Profound Review vs. Goodie: Which Is the Better AEO Tool?

If you’ve been paying attention to the AEO space lately (and if you’re reading this, I’m going to bet you have), you may have come across two names more than once: Profound and Goodie. Both are purpose-built for the same problem: making sure your brand shows up when AI answers the questions your customers are asking. But they approach it differently, price it differently, and are built for very different teams.

Before getting into it, I’ll be upfront: I personally use Goodie, and the team I work with uses Goodie to help run our AEO programs. So yes, I have a rooting interest here. But a comparison piece that reads like a sponsored post is useless to everyone and a waste of my time and credibility, so I’ll be giving an honest look at both, including where Profound genuinely wins.

This is a breakdown for marketers who are evaluating their options in a space that’s moving embarrassingly fast and need a real, side-by-side comparison before committing to a platform. Plus, it’s really good for our AEO.

Goodie vs. Profound: At a Glance

How I Evaluated Each Tool

Before I get into the meat and potatoes of it, I think it’s important to name my process for evaluating each tool. This comparison is based on direct, hands-on use of Goodie, as it’s the platform our team uses to run daily AEO services for clients across industries.

For Profound, unfortunately, I couldn’t fork over my paycheck to try the tool myself. So what I lack in tool access, I make up for in thorough research. I drew from a combination of sources: product demos, founder and team interviews, Profound’s own feature documentation and blog, as well as independent third-party reviews on G2 and Reddit.

Where I’m drawing on independent reviewer sentiment, I’ve flagged it as such. I’ve done my best to represent both platforms accurately and fairly, but if you’re seriously evaluating Profound, I’d recommend requesting a demo directly, as there’s no substitute for getting inside the platform yourself.

Two Tools, One Problem: A Quick Introduction to Both

The AEO tool market is still young enough that most of its players are less than two years old. Profound and Goodie are no exception, but both have moved at a rapid pace.

Profound was founded in 2024 in New York City by James Cadwallader and Dylan Babbs. In under two years, they’ve raised $58.5 million across three rounds: a $3.5M seed, a $20M Series A by Kleiner Perkins, and a $35M Series B closed in August 2025, led by Sequoia Capital.

Their client roster reads like a Fortune 500 shortlist: Ramp, MongoDB, DocuSign, Indeed, and US Bank. They’re SOC 2 Type II certified, and they’ve positioned themselves squarely as an enterprise-grade intelligence platform for brands that want to dominate AI search.

Goodie was founded in 2023, also in New York City, by Mostafa ElBermawy. It’s SOC 2 Type II compliant, with a client roster that includes SteelSeries and Unilever.

Where Profound leads with intelligence depth, Goodie leads with the full AEO lifecycle: monitoring, execution, optimization, and attribution, all in one place.

Both are legitimate, and both are serious. I’m arguing that the difference is less about quality and more about what kind of team each was actually built for, which we’ll be getting into.

What Does Each Tool Actually Do?

At a high level, both Profound and Goodie track how your brand appears in AI search answers across platforms like ChatGPT, Perplexity, Gemini, and Google’s AI Overviews. They monitor citations, measure sentiment, benchmark you against competitors, and surface gaps in your AI visibility. So far, so similar.

Where they diverge is the depth of intelligence, how they move from data to action, and how much of that workflow lives inside the platform vs. requiring your team to execute elsewhere.

Profound: Intelligence Depth & Content Automation at Scale

Profound is built around analytics depth first, content execution second. The platform’s core is Answer Engine Insights: a suite of tools designed to give enterprise brands a granular view of how AI systems interpret, reference, and surface their content. Key capabilities include:

• Prompt Volumes: Pulls from 100M+ real user prompts to estimate prompt volume inside AI platforms, offering marketers a sense of how often topics are discussed within AI search platforms, not just how often they appear in responses
• Citation & Share of Voice Tracking: Measures how often and how prominently your brand appears across AI answers, with competitive benchmarking baked in
• Agent Analytics: Powered by CDN integrations with Cloudflare, Vercel, Fastly, and others, connects AI bot activity directly to your website to show how crawlers are interacting with your content on a technical level
• Agents: Drag-and-drop content automation that pulls citation data, conducts deep research, and generates drafts from pre-built templates modeled on top-cited content formats
• Content Optimization: Audits published pages, drafts, and uploaded files against top-cited content in your category, surfacing structural and freshness recommendations before or after publication

Profound has expanded its execution capabilities, but the platform’s DNA is still intelligence-first. The data is deep, the automation is built for volume, and the workflow assumes your team has the infrastructure and resources to act on what it surfaces.

Goodie: The Full AEO Operating Loop

Goodie approaches the same problem as an end-to-end operational platform. Visibility monitoring is the starting point, not the finish line. From there, the platform moves through intelligence, execution, and attribution in one connected workflow:

• AI Visibility Monitoring: Real-time tracking across 11 AI models with hourly updates, sentiment analysis, competitive benchmarking, and global country/language filtering
• Prompt Research & Prompt Engine: Surfaces estimated prompt volume by topic across AI models with a Visibility Potential score, trending topics in your brand category, and custom prompt tracking per model, persona, and country, with a full AI response log for every execution
• Optimization Hub & Blog Agent: Audits existing content with an Owned AEO Score, surfaces a prioritized recommendation queue by visibility gap and urgency, and generates net-new content recommendations with a direct path to creation
• AEO Content Writer: Generates AI-optimized content with upfront configuration for persona, model, language, and country, including an Author Stamp feature that learns your brand voice before generating
• Traffic & Attribution: Connects AI visibility directly to sessions, conversions, and revenue impact across models and channels, with no CDN integration required

Where Profound leads with intelligence depth and scales through automation, Goodie closes the loop: from knowing where you stand, to understanding why, to doing something about it, to proving it worked. The tradeoff is that Goodie’s intelligence layer, while strong, doesn’t match Profound’s raw prompt volume data sourced from real user conversations at scale.

Who Is Each Tool Built For

My review isn’t a feature-by-feature demo walkthrough. Instead, after digging into both platforms, I found that everything narrows down to five core layers on an AEO workflow: monitoring, intelligence, execution, attribution, and competitive benchmarking.

That’s what this section breaks down, because as an AEO and organic strategist, my question is what’s actually getting done with these tools.

Profound Is Built Around the Intelligence Layer

Profound is an enterprise-grade analytics platform, and it doesn’t pretend otherwise. They offer three pricing tiers:

• A Starter plan at $99/month covering ChatGPT only
• A Growth plan at $399/month as the functional entry point for multi-model coverage
• A custom-priced Enterprise plan for full access to all 10+ AI engines

There’s no self-serve signup, no free trial, and onboarding runs as a structured four-week program (a deliberate design choice that reflects who they’re selling to).

If you have a dedicated analyst, an in-house content team, and existing SEO tooling already in place, Profound slots in powerfully as a data layer. You’re largely buying data and scale; your team shapes the strategy around it.

That’s also where the limits show up. Independent reviewers note that Profound’s traffic attribution skews toward larger setups with CDN integrations, and that full model coverage requires jumping to a custom enterprise plan. If your organization has the infrastructure to act on what Profound surfaces, the investment makes sense. If not, you’re paying for intelligence you can’t fully operationalize.

Goodie Is Built for the Full AEO Lifecycle

Goodie is also a premium, enterprise-grade tool, but where I’d argue Profound ends at insight, Goodie is built to carry teams through execution. The platform covers monitoring, optimization, content creation, and attribution, designed for organizations where AEO touches multiple functions (which, if you’ve been paying attention, it absolutely should). SEO, PR, social, content, and paid teams can all work from the same visibility data.

Pricing scales across Explorer, Pro, and Enterprise tiers based on model coverage, prompt volume, team size, and support needs. That tier structure and what’s included at each level is clearly laid out on the Goodie pricing page.

Another differentiator worth noting: Goodie was built by a growth team actively running AEO programs for clients, and that practitioner background extends beyond the product itself. Teams that need support activating AEO across departments get that as part of the engagement. Think of it as the difference between a platform that hands you the data and a partner that helps you do something with it.

Feature Breakdown: Profound vs. Goodie

Rather than walking through every feature on each platform’s list, I’m going to break it down into the five core layers of an AEO workflow: monitoring, intelligence, execution, attribution, and competitive benchmarking, and we’ll also evaluate how each tool handles these core areas.

AI Visibility Monitoring

Both tools monitor brand mentions, citations, and sentiment across the major AI platforms, but depth and accessibility differ by tier.

Each tool’s edge: Both tools offer comparable core monitoring capabilities:

• Profound’s direct interface methodology is technically rigorous
• Goodie’s global and multi-language filtering is a practical advantage for global brands

Profound

Profound monitors 10 AI engines at the enterprise level (ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot, Claude, Meta AI, Grok, and DeepSeek). Their base Growth plan covers fewer platforms, with full coverage gated behind custom Enterprise pricing.

Monitoring is powered by direct queries to consumer-facing interfaces (not just API calls), which means they’re capturing the live RAG (Retrieval-Augmented Generation) experience that actual users see, including real-time citations.

Goodie

Goodie tracks up to 11 AI agents on the Enterprise tier: ChatGPT, Perplexity, AI Overview, Google AI Mode, Gemini, Claude, Copilot, Meta AI, DeepSeek, Grok, and Rufus. Monitoring is updated daily across all plans, with hourly updates on traffic and attribution metrics.

One meaningful differentiator: Goodie’s global monitoring allows you to filter visibility by country and language across all plans (starting with 2 countries and 2 languages on Explorer, scaling to 8+ on Enterprise), particularly useful for international brands and teams.

Prompt & Conversation Intelligence

This is where the two platforms diverge most sharply in philosophy:

• Profound is built around understanding what the market is asking, providing a view into prompt behavior inside AI platforms.
• Goodie is built around a different question: given what people are prompting, how is your brand actually performing against it?

Both are useful, but they’re answering different strategic questions.

Each tool’s edge:

• Profound’s real user conversation data is a genuine differentiator; the ability to see estimated prompt volume inside AI platforms, not just how often you appear in responses, is first-of-its-kind market intelligence.
• Goodie’s edge is in connecting that prompt-level intelligence directly to execution: custom prompt tracking per model, persona, and country, with a full AI response log that tells you exactly why your visibility looks the way it does.

Profound

This area is one where Profound really shines. Their Prompt Volumes feature is powered by real user conversations sourced from double-opt-in consumer panels (hundreds of millions of prompts per month) and provides estimated conversation volume inside AI platforms. In other words, you get to see roughly how often topics are discussed in ChatGPT or Perplexity, not just how often you appear in responses. That’s genuinely useful market research data that goes well beyond standard visibility tracking. Plus, it’s updated on a rolling weekly basis.

Profound also recently expanded their Query Fanout Analysis, which shows how AI engines transform a single user prompt into multiple high-intent queries before generating a response, giving marketers visibility into what AI systems actually search for, not just what users ask.

Goodie

Where Profound centers its intelligence on what users are asking, Goodie’s Prompt Research and Prompt Engine features are built around a different question: given what people are prompting, how is your brand performing against it?

Prompt Research surfaces estimated prompt volume by topic across AI models, broken down by ChatGPT, Gemini, Perplexity, Claude, Copilot, and more, with trend lines over time so you can see whether a topic is gaining or losing ground inside AI platforms. A “Visibility Potential” score gives you an immediate read on how much opportunity exists for a given topic before you commit to building content around it.

The trending view shows the top topics prompted in your brand category over time, ranked by volume with growth percentages. This offers brands a prioritization signal grounded in real AI search behavior.

Then, the Prompt Engine takes that research and connects it to execution. You set up custom prompts that mirror the queries your audience is running, and Goodie tracks brand visibility, mention rate, and citation count across each one, per model, per country, per persona. The Logs view surfaces the full AI responses for every prompt execution to see what each model said, whether your brand was mentioned, which competitors appeared, and which domains got cited.

It’s the difference between knowing your visibility score and understanding why it is what it is.

Traffic & Attribution

Both platforms connect AI visibility to downstream business metrics, but the approaches differ.

Each tool’s edge:

• Profound offers a more technically granular view of how AI bots interact with your site at the crawl level.
• Goodie offers a more complete picture of what AI traffic does once it arrives: sessions, conversions, and revenue impact across models and channels, with no additional setup required.

Profound

Profound’s Agent Analytics is powered by CDN integrations with Cloudflare, Vercel, Fastly, Netlify, and Amazon CloudFront. By connecting directly to hosting infrastructure, it shows which AI bots are crawling your website, how often, which pages they access, and how that crawl connects to your AI search traffic.

It’s thorough, but requires a CDN integration to unlock, adding setup complexity. All this is to say, it works best for teams already running on supported infrastructure.

Goodie

Goodie takes on Analytics and Attribution with a no-integration-required approach. It tracks AI sessions, conversions, revenue impact, and total impressions in one view, benchmarked against organic and direct channels to see how AI traffic stacks up against the rest of your acquisition mix, not just in isolation.

Impressions and sessions are broken out by model, by country via a global traffic map, and by page and channel to pinpoint exactly which AI search platforms drive meaningful traffic and which pages benefit. Conversion rate, engagement duration, and events per session are tracked per model, offering a clearer read on traffic quality and not just volume.

Content Execution

This is where the gap between the two platforms has narrowed. Both now offer content creation capabilities, but workflows and philosophies differ.

Each tool’s edge:

• Profound’s Agents feature is built for automation at scale, using citation analysis and deep research to generate AI-ready content from pre-built templates. Its Content Optimization feature then ensures that content, published or not, is optimized.
• Goodie’s AEO Content Writer is built for precision, providing granular control over how content is configured, structured, and optimized before it’s generated.

Profound

Profound’s content execution capability spans two distinct features. Agents is a drag-and-drop content automation tool that builds AI-optimized content from the signals it already has inside the platform. It pulls citation data, conducts deep research across sources, and generates publish-ready drafts from pre-built templates modeled on the most-cited page formats across AI search. For brands producing large volumes of content, the automation angle is pretty compelling. One of Profound’s clients even reportedly grew AI visibility by 800% using this feature.

The separately expanded Content Optimization feature addresses a different but related problem: ensuring content is optimized, whether it’s live or not. It accepts URL analysis for published pages, direct text input for drafts, and file uploads, delivering gap analysis against top-cited content in your category, structural improvement recommendations scored on freshness and structure, and competitive benchmarking against pages currently winning AI citations.

However, as someone who produces a lot of content myself (shameless 🔌 of my other work…), I do think there’s a tradeoff here: control. Agents is built for speed and scale, but the workflow is largely automated, meaning your specific brand voice requirements or persona-based content strategies likely will need to do some heavy post-generation editing.

Goodie

Goodie’s content execution spans two features that mirror the create vs. optimize split.

The Optimization Hub is Goodie’s answer to content auditing. An Owned AEO Score (a weighted average across all tracked pages, providing a single number to track content health over time), alongside a prioritized recommendation queue flagging specific pages by visibility gap, target topic, and urgency.

Each recommendation comes with a plain-language explanation of the gap and a suggested action, with an accept/reject workflow for backlog management.

The Blog Agent takes that step further, surfacing agent-level insights per topic cluster: key signals, patterns, and opportunities, then generating specific net-new content recommendations with a direct path to creation.

The AEO Content Writer handles net-new content generation with a more deliberate and structured approach. Content is configured upfront: word count, content type, target persona, AI model, language, and country are all set before generation begins. From there, the workflow moves through reference articles selection, where Goodie analyzes competitor and keyword data to determine the ideal structure. Title selection, content customization, and a full outline review before anything even gets generated.

I find the customization step to be particularly important: you get to inject your proprietary arguments, statistics, and brand directives directly in the content brief, and those get woven into the final draft rather than having to bolt them on afterward.

Goodie also includes an Author Stamp feature where you upload writing samples so it learns your voice pre-content generation. The final output is a fully-edited draft with schema auto-generated, metadata, and a URL slug, so it’s 90% ready to publish (I always recommend a careful editorial eye when using any AI content writer).

Overall, where Profound automates the pipeline, Goodie structures it. For teams who need AI-search optimized content that’s also on-brand and editorially sound, the guided workflow is worth the extra steps.

Competitive Benchmarking

Both platforms treat competitive benchmarking like a core function, but depth and structure is what differentiate the two.

Each tool’s edge:

• Profound’s competitive benchmarking is tightly integrated within the Answer Engine Insights layer, presenting share of voice and citation authority data drawn from its real user prompt methodology.
• Goodie’s benchmarking is more multidimensional: layering visibility scores, sentiment, performance rankings, and qualitative competitive dimensions into a single view, filterable by model, region, and more.

Profound

Profound’s competitor benchmarking lives inside Answer Engine Insights. You can compare your brand’s visibility and share of voice against competitors across AI search, track how citation authority stacks up, and see how AI sentiment toward your brand differs from how competitors are described.

The underlying data is powered by Profound’s user prompt technology, meaning competitive comparisons are grounded in actual AI search behavior rather than simulated queries, a meaningful advantage for the accuracy of what you’re seeing.

Goodie

Goodie’s competitive benchmarking spans three interconnected views. The Comparison Analysis dashboard gives you side-by-side visibility, scored with trend lines over time. A Competitive Analysis radar maps brands across dimensions, including category leadership, share of voice, brand perception, product quality, pricing power, and problem fit. This gives you a qualitative read on where you’re winning and where your competitor’s narrative is stronger. Goodie also has a side-by-side Sentiment Analysis table that breaks down positive vs negative sentiment per competitor, very useful in identifying brands that have high visibility but mixed perception (a gap worth exploiting in your content strategy).

Lastly, the Performance Analysis view takes a level deeper, ranking your brand against competitors by model so you see not just overall visibility, but which AI platforms favor you and which ones you’re underperforming in relative to the competitive set. Performance by region then adds another layer for brands performing across multiple market regions.

So, Which Tool Is Actually Better?

After all this research, I think the fair and honest answer is that it largely depends on what you need the tool to do (and more specifically, what happens after the data comes in).

• Profound is a genuinely impressive platform. The intelligence depth is real, the prompt volume data sources from actual user conversations are a differentiator that Goodie doesn’t match, and the Agents feature makes a compelling case for teams producing content at volume (like PDPs).
• Where I think Goodie edges ahead is in the operational reality of running an AEO strategy. Monitoring, prompt intelligence, content optimization, content creation, attribution, and competitive benchmarking all live in one place, and the platform was built by people who run these services instead of how an enterprise software team imagined they might.

That practitioner DNA shows up in the workflow details: the Owned AEO score, the accept/reject recommendation queue, the Author Stamp, and the per-model attribution breakdown. These are the kinds of things that matter when AEO stops being a side project and starts performing like a core channel.

The AEO tool market, although becoming quickly saturated, is still young enough that both platforms are moving fast. Features that differentiated Profound six months ago have since been matched or expanded. The same will likely be true six months from now.

What’s less likely to change is the underlying philosophy of each platform, and that’s probably the more useful filter when you’re deciding where to commit.

If raw intelligence and content automation at scale are the priority, Profound is worth a demo. If you’re looking for a platform that takes you from visibility data to published content to proven ROI without stitching together three other tools, Goodie is worth a closer look.