This guide simplifies what GEO is, how to measure performance, and reviews the top GEO tools to help marketers, founders, and SEO professionals enhance their visibility in AI-driven searches. We did the research and put together the guide so you don’t have to.

What is Generative Search Optimization (GEO)?

GEO involves optimizing your content to appear prominently in responses generated by AI search engines. Unlike traditional SEO, which targets rankings in search engine results pages, GEO ensures your content is cited or mentioned within AI-generated responses.

GEO focuses on:

• Improving clarity, consistency, and accuracy of content.
• Ensuring your brand is consistently referenced by AI models.
• Crafting content optimized for AI’s contextual understanding.
• Building a website optimized for AI crawlers and agents.

Goodie AI recently published a study, the AEO periodic table on AI search visibility ranking factors, that offers insights into the key variables that impact GEO.

How to Measure GEO Performance

Here are key GEO metrics to monitor:

• AI Visibility Score: Frequency of your brand or content appearing in AI-generated responses.
• Source Citations: How often AI platforms reference your content.
• Competitive Benchmarking: Comparing your visibility against competitors.
• Sentiment Analysis: Ensuring AI accurately and positively portrays your brand.

Tracking these metrics provides insights into your GEO strategy’s effectiveness and helps identify areas for improvement.

Overview of the Market for GEO Tools

Features

Many of the tools we reviewed offer visibility monitoring features, but some are more detailed and extensive than others. The main methodology behind measuring this centers on analyzing multiple prompts and providing insight about a brand’s visibility or lack thereof in the responses to those prompts.

Optimization Capabilities

Most of the current players lack strong optimization capabilities. While they provide helpful insights, those insights are not always coupled with actionable optimization opportunities. Some, however, are more advanced in that regard than others.

Pricing

The space is split between enterprise tools and small business light tools. The light tools are not as accurate and tend to only focus on the visibility aspects of GEO. We found that the enterprise tools like Goodie, Scrunch, and Profound have more capabilities and offer more value, but are also more expensive.

GEO Market Dynamics

There are many new emerging players, so we’ll continue to update this list as the market changes.

New York City houses many of the current players and is rapidly becoming the GEO capital of the world.

How to Choose the Right GEO Tool

When selecting a GEO tool, consider:

• Platform Coverage: Support for major AI platforms (ChatGPT, Perplexity, Google Gemini).
• Real-Time Monitoring: Quick updates and alerts on brand mentions.
• Actionable Insights: Clear guidance on content optimization.
• Integration: Compatibility with existing SEO and analytics tools.
• Ease of Use: Intuitive dashboards and straightforward data interpretation.
• Pricing and Scalability: Transparent pricing and flexibility to scale with your needs.

Top 9 Generative Search Optimization Tools in 2025

1. Goodie AI

Description: Goodie AI is a pioneering AI native platform specializing in Generative Engine Optimization. It helps brands enhance their visibility across AI answer engines like ChatGPT, Gemini, and Perplexity.

Pricing: They offer multiple tiers for startups and enterprises; the exact pricing structure is available upon request.

Founded: 2023

Headquarters: New York City, USA

GEO Features

• AI Visibility Monitoring: Tracks brand visibility and mentions across various LLMs and AI search platforms.
• AI Optimization Hub: Identifies opportunities and provides actionable recommendations to improve AI search visibility.
• AI Content Writer: Identifies gaps and assists in creating content optimized for AI search engines.
• AI Search Analytics & Attribution: Measures and attributes your AI search performance back to the metrics that matter for your business, whether that be user growth or revenue growth.

Pros

• Comprehensive suite of tools tailored for AI search optimization.
• User-friendly interface with real-time analytics.
• Measurement for most major AI platforms, including DeepSeek and Claude.
• Access to an Optimization Hub that’s highly precise and provides actionable GEO insights for each tracked source.

Cons

• As a newer platform, it may lack some integrations with existing marketing tools.
• The tool doesn’t have a report export feature (yet).

2. Semrush

SEMrush recently launched its GEO tool, and it’s currently only available to enterprises. They came late to this GEO tool race and primarily focus on the visibility aspect of things. That being said, they’re the leading traditional SEO tool with massive data capabilities and a large customer base.

• Key Features: Visibility analysis, robust keyword research, competitive analysis, and AI result monitoring on Google.
• Pros: Extensive suite, reliable, user-friendly.
• Cons: Limited to Google-centric AI features, indirect GEO insights.
• Pricing: Starts at $120/month.
• Founded: 2008
• Headquarters: Boston, USA

3. Scrunch AI

Scrunch AI delivers a comprehensive enterprise-focused approach to monitoring and optimizing brand visibility within AI search ecosystems. In a world where users want answers instead of links, Scrunch AI offers a platform to help businesses give users what they’re looking for while boosting your brand’s visibility.

• Key Features: Real-time visibility monitoring, search journey mapping of AI-driven customer interactions, proactive hallucination and misinformation detection.
• Pros: Extensive insights, ideal for large enterprises.
• Cons: Not suitable for small businesses, no self-service option available.
• Pricing: Custom pricing offered upon request.
• Founded: 2022
• Headquarters: Salt Lake City, USA

4. Peec AI

Peec AI simplifies AI analytics with a straightforward approach, ideal for small-to-medium businesses and marketing agencies. Peec AI’s versatility makes it applicable across multiple industries such as healthcare, finance, and marketing. Peec’s dashboard is also user-friendly, making it a great choice if you aren’t an expert in AI platforms.

• Key Features: AI visibility metrics, source citation tracking, competitive benchmarking.
• Pros: Easy to use, clear analytics, affordable.
• Cons: Basic feature set, lacks advanced options like in-depth sentiment tracking or optimization recommendations.
• Pricing: From €120/month.
• Founded: 2023
• Headquarters: Berlin, Germany

5. Otterly AI

Otterly AI is an intuitive and accessible AI search tool designed for monitoring and optimizing your generative engine presence. It’s particularly suitable for smaller businesses and startups that are primarily focused on the monitoring side of the equation.

• Key Features: AI visibility tracking, sentiment analysis, and monitoring link citations.
• Pros: User-friendly interface, affordable, good for beginners.
• Cons: Limited recommendation capabilities, basic analytics.
• Pricing: Starts at $49/month.
• Founded: 2023
• Headquarters: Vienna, Austria

6. Profound

Profound provides a wide range of in-depth GEO analytics specifically tailored to large, global enterprises. One of the early movers in the space, they raised a seed round for Khosla Ventures and South Park Commons, among other notable VCs.

• Key Features: AI visibility tracking, detailed conversation and sentiment analysis, proactive crawler optimization.
• Pros: Highly detailed and robust analytics, multilingual support.
• Cons: Only suitable for enterprises, lacks SEO and content features, and is premium-priced.
• Pricing: Custom pricing upon request. For more information about pricing structure, reach out to Profound’s sales team.
• Founded: 2024
• Headquarters: New York City, USA

7. Hubspot’s AI Search Grader

HubSpot’s AI Search Grader is designed to evaluate content’s search engine performance, providing insights and generative suggestions to help content rank better. It combines AI-driven analysis with SEO expertise, giving users a powerful tool to improve their content strategy.

Instead of just focusing on traditional SEO metrics, it also evaluates the semantic relevance of your content. This includes how well your content aligns with what AI-powered search engines understand in terms of context and user intent.

• Key Features: Provides suggestions to optimize content for better rankings within AI search, compares your content to competitors, and evaluates for conversational AI.
• Pros: Excellent for improving content visibility within AI search.
• Cons: Doesn’t account for all of the AI search algorithms, lacks deeper customization abilities.
• Pricing: Part of HubSpot’s Marketing Hub. Starts at $23 a month and ranges up to $3,200 depending on your subscription tier.
• Founded: This tool was launched in 2023.
• Headquarters: Cambridge, MA.

8. Athena HQ

Athena HQ is an AI search visibility platform designed to assess and enhance the search engine performance of your content. Leveraging advanced AI algorithms, Athena HQ offers in-depth analysis of your website’s visibility, providing actionable insights and tailored suggestions to help your content rank higher in search results. Athena HQ’s tool also evaluates semantic relevance, which determines how well-aligned your content is within the given context.

• Key Features: AI-driven content analysis, semantic relevance evaluation, SEO recommendations, insights into user intent, content performance tracking.
• Pros: Can easily be integrated with other SEO tools and an easy-to-understand reporting dashboard.
• Cons: Limited customization capabilities for niche industries, doesn’t offer a complete GEO/SEO solution.
• Pricing: $400 for the lite version and $900 for their growth version. Also offers an enterprise version for custom pricing options.
• Founded: 2025
• Headquarters: San Francisco, CA

9. Ahrefs

Ahrefs hasn’t really launched anything that is GEO-specific yet, but they provide powerful SEO tools crucial for building and maintaining site authority, indirectly supporting GEO effectiveness. They’re a key player that we cannot ignore in our research, but they aren’t a true GEO tool yet, so we’ve ranked them at the bottom of the list for now.

• Key Features: Comprehensive backlink analysis, site and content auditing.
• Pros: Excellent for improving overall site credibility.
• Cons: Does not directly track generative AI mentions or visibility.
• Pricing: Starts at $99/month.
• Founded: 2010
• Headquarters: Singapore

Generative Search Optimization Tools: FAQs

Final Thoughts

As AI search continues to grow, leveraging these emerging GEO tools to monitor and optimize your brand visibility will be critical. Choose tools aligned with your business size and goals, focusing on clear metrics and actionable insights. Starting with GEO today ensures your content remains visible, authoritative, and relevant as our world continues to be revolutionized by AI.

The post 9 Best Generative Search Optimization Tools (GEO Tools) for 2025 appeared first on NoGood™: Growth Marketing Agency.

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.

However, with the rise of AI answer engines such as ChatGPT, Perplexity, Gemini, and Claude, we’re witnessing a rapid shift in search behavior. People are increasingly turning to LLMs and AI chatbots for their search and research needs, opting for a conversational and direct approach to finding information. In fact, Gartner predicts that traditional search volume will drop by over 25% by 2026 as searchers shift to answer engines to get their questions answered.

As AI models improve and integrate real-time data, we’re confident that traditional Google searches will continue to decline, leading advertisers to reconsider their marketing strategies.

Why Advertisers Should Care

Google Ads has long been a leading driver of conversions and revenue for advertisers. With search volume shifting towards AI-driven answer engines, brands must adapt their strategies to maintain visibility across emerging search platforms. If users are engaging more with AI chatbots instead of traditional search engines, advertising dollars must follow suit.

Ignoring this shift could mean losing a significant portion of the audience to competitors who successfully navigate this evolving space. Marketers must stay ahead by understanding where and how they can place their ads in AI-powered search tools.

Understanding the Main AI LLMs and Their Advertising Capabilities

With more and more AI answer engines coming out each day, it’s important to understand who the leaders in the space are and what their current/future advertising capabilities will look like. In our opinion, these are the leading chatbots that advertisers should be closely monitoring.

ChatGPT

As of now, OpenAI’s ChatGPT does not support direct advertising or have any sponsored content on the platform, but change is likely on the horizon. In an interview with the Financial Times, OpenAI CFO Sarah Friar confirmed that the company is exploring ways to integrate ads into ChatGPT. She stated that they have to be “thoughtful about when and where we implement them,” but it’s low-hanging fruit to improve the business.

OpenAI is actively hiring experts from Google and Meta to develop strategies for seamlessly embedding ads into ChatGPT while maintaining a high-quality user experience. These developments indicate that advertisers should anticipate future opportunities to engage audiences within ChatGPT through ads, similar to what we’re already seeing in Google and Meta AI platforms.

Perplexity

Unlike ChatGPT, Perplexity AI has already started experimenting with advertising. The company has confirmed that they’re testing various ad formats within their platform.

Perplexity’s approach to advertising is still evolving, but early indications suggest that they’re working on a non-intrusive model that maintains a seamless user experience. Perpexity states “Advertising material will be clearly noted as ‘sponsored,’ and answers to Sponsored Questions will still be generated by our technology, and not written or edited by the brands sponsoring the questions.”

The option to run ads within Perplexity is currently in closed beta, featuring brands like Indeed, Whole Foods Market, Universal McCann, PMG, and others. They’re predicted to move to an open beta in the future, allowing more advertisers the opportunity to test running ads on their platform. 

Perplexity does not currently have a platform to run and manage ads, so this will likely be through a sign-up basis for the time being until they develop that platform.

Microsoft Copilot

Microsoft Copilot has fully integrated advertising within its platform. Ads in Copilot are automatically generated from an advertiser’s existing Microsoft Ads campaigns (which also serves Bing), meaning advertisers do not need to opt in manually. However, they also cannot opt out of serving ads within Copilot.

If you’re running search-based campaigns within Microsoft Ads, your ads are already eligible to appear in Copilot. To maximize visibility, optimizing your search campaigns for high performance will improve their chances of showing up in Copilot responses. Some items to focus on include:

• Drafting compelling and relevant ad copy
• Improving quality scores
• Bidding on long-tail conversational keywords

Claude AI

Anthropic’s Claude AI, which has a closed knowledge database, does not currently support advertising, and there is no official word on whether it will in the near future. However, given Google’s significant investment in Anthropic, it would not be surprising if ads are introduced down the line. Google, a dominant force in digital advertising, could leverage Claude to expand its advertising network as searchers leave the platform for chatbots.

Google’s AI Overviews

Google has already begun running ads within its AI Overviews. Similar to Microsoft Copilot, advertisers do not need to take any additional steps to participate. Google Ads campaigns are automatically eligible for these placements, typically below the organic content in the AI Overview.

To optimize for AI Overviews, marketers should focus on:

• Enhancing ad relevance and quality scores
• Leaning into Google Ads automation tools like broad match and PMax
• Bidding on the additional long tail, conversational keywords
• Ensuring ad copy is AI-friendly and easily digestible

Gemini

At this time, Google’s Gemini does not feature advertising. While Google executives have hinted at the potential for native ads within Gemini, they’ve emphasized the importance of maintaining a high-quality user experience.

Google CEO Sundar Pichai recently suggested to investors that native ads could be a future addition: “We always want to lead with the user experience and we do have very good ideas for native ad concepts.”

While we do not expect Gemini ads to launch in 2025, when they do arrive, they will likely be managed through Google Ads in a manner similar to AI Overviews and Copilot, where advertisers are automatically opted in to advertising on the platform.

Predictions for Optimizing Ads in AI Chatbots

As AI-powered search continues to evolve, we predict that advertising in AI chatbots will function similarly to Performance Max (PMax) campaigns — highly automated and data-driven. Here’s what advertisers can expect:

• Limited manual control: Unlike traditional Google Search ads, where advertisers bid on keywords, AI chatbot ads will likely be more automated, with less control over bidding and placements. Ad placements will also likely depend heavily on the turn of a particular conversation.
• AI-driven targeting: Ad delivery will be optimized based on user intent and engagement rather than keyword-based queries.
• Integrated ad formats: Native and contextual ad placements will be crucial to ensuring ads do not disrupt the user experience. People are turning to AI chatbots for a more personalized search experience, and many of these platforms would seek to maintain that.

Key Takeaways for Advertisers

1. Monitor AI chatbot developments: Stay informed on which platforms introduce advertising and how they structure their ad formats.
2. Start testing early: As new ad placements roll out, early adopters will have a competitive advantage in refining their strategies.
3. Optimize for AI-driven search: Ensure your ad creatives and landing pages align with AI chatbot interactions and generative search experiences.
4. Leverage automation: AI advertising will be heavily automated, so leveraging existing machine-learning-driven ad formats (like PMax) will help in transitioning smoothly.

Final Thoughts

The shift from traditional Google search to AI-powered chatbots represents a major transformation in digital marketing. While search engines are not disappearing, user behavior is evolving, and advertisers must adapt accordingly. Brands that proactively explore advertising opportunities within AI chatbots like ChatGPT, Perplexity, and Copilot will stay ahead of the curve.

As AI continues to shape the future of search, one thing is clear: marketers who embrace this change and optimize for AI-driven search will reap the benefits of early adoption.

The post How Answer Engines Are Adopting Advertising Strategies appeared first on NoGood™: Growth Marketing Agency.

Let’s take a look at everything you need to know about AI agents. We’ll also highlight the features of nine AI agents that we think are well-suited to kickstart your business’s growth.

Understanding AI Agents: Your New Digital Growth Partners

AI agents generally fall into three categories:

1. Task-Specific Agents: These are specialized tools designed for functions like customer service, sales outreach, or data analysis. They excel at their designated tasks but have limited flexibility outside their core function.
2. General-Purpose Agents: These versatile agents can handle a wide range of tasks across different domains. They’re the catch-all service option of the AI world, capable of everything from content creation to process automation.
3. Collaborative Agents: These advanced systems work together in teams, each handling different aspects of complex tasks. Think of them as your AI workforce where multiple agents coordinate to achieve your desired goals.

These various types of AI agents can contribute to business growth through three different streams of business operations: revenue generation, cost reduction, and customer experience enhancement.

The most important choice to make is whether you are looking for a full-service AI agent to act as a business partner or if you are looking for AI agents to supplement the skills of your current employees. Our list includes all three types of AI agents to best help you in choosing the right one for your business growth partner. 

Top 9 AI Agents for Growth

1. Goodie – Best LLM Optimization AI Agent

Growth Focus: Full-service AI visibility tracking and optimization tool

Goodie’s ability to track brand visibility on the top LLMs stands out as an all-around optimization agent. It can be used to track brand positioning on top LLMs, recommend optimizations, and create content all based on your brand’s profile.

Key Growth Features:

• Track brand AI visibility across ChatGPT, Gemini, Deepseek, Claude, Perplexity, and Llama through a performance dashboard.
• Optimization hub to identify earned opportunities and control brand narrative
• Compare brand performance with competitive benchmarking
• Global monitoring of brand presence
• Sentiment Analysis

Pricing:

Contact Goodie for pricing options.

2. Lindy – Most Well-Rounded Growth Agent

Growth Focus: Full-service business growth through custom AI agents

Lindy stands out as the top choice for businesses seeking all-around growth. This versatile AI agent platform combines multiple growth-driving capabilities in one solution by automating sales, marketing, and customer support all without requiring any coding experience. Users can automate workflows and decision-making, saving substantial time for employees.

Key Growth Features:

• Multi-channel automation for sales and marketing
• Customer interaction optimization
• Data-driven decision making
• Workflow automation
• Custom agent creation for specific growth needs

Pricing:

• Free trial available
• Starting at $49/month for basic features
• Enterprise plans available for scaling businesses

Best For: Companies looking for a comprehensive growth solution that can scale with their needs.

3. HubSpot Breeze Agents – Best for Revenue Growth / Sales

Growth Focus: Sales pipeline expansion and revenue generation

HubSpot’s AI Sales Agent Breeze specializes in automating and optimizing the entire sales process, from prospecting to closing deals. Breeze can be used for content, social media, prospecting, and customer services.

Key Features:

• Automated lead scoring and qualification
• Personalized sales outreach
• Meeting scheduling automation
• Sales forecasting and analytics
• Pipeline optimization

Pricing:

• Hubspot costs $15 per month per seat; the cost of Breeze Agent depends on your needs.
  • Content Agent: $500 USD / month for 3 seats
  • Social Media Agent: $890 USD / month for 3 seats
  • Prospecting Agent: $100 / month for 1 seat
  • Customer Agent: $100/ month for 1 seat
• Enterprise pricing available for larger teams

Best For: B2B companies focused on scaling their sales operations.

4. Glean – Best for Internal Company Knowledge

Growth Focus: Information sharing across internal departments and documentation

As an AI model powered on your company’s knowledge and internal documentation, Glean simplifies the document sharing process. All company data is centralized on a platform for quick and secure deployment.

Key Growth Features:

• AI search across company data
• AI assistant with powerful advanced prompting
• Integration into your current tech stack
• Tech assistance through the handling of IT requests and engineering issues
• Customizable features

Pricing:

• Contact for pricing.

Best For: Teams looking to connect internal documents and automate company processes.

5. Rasa – Best for Customer Experience Growth

Growth Focus: Customer satisfaction and retention improvement

Rasa is an open-source conversational AI agent that enables businesses to build advanced chatbots, and virtual assistants for customer support. By combining the different available Rasa products; Rasa Pro and Rasa Studio, businesses can automate processes creating AI workflows for customer interaction.

Rasa Pro is the commercial version offering advanced features, security, and enterprise support. Rasa Studio is a low-no code conversational AI builder. Companies can create an AI agent driven by personalized customer journeys.

Key Growth Features:

• Advanced conversational AI
• Personalized customer journeys
• Multi-language support
• Integration with existing CRM systems
• Customer behavior analysis

Pricing:

• Open-source version available
• Enterprise plans start at $499/month

Best For: Companies prioritizing customer experience as their growth driver.

6. DataRobot – Best for Data-Driven Growth

Growth Focus: Analytics and prediction-based growth strategies

DataRobot helps businesses leverage their data for strategic growth decisions. The analytics agent can analyze data, forecast market trends, and make strategic decisions. This AI agent leverages all aspects of your business, integrating into your current process, apps, and platforms and eliminating risk to maximize impact on your team.

Key Growth Features:

• Automated machine learning
• Predictive analytics
• Growth opportunity identification
• Risk analysis
• Market trend prediction

Pricing:

• Custom pricing based on usage
• Enterprise solutions available

Best For: Data-driven organizations looking to base growth decisions on solid analytics.

7. Automation Anywhere – Best for Process Growth

Growth Focus: Operational efficiency and scalability

Automation Anywhere specializes in automating business processes to enable faster growth through robotic process automation (RPA). It creates AI agents that can learn from data and complete repetitive tasks, optimize workflows, and improve operational efficiency.

Key Growth Features:

• Process automation
• Workflow optimization
• Resource allocation
• Cost optimization
• Performance tracking

Pricing:

• Starts at $750/month
• Custom enterprise solutions available

Best For: Organizations looking to scale through improved operational efficiency.

8. Devin – Best for Developers

Growth Focus: Developers AI agent colleague

Devin’s AI agent excels at acting as a collaborative employee. It’s capable of writing its own code and going through the steps of testing that code for accuracy. This goes beyond the capabilities of an LLM that can write its own code. Devin can autonomously conduct tests and automatically update the code to debug it based on test results.

Key Growth Features:

• Build code using natural language requests
• Real time results and feedback
• Code testing to find errors and improve accuracy
• Catch problems and act as an additional developer making its own decisions and recommendations

Pricing:

• Starting plan: $500 USD/month

Best For: B2B companies focused on conversation-led growth.

9. Intercom’s AI Agent Fin – Best for Support Scalability

Growth Focus: Customer support automation and scaling

Intercom’s AI agent Fin helps businesses deliver quality services through a human-centered approach. It automates responses, resolves common queries, and integrates directly into the company’s knowledge base to provide accurate assistance to customers. Fin can be integrated into your current platform or function independently.

Key Growth Features:

• Automated customer support
• Knowledge base optimization
• Custom resolution flows
• Multi-language support
• Support analytics

Pricing:

• Starts at $29 USD / month with Fin AI $0.99 per resolution
• Advanced plan $85 / month includes workflow automation
• Custom pricing for larger teams

Best For: Growing companies needing to scale their customer support.

10. CrewAI – Best for multi-agent integration

Growth Focus: Creating agents that work together to solve complex tasks

CrewAI allows developers to create agents that can work together in managing multiple platforms through complex workflows using LLMs and cloud platforms. This allows for quick development and the ability to scale effectively. CrewAI can automate market research and competitive analysis by acting as a data collection agent, sentiment analysis agent, report generation agent, and strategic recommendation agent. This saves employees time spent on manual research and provides data-driven strategies without needing human oversight.

Key Growth Features:

• AI tool integration
• Complex multi-agent interactions
• Multi-format AI workflows
• Growing AI agent ecosystem

Pricing:

• Open-source but offering enterprise services if requested

Best For: Complex AI systems and companies looking to streamline operations

11. AirOps  – Best at scaling content operations

Growth Focus: Centralized AI agent for scaling operations, workflows, and AI model integration

Airops is an AI agent that combines knowledge of LLMs, brands, and live data to drive content-powered growth. It helps brands turn websites into revenue engines through detailed workflows and content recommendations.

Key Features:

• Uses brand guidelines and expertise to power AI that captures your brand voice.
• Create AI workflows to test ideas, refine outputs, and scale work
• Run workflows at scale to assess outputs and monitor their impact
• Scale quality content and supervise AI workflows
• Automate through AI agents growth strategies

Pricing:

• Solo: $0/month
  • 1 user, basic templates, single brand kit, 1,000 tasks/month and 5 knowledge based sources
• Scale: Contact for pricing
  • Unlimited users, advanced templates, 3+ brand templates, 3+ brand kits, unlimited knowledge base sources, custom tasks (additional features include all features from Solo, Semrush SEO data and more)
• Agency: Contact for pricing
  • Unlimited users, advanced templates, 3+ brand templates, 3+ brand kits, unlimited knowledge base sources, custom tasks (additional features include all features from Solo and Scale and multi-account CMS integrations and more)

How to Choose the Right AI Agent for Growth

Choosing the right AI agent depends on your business’s unique needs. Whether your AI agent choice is driven by growth goals, integration needs, budget considerations, technical capabilities, or scalability, the variety of AI agents available should be able to fulfill most tasks you need. Whether you’re focusing on sales, marketing, customer experience, or operational efficiency, there’s an AI agent that can help accelerate your growth journey.

Remember that successful implementation requires a clear strategy, proper integration, and ongoing optimization. Start with a clear understanding of your growth goals, and choose an agent that best aligns with those objectives.

Frequently Asked Questions

The post 11 Best AI Agents for Growth in 2025 appeared first on NoGood™: Growth Marketing Agency.

By 2027, over 90 million U.S. users are expected to use generative AI for online searches, up from 13 million in 2023. 

Users increasingly rely on answer engines for quick, conversational answers. This shift has reduced reliance on traditional search results. Many users now skip blue links entirely. People want quick, reliable answers without having to skim an entire blog post and parse the information themselves.

AI search engines are the future of how people will discover information online. If you haven’t started building your authority for AEO, you’re already behind.

SEO vs AEO: What’s the Difference for Building Authority?

Traditional SEO focuses on optimizing content for organic rankings and SERP features like featured snippets, knowledge panels, and local search.

AEO, or answer engine optimization, focuses on optimizing websites for answer engines like AI overview and LLMs like Perplexity, Claude, and ChatGPT.

So how do they differ when it comes to building authority?

For traditional SEO, marketers focus on building authority through long-form content that addresses general search intents by offering helpful information that users can explore further.

For AEO, marketers position their websites as a trusted source by providing helpful, direct answers to users’ queries. It caters to users who need quick solutions without navigating through multiple pages.

6 Strategies to Build Authority for AEO

1. Focus on H-E-E-A-T Content

H-E-E-A-T content (Helpfulness, Experience, Expertise, Authoritativeness, and Trustworthiness) improves authority for AEO by meeting key criteria that AI-driven search engines prioritize when selecting authoritative answers for user queries.

H-E-E-A-T content incorporates firsthand knowledge or real-life examples, demonstrating authenticity and reliability. AI search engines prioritize content that demonstrates expertise and experience in a given niche, so they can communicate accurate information to users. 

For instance, providing case studies or personal insights ensures the content resonates with users and AI systems alike.

By citing credible sources and showcasing industry recognition (e.g., certifications or partnerships), H-E-E-A-T content signals authority to search engines, increasing the likelihood of being featured in voice search or snippets.

H-E-E-A-T content focuses on answering specific user queries with clarity and precision, which is essential for AEO. For example, structuring content around common questions ensures it directly addresses user intent while improving engagement metrics like time on page.

2. Create High-Quality Social Media Content and Engage Your Audience

Bing informs ChatGPT, so by optimizing and ranking on Bing, we’re also optimizing for visibility on ChatGPT.

Bing considers likes, shares, and comments on social media platforms as indicators of content quality and relevance. Higher engagement on platforms like Facebook, Twitter, and LinkedIn can positively influence a page’s ranking on Bing.

The more frequently content is shared and reshared on social media, the better it may perform in Bing’s search engine results pages (SERPs). This approach acknowledges the value of word-of-mouth recommendations in the digital space.

Much like your millennial social media manager and Gen Z intern, Bing keeps up with social trends. The algorithm collects publicly available information from social media in real time, processes it, and quickly factors it into its ranking algorithm.

This allows for more up-to-date search results based on the conversations happening on social media. By integrating social signals, Bing aims to provide search results that reflect not just facts, but also the opinions of trusted friends and the collective wisdom of the web.

Bing evaluates the overall social influence of a brand or website, considering factors such as the authenticity of followers and the rate of follower growth. This means that genuine, organic social media growth is more valuable than artificially inflated follower counts.

Bing also incorporates social media data into its SERP features, such as knowledge graphs, providing users with additional context and information. Bing also incorporates Facebook posts and allows users to comment directly in the SERP. By optimizing your social profiles and content for Bing, you open a new opportunity for your content to be featured.

How to Fuse your AEO and Social Media Strategies

• Connect your socials to your website and share content seamlessly between them 
• Embed TikToks, Shorts, Reels, and long-form YouTube videos directly into your blog content and landing pages 
• Engage with your audience on social to drive more likes, comments, and shares

3. Technical SEO for Bing and Google

Pages that load quickly improve user experience and reduce bounce rates, which are key indicators of quality for AI systems like Google AI Overview and Bing’s Copilot.

Slow-loading websites lead to higher bounce rates as users abandon pages that take longer than 3 seconds to load. Faster sites retain visitors, signaling relevance and authority to AI algorithms.

Metrics like Time to First Byte (TTFB) and page load time are key indicators of website performance. Sites with lower TTFB and faster rendering times are more likely to be prioritized in AI search results, enhancing their authority.

Secure websites are also favored by both Google and Bing, as they signal trustworthiness — a core component of authority in AEO. A secure website is characterized by the ‘s’ in ‘https’.

4. Engage in Discussions on Reddit and Quora

Participating in relevant discussions on forum sites like Reddit and Quora allows brands or individuals to answer specific, high-value questions, showcasing their expertise in a relevant domain. This aligns with AEO’s focus on addressing user intent and providing concise, authoritative answers. Posting on forums also helps build topical authority by demonstrating expertise in a niche topic.

Regularly providing thoughtful, well-researched responses helps establish a reputation as a credible source of information. This credibility can influence how AI systems perceive authority when summarizing content for users.

While direct promotion is often frowned upon on these platforms, insightful contributions can lead to organic backlinks when users reference your expertise or link back to your content.

Quora has over 400 million monthly active users. There are constantly new questions being asked that you can answer to demonstrate your authority.

Meanwhile, Reddit has over 130,000 active subreddits, allowing you to interact directly with communities relevant to your niche.

Active participation adds a personal touch to your brand. For instance, Amazon’s representative “Tony” became beloved on the subreddit /r/gamedeals by offering helpful responses and signing posts personally, enhancing both trust and brand perception.

Engaging in discussions helps uncover common questions or pain points in your niche. This insight allows you to create content that directly addresses user intent, improving your chances of being featured in AI-driven search results.

Each subreddit has unique guidelines and expectations. Carefully review the rules in the sidebar or pinned posts before participating to ensure your content aligns with the community’s standards.

Spend time understanding the tone, type of content that performs well, and how members interact. This helps you tailor your contributions appropriately.

Add links to your website or projects in your Reddit profile bio rather than directly in posts, allowing interested users to explore further without feeling pressured.

If relevant, conduct an “Ask Me Anything” (AMA) session where you transparently discuss your work while engaging deeply with user questions. This builds credibility while subtly promoting your expertise.

Use tools like Reddit analytics or third-party platforms to monitor upvotes, comments, and traffic generated by your posts. This helps refine your approach and identify what resonates with the community.

You can also create a brand Subreddit to answer product questions and engage with your audience in a genuine, conversational way. However, creating a subreddit may not be applicable for every brand. This strategy works best for B2C companies in spaces like eCommerce, SaaS, and Fintech who have users actively talking about their products and services.

5. Optimize for Voice Search

Voice search optimization ensures AI assistants like Alexa or Google Assistant recognize your business as a trusted source for information.

Voice search users expect quick, accurate answers. That means we need to structure our content in this way to optimize for voice search queries.

Voice searches are typically phrased as natural, full-sentence questions like, “What’s the best Italian restaurant near me?” By focusing on question-based keywords (e.g., “how,” “why,” “what”), businesses can create content that directly satisfies the needs of voice search users. This positions the content as a reliable source for AI-driven search engines.

Voice assistants often pull answers from featured snippets. Optimizing for concise, structured answers (40–60 words, bullet points) increases the likelihood of being selected as the authoritative response, boosting visibility and credibility.

Many voice searches have local intent (“near me” queries). Optimizing for location-based keywords and ensuring accurate business listings help businesses rank higher in local searches, reinforcing their authority in specific areas.

Providing clear, concise responses also improves user satisfaction for mobile and desktop users, which improves engagement metrics like time on page and bounce rates. These metrics influence how AI systems assess authority.

However, building authority for AEO isn’t just about structuring your content in a certain way. You need to position yourself as a trustworthy source through H-E-E-A-T content to increase your likelihood of being selected for a voice search result.

In all your content, you should include real-life experiences, examples, and links to other credible sources to prove your trustworthiness to answer engines.

6. Gain More High-Quality Reviews

High-quality Google reviews (positive ratings and detailed feedback) signal trustworthiness to Google, which is a core component of H-E-E-A-T. This improves your business’s perceived authority and reliability in search results.

Reviews are a form of UGC that provides authentic insights about your business. This aligns with Google’s preference for credible, user-driven content, which directly impacts authority in AEO.

Google uses reviews to assess how well-known and trusted a business is in its local area. More positive reviews increase prominence, improving your chances of appearing in local search results and AI-driven answers.

Reviews often include relevant keywords naturally used by customers, such as long-tail phrases or specific product/service mentions. These keywords help Google associate your business with relevant queries, boosting your authority in AEO.

Responding to reviews demonstrates active engagement with customers, which Google considers when ranking businesses. This also builds trust with potential customers and reinforces your credibility.

For local businesses, Google reviews are particularly impactful because they help refine local search relevance. AI systems prioritize businesses with strong review profiles when answering location-specific queries.

Future-Proofing your AEO Strategy

Building authority for Answer Engine Optimization is essential. To stay competitive, marketers must embrace strategies that prioritize credibility, user intent, and technical excellence. By focusing on creating high-quality, structured content, optimizing for voice and conversational queries, and leveraging technical fixes, you can position your brand as a trusted source for AI-powered answer engines.

The key to future-proofing your AEO strategy lies in adaptability. Stay ahead of trends by monitoring AI advancements, understanding how users interact with changes in answer engines, and consistently refining your approach to meet users’ evolving expectations. Remember, the brands that thrive in the AI search scene will be those that don’t just chase rankings but build lasting authority through trust, expertise, and user-focused solutions.

If you want to create content tailored to AI search, check out Goodie, the pioneering answer engine optimization platform to help you optimize for AI search engines and monitor your brand visibility.

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