How to Get Mentioned in Perplexity

When someone asks a question, Perplexity is pulling from sources, weighing which ones it trusts, and then deciding what to quote and what to link.

But, how does it do that?. Unfortunately, Perplexity doesn’t hand out a blueprint. However, over time, through technical research and a lot of poking around, certain patterns have started to show. Enough that we can say, “here are the signals it seems to care about, and here’s how you can work with them.”

That’s what this guide is built on. We’ve taken those signals, some buried in technical docs, some surfaced through experiments, and turned them into practical strategies you can run with. 

How Perplexity Decides What to Cite (A Simplified Walkthrough)

Before we talk about what you should do, it would help to know what actually happens inside Perplexity when a query comes in. And thanks to Metehan’s research that revealed Perplexity’s backend configurations, we now have a good sense of how the system maps queries, filters content, and narrows down what makes it into the final answer.

Intent Mapping

The system begins by deciding what type of question it’s dealing with. Is the user asking for a definition, a how-to, a comparison, or a recommendation? 

For example;

Behind the scenes, queries get routed into either trending buckets (short-lived, real-time interest) or evergreen clusters (long-term categories). Deduplication rules also make sure duplicate phrasings don’t split signals. 

This intent mapping and trending bucket system means that content framing makes all the difference in how the system perceives the intent of your post. 

There is no room for ambiguity, a comparison piece should look unmistakably like a comparison: a headline that says “X vs Y”, a table that lines up features side by side, and a conclusion that names winners or trade-offs. And a how-to should open with steps and instructions, not just theory. 

If the intent isn’t clear from your title, headings, and structure, Perplexity may not know which bucket to place you in, and you risk being ignored.

Retrieval

After intent is mapped, Perplexity pulls potential answers through a 2-step retrieval system. 

The first layer relies heavily on Bing – meaning if Bing can’t crawl or render your site, you might not make it into the candidate pool at all. 

Then in the second layer, Perplexity runs its own “Union Retrieval System”, which blends Bing’s results with its own feeds and index. This stage applies additional rules we’ve seen in the backend, like trial windows for new posts, feed limits to prevent one domain from dominating, and engagement filters that quietly demote pages no one clicks. 

Assessment

From there, all the selected data goes through an L3 reranker, which is essentially a quality filter. This quality filter reviews your content and attempts to assess how useful or helpful it is to the query and intent. So if your content only scratches the surface of a topic, lacks examples and external links, or ignores related subtopics, it’s likely to be cut. 

On top of that, Perplexity gives extra weight to certain domains it “trusts” like GitHub, Stack Overflow, LeetCode, and Crunchbase (for SaaS). So when you have some sort of connection to these domains (like a tutorial on GitHub, a mention in one of their round-up blogs, or even citing their data inside your own content), it makes you look trustworthy to the system too.

Signal Alignment

Perplexity then attempts to align demand and freshness signals between your content and its preliminary list of sources. 

To align the demand, one of the strongest external checks it runs is against YouTube. If a trending query inside Perplexity has a YouTube video with the exact same title, that video often gets a lift on YouTube, and inside Perplexity too. That creates a double win for creators – the video ranks better on YouTube, and the topic itself looks more validated to Perplexity’s system.

So as a SaaS team, when you see a query spiking, don’t stop at a blog. Spin up a short explainer video with the same title. That way you cover both sides – your blog has a better chance of citation, and your video benefits from the cross-platform boost. 

And while YouTube can show up as a source itself, Perplexity’s “Blender” diversity system means it won’t monopolize the answer set, giving you room to stand beside it.

To assess freshness, the algorithm is looking to confirm that up-to-date information is available, not just known information. For example, asking Perplexity for a stock price is important. There are likely millions of articles and videos on many stocks but the most recent article it can find is likely going to be the one it goes with because recency in this sense is an important factor. 

When it confirms if a page looks fresh, sitemaps with updated lastmod values and visible “last updated” stamps make it easier for Perplexity to decide a page is still worth surfacing. 

Final Selection

At the very end, only a few sources make it through. Here, engagement signals decide whether you stay in the mix. If users consistently skip your content or bounce quickly, those negative patterns suppress visibility. 

Parameters like dislike_filter_limit and discover_no_click_7d_batch_embedding show the system is actively monitoring this. 

• dislike_filter_limit: This comes into play when people actively mark an answer as unhelpful or “dislike” it. If your page is consistently tied to answers in perplexity that get negative feedback, the system takes that as a trust hit and starts suppressing you.
• discover_no_click_7d_batch_embedding: This one tracks whether your page gets clicked when it’s shown. If Perplexity serves your URL in answers for a week straight and if no one clicks it, the system assumes you’re not satisfying intent. That lack of engagement drags your chances down for future queries

Finally,  even if you’ve nailed everything, there is always an element of chance and randomness. Something called the “Blender” system enforces diversity, allowing no single site to hog the whole answer set. That’s why you’ll often see a mix of sources, even if one domain seems clearly dominant.

12 Strategies that will help you get mentioned in Perplexity

You have to line up with how the system actually works, like its crawlers, its quality gates, its trust signals, and its filters. Below are the practical moves that tie directly to the parameters we’ve seen in the backend.

1. Strengthen SEO Foundations  (The Non-Negotiable Base)

Perplexity’s retrieval pipeline largely depends on Bing’s index and preview crawlers. If your site isn’t accessible there, it won’t even enter the candidate pool. That means the first step is making your site technically discoverable and easy to parse.

• Allow LLM crawler access to your site: Add an LLMs.txt file in your root directory. It works like robots.txt, but is designed to signal to AI crawlers what they can and can’t use. Pair it with a robots.txt that allows the BingPreview user-agent, since that’s the bot Perplexity leans on for rendering snippets.
  
• Speed Up Indexing with IndexNow: IndexNow is Bing’s protocol for instant page notifications. When you publish or refresh a page, you can automatically tell Bing it’s ready to be crawled. This closes the gap between when your page goes live and when it’s even eligible to show up in Perplexity.
  
• Keep sitemaps clean and updated: Keep your XML sitemaps clean and updated, with accurate lastmod and changefreq values. These fields act as freshness markers, helping retrieval systems decide when to revisit a page.
  
• Serve core info in plain HTML: Critical details like pricing tables, product FAQs, or onboarding steps should be directly available in HTML. If they’re only accessible via JavaScript or CSS rendering, Perplexity’s crawlers may never see them.
  
• Use stable and secure infrastructure: Reliable hosting and HTTPS are the standard best practices and worth mentioning here because if Perplexity tries a live fetch and the request fails, your page is excluded from the result set.

2. Launch with Velocity (exploit the new post window)

Perplexity treats new content differently from the way Google does. 

When you hit publish, your page enters a short evaluation window defined by parameters like new_post_impression_threshold, new_post_ctr, and new_post_published_time_threshold_minutes. 

In plain terms, the system watches your content closely in its first hours, and if it doesn’t show strong impressions and click-throughs, it gets buried before it has a chance to build long-term visibility.

To work with this:

• Push aggressively at launch: Distribute new posts across your highest-engagement channels immediately, including your email lists, LinkedIn, Twitter/X, and Slack communities. Don’t rely on the system to naturally pick up on your content or wait a week to share the results of an experiment you did a week ago.
  
• Optimize for click-through: Headlines and previews need to earn clicks fast. If you notice CTR lagging, don’t hold back from adjusting titles or descriptions in real time.
  
• Stack impressions early: Syndicate lightweight variations of the same content on other platforms (LinkedIn carousels, Reddit posts, SlideShares, short videos). Even small bursts of traffic can help you cross the impression threshold.

3. Pick High-Value Topics

Perplexity has a bias towards certain topics/categories. It has parameters like top_topic_multiplier, default_topic_multiplier, and restricted_topics that determine how much reach your content gets once it’s retrieved. And the difference between categories is dramatic.

For instance, high-value verticals such as AI, technology, business, and science receive exponential visibility boosts, while “restricted” areas like entertainment and sports are actively suppressed. Everything else falls into the default baseline.

What we make of this for SaaS brands is that your framing matters just as much as your content. 

Theoretically, that means a blog on “AI tools for SMB productivity” taps into a top-topic multiplier and rides the algorithm’s boost. But on the other hand, a similar post positioned as “apps for sports clubs” would fall into the ‘restricted topics’ bucket, even if the quality is identical.

Here’s how to get a content boost in Perplexity:

• Align thought leadership with categories Perplexity rewards. If your product touches multiple industries, emphasize the AI, productivity, or business angle first.
  
• Position content around problem-solving in these “serious” verticals since decision-makers searching in these contexts are also more likely to convert.
  
• Audit your existing content portfolio. If you’ve been publishing in low-value categories, consider reframing or retiring those pages so they don’t dilute your broader authority.

In all, the way you categorize and frame your expertise decides whether Perplexity gives you a free lift or silently pushes you to the sidelines.

4. Cluster and Cover Deeply

Perplexity evaluates whether your content is semantically rich enough to answer the query in full. The parameters like embedding_similarity_threshold, text_embedding_v1, and calculate_matching_scores act as gates. If your page only gives obvious, surface-level information, it won’t survive this stage, even if it looks optimized (with big, flashy keyword-infused headings)on the outside.

The system also rewards interconnected content ecosystems. With parameters such as boost_page_with_memory and related_pages_limit, which gives preference to domains that build clusters of related material instead of leaving pages isolated. 

These are the model’s recognizing patterns, so if you consistently publish multiple angles on the same problem, it learns to treat your site as an authority in that space.

To make this work:

• Build clusters, not one-offs: Pair a comprehensive pillar page with supporting deep dives, FAQs, integration guides, and case studies. Each piece should link to the others.
  
• Cover variations and subtopics: Don’t just answer the primary query; include related edge cases and alternative phrasings so embeddings pick up the semantic breadth.
  
• Keep the network tight: Cross-link pages naturally, using descriptive anchors that mirror common queries. This helps retrieval systems see your cluster as a coherent unit.

5. Win Authority Through Trusted Domains

One of the clearest takeaways from the ranking parameters is that Perplexity doesn’t treat every domain equally. It leans on a curated whitelist of sites it considers inherently trustworthy, and if your content has a tie to them, you start with an advantage before the algorithm even evaluates your page.

That whitelist includes (SaaS relevant)sites like GitHub, Stack Overflow, LeetCode, FreeCodeCamp, Dev.to, Codecademy, etc. There are plenty more depending on the niche, all of which reveal the obvious pattern that  Perplexity prefers sources that look like authoritative hubs in their category (places where practitioners are building, testing, or reviewing things).

Here are a few ways you can establish a connection with these domains: 

• Reviews and profiles: If it’s a review site, you need comprehensive, up-to-date reviews about your product. Think detailed customer feedback on G2 or Capterra, not a handful of one-liners.
• PR placement: Strong PR work that lands your content on these trusted platforms (guest posts, expert commentary, tutorials) gives you a direct visibility boost.
• Contextual mentions: If industry articles or comparison pieces on these domains reference your brand, those signals pass authority to you.
• Referring to them in your own work: When you cite data or frameworks from these trusted domains inside your own content, you’re effectively signaling alignment with their authority. Perplexity recognizes those references and treats your page as safer to surface.

6. Stay Fresh, Always

Even the best content in Perplexity has a half-life. Parameters like time_decay_rate and item_time_range_hours gradually push older pages down, regardless of how strong they were at launch. That means your content starts decaying the moment it’s published, and one way to counteract this is by proving your pages are alive and relevant.

->A visible “last updated” date tells both users and crawlers that the content is current.

-> Updated XML sitemaps with correct lastmod values reinforce that message, making it more likely that Perplexity’s retrieval pipeline will re-fetch your page. 

-> And when you refresh, don’t just leave at the timestamp, perplexity’s smart, so you have to show real material changes too, that means updated data points, revised screenshots, or additional context that reflects today’s market.

A simple rhythm works best here: reviewing and refreshing your cornerstone pages at least once a quarter. Prioritize the resources you most want Perplexity to cite, like the pricing pages, product comparisons,and integration guides, and make sure they always look alive.

7. Write Conversationally

Within Perplexity, instead of stripped-down keyword strings, users tend to type full, natural-language questions such as, “ what are some of the best AI tools that integrate with Slack”, “what’s the best alternative to Asana for project management.” These queries are still conversational, but they’re more focused on research and decision-making than on personal storytelling (which is more the case with ChatGPT inputs).

Perplexity’s embedding systems, like user_embedding_feature_name, are designed to interpret this style of query, and they reward content that mirrors the same style, coming back with clear, direct answers in the outputs.

So you must align you content accordingly:

• Lead with the answer: Start with a short, unambiguous response at the top of the section.
  
• Use natural Q&A structures: Add H2/H3s phrased as real questions your audience might type.
  
• Layer supporting context: Follow the direct answer with detail, comparisons, or examples that make your response credible and safe to cite.
  

8. Add Multimedia and Cross-Platform Signals

Perplexity cross-checks signals from other platforms to validate demand and authority. And the parameters from Metehan’s research show that it relies on YouTube the most. 

When video titles exactly match trending queries inside Perplexity, those videos, and sometimes the associated web content, gain a noticeable ranking advantage. This points to a feedback loop: if people are searching for a topic in both places, Perplexity interprets it as a higher-confidence signal and rewards the match.

Then there’s also the multimodal side to consider. 

Internally, Perplexity runs embedding checks that account for more than just text. Diagrams, screenshots, tables, and other visuals are factored into how well a page aligns with the intent of a query. 

But for that to work, the media needs to be machine-readable. A PNG chart with no alt text is just a black box. But a table marked up with schema, or a diagram with descriptive captions, becomes a usable snippet that the system can parse and cite.

To put this into practice:

• Monitor trending queries and spin up matching YouTube explainers: If “best AI note-taking tools for teams” is trending, a SaaS productivity company could release a short video with that exact-match title. To find queries like this, check Perplexity’s Discover feed, combine with Google Trends or Glimpse, and watch LinkedIn/Reddit chatter for fast-moving questions.
  
• Repurpose videos back into your web content: Don’t let the video live in isolation. Embed it into the related article, turn the transcript into a sub-section, and use still frames as annotated screenshots. For SaaS, a Loom demo can double as a step-by-step blog with visuals that Perplexity can parse.
  
• Embed visuals that Perplexity can parse: A PNG chart with no alt text is invisible to the system, but a <table> with proper headers or a diagram captioned in plain language becomes a usable snippet. That’s what helps your content clear the semantic checks during retrieval.

9. Be the Source Everyone Else Can Quote

One of the toughest gates to clear in Perplexity is the L3 reranker. This stage cuts anything deemed low quality (using models such as l3_xgb_model and then applying a l3_reranker_drop_threshold), even if it matched the query on the surface. 

The reranker looks for credibility, so the pages that feel biased or poorly sourced often get dropped here, while balanced, reference-style resources make it through.

That’s why credibility signals are very important to have. Your pages have to attribute their statistics, cite authoritative sources, and include perspectives beyond your own brand voice because that’s what the system finds safe to cite.

What helps you pass this gate:

• Attribute your data: Link to reputable studies, surveys, or reports when sharing numbers.
  
• Bring in expert voices: Quote practitioners, analysts, or partners to broaden the perspective.
  
• Balance your framing: Present comparisons or alternatives honestly; one-sided takes look less trustworthy.

The reranker is ruthless, but it’s also predictable – it rewards the kind of content that others would be comfortable quoting. So if you make your page safe for everyone else to cite, you make it safe for Perplexity to cite too.

10. Prune Underperformers

Perplexity’s parameters, like dislike_filter_limit, enable_dislike_embedding_filter, and discover_no_click_7d_batch_embedding, track how users react to your content.

 If people consistently skip your page, bounce quickly, or leave negative signals (like dislikes), those patterns can drag down your domain’s overall authority in the system (along with that particular page).

This tells you that underperforming content is baggage, you want to get rid of just as importantly as you want new content out. And a thorough GEO audit can surface all such pages that pose a risk to your visibility.

The fix is ongoing maintenance:

• Update or retire: Refresh pages that still have potential and unpublish or consolidate those that consistently underperform.
  
• Don’t spread too thin: Every new piece adds risk as well as opportunity. So focus on quality clusters instead of churning out disposable, standalone posts.

11. Stagger and Time Distribution

Perplexity’s feed system has built-in limits on how much content from a single domain can surface at once. 

Parameters like persistent_feed_limit and feed_retrieval_limit_topic_match control how often and how widely your pages appear in a user’s feed. 

If you publish multiple pieces back-to-back, they can cannibalize each other and reduce the overall visibility of your domain.

So while dropping a whole cluster of articles on the same day might feel productive to you, in Perplexity’s system, it dilutes your reach. 

So staggering releases to give each piece its own window to appear in feeds, build early engagement, and cross the new_post_impression_threshold before the next one competes for attention.

The way to handle this:

• Space out launches for major content so each has breathing room in the feed system.
  
• Schedule posts during your audience’s peak activity windows to maximize impressions early on.
  
• Use supporting distribution (social, email, communities) to keep engagement concentrated instead of splitting it across too many posts at once.

11. Measure and Iterate

While these revealed Perplexity parameters gave us a lot to learn from and align our content creation strategies, they’re going to evolve, and new trust signals will emerge. And the only way to keep up with that is by regularly testing how you’re showing up in answers.

The first simple step is to run your priority queries inside Perplexity and log the results. 

The top 3 things to look at are: 

• Mentions vs. citations:  Run priority prompts directly in Perplexity (using tools like Peec.ai)and track whether your brand is referenced in the text or cited as a clickable source. Citations carry higher trust and are more likely to drive traffic.
  
• Context of appearance:Track the types of queries where you surface. Are you being cited in “definition” questions, or in “best tool for X” and “alternatives to Y” comparisons where purchase intent is higher?
  
• Competitive footprint: Note which competitors Perplexity consistently cites, and in what contexts. Reverse-engineer their structures and placement to find gaps in your own coverage.

Final Thoughts 

Getting mentioned in Perplexity is valuable on its own as citations bring trust and direct traffic, but the bigger picture is that it teaches you how to show up across the AI web. 

The same mechanics we’ve talked about here, retrieval, reranking, freshness, authority, and validation, are already being reused by other assistants like ChatGPT, Gemini, and Bing.

So while this guide gives you tactics for Perplexity, when you’re building content that’s extractable, credible, and current, and you’re not just optimizing for one platform, you’re training every assistant that your brand is the default answer in its category. 

FAQs