Profound vs Waikay
Choosing the right AI tracking tool is no small task. As businesses and agencies adapt to a world where large language models are increasingly shaping brand perception and search behaviour, the need for accurate, actionable AI intelligence has never been greater. The challenge lies not just in finding a tool that works, but in finding the one that works best for your team’s priorities, workflows, and budget.
In this post, I compare two leading options—Waikay and Profound—focusing on the elements where a direct, like-for-like evaluation is possible. While both serve the same overarching purpose, they approach the task in markedly different ways. Profound leans into polished prompt data visualisation and a design-led user experience, while Waikay prioritises accessibility, delivering deep, topic-based insights at a more approachable cost.
Here’s how they compare across key areas:
Insight Type | Profound | Waikay |
Prompt Tracking | ✅ | ✅ |
Platforms | ✅ | ✅ |
Commercial Visibility | ✅ | ✅ |
Competitor Breakdown by entities | ❌ | ✅ Shown via Entity Heatmap |
Brand comprehension | ❌ | ✅ |
Sentiment | ✅ (“Sentiment”) | ✅ (“Facts”) |
Citations | ✅ | ✅ |
Regions | ✅ | ✅ |
Conversations / Queries | ✅ (“Conversational Tracking”) | ❌ |
Shopping | ✅ | ❌ |
Following the features listed above—while omitting an in-depth review of the shopping and conversation tools due to limited access—I will evaluate the tools.
Prompt Tracking/Commercial visibility
An overview into how prompts are inputted and organised.
Waikay
Waikay organizes prompts at the project level, fully integrated into its Brand Visibility tool. Users can add custom prompts or choose from suggested ones, making setup both flexible and straightforward.
Additional flexibility comes from prompt scheduling—choose to rerun prompts daily, every other day, weekly, or monthly—with clear cost transparency. You also decide which LLM models to query per prompt (ChatGPT, Gemini, Claude, Perplexity), optimizing budget and data granularity.
Once you have chosen prompts, the interface lets you quickly toggle between prompts for fast, granular review. Waikay automatically tracks competitor data for the brands mentioned in LLM-generated responses across prompts. It analyzes each brand using entities—key concepts, themes, and ideas that LLMs associate with those brands.
Data interpretation of the prompts
The two tools focus on different ways to interpret the data. Where profound really goes in on a granular and extensive view of every prompt, Waikay takes a step back and tries to find emerging topic patterns over time. This is likely the biggest reason for the discrepancy in the two prices, as profound will spend lots on getting visually appealing, report ready data at prompt leve;l, Waikay tries to make insightful, entity level signals.
Firstly, you will see a breakdown of your visibility as a percentage of how much space your brand takes up in prompt reports:
This view can change per prompt, or be set to ‘all prompts’ so you can get an average of every prompt.
It also gathers data on your competitors per prompt:
And it covers up to the top 20 competitors without any hidden charges.
A standout feature is Waikay’s built-in Entity Heatmap. Unlike typical SEO keywords, this heatmap visualizes how LLMs semantically connect brands, topics, and tools. It shows:
- Which entities are most frequently linked to your brand
- How these associations shift across prompts
- Where your brand is under-associated compared to competitors
This transforms Waikay from a passive tracker into a diagnostic tool. For example, if your brand isn’t linked with a critical topic—like “internal linking”—where competitors are strong, the heatmap highlights this gap. Conversely, you can confirm if your brand is avoiding unwanted associations strategically.
Beyond observation, the heatmap is actionable: it explains why visibility scores might be low (e.g., missing topical connections or brand mentions). Combined with Waikay’s Topic Reports, you get a seamless workflow from identifying issues to implementing targeted content strategies—all in one platform.
Profound
Profound’s strength lies in the sleekness and transparency of its prompt reports. Users can track each prompt individually and read the full AI-generated responses. This offers a deep, quantitative understanding of how your brand is visible across different questions and themes.
It organises prompts based on topics which is a great way to structure these. The overviews can be seen on this page and you can quickly flit between any you see falling.
Data visualization of the prompts
Profound has fantastic prompt data visualisation.
A key feature is the world heatmap visualization for prompts. Based on the regions you assign, you can see a geographic breakdown of your brand’s visibility side-by-side. For example, with a prompt like “What are the best credit cards?”, you can compare how your brand ranks across countries or regions within a single view. This however does not necessarily mean that every prompt is tracked for every region, you will most likely have to spend prompt budget to re-prompt in other countries and regions.
In contrast, Waikay’s regional settings are at the project level, so you’d need to switch between projects to achieve similar comparisons. Profound’s per-prompt regional heatmap makes market-by-market monitoring seamless for single-brand users.
Profound also offers sentiment analysis at the prompt level, tagging AI-generated text as positive, negative, or neutral. While this aids surface-level monitoring, it’s important to remember that LLMs do not have emotions. Negative phrasing reflects factual content drawn from sources, not feelings. Sentiment scores should be viewed as signals of perception or reputation—not actual emotional tone.
While the scope of data is similar to Waikay’s, Profound excels at providing full access to prompt responses and a clean, interactive regional overview—valuable for those focused on deep qualitative prompt-level analysis.
Bottom line
Waikay prioritizes actionable insights, helping users identify where their brand is underperforming on specific topics. It makes this accessible for small business owners by building data from the ground up and not spending money on different visualizations. Designed for hands-on SEOs and marketers, Waikay supports deep entity analysis and strategic decision-making beyond surface-level visibility metrics.
Profound excels at tracking prompts and regional visibility with polished, commercially appealing data. It suits marketers who need clear, high-level insights to flag issues to executives and secure buy-in or funding. However, it doesn’t guide users on how to notice entity-level discrepancies—offering great alerts but less potentially less strategic depth.
In short:
- Profound is ideal for marketers seeking quick-start insights and executive-ready reports.
- Waikay is best for those ready to build a nuanced, actionable picture and drive real change.
Quick Comparison Table
Feature | Waikay | Profound |
Prompt Organization | Project-level, flexible | Topic folders, daily runs |
Competitor & Entity Analysis | Entity Heatmap, top 20 brands | Limited entity depth |
Regional Insights | Project-level regions | Per-prompt regional heatmaps |
Sentiment Analysis | Focuses on verifiable statements (“facts”) | Sentiment tags (surface level) |
Actionable Insights | Strong, integrated workflows | Alerts and reporting |
Brand comprehension (knowledge reports)
This is a tricky area to compare directly, because Waikay approaches brand comprehension differently from Profound. Profound stops at commercial based data- like where you are showing up compared to your competitors. It is great at visualising this and the depth that brand visibility data goes to is fantastic. Waikay, however, doesn’t stop at the commercial visibility, it goes much deeper, taking a highly granular NLP-based approach to benchmark how well large language models actually understand your brand against 2 direct competitors. Not asking where do you show up, but how you show up and the topic data centred around you, not your competitors.
In Waikay, you create “Topic Reports”. Here, you select two of your biggest competitors and benchmark how well LLMs understand you as a single entity compared with those competitors. This isn’t the same as brand visibility from prompt tracking—Topic Reports dig into all the semantic associations LLMs have about your brand in a specific context.
Here’s how it works: Waikay prompts each LLM with a question like, “What do you know about American Express in the context of credit cards?” It repeats the process for each competitor, across four different models. That’s 12 API calls in total. Waikay then runs NLP analysis on the responses to determine how well you’re understood based on entity analysis.
From here, you can spot entity gaps- areas where your brand’s comprehension lags behind competitors.
Each LLM response also includes its own citations. These are particularly valuable because they’re tied to the knowledge of your brand, not just the commercial queries in your prompt data. This lets you see a clear contrast between citations used when models are describing your brand itself versus those used in competitive or commercial contexts.
Action plans
Both tools provide action plans—steps you can take based on their data to improve your LLM visibility. The difference is… one feels a lot more useful than the other.
Profound
Most of their recommendations are based on citation data. That’s useful—it shows who your biggest competitors are in terms of LLM visibility—but it’s not the full picture. High citations tell you who is showing up, but not why. Are they dominating in specific topics? Are they being mentioned often but still misunderstood? Citation counts alone won’t answer that. Here is one of the top actions for a travel company (as used in their training video). They will create a benchmarking tool and run topic level prompts around this to get more understanding of brand visibility- but Waikay focuses on brand understanding.
Waikay
Waikay, on the other hand, acts as a true benchmarking tool. It doesn’t just show who is ahead—it shows how they’re ahead, where the gaps are, and what’s driving the difference.
Where you’re falling behind entity level:
What that means in real words:
How to implement that:
Sentiments/facts
Profound
Profound uses sentiment analysis to gather data on what is being said about your brand and whether it is positive or negative. This framing can introduce selection bias because it usually requires prompting the LLM with “pros and cons” of a brand to get the results. That framing means the AI will always return both positives and negatives, even if it might not have done so without the prompt. For example, if you were to ask ‘what do you know about Amercian Express, the LLM will likely talk about facts it know as opposed to giving negative reviews of the brand. The method is still solid and provides a useful way to interpret certain LLM reports for brands. Profound also produces an AI-generated summary of this sentiment data, which is easy to access and a great way to understand what people might be seeing about your brand narrative. Awesome for the PR side of things!
Waikay
Waikay focuses on facts. It takes statements about your brand from the topic report responses and presents them as single-sentence lists, organised by topics and models, for you to review. The advantage is that it does not force the LLM to think in terms of pros and cons, so you can identify anything in natural responses that is negative or incorrect. This has been particularly useful for medical companies or anyone handling sensitive information. You can flag individual sentences because even if they are not negative, they could still be wrong and worth correcting on your site.
For example, when tracking inlinks.com on Waikay, we discovered it was being reported as having been acquired by Semrush. A quick fact review showed that this came from a YouTube video and its comments. We were able to address the source quickly, and the incorrect fact has not appeared since.
Citation data
Citation data is strong in both tools
Profound
Profound allows you to check citations for each prompt, gathering thousands of data points and giving you a comprehensive view of what is being discussed. It uses this data to inform action plans, working from the understanding that visibility and citations are closely linked.
One standout feature in Profound is its “citation share” metric, which shows the proportion of citations each competitor holds. You can view this per prompt and also see the top cited domains. Profound tags each citation as “earned,” “owned,” “social,” or “competition.” I am not entirely sure how “earned” is defined in this context, but the tagging system likely adds valuable context for users who work heavily with citation data.
Waikay
Waikay also provides citation data per prompt, but you cannot open the original prompt to see the exact context that generated the citation. Instead, it aggregates these citations and reports on top domains and URLs over time.
The real strength of Waikay lies in how it distinguishes between citations from knowledge reports (brand comprehension) and those from commercial queries. In other words, it separates the domains cited when models are describing your brand specifically from the ones cited when mapping the competitive landscape. You can then place these two sets side by side and identify domains that appear in both. These overlapping domains are likely to be the strongest targets for outreach or content strategy.
Regions
Both Waikay and Profound allow you to separate data by region, but they take different approaches depending on how you want to structure your analysis.
Waikay sets regions at the project level, which is ideal for managing multiple clients, campaigns, or market segments. Each project has its own location, meaning all prompts and data are tied to a specific region from the outset. This setup keeps things organized and scalable—perfect for agencies and large teams alike. Even for big organizations, this structure makes it easy to run regional comparisons across multiple initiatives without clutter.
Profound takes a more granular approach, letting you assign regions per prompt. This is useful for large, single-brand organizations that want to fine-tune prompts across different markets without creating multiple setups. It’s quick to toggle and explore regional variation in a more exploratory way.
Bottom line
Waikay supports both agency-style multi-region setups and large-scale organizational tracking. Profound’s per-prompt flexibility is nice for single-brand teams focused on market-by-market testing.
Other tools
This is where the direct comparisons can really end, but Profound does have some other sections like shopping and prompt volume. I encourage you to look at these.
You can also see our comparison of Waikay vs Peec.
Conclusion
Both Waikay and Profound are powerful in their own right. Profound is the go-to if you want beautifully presented, highly granular prompt-level data and have the budget to invest in deep visualisation. Waikay, on the other hand, is the choice for teams that want actionable, topic-led insights with clear strategic takeaways—without paying for extra visual polish.
If your priority is to explore every prompt in detail and immerse yourself in the data, Profound will feel like home. If you’d rather focus on how AI sees your brand in the bigger picture, and you value simplicity and affordability, Waikay will get you there faster.
Ultimately, the “best” tool comes down to your workflow, your goals, and how much you want to pay for presentation versus actionability.
