Google has remained a stable source of traffic to news publishers over the past year. Although many websites have seen their traffic significantly impacted by Google’s AI Overviews, Chartbeat data shows that for 565 U.S. and UK news publishers:
Search referrals made up 19% of traffic in July, little changed since early 2019.
Google dominates search traffic: 96% of publisher referrals.
Yes, but. “Search” here includes Google Discover, which is not traditional search. Discover is now the primary driver of Google referrals.
Why we care. Search traffic hasn’t collapsed. However, the stability is somewhat masked by a shift from traditional Google Search to Google Discover.
Direct traffic is shaky. Efforts to build a loyal, “type-in” audience have largely stalled, leaving publishers more dependent on Google and aggregators. Direct traffic to homepages and landing pages has fallen to 11.5% from a pandemic-era high of 16.3%.
Social keeps sinking. Social’s decline means fewer diversified referral sources:
Facebook referrals are down 50% since 2019, despite a recent bump.
X traffic is down 75% vs. 2019.
Only Reddit is surging – up 220% since 2019, boosted by Google visibility and an AI training deal (but it still sends less referrals than Facebook and X).
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/how-publisher-traffic-referral-types-are-stacking-up-T7pCfN.png?fit=1220%2C758&ssl=17581220http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-19 18:06:512025-08-19 18:06:51Google traffic to news publishers is steady, but it isn’t traditional Search
Advertisers can now see exactly where their Search, Shopping, and App campaign ads are running across the Search Partner Network (SPN), with full site-level impression data.
How it works:
Reports list all SPN sites where your ads appeared.
Impression data is broken down at the site level.
Works like existing placement reports in Performance Max.
Why we care. Transparency has long been a sticking point with SPN. This update gives advertisers the visibility they’ve been asking for – and the ability to make smarter, brand-safe decisions.
The big picture. This change empowers advertisers to:
Audit brand suitability more effectively.
Optimize spend by analyzing which sites drive value.
Gain tighter control over campaign performance.
First seen.This update was first noted by Anthony Higman, founder and CEO of ADSQUIRE. He is still skeptical of Search Partner Networks despite it being an answer to a request advertisers have made for years:
“Still Most Likely Wont Be Participating In The Search Partner Network But This Is Unprecedented And What ALL Advertisers Have Been Requesting For Decades Now!!!”
Bottom line. Advertisers finally have the transparency and control needed to run on SPN confidently and optimize placements for better results.
Google announced it will shut down the Content API for Shopping on Aug. 18, 2026, officially making the Merchant API the new standard for managing Merchant Center accounts.
Why we care. For over a decade, advertisers and retailers have relied on the Content API to push product data into Google Shopping. The new Merchant API promises a simpler, more powerful way to control how products appear across both organic and ad surfaces – but it means developers and PPC teams need to start planning migrations now.
Details:
The Merchant API has been available in beta since May 2024, but is now generally available.
Google describes it as a “simplified interface” for scaling product feeds and gaining programmatic access to data, insights, and unique capabilities.
It will serve as the primary tool for product data management, spanning both paid and organic listings.
What’s next. The Content API remains available until August 2026, but Google urges advertisers to migrate sooner.
Help docs are live to guide developers through the transition.
Expect growing forum chatter as advertisers share migration challenges and best practices.
Bottom line. If your ecommerce business relies on the Content API, the clock is ticking. Moving to the Merchant API isn’t optional, and early adopters may gain a smoother path to scaling feeds and campaigns.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/Google-Shopping-Ads-Google-Ads-VSHoy9.jpg?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-19 15:26:462025-08-19 15:26:46Google replaces Content API for Shopping with new Merchant API
Generative AI is reshaping how people find information — but it hasn’t replaced search engines like Google. That’s according to a new Nielsen Norman Group study:
While users increasingly experiment with ChatGPT, Gemini and AI Overviews, most still default to old habits: starting with Google.
Why we care. Google is a habit – and habits are hard to break. That gives Google a built-in edge: even as AI eats into clicks, Google remains the default starting point for users. That means organic visibility still matters for brands and businesses. AI is reshaping the journey, but it won’t erase search overnight.
The big picture. According to the study:
AI overviews = fewer clicks. People notice and often rely on Google’s AI summaries, reducing the need to visit websites. Not new, and still bad news for publishers.
AI chat boosts efficiency. Once users tried Gemini or ChatGPT for complex tasks, they found them faster and more useful than traditional search.
Search isn’t gone. Even heavy AI users still cross-check with Google or visit content pages. No participant relied solely on AI for all information needs.
Familiarity wins. Just as “Google” became a verb, some users now casually call ChatGPT “Chat.” Brand familiarity may be the biggest advantage in AI search.
Bottom line. Generative AI is changing how people research – but it’s an evolution, not a revolution. The biggest barrier to AI adoption isn’t accuracy or UX, it’s human habit.
About the data. Nielsen Norman Group conducted remote usability testing with nine participants in North America and UK, representing diverse demographics and levels of AI experience. Sessions explored how users approached real research tasks with search engines and AI tools.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/generative-ai-search-google-5vSPei.webp?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-19 15:12:532025-08-19 15:12:53Generative AI is changing search, but Google is still where people start: Study
After Amazon pulled its ads from Google Shopping on July 23, clicks became cheaper, and volumes rose, but the value of that traffic dropped. That’s according to a new study from Optmyzr, which analyzed 6,137 advertiser accounts.
By the numbers (all categories combined):
Clicks: +7.8%
CPC: -8.3%
Conversion Value: -5.5%
ROAS: -4.4%
Why we care. Less competition doesn’t automatically help advertisers, and more traffic doesn’t always mean better business. Amazon-trained shoppers still expected rock-bottom prices, fast shipping, and seamless buying. When competitors couldn’t deliver, conversion value fell.
Category winners and losers. Electronics was the clear winner. Retailers like Best Buy and Apple matched Amazon’s offer, driving +81% conversions and +7% ROAS. In other categories:
Home & Garden, Sporting Goods, Tools, Apparel: Fell into the volume trap – more clicks, but lower value and weaker ROAS.
Health & Beauty: Traffic converted, but at a lower per-sale value.
Apparel & Accessories: The largest category by volume, but saw a -9.5% drop in conversion value.
Between the lines. Amazon wasn’t just another bidder – it was shaping shopper expectations across categories. When Amazon left, those expectations didn’t reset, the study suggests.
Bottom line. For PPC advertisers, cheaper clicks aren’t a win if they don’t turn into profitable customers. Without Amazon-level pricing and convenience, many brands risk falling into the volume trap.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/Screenshot-2025-08-19-at-13.36.28-Vcw75n.webp?fit=882%2C631&ssl=1631882http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-19 14:21:112025-08-19 14:21:11Clicks rose, ROAS fell when Amazon left Google Shopping
AI search is evolving fast, but early patterns are emerging.
In our B2B client work, we’ve seen specific types of content consistently surface in LLM-driven results.
These formats – when structured the right way – tend to get picked up, cited, and amplified by models like ChatGPT and Gemini.
This article breaks down five content types gaining notable AI search visibility, what makes them effective, and how to optimize them for LLM discovery:
Comparison pages.
Integration docs/open APIs.
Use case hubs.
Thought leadership on external platforms.
Product docs with schema.
1. Comparison pages
Our analysis shows that Gemini frequently surfaces “X vs. Y” content in AI Overviews and AI Mode – even when the query doesn’t ask explicitly for the comparison.
What to include
Publish /vs/ pages with pros, cons, pricing, use case match, and schema.
Do this for any competitors that bring in a decent volume of comparison queries, along with any comparisons that are easily related to your product or service.
2. Integration docs/open APIs
Our analysis has provided numerous instances of GPTs and Copilot citing SaaS APIs and dev docs in answers.
Example
A ChatGPT prompt for “setting up span metrics for backend services” cited a docs page from performance monitoring company Sentry in a list of best practices.
What to include
Maintain clear documentation + changelogs with versioning and schema.
LLMs pick up posts from company experts, including founders, SMEs, and established thought leaders, on outlets like Medium and Dev.to for strategy-based questions.
Example
What to include
Syndicate posts from a company founder, SME, or brand ambassador with a unique POV, then include a canonical link back to the business website.
5. Product docs with schema
Gemini AI Mode lifts from product docs if they’re structured with FAQs, How-to sections, and/or breadcrumb structured data.
Example
What to include
Add FAQPage, HowTo, breadcrumb structured data, and SoftwareApplication schema types to product docs.
3 overarching recommendations
You should never veer from the E-E-A-T principles that have long underpinned traditional SEO. Those same tenets will serve you well for LLM discovery, too.
Beyond them, however, there are a few LLM-specific steps to consider if your goal is to increase AI search visibility.
I’ll break down three key recommendations.
Optimize for multi-modal support
AI search systems are increasingly retrieving and synthesizing multimodal content (think: images, charts, tables, videos) to better answer user queries.
Flex your content across multiple media types to provide more useful, scannable, and engaging answers for users.
Specific recommendations:
Ensure images and videos remain crawlable for search and AI bots.
Serve images via clean HTML and avoid lazy-loading with JavaScript-only rendering, since LLM-based scrapers may not render JavaScript-heavy elements.
Images should use descriptive alt text that includes topic context.
Add captions to images and videos with an explanation right below or beside the visual.
Use <figure>, <table>, etc., with contextually correct markup to help parse tables, figures, and lists.
Avoid images of tables. Use HTML tables instead for a machine-readable format supporting tokenization and summarization.
Optimize for chunk-level retrieval
AI search engines don’t index or retrieve whole pages.
They break content into passages or “chunks” and retrieve the most relevant segments for synthesis.
Optimize each section like a standalone snippet.
Specific recommendations:
Don’t rely on needing the whole page for context. Each chunk should be independently understandable.
Keep passages semantically tight and self-contained.
Focus on one idea per section: keep each passage tightly focused on a single concept.
Use structured, accessible, and well-formatted HTML with clear subheadings (H2/H3) for every subtopic.
AI search engines synthesize multiple chunks from different sources into a coherent response.
Aim to make your content easy to extract and logically structured to fit into a multi-source answer.
Specific recommendations:
Summarize complex ideas clearly, then expand (A clearly structured “Summary” or “Key takeaways”).
Start answers with a direct, concise sentence.
Favor a factual, non-promotional tone.
Use structured data to help AI models better classify and extract structured answers.
Use natural language Q&A format.
Create B2B content that wins in AI search
An added benefit of these five content types is that they span multiple intent stages – helping you attract prospects and guide them through the funnel.
Just as important: make sure your AI search measurement systems are in place (we use Profound, GA, and qualitative research) so you can track impact over time.
And stay tuned to reports and industry updates to keep pace with new developments.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/does-carbon-steel-rust-AI-Overview-uHICar.png?fit=1600%2C680&ssl=16801600http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-19 13:00:002025-08-19 13:00:005 B2B content types AI search engines love
When it comes to AI-powered search, visibility isn’t just about ranking – it’s about being included in the answer itself.
That’s why generative engine optimization (GEO) matters. The same technical SEO practices that help search engines crawl, index, evaluate, and rank your content also improve your chances of being pulled into AI-generated responses.
The good news? If your technical SEO is already strong, you’re halfway there. The rest comes down to knowing which optimizations do double duty: improving your rankings while boosting your visibility in generative results.
This article breaks down four technical pillars with the biggest impact on GEO success:
Schema markup.
Site speed and performance.
Content structure.
Technical infrastructure.
1. Schema markup: Speaking AI’s language
Schema has long been essential for SEO because it removes ambiguity. Search engines use it to understand content type, identify entities, and trigger rich results.
For GEO, schema clarity is even more important. LLMs favor structured data because it reduces ambiguity and speeds extraction. If your content is marked up clearly, it’s more likely to be selected and cited.
Priority schema types for GEO
Focus on evergreen types that improve visibility:
FAQPage: Clearly labeled Q&A helps LLMs match user queries and surface your answers.
HowTo: Structured step-by-step processes are easy for AI to extract.
Product / Service: Defines pricing, availability, and specifications for accurate inclusion.
Article / NewsArticle with Author: Authorship adds a trust signal to your content.
Organization / LocalBusiness: Reinforces your identity, entity clarity, and local authority.
Review / AggregateRating: Provides social proof that AI engines use as quality signals.
VideoObject / ImageObject: Makes your multimedia easier for AI to find and feature.
BreadcrumbList: Improves context and page hierarchy mapping.
Implementation best practices
Use JSON-LD format (Google’s recommended approach).
Test rigorously with Google’s Rich Results Test and Schema Markup Validator.
Keep markup synced with your visible content – outdated schema erodes trust.
Don’t overdo it: mark up only what helps explain the content.
Bottom line: Schema improves your chances of being cited in AI answers, keeping competitors out of the box.
2. Site speed and performance: A (dis)qualifying factor
Generative engines pull from billions of pages. If yours is slow or unstable, they can skip it in favor of faster, more reliable sources.
Quick performance wins
Compress images; use WebP or AVIF; enable lazy loading.
Eliminate render-blocking CSS and JavaScript.
Target a server response time (TTFB) under 200ms.
Use a CDN to reduce latency.
Bottom line: Speed could be a tiebreaker between equally relevant sources. Faster pages have higher odds of inclusion in AI-generated answers – and they convert better once users click through.
3. Content structure: Making information machine-readable
LLMs rely on clarity. The easier it is for machines to parse and organize your content, the more likely it is to appear in AI-generated results.
JavaScript rendering: Don’t hide core content behind heavy client-side rendering. Use server-side rendering for anything essential.
Bottom line: If search or generative engines can’t crawl, verify freshness, or trust your site, your content won’t be considered – no matter how authoritative it is.
Building for search and AI success
The technical elements that drive GEO success aren’t new. They build on SEO fundamentals you already know:
Schema.
Performance.
Structure.
Infrastructure.
But in the AI era, these aren’t just best practices – they’re the deciding factors between being featured and being forgotten.
Getting this right will preserve your search visibility and put your content at the center of AI-driven answers.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/technical-seo-geo-EJueUs.webp?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-19 12:00:002025-08-19 12:00:00A technical SEO blueprint for GEO: Optimize for AI-powered search
TikTok is capping hashtags at five per post, a shift some users have recently noticed through in-app notifications.
Details. TikTok hasn’t formally announced the update. A Reddit user said a TikTok notification explained the change is aimed at:
Reducing hashtag clutter,
Discouraging spammy usage,
Improving discovery relevance.
TikTok is the latest social platform to sideline hashtags:
X dropped hashtags from ads.
Meta’s Threads limits posts to one topic tag, while Instagram is testing a five-hashtag cap.
LinkedIn has de-emphasized them.
Why we care. Hashtags have long been used to boost reach, but platforms are dialing them back as algorithms rely more on engagement signals – and as spammy, irrelevant tags clutter feeds. This could improve relevance and reduce spammy competition, but it also raises the stakes for picking the right hashtags to ensure campaigns still surface in discovery.
The big picture. For creators, the change means quality over quantity. Picking the most relevant hashtags matters more than piling on extras. TikTok’s Trends dashboard can help surface the tags most likely to drive discovery.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/tiktok_hashtags-GzFiUk.webp?fit=320%2C692&ssl=1692320http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-18 18:52:522025-08-18 18:52:52TikTok limits posts to five hashtags
Google’s AI results are changing everything about how local businesses get discovered—and reviews are now at the center of it all. They shape visibility, build trust, and, when leveraged effectively, drive conversions.
In this live webinar, GatherUp VP of Marketing Mél Attia and renowned Local SEO expert Miriam Ellis will share never-before-seen research findings on how AI and consumer behavior are reshaping local SEO. You’ll discover:
How Google’s AI-powered results are prioritizing local businesses
What consumers really care about when evaluating businesses
Why reputation and reviews are the ranking lever most agencies underutilize
New consumer data, benchmarks, and tactical frameworks to boost your clients’ results
Whether you’re helping clients gain visibility, prove trustworthiness, or turn reviews into revenue, this session will equip your agency with actionable insights—and a narrative that makes review strategy impossible to ignore. You can save your seat here!
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/Search-Engine-Land-live-event-save-your-spot-yrSwPI.jpg?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-18 18:31:472025-08-18 18:31:47Winning the local SEO game in the age of AI by Edna Chavira
Search is changing fast. This year, we’ve seen more instances of search engine results sharing space with AI-powered features that are changing how people find information.
Along with the changes to how search engines display information, we’re also seeing users explore new methods to search for information. Google AI Mode, Gemini, ChatGPT, Perplexity – there are many large language models (LLMs) capturing users’ attention, providing new ways for users online to discover and make decisions about your brand.
Customer sentiment, shown through reviews and ratings, is becoming a key part of both local and branded search.
For brands looking to stay ahead, focusing on sentiment, review ratings, and authority signals will be key. These are the items that not only affect rankings but also impact what shows up in search snippets and LLM responses.
LLMs like Google’s AI Mode are pulling together and highlighting customer sentiment within their responses when asked about specific brands or for geo-modified search queries, think “home repair near me”.
For businesses, paying attention to their review strategy and reputation will be key to standing apart in local results, overall organic visibility, and showing up favorably in AI responses. However, even with these changes, many of the tried-and-true best practices that have helped brands succeed in local search in the past still apply.
Searches with local intent: Google’s AI Mode
When it comes to local search, “near me” queries continue to be highly important. In traditional search, these typically trigger a Local Pack followed by organic blue links.
In Google’s AI Mode, the experience is similar. Users are shown a list of local businesses, often with short descriptions, star ratings, and review summaries.
The links cited are usually citation platforms like Yelp or TripAdvisor, business websites, or publications, and it’s common to find Google Business Profile place cards. Clicking these opens the familiar Google Business Profile interface, keeping users within the Google ecosystem.
What does this mean for businesses aiming to capture visibility in AI-driven local search results? Many of the foundations of local SEO still apply.
NAP consistency: Ensure your business name, address, and phone number (NAP) are accurate and consistent across all listings.
Citations: Maintain listings on trusted third-party sites like Yelp, TripAdvisor, and local directories to help reinforce credibility.
Google Business Profile optimization: Fully complete and regularly update your profile with accurate info, photos, business hours, and relevant categories.
Reviews: Generate and respond to reviews to build trust and signal relevance to both users and search engines.
Branded search results for local businesses
When searching for a local business using branded terms in AI Mode, it’s common to see many of the same elements and data sources as traditional search. These business overviews often include a description of the company, the products or services offered, and customer sentiment.
Often, the customer sentiment section summarizes review data pulled from multiple sources, such as TripAdvisor, Yelp, industry-specific sites such as Apartments.com, and Google Business Profile.
What’s unique about AI Mode is that it provides unbiased summaries of pros and cons about a business based directly on available customer reviews, which can come directly from Google Business Profile or be a mixed of review data from trusted online sources. These clear overviews include overall sentiment and often link to the business profiles.
AI Mode isn’t the first time Google has experimented with review summaries.
Some industries, like restaurants, already have “Review Summaries” in organic search results. These generative AI summaries highlight Google Business Profile review data, usually with a more positive tone, alongside the star rating and list of reviews.
The importance of reviews
Reviews shape how your brand appears online, whether they are displayed front and center on your Google Business Profile or surfaced as snippets in responses from LLMs. Google’s AI Mode, ChatGPT, and Perplexity all returned some information or mention of customer reviews when searching for local businesses, especially for branded queries.
These responses emphasize how both positive and negative offline experiences can influence what is said about your brand online and the importance of customer perception, especially when those experiences get highlighted for customers who may be discovering your brand for the first time.
Businesses need to pay attention to reviews, if not across all platforms, then at least on Google Business Profile. Review data is being pulled into AI-driven results and also plays a role in local search visibility.
“Prominence means how well-known a business is. Prominent places are more likely to show up in search results. This factor’s also based on info like how many websites link to your business and how many reviews you have. More reviews and positive ratings can help your business’s local ranking.”
How can businesses adapt?
By following the tactics local businesses should already be doing to succeed in local search:
Focus on generating new, recent reviews.
Respond to both positive and negative reviews.
Read reviews to understand the strengths and weaknesses of your business. Seeing a trend in negative reviews? That could indicate it’s time to make some changes and address those weaknesses.
Monitor brand mentions not just for backlinks but also to understand what people are saying about your business online, including community forums, social media platforms, and online publications.
In addition to traditional review sites, platforms like Reddit, TikTok, and Quora are showing up more frequently in branded and local search results. These conversations are also being picked up and summarized in tools like Perplexity and ChatGPT. That means the things people are saying about your business in comment threads or short-form videos can influence how your brand is being represented across both organic and AI-powered results.
What else can be done:
Look closely at how your business is perceived online and do the same for your competitors.
Compare your review count and average star rating to those of businesses showing up alongside you in the Local Pack. How does your business stack up?
Check how AI tools like LLMs or Google’s AI Mode describe your competitors during branded searches and identify where they source that information.
Try asking AI tools to compare your business and a competitor. The way these tools summarize differences can give insight into strengths, weaknesses, and areas where you may need to improve to stay competitive in the market.
LLM data sources
LLMs pull from a range of online sources to build summaries about businesses. For local and branded search queries, much of the information they use closely mirrors what shows up in traditional organic search results. This includes data from:
Google Business Profiles.
Third-party review sites.
Official business websites.
Wikipedia.
Online directories and aggregators.
News articles.
Public conversations on forums or social media.
LLMs don’t use the same ranking algorithm as Google Search, but they rely on much of the same publicly available information.
Why this matters:
The efforts businesses make to improve local SEO, such as maintaining accurate listings, collecting reviews, and building authority, also help shape how their brand is represented in AI-generated search results.
Reinforces the importance of managing your presence across multiple platforms and staying aware of where your brand is mentioned.
Highlights trusted third-party sites where your business may be listed but not actively managed. These listings still influence visibility and should not be overlooked.
Identifies which platforms are trusted within your specific industry, revealing opportunities to strengthen your presence on niche or vertical-specific sites.
Managing reputation at scale for multi-location businesses
For multi-location and microbrand businesses, managing sentiment at the local level adds another layer of complexity. It is not just about how the overall brand is perceived, but how each location appears in search results. This is especially important for industries like senior living, apartment communities, and healthcare, where customer experience and trust are crucial in decision-making.
A few negative reviews tied to a single location can shape perception across the board. That is why reputation strategies need to scale while still staying localized. Each location needs a clear plan to monitor feedback, respond to reviews, and build a strong presence in both traditional and AI-powered search results.
Core local SEO principles remain
Search is evolving fast, and we can expect more LLMs and AI-powered features to continue to shape how information is delivered to users.
Customer sentiment and brand perception are now more important in shaping how a business appears online, whether it’s in traditional organic search results or another platform.
Why?
Because perception matters, both online and in real life. Tools like Google’s AI Mode, Perplexity, Gemini, and ChatGPT are putting reviews, ratings, and sentiment summaries front and center, making customer feedback more visible than ever.
Now is the time for brands to take a close look at how they appear in LLMs, understand the feedback being surfaced, and identify areas to improve. Doing this not only helps with visibility in AI-driven search but also strengthens your local market presence.
As part of a broader brand reputation and visibility strategy, it’s essential to regularly monitor how your business is showing up in both traditional and AI-powered search results. That includes checking branded SERP features like AI Overviews, People Also Ask, video carousels, and social content pull-ins. These elements shift often, and staying aware of what’s being surfaced helps inform both SEO and reputation efforts.
You don’t need to reinvent the wheel. To keep up with the changing search landscape, you just need to focus your efforts in the right direction.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/08/running-store-near-me-google-ai-mode-FbvBhZ.png?fit=767%2C622&ssl=1622767http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-08-18 18:03:342025-08-18 18:03:34Want to win at local SEO? Focus on reviews and customer sentiment
Clicks: +7.8%
CPC: -8.3%
