Pinterest isn’t just another social media platform… it’s actually a visual search engine disguised as a social network.

And if you’ve been treating it like Google, Instagram or Facebook, that’s probably why your traffic isn’t where you want it to be.

After diving deep into Pinterest’s actual patents and engineering papers (yeah, I’m that nerdy), I’ve figured out exactly how their algorithm works behind the scenes.

Here’s what’s really happening when you create a pin, and more importantly, how you can use this knowledge to get more traffic to your blog.

The Pinterest Algorithm is Actually Three Systems Working Together

Most people think Pinterest has one algorithm, but it’s actually three different machine learning systems working together:

1️⃣ The Content Graph – How Pinterest understands what your pins are about

2️⃣ The User Graph – How Pinterest figures out what each person wants to see

3️⃣ The Matching System – How Pinterest decides which pins to show to which people

Let me break down each one…

Part 1: How Pinterest Understands Your Content (The Content Graph)

Pinterest sees its entire platform as a massive web of connections between pins and boards.

Every time someone saves a pin to a board, Pinterest learns something new about how topics relate to each other.

Think of it like this… if thousands of people save your “easy chicken recipes” pin to boards titled “weeknight dinners,” “family meals,” and “quick cooking,” Pinterest learns that your pin belongs in that neighborhood of the content graph.

The Power of Pinterest’s Vocabulary Database

Here’s something most people don’t know… Pinterest has an internal dictionary of approved keywords called annotations.

These aren’t just random words. They’re specifically chosen terms that Pinterest uses to categorize and understand content.

When you use these official interest keywords in your pin titles, descriptions, and board names, Pinterest immediately knows exactly what your content is about.

This is where PinClicks becomes incredibly valuable. It pulls keyword data directly from Pinterest’s vocabulary database, so you can see the exact terms Pinterest recognizes and uses for recommendations.

Instead of guessing which keywords to use, you can target the exact phrases Pinterest’s algorithm is looking for.

Content Signals Pinterest Analyzes

Pinterest doesn’t just look at your pin description. It analyzes multiple text sources to understand your content:

• Pin title and description
• Board name where it’s saved
• Text from your linked blog post (title, meta description, headings)
• Image captions generated by AI
• URL structure

The more these signals align and reinforce the same topic, the better Pinterest understands what your pin is about.

Topic Cohesion Score (Why Your Blog Post Matters)

Pinterest has a “topic cohesion score” that measures how well your pin matches your blog post content.

If your pin is about “meal prep ideas” but your blog post is actually about “budget grocery shopping,” Pinterest notices this mismatch.

Low cohesion scores can hurt your pin’s performance, while high scores boost it.

This is why your pin needs to accurately represent what people will find when they click through to your site.

Part 2: How Pinterest Understands Users (The User Graph)

Pinterest doesn’t just show random pins to random people. It builds detailed profiles of each user’s interests and preferences.

Multiple Interest Clusters

Instead of seeing each user as having one general interest, Pinterest recognizes that people have multiple, distinct interest clusters.

For example, one person might be interested in:

• Minimalist home decor
• Keto recipes
• Travel photography
• DIY crafts

Pinterest tracks these separately and serves relevant content for each interest area.

Real-Time Intent Signals

Pinterest pays close attention to what users do right now, not just their historical behavior.

If someone just searched for “summer salad recipes,” Pinterest will immediately start showing them more food content, even if they usually engage with home decor pins.

This real-time personalization is why fresh, trending content often gets a boost.

The Interest Taxonomy

Pinterest organizes all topics into a massive hierarchical tree called the Interest Taxonomy.

It goes from broad categories like “Food and Drink” down to very specific subcategories like “Vegetarian Slow Cooker Recipes.”

The more specific your content targeting, the better Pinterest can match it to users with those exact interests.

PinClicks helps you identify these specific interest categories so you can create content that aligns with Pinterest’s internal classification system.

Part 3: How Pinterest Decides What to Show (The Matching System)

This is where the magic happens. Pinterest uses a system called Pixie to generate recommendations.

How Pixie Works

When someone opens Pinterest, Pixie starts with pins they recently engaged with and “walks” through the content graph to find similar content.

It’s like following a trail of breadcrumbs through related pins and boards.

Here’s what’s interesting… Pixie specifically looks for fresh content (pins less than 7 days old) when exploring these connections.

This is why new pins often get an initial boost in visibility.

The Importance of Board Organization

Your board structure directly impacts how Pixie discovers your content.

Pinterest favors boards that are focused on single, specific topics rather than diverse collections.

A board called “Healthy Dinner Recipes” will perform better than a board called “Food Ideas” because it provides clearer context signals.

Pinterest actually prunes (ignores) overly diverse boards from its recommendation system because they don’t provide useful relationship data.

Engagement Signals That Matter

Pinterest tracks several engagement signals, but not all are equal:

Saves (Repins) – The strongest positive signal. When someone saves your pin, it tells Pinterest this content is valuable enough to keep.

Long Clicks – Clicks that last 35 seconds or more. These signal genuine interest and quality content.

Regular Clicks – Basic click-through traffic. Important but can be misleading (clickbait gets clicks but not saves).

Close-ups – When someone taps to see your pin larger. Shows visual interest.

The algorithm optimizes for combinations of these signals, not just one metric.

Visual Recognition and Pin Design

Pinterest uses advanced computer vision to understand images.

It can identify objects, colors, styles, and even detect near-duplicate images.

Why Original Visuals Matter

If multiple pins use the same image, Pinterest groups them together and typically favors the original or highest-performing version.

Creating unique, high-quality visuals ensures your pins don’t get lost in clusters of similar content.

Object Detection for Discovery

Pinterest can identify specific objects within your images and surface your pins when people search for those items.

For example, if your pin shows a living room with a specific lamp, people searching for “table lamps” might discover your interior design content.

Actionable Strategies Based on Algorithm Insights

1. Optimize for Pinterest’s Vocabulary

Use PinClicks to identify official Pinterest interest keywords and incorporate them into:

• Pin titles and descriptions
• Board names
• Blog post titles and headers
• Meta descriptions

2. Create Topic-Focused Boards

Keep boards narrowly focused on specific subtopics rather than broad categories.

Instead of “Home Decor,” create separate boards for “Modern Farmhouse Living Rooms,” “Small Space Organization,” and “DIY Wall Art.”

3. Align Pin and Content Topics

Ensure your pins accurately represent your blog post content.

The stronger the topical alignment, the higher your cohesion score and the better your performance.

4. Design for Engagement

Create pins that inspire action:

• Use clear, readable text overlays
• Include benefit-driven headlines
• Design for mobile viewing
• Make the value proposition obvious at a glance

5. Target Specific Interest Categories

Instead of creating broad content, niche down to specific interest taxonomy nodes.

“Budget meal prep for busy moms” will outperform generic “meal prep” content because it targets a more specific user intent.

6. Optimize for Fresh Content Boosts

Pinterest favors new pins, so:

• Create multiple pin designs for each blog post
• Space out pin creation over time
• Update and refresh older pins with new designs

The Bottom Line

Pinterest’s algorithm is sophisticated, but it’s not mysterious.

It rewards content creators who:

• Use Pinterest’s official vocabulary and interest categories
• Create focused, cohesive content experiences
• Design visually appealing, original pins
• Organize content into topically pure boards
• Provide genuine value that inspires saves and long engagement

Understanding these systems gives you a massive advantage over creators who are just guessing or following outdated advice.

The key is treating Pinterest like the search engine it actually is, not like a social media platform.

When you align your content strategy with how Pinterest’s algorithm actually works, you’ll see significantly better results in both reach and traffic.

And tools like PinClicks make this optimization process much easier by giving you direct access to Pinterest’s internal keyword vocabulary and interest categories, rather than forcing you to guess which terms will work best.

The algorithm isn’t working against you… it’s actually designed to help quality content find the right audience.

You just need to speak its language.

👉 Want to dive deeper? Here’s everything you need to know about getting traffic from Pinterest