Recently, we’ve seen a rapid rise of LLMs and AI search, but in contrast, community and social search are powered by human ingenuity and connection. This marks a new paradigm where authenticity, community validation, and real-time engagement form the cornerstones of brand visibility and consumer trust today. 

The Trust Deficit and the Rise of Community Validation

Recent data highlights a significant erosion of trust between consumers and brands, emphasizing a critical need for transparency and ongoing engagement. Consumers today are not just skeptical — they actively seek validation from trusted communities and peers. 

This shift is evident in changing search behaviors, with many adding “Reddit” to the end of their Google searches or turning to niche search engines, social platforms, and AI-powered answer engines for more authentic insights. User-generated reviews, trusted creator partnerships, and peer-to-peer recommendations are now pivotal in guiding consumer decisions, offering brands opportunities to rebuild trust through authentic community conversations and validated content.

Brands that authentically plug into conversations and use UGC effectively find themselves well-positioned to build credibility. For instance, relatable customer reviews and non-forced testimonials have consistently proven more persuasive than branded advertisements, directly impacting purchase decisions. Partnerships with creators and influencers who effortlessly align with a brand’s values further amplify this trust, forging deeper, more authentic consumer relationships.

This trust deficit is rampant in the creator economy as well. Creators remain central to brand discovery, but authenticity is paramount. Modern consumers readily discern between genuine endorsements and overtly promotional messaging, valuing the former significantly more. Approximately 71% of consumers report a higher likelihood of purchasing products endorsed by trusted influencers. Consequently, brands must focus on aligning with creators whose values and messaging resonate authentically with their target audiences.

Successful creator partnerships prioritize long-term relationships, fostering genuine connections rather than one-off campaigns. Brands that adopt this approach gain sustained credibility and deeper consumer engagement, capitalizing on influencers’ ability to drive meaningful, authentic interactions.

The Fragmentation of Search: The Rise of Social Search

Conventional search engines like Google and Bing no longer monopolize how consumers discover brands. In addition to AI search platforms, social platforms like TikTok, Instagram, LinkedIn, and YouTube have emerged as significant channels for brand exploration and discovery. Approximately 78% of global internet users utilize social media for product research, and notably, around 40% of Gen Z adults specifically prefer these platforms for brand discovery.

With today’s fragmented search landscape, almost anything can be a search engine. That’s why there’s also a rise of specialized search engines and vertical-specific platforms that help users get better answers, faster.

Instead of turning to Google as the source of truth for all search queries, users, particularly younger Gen Z consumers, are using Beli or Yelp to find restaurants, Zocdoc to find doctors, Expedia to find hotels, and Spotify to discover new music. This shift underscores the need for brands to rethink content strategies, optimizing not just for keywords but also for relevant visibility and engagement within social search contexts.

Social search thrives on authentic, visually engaging, and rapidly consumable content — short-form videos, concise storytelling, and visually rich experiences that align with user browsing behaviors. But beyond seeking direct answers, users increasingly turn to social search for community perspectives and nuanced opinions that help shape their own viewpoints.

Brands that understand and master these new search behaviors stand to significantly improve their discoverability and foster deeper community engagement by tapping into conversations that reflect collective experiences, not just transactional queries.

Generative AI Meets Social Search: The Future of Search Experiences

The intersection of generative AI with social search is reshaping how users discover and interact with brands. Platforms such as TikTok increasingly function as dynamic, personalized search engines driven by AI algorithms that prioritize engaging, authentic, and community-validated content.

An April 2024 survey found that 45% of Gen Z users prefer TikTok over Google for discovering new products and information, highlighting a substantial shift towards interactive, AI-enhanced search experiences. TikTok doubled down on this shift by expanding its search capabilities, more recently adding search highlights by providing summaries to top-ranking videos and allowing search ads on the platform. 

When you think about it, this makes the news of Perplexity AI’s interest in acquiring TikTok no surprise, as it underscores a strategic alignment: leveraging TikTok’s extensive community-driven data to enhance AI search and recommendation systems. This probably offers the best example of how generative AI meets social graph. These integrations point toward a future where social content significantly informs generative AI capabilities, delivering highly personalized and credible search experiences.

Social Content as Retrieval Sources for AI Search & LLMs

According to Goodie AI’s recent AEO periodic table, social content – including consumer sentiment, mentions, and reviews – has become invaluable for AI search engines and LLM retrievals. They’re key variables in deciding a brand’s visibility.

Platforms like Reddit, known for authentic, unfiltered user-generated content, provide rich, nuanced data that significantly enhances the authenticity and relevance of AI-generated responses. Brands actively engaging in such communities not only increase their visibility but also influence AI conversations about their products and brand narrative.

To put it in context, Reddit.com saw a 1,328% increase in SEO visibility on Google between July 2023 and April 2024, according to Sistrix data cited by Amsive. The major change that year was the introduction of Gemini and AI overview, which favors Reddit as a source to validate claims and user sentiment.

By tapping into real-time social content, AI search experiences can offer depth and accuracy, positioning brands effectively within genuine consumer conversations. This integration further reinforces consumer trust by ensuring search results reflect authentic community feedback rather than solely brand-produced narratives.

Leveraging Community-Driven Content for Enhanced Discoverability

Actively engaging with community-driven content — customer reviews, forums, and social media interactions — is essential for brands aiming to boost discoverability and authenticity. Encouraging and amplifying customer experiences helps brands organically improve their visibility across social platforms and search results.

Community engagement itself has become a key strategy for brands’ social media teams, as comment sections become more and more of a space for brands to participate in relevant conversations and show off their unique tone of voice or point of view.

Brands successful at facilitating vibrant community interactions through dedicated forums, discussion groups, UGC content or micro-community platforms, enjoy not just increased visibility but also heightened trust and loyalty from their customer base. This active involvement significantly enhances both brand reputation and reach.

Case Studies of Community & Social Search Success Stories

Duolingo’s Community Powering Language Learning Ecosystem

Duolingo revolutionized language learning discovery by creating a multi-layered community ecosystem that drives both engagement and organic growth. Their approach centered on transforming traditional education into a community-validated experience through several key initiatives:

• The Duolingo Forums: A dedicated space where learners discuss language nuances, cultural contexts, and learning strategies, generating over 25,000 monthly posts that serve as rich retrieval sources for AI-powered search.
• User-Generated “Stories” Feature: Community members create and share language learning narratives, resulting in 3.2x higher retention rates for users who engage with community content.
• TikTok-Optimized Learning Snippets: User-generated language tips that drove a 189% increase in organic app discovery, particularly among 18-24 year olds.

Notably, Duolingo found that learners who discovered the platform through authentic community content demonstrated 47% higher daily engagement and 2.8x longer lifetime value compared to users acquired through traditional advertising.

The company’s approach directly aligns with the evolution of community-driven search by prioritizing authentic peer validation, leveraging user-generated content across multiple platforms, and creating an ecosystem where community insights directly inform product development, creating a trust-building feedback loop.

Lululemon’s Product-Led Community Strategy

Lululemon transformed its approach to product discovery by creating a robust community feedback loop centered around their mobile app. By implementing community product ratings, authentic user-generated content, and direct integration with their ambassador network, Lululemon achieved remarkable results:

• 72% increase in product discovery through community recommendations
• 4.8x higher conversion rate for products with user-generated imagery compared to professional photography alone
• 68% of new customers reported discovering the brand through peer recommendations or community content

The company further leveraged this strategy by integrating community feedback directly into product development, creating a virtuous cycle where customer input shapes future offerings, strengthening loyalty, and amplifying organic discovery.

Glossier’s Reddit-First Approach

Glossier pioneered a “Reddit-first” strategy that prioritized authentic community engagement over traditional marketing. Rather than simply monitoring mentions, the brand actively participated in skincare and beauty subreddits, providing valuable expertise without overtly promoting products. This approach yielded:

• 215% year-over-year increase in organic search traffic from community-driven platforms
• 3.2x higher customer retention rates for customers acquired through community channels
• Significant improvement in AI-powered search visibility as their content became a trusted retrieval source

Most notably, when Glossier launched new products, they saw 40% of first-week sales come directly from Reddit community members, demonstrating the powerful conversion potential of authentic community engagement.

Oatly’s TikTok Community Strategy

Oatly reimagined brand discovery by prioritizing TikTok’s community-driven search ecosystem. Instead of creating overtly branded content, they empowered customers and micro-creators to showcase authentic product experiences, resulting in:

• 11 million user-generated impressions in a single quarter
• 189% increase in brand discovery among Gen Z consumers
• 5.7x ROI compared to traditional digital marketing channels

Critically, Oatly discovered that when consumers discovered their products through authentic TikTok content, they were 3.4x more likely to become repeat purchasers compared to those who discovered the brand through paid advertising, highlighting the trust premium associated with community-validated discovery.

Emerging Trends Shaping Social and Community Search

Several additional trends merit attention for brands navigating next-gen discoverability:

• Micro-Communities: Platforms such as Discord and Substack allow brands to foster close-knit, highly engaged communities, offering targeted visibility and deeper trust-based relationships. 
• Searchtainment: Younger audiences view search as entertainment, consuming informative yet visually engaging content. Brands embracing this style align closely with user expectations, boosting engagement.
• The Authenticity Paradox: Brands face the delicate balance of demonstrating authenticity without appearing contrived. Transparency and genuine behind-the-scenes content resonate deeply, enhancing consumer trust.
• Peer-to-Peer Recommendations: Direct peer recommendations remain the most trusted brand endorsements, moving beyond traditional reviews into intimate digital spaces like WhatsApp and private messaging platforms.
• Co-Creation with Communities: Brands actively involving their audiences in content creation, product design, and strategic decisions foster higher trust and alignment with consumer needs, driving brand advocacy.

By strategically integrating these insights and tactics in GTM motions, brands can adeptly navigate the shifting landscape of discoverability, turning consumer skepticism into authentic engagement and enduring brand loyalty.

Community and social search not only redefine brand discovery but also elevate trust, connection, and visibility, setting the foundation for future marketing and distribution and the war for consumer attention. 

The post The Future of Brand Discovery Between Social Search & Generative AI appeared first on NoGood™: Growth Marketing Agency.

In traditional organic search and SEO, most strategies revolve around climbing rankings on search engine results pages (SERPs). But with Generative Engines like ChatGPT, Perplexity, and Gemini are driving more and more search behavior, users are asking questions in a conversational way and receiving synthesized, context-rich answers that often eliminate the need to click on external links.

The concept of Generative Engine Optimization (GEO) emerges as the strategic framework to ensure your brand is both discoverable and cited by these new highly intelligent engines. This is an area that we have research and written about extensively. To succeed in this new landscape, brands need a playbook that weaves together the sustainable SEO fundamentals as well as AI Search insights.

This guide will walk you through why GEO matters, how it differs from standard SEO, what ranking factors drive AI-based visibility, and how to implement effective GEO strategies and measure impact.

Why GEO Matters More Than Ever

Generative AI has turned the concept of “search” on its head. Users no longer need to browse through lists of blue links; advanced LLMs can synthesize meaningful answers in real time, often without sending the user to an additional website. This answers-first paradigm carries big implications for brands and marketers:

• Visibility is more elusive: Simply ranking #1 on Google doesn’t guarantee you’ll be featured in an AI-generated response.
• Users expect concise, context-rich replies: They might never see your well-optimized landing page if the AI chat interface provides everything they need.
• Multi-turn conversations: Users can refine queries on the fly and ask follow-up questions, shifting from “What are the best running shoes?” to “Which brand is eco-friendly?” and “Where can I buy them locally right now?”—all in a single session.

In this environment, your brand must be recognized by AI engines as authoritative, trustworthy, and contextually relevant. Generative Engine Optimization (GEO) ensures that you not only exist in a search index, but also become a central piece of the conversation—that is, the conversation between the user and the AI model.

The Consequences of Not Adapting

Brands that ignore GEO risk fading out of AI-driven ecosystems, losing mindshare and, ultimately, conversions. Traditional SEO alone is no longer sufficient; even if your page ranks well on Google, AI results may overshadow standard SERPs or reduce click-through rates. Thus, investing in GEO now is an investment in future-proofing your brand’s discoverability.

What Is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the practice of influencing and optimizing how AI-driven search systems—especially those powered by LLMs—access, interpret, and include your content in their automatically generated answers.

While SEO focuses on ranking in traditional SERPs, GEO goes a step further. With GEO, your objective is to:

1. Embed your brand, data, and expertise into the knowledge base and training sets of AI models.
2. Align your content structure and signals so that real-time AI search engines (e.g., Perplexity, Bing Chat, ChatGPT Search) see you as a relevant, high-authority source.
3. Encourage AI to cite or reference your brand and offerings in the final, synthesized response it delivers to the user.

It’s a holistic approach that blends technical SEO with content quality, brand authority, and community engagement, all under the lens of how advanced AI systems process and produce information.

Generative Engine Optimization (GEO) vs. Answer Engine Optimization (AEO): What’s the Difference?

GEO and AEO are both strategies aimed at boosting the visibility of your content online in AI-driven search functions, but AEO encompasses additional platforms beyond those targeted by GEO practices, and GEO is geared toward ensuring your content is one of many sources used in the synthesis process that enables AI platforms to provide succinct and summarized answers.

Both AEO and GEO methodologies strive to provide concise, direct answers to user queries to increase the chance of appearing in AI-generated results. With GEO, as we’ve discussed, this refers to AI-driven search systems, and particularly LLMs. With AEO, this can also mean AI Overviews or other AI-powered aspects that are beginning to populate more traditional search engines.

At the foundation of both AEO and GEO is understanding user intent, incorporating relevant keywords, structuring content effectively to align with algorithms and AI crawlers, and using clear language throughout your content. The same techniques are used for both AEO and GEO since all generative engines are a type of answer engine.

Market Growth and User Adoption of Generative Search and LLMs

To understand the urgency behind GEO, consider the rapid adoption of LLMs and AI-based search technologies:

• ChatGPT reached 100 million monthly users within two months of launch, making it one of the fastest-growing consumer applications in history. In November of 2024, it had 3.8 billion visits, showing that initial hype is transitioning into mainstream usage.
• According to a recent survey from investment banking firm Evercore, 8% of Americans use ChatGPT as their go-to search engine.
• A McKinsey survey in mid-2024 found that 65% of organizations now regularly use generative AI, up from just 33% the previous year. This aligns with the broad enterprise pivot toward AI-driven insights.
• Gartner projects that by 2026, 25% of all queries could shift from traditional search engines to AI-driven interfaces, reducing organic search traffic for many companies by up to 50%.

These trends highlight the explosive growth of AI search channels. If your brand is absent from these channels—or if your mentions are inaccurate—you could be missing out on millions of high-intent users.

What’s the Difference Between GEO and SEO?

At a glance, GEO seems like a natural extension of SEO. Both revolve around making content visible and authoritative, but the mechanics of each differ significantly.

One of the biggest contrasts is that SEO is built around competition for finite SERP positions (rank #1, #2, #3, etc.), whereas GEO is more about influencing what an AI engine “thinks” and “says” when it fields questions.

Because AI’s answers are generated dynamically—and often vary from user to user—traditional ranking trackers don’t apply. Instead, you might look at brand presence across AI responses, the quality of mentions, and how these mentions convert into brand searches or direct visits later.

GEO Optimization and Ranking Factors

AI systems weigh a combination of technical, content, brand, and engagement signals when generating answers. While each generative model has its own training and referencing logic, several overarching factors frequently determine whether (and how) your brand appears.

Content Quality & Context

Generative models thrive on detailed, high-quality content. If your pages offer superficial or repetitive information, an LLM may ignore them. Focus on:

• Topical Depth: Provide unique data, expert opinions, or original research.
• Contextual Relevance: Align content around real user questions and pain points, anticipating the queries people pose to AI.
• Readability & Structure: Format text with headings, bullet points, and concise paragraphs to make it easy for AI to parse.

Technical Accessibility & Structured Data

As with SEO, you must ensure your site is crawlable and indexed. You should:

• Include Schema Markup (JSON-LD): e.g., FAQ, Article, Product, and Author schema help AI understand your site.
• Ensure Open Access: Allow GPTBot and other AI crawlers if you want your data included in their training sets or live indexing.
• Optimize Site Speed & Mobile-Friendliness: Real-time AI crawlers assess site performance and may discard or deprioritize slow, clunky pages.

Entity and Brand Authority

LLMs generally rely on an entity-based understanding of content:

• Entity Confirmation: Ensure your brand is defined consistently across platforms, from social media to Wikipedia.
• Authority Cues: Publications, academic references, news mentions, and strong domain-level authority all indicate trustworthiness.
• E-E-A-T Alignment: Google’s emphasis on Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T) also extends to how LLMs interpret your site.

Off-Page Signals & Community Mentions

Generative AI training can involve everything from social media posts to discussions on forums. Mentions in these spaces can shape how the model perceives your brand:

• Unlinked Brand Mentions: LLMs can learn about your product even from references without a hyperlink.
• Community Discussions: When your brand is actively recommended or debated in communities like Reddit or Quora, that can surface in AI’s knowledge base.
• Social Proof: High engagement on social posts and user-generated content signals real-world relevance.

Engagement & User Experience

While Google may or may not take bounce rates into account for rankings, AI systems are beginning to incorporate user feedback loops:

• Conversational Flow: If users repeatedly mention or engage with your brand in multi-turn queries, the AI may rank you higher or keep referencing you.
• Positive Sentiment: LLMs can parse sentiment in reviews or discussions to gauge brand favorability and will rank brands with positive sentiment higher than those more negatively regarded.

GEO Implementation Strategies: How to Get it Right?

Many of the most impactful strategies for GEO focus on developing and distributing high-quality content that aligns with and supports the authority of your brand. Think of your content as the backbone of your GEO strategy.

Research & Planning

To create content that resonates with your audience and will be relevant to their queries, you must start with research:

1. Discover User Questions: Map the long-tail, question-based queries people ask about your industry. Tools like AnswerThePublic, Semrush’s “Questions” feature, and even direct prompts to ChatGPT or Perplexity can yield potential user phrasing.
2. Identify AI Engine Types: Pinpoint whether your audience is more likely to use ChatGPT’s offline data or Bing Chat’s real-time engine. This dictates your approach to content freshness and domain authority.
3. Competitor Analysis: Ask generative engines about your competitors. Check how they appear in responses. Identify gaps you can exploit.
4. Brand Perception: Dig into how your brand is perceived by those who are searching in your niche. Understand what people are saying about your brand so you can grasp the current sentiment and figure out where you may need to make changes.

Content Creation & Structuring

What you include in your content and how you structure it directly impacts how LLMs are able to understand your relevance to and your expertise on a certain topic. Focus heavily on providing detailed, thoughtful, and original perspectives on important topics in your industry.

When structuring your content, you should:

• Provide Direct Answers: Start content pieces with a concise, “TL;DR”-style summary. AI often lifts these for quick responses.
• Use Clear Headings: Group subtopics with H2/H3 labels so LLMs can easily identify relevant sections.
• Include Original Data & Quotes: Studies show that LLMs prefer referencing content with statistics, quotes, or unique angles.
• Multi-Format Approach: Embed videos, infographics, or tables for depth; advanced models can incorporate them into answers.
• Incorporate FAQ Sections: Build FAQ sections, especially in longer content, to address common questions and make it easy for AI to pull relevant information.

Optimizing for Different Generative AI Engine Types

Training-Based Models (ChatGPT, Claude, Llama) rely on a set library of knowledge, usually with a cut-off date. To optimize for these models, consider long-term and evergreen approaches:

• Get your brand into widely crawled sources (news outlets, authoritative databases).
• Focus on timeless, high-authority content that remains valid well after the model’s training cutoff.

Real-Time & Hybrid Models (Perplexity, Bing Chat, Gemini, ChatGPT with browsing) can browse the internet as they’re processing a query to build the most relevant response. Focus on more immediate fixes and updates to optimize for these models, such as:

• Technical SEO Best Practices: Fresh, indexed content is essential; site speed, structured data, and mobile optimization are also critical for AI to quickly parse and synthesize information on your website.
• Timely Updates: Publish frequent updates, new research, or product info so the real-time crawler picks it up. Consistent and timely content publishing ensures you stay relevant in your particular industry.

Distribution & Community Building

Today with the rise of GEO, community building has become the new link building. Since LLMs are trained on a wide variety of data from all corners of the internet, make sure to amplify and take part into your brand discussions beyond your website:

• Active Forum Participation: Contribute meaningfully on Reddit, Quora, and niche communities.
• Social Media Seeding: Post share-worthy insights on LinkedIn or industry-specific networks.
• Guest Podcasts & Webinars: Voice your expertise in events that might be transcribed and then included in AI training sets.

Testing & Iteration

Many AI models are still being trained, new AI models are being released, and new features are being added to the ones that already exist. Keep close tabs on your GEO strategy implementation and test where necessary to ensure you’re seeing results:

• Prompt Experiments: Regularly ask ChatGPT, Gemini, Perplexity, etc. about your brand or key topics. Track if you appear and in what context.
• Refine & Re-Test: Adjust content structure or brand mentions and test again. This cyclical process is crucial for incremental GEO improvements.
• Collaboration with R&D: If your company has data scientists or partnerships with AI tool providers, collaborate to see how training sets are curated.

Case Studies and Practical Examples

Case Study 1: B2B SaaS Gains AI Mentions

A B2B SaaS company in the project management niche found they rarely appeared in ChatGPT’s offline knowledge. To remedy this, they:

• Partnered with Industry Blogs: They published joint reports with tech sites that had high domain authority.
• Increased Wikipedia Presence: They created a well-cited Wikipedia entry referencing their white papers.

Result: Within the next model update cycle, ChatGPT began including them in the top “best project management tools” references, boosting direct brand searches by 25%.

Case Study 2: eCommerce Brand Optimizes for Perplexity

An eCommerce retailer specializing in eco-friendly lifestyle products noticed Perplexity was growing in popularity among sustainability-minded consumers. To drive inclusion of their brand in Perplexity’s results, they implemented:

• Structured FAQ: They added custom FAQ schema with concise Q&A blocks to their product pages.
• Community Advocacy: They encouraged satisfied customers to share experiences on subreddits like r/ZeroWaste.

Result: In under two months, the brand appeared consistently in Perplexity’s “top eco-friendly stores” suggestions, correlating with an 18% bump in monthly revenue.

Case Study 3: Consultancy & Hybrid Systems

A consultancy wanted to rank in Google Gemini and also appear in ChatGPT’s real-time browsing variant. To achieve this, they focused on:

• Weekly Thought Leadership: They posted in-depth blog posts on trending management topics, ensuring daily crawls by Google.
• Citation Seeds: They proactively commented on Fortune 500 LinkedIn posts, dropping relevant data bites that earned them news coverage.
• Result: Gemini frequently included their quotes, and ChatGPT-with-browsing began citing their blog for “up-to-date leadership insights.”

How to Measure GEO and AI Visibility

Measuring success in GEO can feel elusive if you’re used to the more stable metrics of traditional SEO. While SEO performance may shift on a weekly or monthly basis, GEO is even more inherently dynamic—AI answers can shift from day to day, or even query to query.

Key Metrics

1. AI Citation Frequency
   • How often does the model mention or source your brand?
   • Does it list your domain as a reference or recommended link?
2. Brand Visibility in AI Overviews
   • Are you recommended in relevant top-tier queries? (e.g., “best enterprise software solutions”)
   • Does your brand appear in “buying guide” or “how-to” generative answers?
3. Post-AI Direct Traffic
   • When AI references your brand, do you see a spike in branded searches or direct visits?
   • Do you see an increase in brand + product name queries? This is a solid sign of AI-driven awareness.
4. Referral Data
   • Some AI chat interfaces provide clickable citations. Monitor referral traffic from these sources.
5. User Engagement
   • Keep an eye on lead volume, time on site, or newsletter sign-ups. Sometimes, AI references warm up leads before they even arrive.

Monitoring Tools & Methods

A strong GEO strategy requires established methods for measuring performance and impact of optimizations. Consider the following to track visibility:

• Prompt Testing: Manually check responses by asking the AI about your brand or relevant keywords.
• Brand Mention Tools: Invest in a tool from the new wave of software that specifically tracks brand references in generative AI outputs.
• Analytics: Use Google Analytics (and similar) to monitor direct traffic spikes; use Google Search Console to track brand search volume.
• Social Listening: Incorporate a tool that tracks social sentiment and discussions that could feed into AI training sets.

Goodie AI for Visibility Analysis

Goodie AI is an emerging platform that helps brands gain insights into how they show up in generative AI outputs. It offers:

• Real-Time Prompt Testing: The platform automates query testing across multiple AI engines (ChatGPT, Gemini, Perplexity).
• Citation Tracking: It logs whenever your brand is mentioned, along with the conversation context.
• Competitive Benchmarking: Goodie compares your brand’s generative presence to key competitors.
• Performance Dashboards: The platform includes a consolidated view of impressions, mention frequency, and potential referral traffic.

Integrating a tool like Goodie AI can streamline your entire GEO measurement process, giving you actionable data to refine your strategy over time.

Future of GEO and AI Search: Closing Thoughts

Generative AI is rapidly transforming how people search, research, and make decisions. Far from a temporary hype cycle, LLMs are already mainstream and improving continuously with each iteration. This means:

1. Data Quality & Freshness Will Become Essential: AI engines that rely on real-time data will increasingly factor in recency and reliability. Maintaining updated content is critical.
2. Deeper Personalization Is on the Horizon: Future AI systems may tailor their responses based on the user’s past interactions, location, or personal preferences. Optimizing for broader “personas” might become as important as keyword targeting once was.
3. Voice & Visual Inputs Will Blend With Text: As voice-based and image-based queries increase, GEO strategies will expand to cover multimodal content optimization.
4. Ethical & Trust Factors Will Be Increasingly Important: Misinformation and AI “hallucinations” remain hot-button issues. Brands that prove trustworthiness—through robust references, transparency, and verified credentials—will likely earn preferential treatment from AI systems looking to minimize errors.
5. Standardization Could Emerge: As generative AI matures, there may be regulations or standard practices for citing sources—akin to how search engines have guidelines for indexing.

The Bottom Line

Generative Engine Optimization isn’t just “SEO with a twist.” It’s a new frontier that intersects branding, content strategy, technical optimization, and community influence. In an era when user queries can be answered entirely within a chat window, ensuring that your brand’s perspective informs that answer can make the difference between winning a new lead or never being discovered at all.

By focusing on quality content, structured data, brand authority, and active community engagement, you position your organization to capitalize on the AI revolution—rather than be sidelined by it. Embrace GEO now to protect and amplify your brand’s digital visibility for the next decade and beyond.

The post Generative Engine Optimization (GEO): Strategies to Boost AI Search Visibility appeared first on NoGood™: Growth Marketing Agency.

Despite the hype, many marketers’ day-to-day hasn’t changed much from two years ago. We’re still designing, creating content, and spending time analyzing ad platform data, CRMs, and Google Analytics like we always have.

But amidst the AI noise, a new breed of marketer is rapidly emerging.

Introducing the 10X AI Marketer

In engineering, we often hear the term “10X engineer.” It’s usually used to describe a software engineer who is considered significantly more productive than their peers and performs at a level roughly ten times more effective than the average engineer. This concept was rarely applied to marketers. That’s largely because, until now, marketers haven’t had the tools to design and orchestrate large-scale systems the way engineers do.

But I believe this is the time for it.

With the advent and integration of AI, marketers have the chance to become 10X AI marketers, utilizing AI to supercharge and optimize their workflows for better outputs, faster.

In short, 10X AI marketers get 10 times the results in a fraction of the time without doing 10 times the work themselves—AI is doing the heavy lifting. Here’s what makes them stand out:

1. They Move Fast. They rapidly prototype ideas, spin up automations, and experiment with novel workflows. AI helps them iterate at lightning speed.
2. They Automate Processes. From email campaigns to content creation, they streamline production through AI automations. Mundane manual tasks become automated processes.
3. They Master Multi-Tool Ecosystems. They tap into a range of tools—automation platforms, data layers, and LLM APIs—to piece together custom marketing solutions that fit their GTM motion. 
4. They Deliver Substantial Productivity Output. Their ability to fuse AI with their marketing know-how unlocks a multiplier effect, propelling key metrics and organizational growth.

So, how did we get here?

AI and the Collapse of the Talent Stack

Our work is often defined by our goals and the tools we use to achieve them. For the past two decades, our talent stack and team structures have remained largely unchanged, including how we define roles and the lines between them.

For the most part, someone was considered a “unicorn” if they had skills and capabilities outside of their main area of expertise. Progressing in your field meant specializing, further solidifying the lines between roles and responsibilities.

But as AI capabilities continue to expand, traditional job roles will begin to blur. Product managers will casually code, performance marketers will design their own ads, and designers will step into copywriting—all powered by AI. What was once considered “unicorn” territory will become the new baseline.

In the coming years, it will be critical to think strategically and adapt quickly to emerging tech to thrive.

This shift isn’t limited to marketing; it will impact the entire talent stack. However, marketing functions are likely to be the most affected, as reflected in recent AI job impact reports and studies.

From Individual Contributor to Systems Orchestrator: AI Agents & Changing Team Structures

The classic SaaS martech stack we’ve relied on for so long is evolving as it’s challenged by the promise of AI agents. As these agents come to fruition, they’ll have a substantial impact on both team structures and roles of individual contributors. The role of the AI agent—and how marketers are using them—is going beyond automating tasks to impact how teams operate, scale, and deliver value.

In the past, traditional marketing roles focused on personal output: campaigns managed, content created, or leads generated. The AI-native marketer, however, can utilize AI agents to build and then orchestrate systems that multiply their contributions and impact beyond these simple outputs.

As these roles start to shift, it’s becoming abundantly clear that with the right AI-powered tools, anyone—across levels and functions—can push themselves to new heights as systems designers, managers, and orchestrators.

How This is Unfolding in Performance Marketing: AI-Native Pods

Ad buying is becoming increasingly streamlined as AI automates campaign management. Tasks that once took hours—like setting up campaigns, conducting keyword research, and configuring ad groups—are now faster and easier.

Today’s performance marketers are expanding their roles beyond managing and optimizing campaigns. They’re making creative decisions, producing ads, and setting up analytics and tracking systems.

What was once a unique, “unicorn” skill composition, often found in small teams or at fast-growing startups, is becoming the industry standard going forward. With this shift, we’re seeing silos and boundaries between roles break down and marketers developing AI-powered systems to fuel their workflows.

Content Generation Systems have already replaced individual content creation, with many marketers now designing content frameworks that auto-generate variations for different channels, adapt tone based on audience segments, and optimize based on performance data.

Teams will start to reshape, consolidate, and organize around these functional systems, forming function-oriented pods. A Demand Generation Pod, for example, would combine the capabilities and skill sets of automation engineers, content strategists, and analytics specialists. The Customer Journey Pod would merge product marketing, customer success, and technical integration, while the Brand Experience Pod would unite creative direction, content systems, and engagement automation.

Teams structured this way are true AI-native teams, powered by 10X AI marketers.

The Rise of 10X AI Marketers

Your CEO or founder likely had a bunch of AI initiatives in 2024. The marketer that showed the most curiosity, rushed to be there first, and ran the most experiments is likely your future 10X AI marketer.

Imagine a marketer fluent in AI tools, automation workflows, and data analytics—someone equally comfortable in strategic boardroom discussions and prompt-engineering brainstorms. They’re not intimidated by new, seemingly complex tech; they thrive on it. They run experiments with agents, memory modules, and knowledge bases to push campaigns further, faster.

Instead of treating AI like a mysterious black box or hesitating in the face of this major change, they see it as a partner, an extension of their own marketing expertise, and a way to refine their talents and ensure they stay relevant. Driven by curiosity, they constantly explore fresh applications, workflows, and prompts. Their end goal: drive business growth with measurable, AI-fueled outcomes.

The Core Skill Set of a 10X AI Marketer

• Strong Automation Know-How: These marketers are comfortable with workflow automation platforms like Make.com, N8N, or Zapier for managing data flow and automating anything from lead nurturing to social media scheduling.
• Coding or Rapid Prototyping Skills: Even basic coding literacy can be a massive advantage. Whether it’s tweaking an API or setting up a custom script, these marketers quickly turn ideas into action.
• Data Analytics Background: AI thrives on data, so understanding how to collect, analyze, and interpret it is crucial for guiding smarter decisions and measuring impact.
• Prompt Engineering Foundation: They know how to coax the best outcomes from large language models—whether via zero-shot, few-shot, or chain-of-thought prompting.
• Critical and Strategic Thinking: AI doesn’t replace strategic acumen. It amplifies it. 10X AI Marketers understand the marketing funnel end to end and apply AI where it matters most.
• Copywriting and Empathy: AI can generate text, but it can’t always sense the emotional undercurrents of your audience. Strong human copywriting skills ensure the final message resonates.
• Tech Savvy and Adaptable: With AI evolving daily, a willingness to learn, test, and pivot is essential. 10X AI Marketers are always on the hunt for next-gen tools and capabilities.
• Curiosity and Ongoing Learning: The AI frontier is still wide open. 10X AI Marketers embrace continuous learning—always refining workflows and exploring fresh solutions.

The Core Concepts 10X AI Marketers Must Master

1. Prompt Engineering

Prompt engineering is about speaking to an LLM in a way that elicits high-quality, relevant responses. The best AI Marketers know how to:

• Use Zero-Shot and Few-Shot Approaches: Specify the context, target audience, or writing style to get the best possible copy.
• Chain of Reasoning: Have the LLM walk through logical steps, improving the detail and clarity of the response.
• Iterate and Refine: They’re not satisfied with the first draft—they experiment, revise, and push the AI to produce sharper content.

2. Leveraging AI Agents and Agentic Workflows

LLMs can do more than answer questions—they can act as agents that handle tasks end to end. By wiring up an LLM to a database and knowledge system, you can create fully- or semi-automated workflows. For example, an AI agent might:

• Monitor incoming data, such as new leads or signups.
• Generate personalized follow-ups.
• Update CRM entries automatically based on user signals.

This is sometimes referred to as an “agentic workflow”—where software is built around an LLM brain with memory and a knowledge base. These intelligent processes can be custom built to meet specific needs, reach certain goals, or provide defined outputs. They can also learn and evolve based on new data, gradually increasing their sophistication and value to the business.

Common Tech-Stack for 10X AI Marketers

These are the commonly used tools in an AI marketer’s tech stack, but we see a lot of evolution and consolidation between these tools. Foundational LLMs are also becoming so much more integrated and versatile in use that you often don’t need a ton of tools for day-to-day execution.

Why Invest in 10X AI Marketers

• Velocity and Iteration: Traditional marketing campaigns can take weeks—or even months—from concept to execution. A 10X AI Marketer can rapidly test ideas, generate new angles, and optimize messaging in mere hours.
• Resource Efficiency: Entire marketing teams can shift to higher-level strategy and problem-solving when routine tasks are automated. This not only saves costs but elevates creativity across the board. After all, the cost of marketing talent and resources is part of our loaded CAC. 
• Data Informed Actions: By combining analytics with AI, they see patterns faster and act on them immediately. Instead of being stuck in endless data crunching, they let AI highlight anomalies, suggest next steps, or trigger proactive interventions.
• Hyper-Personalization at Scale: One of AI’s greatest strengths is personalization. 10X AI Marketers feed user data and context into LLMs to tailor messaging at the individual level, creating more meaningful customer experiences.
• Competitive Advantage: In a world where attention is scarce, being first to market with new AI-driven tactics can be the difference between leading the pack and playing catch-up. The 10X AI Marketer stays ahead of trends, making their brand impossible to ignore.

Final Thoughts

AI-led growth represents the new frontier of marketing. The AI shift and the current tech stack of agents and tools will enable the right marketers to become 10X versions of themselves—10X AI Marketers—who use available tech to push past traditional marketing and team limits to accelerate results. From prompt engineering prowess to agile automation design, their secret weapon lies in integrating newly accessible tech with strategic vision.

It’s about seeing AI not as a replacement for human creativity and strategy but as an amplifier of our capabilities. The most successful practitioners in this space are those who can bridge the gap between technical possibilities and business realities.

The 10X AI Marketer is more than a role—it’s a mindset. When embraced, you’ll find that AI-led growth isn’t a passing trend, it’s the path to becoming an unstoppable force in today’s hyper-competitive market.

The post AI-Led Growth: The Rise of the 10X Marketers and AI-Native Teams appeared first on NoGood™: Growth Marketing Agency.

As a result, Snapchat marketing and creative agencies are now in high demand. In this blog post, we’ll explore the top Snapchat marketing agencies for Snapchat paid ads, content creation, and influencer campaigns.

Our Best 14 Snapchat Marketing Agencies:

1. NoGood
2. VaynerMedia
3. Viral Nation
4. Ignite Social Media
5. Disruptive Advertising
6. inBeat Agency
7. Newbird
8. Online Optimism
9. AdvertiseMint
10. The Social Shepherd
11. MuteSix
12. Voy Media
13. Taktical Digital
14. The Snow Agency

1. NoGood

Description: At NoGood, we’re a dynamic growth and performance marketing agency in the heart of New York City. Our experience in effectively executing both paid and organic Snapchat campaigns runs deep. Our client roster includes esteemed names like Nike, ByteDance, JVN, and Intuit, as well as various startup ventures and ambitious scale-ups.

When you choose to partner with us, we assemble a customized growth team of established experts. We don’t just grasp the intricacies of your business – we’re fully committed to propelling rapid expansion that unlocks your complete potential.

Office Location: New York, NY (HQ)

Year Founded: 2017

Team Size: 50 – 100 employees

Key Services: Creator Studio, Social Ads, Content Marketing, Influencer Marketing, Video Marketing

Industries Served: SaaS, Healthcare, Fintech, B2B, Consumer, Crypto

Case Studies: View all case studies.

2. VaynerMedia

Description: VaynerMedia is a digital and creative agency that specializes in social media marketing, including Snapchat. They offer services such as strategy and planning, creative development, influencer marketing, and media buying. They’ve worked with brands like PepsiCo, Toyota, and Unilever to create engaging content for Snapchat. Their team of experts can help you create customized Snapchat filters, ads, and sponsored lenses that resonate with your target audience.

Office Location: New York, NY, with offices around the world

Year Founded: 2009

Team Size: 501 – 1,000 employees

Key Services: Social Media Management, Video Ads, Marketing Content, Brand Building, Video Production

Industries Served: N/A

Case Studies: N/A

3. Viral Nation 

Description: Viral Nation is a leading influencer marketing agency that has expanded its services to include Snapchat advertising campaigns. They specialize in creating engaging content for Snapchat, including filters, lenses, and sponsored posts. Their team of experts can help your brand reach a wider audience, generate leads, and drive sales through targeted Snapchat ads. Viral Nation also offers comprehensive analytics to track the performance of your campaigns. Their pricing is based on a commission structure.

Office Location: Mississauga, Ontario

Year Founded: 2014

Team Size: 201 – 500 employees

Key Services: Influencer Marketing, Personalized Content Creation, Social Media Marketing Services, Advertising Strategies, Community Management

Industries Served: Beverages, Gaming, Consumer

Case Studies: View all case studies.

4. Ignite Social Media 

Description: Ignite Social Media is a social media marketing agency that offers Snapchat advertising services. They specialize in creating visually stunning and engaging Snapchat content for brands, including sponsored stories, lenses, and filters. Ignite Social Media can help you reach new audiences and achieve your marketing goals through innovative Snapchat campaigns. Their pricing is based on a project basis.

Office Location: Cary, North Carolina

Year Founded: 2007

Team Size: 51 – 200 employees

Key Services: Social Media Platforms Marketing, Digital Advertising, Content Marketing, Influencer Marketing, Blogger Outreach, Community Management

Industries Served: Automotive, Food & Beverage, Consumer, Health & Wellness, Entertainment, Non-Profit

Case Studies: View all case studies.

5. Disruptive Advertising

Description: Disruptive Advertising leverages Snapchat’s ads to elevate brand awareness, encourage audience interest, and boost conversions for businesses. To ensure the suitability of Snapchat as a potent marketing channel for their clients, the agency undertakes a comprehensive audience assessment. The process entails scrutinizing demographic data, primarily obtained from the client’s Facebook, Instagram, and Google data insights. By doing so, they gain valuable insights into the age, gender, and lifestyle demographics of the client’s current audiences. This data is then directly compared to Snapchat’s demographics to gauge alignment and potential reach.

Office Location: Pleasant Grove, UT

Year Founded: 2012

Team Size: 51 – 200 employees

Key Services: Paid Search Advertising, Conversion Rate Optimization, Social Media Marketing Services, Display Advertising, Google Analytics, SEO, Lifecycle Marketing, Creative

Industries Served: eCommerce, Tech, Health & Wellness, Financial Services, Beauty, Home Services

Case Studies: View all case studies.

6. inBeat Agency

Description: inBeat is a premier digital marketing agency that specializes in Snapchat advertising. With a focus on empowering brands, they offer top-notch marketing campaigns to engage potential customers effectively. Leveraging Snapchat’s competitive CPM and audience-specific targeting capabilities, inBeat’s marketing team ensures maximum impact and helps businesses achieve their specific business goals.

As a dedicated Snapchat ads agency, inBeat takes pride in cultivating strong relationships with top creators. This enables them to produce outstanding user-generated content that stands out from the crowd and resonates with potential customers. Their expertise in crafting compelling marketing strategies ensures brands receive optimal visibility and engagement on the platform, aligning seamlessly with their unique business objectives.

Office Location: New York, NY, with offices around the world

Year Founded: 2018

Team Size: 51 – 200 employees

Key Services: Influencer Marketing, Social Media Management, Digital Marketing Agency, Marketing Content Creation

Industries Served: Consumer Packaged Goods, DTC, Healthcare, App Marketing

Case Studies: View all case studies.

7. Newbird

Description: Newbird is a top advertising agency that boasts a decade of unparalleled experience crafting captivating and successful Snapchat ad campaigns for a diverse clientele. With a remarkable track record of over 400 satisfied clients, Newbird’s profound knowledge of Snapchat advertising makes them the ultimate choice for businesses seeking to connect with a younger audience and attain their objectives through this dynamic platform.

Newbird’s mastery of Snapchat advertising shines through its comprehensive approach, placing utmost importance on grasping a client’s brand essence and understanding their unique customer journeys. This customer-centric strategy allows them to create tailored marketing materials that resonate deeply with the target audience, ensuring maximum impact on this vibrant advertising platform.

Office Location: Buffalo, New York

Year Founded: 2008

Team Size: 11 – 50 employees

Key Services: Website Design, Social Media Marketing Services, Mobile App Marketing, Internet Marketing, Branding, Video Production & Content Development, SEO, PPC, Paid Media Advertising, Email Marketing

Industries Served: Beauty, Health, Clothing

Case Studies: View all case studies.

8. Online Optimism

Description: Online Optimism is a leading ad agency proficient in assisting businesses with effectively reaching their target audience on the immensely popular social media platform. With their Snapchat Ads Certified social media team, Online Optimism remains updated on the latest social media strategies, guaranteeing optimal outcomes for their esteemed clients.

Functioning as a seasoned Snapchat advertising agency, Online Optimism designs ad campaigns that strategically target audiences across various stages of the sales funnel. Collaborating closely with their clients, they adeptly set ad budgets and pinpoint ideal audience personas, ensuring exceptional return on investment (ROI) for each campaign, even on a tight budget.

Office Location: New Orleans, LA

Year Founded: 2012

Team Size: 11 – 50 employees

Key Services: Website Design, Search Engine Optimization, Social Media Management, Digital Advertising, Content Marketing, Branding 

Industries Served: Hospitality, Healthcare, Automotive, Legal, Education, Government, Non-Profit, Cybersecurity, Consumer

Case Studies: View all case studies.

9. AdvertiseMint

Description: AdvertiseMint is a digital advertising agency specializing in aiding prosperous companies with advertising effectively on Snapchat. Their extensive knowledge of Snapchat advertising coupled with a strong emphasis on cost-effectiveness and user-friendly approaches positions them as a dependable option for businesses seeking to optimize their presence on the platform.

At AdvertiseMint, a team of Snapchat experts wholeheartedly dedicates themselves to curating captivating and customized ad campaigns tailored to meet each client’s unique needs. Their commitment to delivering engaging and relevant content ensures businesses receive the best possible results from their Snapchat advertising endeavors.

Office Location: Los Angeles, CA

Year Founded: 2014

Team Size: 11 – 50 employees

Key Services: Social Advertising, Instagram Advertising, Facebook Advertising, Digital Advertising

Industries Served: N/A

Case Studies: N/A

10. The Social Shepherd

Description: The Social Shepherd is made up of renowned experts in customer acquisition and marketing campaign scaling for their esteemed clients. With a wealth of experience in effectively managing Snapchat Ads, complemented by their exceptional creative abilities, The Social Shepherd guarantees outstanding outcomes for all campaign endeavors.

Having a solid track record of delivering remarkable results, The Social Shepherd boasts an impressive 5.4x return on ad spend (ROAS) for prominent clients like the UK’s Love Leggings. This success story is a testament to their proficiency and ability to deliver exceptional results for businesses they partner with.

Office Location: New York, NY, with offices in the UK

Year Founded: 2018

Team Size: 50 – 200 employees

Key Services: Social Media Marketing, Paid Social, Video Production, Influencer Marketing, eCommerce Marketing, Social Media Content

Industries Served: Skincare, Food & Beverage, Consumer, Jewelry, Clothing

Case Studies: View all case studies.

11. MuteSix

Description: MuteSix boasts a team of expert strategists and creatives well-versed in streamlining the production of captivating Snapchat ads that instantly capture attention. Their diverse ad formats, including Single Image, Video, Lenses, and Story Ads, are thoughtfully optimized to engage customers effectively throughout their journey.

Through extensive A/B testing, MuteSix uncovers the most successful elements of their Snapchat-specific content to thrive on this multimedia platform. This invaluable insight fuels their ability to consistently deliver successful campaigns and drive impressive client results.

Office Location: Culver City, California

Year Founded: 2014

Team Size: 201 – 500 employees

Key Services: Paid Social, Paid Search, Email Marketing, Amazon Marketing, SMS Marketing, Content Creation, Lifecycle Marketing

Industries Served: Home Goods, Consumer, Food & Beverage, App Marketing

Case Studies: View all case studies.

12. Voy Media

Description: Voy Media brings a wealth of experience, catering to an extensive clientele spanning Fortune 500 companies to burgeoning start-ups. Their success stories include helping businesses achieve substantial sales growth and establishing a proven track record of excellence.

The team’s expertise lies in crafting captivating images that effectively halt scrolling and copy that captivates readers. Doing so safeguards their clients’ marketing efforts from disappearing into the digital abyss, ensuring maximum visibility and engagement for their brand messages.

Office Location: New York, NY

Year Founded: 2016

Team Size: 11 – 50 employees

Key Services: Facebook Ads, Mobile Attribution, Lifecycle Marketing, Mobile App Marketing, Digital Advertising

Industries Served: Gaming, Beauty, App Marketing, Education, Fashion, Food & Beverage, Health & Wellness

Case Studies: View all case studies.

13. Taktical Digital

Description: Taktical Digital is an award-winning advertising agency with a team of data-driven specialists that are dedicated to Snapchat advertising. Their advertising campaigns help raise awareness for your brand on this dynamic social media platform.

Taktical Digital recognizes that storytelling is at the heart of advertising on Snapchat, and they work to present the brands they work with through compelling narratives and eye-catching visuals. They offer multiple Snapchat ad formats and employ an in-house creative team, so you can be confident in every aspect of your campaign.

Office Location: New York, NY

Year Founded: 2013

Team Size: 51 – 200 employees

Key Services: SEO, Paid Social, Paid Search, Landing Page Optimization, Content Marketing, eCommerce Advertising

Industries Served: Home Goods, Clothing, Jewelry, Footwear

Case Studies: View all case studies.

14. The Snow Agency

Description: The Snow Agency is an award-winning social media and influencer marketing agency that strives to bring cutting-edge advertising solutions to their clients to connect brands with their target audiences. They boast expertise across a wide variety of social media platforms, including Snapchat, and they work closely with direct-to-consumer brands to launch and scale their advertising efforts.

They take a clearly outlined approach to Snapchat advertising, beginning with analyzing your objectives and goals. Then, they determine who exactly they want to target, and from there, they launch your campaign and monitor it closely to ensure it’s performing as expected and driving the results you deserve.

Office Location: Miami, Florida

Year Founded: N/A

Team Size: 51 – 200 employees

Key Services: Paid Social Ads, UGC Content Marketing, SEO, CRO, Web Design, Email & SMS Marketing

Industries Served: Beauty & Cosmetics, Home Goods, Clothing, Health & Wellness, Sports

Case Studies: View all case studies.

Frequently Asked Questions

Push the Boundaries of Your Advertising on Snapchat

Snapchat has become an essential platform for brands looking to engage with their target audience in a creative and impactful way. These top Snapchat marketing agencies offer a range of services, including paid ads, content creation, and influencer campaigns. 

Each agency has its unique strengths, so it’s essential to carefully evaluate their offerings and expertise to find the perfect partner for your brand. Armed with this information, you can confidently choose the right agency to help your brand succeed on Snapchat.

The post Top 14 Snapchat Marketing Agencies for 2025 appeared first on NoGood™: Growth Marketing Agency.

Local Search

One of the biggest issues with SearchGPT is its local search capabilities. For example, when I searched for “growth marketing agencies,” I was surprised to see “Juice Generation,” a local juice store, show up as the second result—definitely a new level of hallucination unlocked!

Local search is crucial for users looking for nearby services or products, and this is an area where Google excels. Google provides detailed results that often include user reviews, business hours, and contact information. The inability of SearchGPT to deliver reliable local search results makes it a less appealing option for those who need immediate, actionable information.

Moreover, when searching for products or services, Google pulls in user reviews and ratings from various platforms, offering a comprehensive overview of customer experiences. SearchGPT does not provide such reviews, making it difficult for users to assess the quality of a product or service.

Intent Recognition and Understanding Synonyms

Another major issue I encountered with SearchGPT was its intent recognition. When I used keywords in my searches, the extension often missed the intent behind my queries. While it can craft personalized responses, it struggles to understand user intent, especially with short phrases.

For instance, if I searched for a word’s meaning, correct pronunciation, or spelling without fully framing my question, ChatGPT would often get confused. In contrast, Google delivers expected answers almost instantly. This expectation has built up over years of using Google, so when an alternative falls short, it can be frustrating.

Additionally, Google has built an impressive ability to recognize synonyms and related terms, enhancing its effectiveness. For example, searching for “automobile” and “car” yields similar results on Google, while SearchGPT may not make that connection as effectively, leading to missed relevant content.

Usage Limits

Once you enable the SearchGPT Chrome extension, it becomes the default search engine in your browser. However, I faced a frustrating limitation: the extension can suddenly stop working and display a daily limit message. This kind of behavior is unacceptable for a default search experience, as it forces users to switch back to alternatives that don’t impose such restrictions.

This limitation disrupts the search process and diminishes the overall user experience. In today’s digital age, where seamless interactions are expected, having to revert to another tool due to usage limits is a significant drawback for SearchGPT.

Missing Search Use Cases

SearchGPT also falls short in offering a variety of search use cases. Features like images, travel, video, news, and shopping are either underdeveloped or completely absent. In a world where users expect to conduct various types of searches effortlessly, this limitation is notable.

Google thrives in this area, allowing users to search for images, track flights, watch videos, and find news articles all in one place. SearchGPT’s lack of these functionalities makes it feel like a limited tool rather than a comprehensive search engine.

Google provides a diverse range of content types, including articles, videos, infographics, and podcasts. For example, if you search for “marketing trends,” Google will return articles, videos, and relevant statistics. SearchGPT may not offer the same variety, limiting the depth of information available.

Grounding and Real-Time Information

When it comes to providing real-time information, Google excels. Whether it’s weather updates, local alerts, or news, Google consistently delivers accurate and timely information. In contrast, SearchGPT struggles to keep up with current events or dynamic data, making it less reliable for urgent inquiries.

This ability to provide real-time information is crucial for users who need accurate, up-to-date data to make informed decisions. Without this capability, SearchGPT risks becoming irrelevant in a fast-paced digital environment.

Additionally, Google often highlights trending searches and popular content. If you search for something like “latest news in AI,” Google shows current trends and hot topics. SearchGPT may lack the ability to reflect real-time popularity or trends in its responses.

The Barrier of Breaking Old Habits

It’s clear that our habits with Google are hard to break without a better alternative. While I hoped SearchGPT would provide a more effective approach to search, my experience fell short. The extension simply doesn’t measure up to our expectations for a default search engine. Perhaps Perplexity just set our expectations of new search engines to a high standard. Making it even more difficult for newer platforms like SearchGPT that just aren’t quite fully ready to be a default search engine.

That said, SearchGPT is a notable addition to the OpenAI family and contributes to the evolving AI search landscape. However, as of now, Perplexity continues to stand out among new answer engines, especially for knowledge searches. Yet, the world of search encompasses much more than just these inquiries. Users need a comprehensive tool that can effectively address a wide range of search needs.

Here is how I would personally rate these search experiences against one another:

The post Why I Uninstalled the SearchGPT Chrome Extension: A Comparison with Google and Perplexity appeared first on NoGood™: Growth Marketing Agency.

Picture this: A Gen Z user wanting to find the best ramen spots in town. Instead of typing a query into Google, they’re more likely to fire up TikTok or Instagram, scrolling through vibrant videos and authentic reviews from fellow food enthusiasts. This isn’t just a fleeting trend—it’s a fundamental shift in information discovery that’s sending ripples through the worlds of marketing, tech, and consumer behavior.

Those in our community remember when we released our first future of search report back in 2022, pointing out the rise of TikTok and the challenge it presents to Google, which was later confirmed by Google’s own search team.

In this deep dive, we’ll explore how social search has evolved over the past year with the introduction of Generative AI and platforms doubling down on search, why it matters so much (especially to younger generations), and what it means for brands trying to stay relevant and take advantage of emerging opportunities in a rapidly evolving space.

What is Social Search?

Social search integrates social signals, such as user recommendations, shares, likes, and comments, into search results. Unlike traditional search engines that rely on algorithms to rank web pages based on keywords and links, social search engines prioritize content that has been validated by users within a social network. This approach offers more personalized and relevant results based on the user’s social connections and interactions.

The Evolution of Social Search

In the past year, social search has undergone a significant transformation, primarily driven by the increasing use of platforms like TikTok, Instagram, and others. Here are some key developments:

1. Algorithm Enhancements: Platforms have refined their algorithms to provide more accurate and personalized results. For instance, TikTok’s algorithm is renowned for its ability to surface highly relevant content based on user behavior and preferences.
2. Influencers and creators Impact: Influencers play a crucial role in social search, with their content often ranking highly due to high engagement rates. This trend has grown stronger with the rise of micro-influencers who have more niche and engaged audiences.
3. Integration with E-commerce: Social search is increasingly intertwined with e-commerce, allowing users to search for products directly within social platforms and make purchases without leaving the app.
4. Visual and Video Search: There has been a shift from text-based search to visual and video search. Users are now more likely to search for content using images and videos, which is particularly evident on platforms like Instagram and TikTok.

How Social Search Differs from Conventional Search

Conventional search engines like Google and Bing rely on keyword matching, backlinks, and other SEO factors to rank content. In contrast, social search engines prioritize:

1. User Engagement: Content with high engagement (likes, shares, comments) is ranked higher.
2. Social Validation: Recommendations from users’ social networks play a crucial role in ranking.
3. Real-Time Trends: Social search engines are more attuned to real-time trends and viral content, providing up-to-date results.

Search and The Power of Social Graph

Platforms like TikTok and Instagram leverage a social graph—a map of social connections and interactions—which significantly enhances search capabilities. This social graph allows for a high degree of personalization, as search results are tailored to the user’s social network, making the content more relevant and engaging. Users see results influenced by their friends, family, and influencers, increasing the trustworthiness and relevance of the information.

Credibility is elevated when content comes from within a user’s social network. Recommendations and content from friends or influencers are perceived as more authentic compared to anonymous sources, making users more likely to trust and act on them. Social interactions like likes, shares, and comments boost content visibility, creating a feedback loop where engaging content gains more visibility and further engagement.

The real-time nature of social search means trends and viral content surfaced quickly, providing users with current and popular information. This immediacy sets social search apart from traditional search engines, which often rely on static data. Overall, the social graph transforms search into a dynamic, interactive, and personalized experience, offering a distinct advantage over conventional search methods.

Rise of Social Search Among Gen Z

Gen Z, the digital native generation, has significantly influenced the rise of social search. According to Business Insider, 60% of Gen Z use Instagram for product discovery, and 40% of Gen Z prefer using TikTok and Instagram over Google for search (Google internal data).

Here’s why searching on social makes sense for them:

1. Preference for Visual Content: Gen Z prefers visual content over text. They are more inclined to search for information through videos and images, making platforms like TikTok and Instagram their go-to sources.
2. Trust in Peer Recommendations: This generation places high trust in peer recommendations and user-generated content. Social search aligns with this trust by showcasing content validated by their social circle.
3. Instant Gratification: Gen Z expects quick and relevant results. Social search, with its emphasis on personalized and real-time content, meets this expectation effectively.
4. Authenticity: User-generated content feels more genuine and relatable than polished marketing materials.

TikTok: The Rising Star of Social Search

TikTok’s ascent as a search engine has been meteoric. Its algorithm’s ability to surface relevant, engaging content has made it a formidable player in the search landscape. Here’s how:

1. Algorithmic Precision: TikTok’s sophisticated algorithm tailors content to user preferences, making search results highly relevant.
2. User Engagement: High levels of user engagement with content boost the visibility and credibility of search results.
3. Visual-First Approach: TikTok’s highly engaging video-centric format aligns with how younger users prefer to consume information.
4. TikTok Authentic: TikTok arguably led the way in the culture of social authenticity; its content feels more genuine and relatable than traditionally polished Instagramable content.
5. Discoverability: TikTok’s algorithm excels at surfacing niche and trending content, often outperforming traditional search engines in certain categories.
6. Short-Form Video Content: TikTok’s focus on short-form videos makes it an ideal platform for quick, engaging search results.

Generative AI Impact on Social Search

Generative AI is transforming social search by making it conversational, personalized, and incredibly user-friendly. Imagine chatting with an AI that feels like a knowledgeable friend, instantly providing detailed answers tailored to your questions. This natural interaction makes finding information feel less like a chore and more like a seamless conversation.

Personalization is where AI really shines. By analyzing your habits and preferences, it delivers search results that match your interests perfectly. No more wading through irrelevant content – the AI knows what you like and serves up the most engaging and relevant results. Over time, it gets even better at predicting what you’ll enjoy, creating a search experience that feels uniquely yours.

Content curation is another game-changer. AI sifts through vast amounts of data to highlight the best content, ensuring you always see the highest quality and most relevant information. This means less time searching and more time enjoying content that matters to you.

For brands, AI offers deep insights into user behavior, helping them create content that truly connects with their audience. It’s a win-win: users get the content they love, and brands engage more effectively. With AI delivering personalized, instant responses, users find everything they need right on their favorite platforms, reducing the need to turn to traditional search engines like Google. This shift not only enhances user experience but also keeps them engaged longer on social platforms.

Meta’s Inclusion of Llama 3 in the Search Bar

Meta’s integration of Llama 3 into its search functionality across platforms with over 3 billion users marks a significant milestone. Here’s why it matters:

1. Enhanced Search Accuracy: Llama 3’s advanced AI capabilities improve the accuracy and relevance of search results.
2. Unified Experience: Users get a seamless search experience across Meta’s platforms, including Facebook and Instagram.
3. AI-Powered Insights: Brands gain deeper insights into user behavior and preferences, helping them tailor their content and marketing strategies.

Social Search Impact on Brands

The shift towards social search has profound implications for brands:

1. Content Strategy: Brands need to focus on creating engaging, shareable content that resonates with their target audience.
2. Influencer Partnerships: Collaborating with influencers who have high engagement rates can boost a brand’s visibility in social search results.
3. Real-Time Engagement: Brands must stay attuned to real-time trends and be ready to engage with users promptly.

Comparative Analysis of Social Search Platforms:

Adapting to the Changing World of Social Search

Brands can adapt to the evolving landscape of social search by:

1. Leveraging Creators as part of GTM strategy:: Partner with creators and influencers to create authentic, engaging content that can boost visibility in social search results.
2. Creating Shareable Content: Focus on creating high-quality, visually appealing content that encourages user interaction.
3. Utilizing AI Tools: Use AI tools to analyze trends, generate content, and personalize user interactions.
4. Engaging in Real-Time: Monitor social trends and engage with users in real-time to stay relevant and visible.
5. Optimizing for Visual Search: Optimize content for visual and video search by using relevant hashtags, keywords, and engaging visuals.

Practical Strategies for Social Search Optimization

As social search continues to gain prominence, optimizing your content for these platforms becomes crucial. Here’s a practical, step-by-step approach to enhance your brand’s visibility in social search results:

1. Keyword Research for Social Platforms
   • Use platform-specific tools like TikTok’s Keyword Insights or Instagram’s Explore page to identify trending topics and hashtags.
   • Analyze competitor content to spot frequently used keywords in your niche.
   • Pay attention to how your target audience phrases their queries on social platforms.
2. Optimize Content Descriptions and Captions
   • Front-load key information and keywords in the first few lines.
   • Use a mix of broad and niche hashtags (5-10 for Instagram, 3-5 for TikTok).
   • Include relevant keywords naturally throughout the caption.
3. Create Search-Friendly Video Content
   • Start videos with a hook that includes your main keyword or topic.
   • Use on-screen text to highlight key points and include searchable terms.
   • Create content that directly answers common questions in your niche.
4. Leverage User-Generated Content (UGC)
   • Encourage customers to create content using your branded hashtag.
   • Repost and engage with UGC to boost visibility and authenticity.
   • Run contests or challenges that prompt users to create searchable content related to your brand.
5. Optimize Your Brand Profile
   • Use relevant keywords in your bio, profile name, and username.
   • Keep your profile public and use a clear, recognizable profile picture.
   • Include a link to your website or a landing page with additional resources.
6. Engage Actively and Consistently
   • Post regularly (aim for at least 3-5 times per week on major platforms).
   • Respond promptly to comments and messages to boost engagement.
   • Participate in relevant conversations using trending hashtags.
7. Utilize Platform-Specific Features
   • For TikTok: Use trending sounds, participate in challenges, and create content for the “For You” page.
   • For Instagram: Utilize Reels, Stories, and IGTV to diversify your content and increase discoverability.
   • For Pinterest: Create vertical images with text overlays and detailed descriptions.
8. Implement Cross-Platform Strategies
   • Adapt successful content from one platform to suit others.
   • Use consistent branding and messaging across all platforms to reinforce brand identity.
   • Cross-promote content to drive traffic between your social profiles.
9. Monitor and Analyze Performance
   • Use built-in analytics tools to track which content performs best in search.
   • Pay attention to metrics like watch time, engagement rate, and follower growth.
   • Regularly review and adjust your strategy based on these insights.
10. Stay Updated with Platform Changes
    • Follow official platform blogs and announcements for algorithm updates.
    • Experiment with new features early to gain a potential advantage in visibility.
    • Attend webinars or courses offered by platforms to stay ahead of best practices.

By implementing these practical steps, brands can significantly improve their visibility in social search results. Remember, social search optimization is an ongoing process. The key is to remain agile, consistently produce high-quality, relevant content, and always keep your audience’s needs and preferences at the forefront of your strategy. This approach to social search optimization not only helps in improving discoverability but also enhances overall engagement and brand loyalty.

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