’re staying visible so customers think of you first when their water heater breaks or their AC stops working.

Focus on Facebook and Instagram for residential customers, and add YouTube for educational content. LinkedIn works if you target commercial property managers or businesses.

What works for home services social media:

Post before-and-after photos of completed jobs. Show the clogged drain versus the clean pipe. The old HVAC unit versus the new installation. Visual proof builds credibility and gives customers confidence in your work quality.

Share customer testimonials and video reviews. Ask satisfied customers to record a 30-second video explaining their experience. Video testimonials feel more authentic than text reviews and perform better on social platforms.

Show your team and trucks in action. Post photos of your technicians arriving at jobs, working on repairs, or attending training. This humanizes your business and helps customers recognize your branded vehicles in their neighborhood.

The example below shows a foundation repair company’s Instagram feed with informational content, team photos, and customer shoutouts. 

A foundation repair company's Instagram page.

Engage with local community content. Share local events, sponsor youth sports teams, or highlight neighborhood news. This positions you as a community business, not just a service provider.

Post 3-4 times per week minimum. Consistency matters more than perfection.

Email Marketing For Home Services

Most home services businesses ignore email marketing, which leaves money on the table. Email keeps you connected with past customers and turns one-time jobs into repeat business.

Home services have natural repeat cycles. HVAC systems need annual maintenance. Gutters need cleaning twice a year. Pest control requires quarterly treatments. Email reminds customers to book before they call someone else.

How to use email for home services:

Send seasonal maintenance reminders. Email past customers in April about AC tune-ups before summer heat. In October, remind them about furnace inspections before winter. These emails generate easy repeat bookings.

Automate post-job follow-ups. Three days after completing a job, send an automated email asking for a review with direct links to your Google Business Profile. Follow up 30 days later with maintenance tips or related service offers.

Share monthly tips in newsletters. Send seasonal advice like “How to prevent frozen pipes” or “Signs your water heater is failing.” Educational emails keep you top-of-mind without being pushy.

The screenshot below shows a house cleaning company’s new stripping and waxing service seasonal email reminding customers to book spring maintenance. Notice the clear call-to-action button, features, and service photos.

A seasonal email from a house cleaning company.

Win back inactive customers. Email customers who haven’t booked in 12+ months with a special offer.

Home Services Reputation Management

Your online reputation directly impacts whether customers call you or scroll to the next business. Studies show 97% of consumers read customer reviews before choosing a local service provider. For home services, where customers invite strangers into their homes, reviews matter even more.

A competitor with 150 five-star reviews will get calls over you, even if your prices are lower and your service is better. Reputation management isn’t optional.

How to manage your reputation:

Ask for reviews immediately after completing jobs. Send a text or email within 24 hours with direct links to your Google Business Profile and Yelp. Happy customers forget to leave reviews if you wait too long. Make it easy with one-click links.

Respond to every review within 48 hours. Thank customers for positive reviews and mention specific details (“Glad Tom could solve your drainage issue so quickly”). For negative reviews, respond professionally, acknowledge the problem, and offer to make it right offline.

Display reviews prominently. Add a reviews widget to your website homepage. Screenshot your best Google reviews and share them on social media. Ideally, you should have as many ways as possible to feature testimonials.

Reviews on a home service website.

Monitor mentions across platforms. Use tools like Podium, Birdeye, or Google Alerts to track when your business is mentioned online.

Home Services Mobile/SMS Marketing

SMS marketing works exceptionally well for home services because customers open 98% of text messages within minutes. For time-sensitive communications like appointment confirmations and service updates, texting beats email every time.

How home services use SMS effectively:

Send appointment confirmations and reminders. Text customers 24 hours before scheduled service: “Reminder: Tom will arrive tomorrow at 2pm for your AC repair. Reply C to confirm or R to reschedule.” This reduces no-shows significantly.

Update customers on technician arrival. Text “Your technician is 15 minutes away” when your crew is en route. This courtesy builds trust and reduces anxious phone calls asking “Where are you?”

Request reviews via text. Send a review request within hours of completing a job: “Thanks for choosing us! How did we do? Leave a review: [link].” SMS review requests get 3x higher response rates than email.

Send seasonal promotions to past customers. Text previous clients with limited-time offers: “Spring AC tune-up special: $79 (reg $129). Book by 4/30. Reply BOOK to schedule.”

Keep messages short, personalized, and always include an opt-out option to stay compliant with 

Measuring Your Home Services Marketing Success

Tracking results tells you what’s working and where to invest more budget. Home services businesses should focus on metrics that directly tie to revenue: calls, bookings, and cost per customer.

Key metrics to track:

Phone call volume and source. Use call tracking software like CallRail or CallTrackingMetrics to see which marketing channels drive calls. Tag different phone numbers for your website, Google ads, and Facebook page to identify your best sources.

Form submissions and online bookings. Track how many people fill out contact forms or book appointments through your website. Set up conversion tracking in Google Analytics to measure this.

Google Business Profile insights. Check your profile’s dashboard monthly to see how many people viewed your listing, clicked for directions, called your business, or visited your website. This shows your local visibility trends.

Cost per lead and cost per customer. Calculate how much you spend to acquire each lead and each paying customer. If your Google ads cost $2,000/month and generate 40 leads with 10 becoming customers, your cost per customer is $200.

The screenshot below shows a CallRail dashboard tracking phone calls by source. Notice how it attributes calls to specific campaigns (Google Ads, organic search, Facebook) so you know exactly what’s driving results.

The CallRail Interface.

Source

Use Google Analytics, Ubersuggest, and your CRM to centralize this data in one dashboard.

FAQs

What is home services marketing?

Home services marketing is the process of promoting businesses like HVAC, plumbing, roofing, pest control, and other similar categories. It includes strategies like SEO, paid ads, local listings, email, and referral programs to attract and retain customers.

How to market home services?

Start with the basics: claim your Google Business Profile, build a review strategy, create local SEO-optimized service pages, and run targeted PPC campaigns. From there, test channels like email and SMS to nurture leads and win repeat business.

Conclusion

More leads, more reviews, and a full calendar don’t happen by accident. Home services marketing builds the visibility and trust that turn searchers into paying customers.

Start with local SEO and your Google Business Profile. These give you the foundation to appear when customers search for help. Add customer reviews to build credibility, then layer in paid ads and content to capture customers at every stage.

Track your results monthly. Know which channels drive calls and which waste budget. Double down on what works.

If you need help building a marketing strategy that fills your schedule, NP Digital works with home services businesses to create campaigns that generate real ROI.

Read more at Read More