It transformed my content strategy for the better as I discovered hidden gems along with their search volumes that Pinterest kept hidden from me until now. People often consider Pinterest an engine of inspiration because it’s a place to find beautiful imagery or any creative ideas: a real visual playground. Well, it turns out that Pinterest has a lot more to offer than meets the eye. Data is often locking within keywords. I’m more than happy to share my experiences of Pinterest keywords with you as well as their search volumes.
The Spark: Why Pinterest Keywords?
People’s online idea searching behavior has been a source of fascination for many years. Pinterest, with its image-led search engine, was the perfect mystery to decode. My initial thoughts were far from reality: Pinterest is just like any traditional search engine. But, I was severely mistaken. Pinterest is rather vague in comparison. But, my thoughts changed as I discovered the numerous images and pins were hinting at something more, something bigger. They were pointing towards keyword trends and search volume data that many marketers overlooked.
The Challenge
This is where the twofold challenge began:
Finding a way to uncover those secret gems: A popularity metric and keywords will never just be readily available due to the interface.
Extracting search volume data: Add in the number of people searching a given term, even if you managed to identify relevant keywords in the first place, and the value increases by a whole new level.
My inquisitiveness drove me to examine the deeper levels of Pinterest’s algorithm along with its data layers, and I decided that I will be uncovering the secrets which can assist content creators, bloggers, and marketers in general.
The Journey Begins: Initial Research and Hypothesis
Let’s start with the questioning of the accepted norms. Pinterest is not just a place where one goes for beautiful pictures – it is a search engine. The same SEO logic must apply. I reasoned that if I understood how Pinterest’s search infrastructure actually worked, it would be possible for me to mine for keywords that tend to elude even the most casual of users.
Setting Up the Experiment
My next step was to experiment with my hypothesis. This is how I went about it:
User Behavior Analysis: I searched for available pieces of evidence from forums blogs and insider communities in order to construct how Pinterest’s search function works.
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Testing Search Queries: My next step was to just input different search phrases into the Pinterest’s search bar. During my observation, when I started typing Pinterest suggested some keywords. These suggestions seemed to be popular searches, but what piqued my interest was actual search volume data.
Browser Tools Investigation: With the developer tools of the browser at the ready, I was monitoring the network activity as I searched on Google. I anticipated the API endpoints or data responses containing search volume figures.
It didn’t take too long before I found something captivating.
The Breakthrough: Exposure of the buried information
While I was browsing Pinterest, I ran my developer tools and recorded the network calls. Some of the API responses had metadata information which appeared to have the keyword metrics. On further investigation, I found out that the data was indeed part of the metadata, but it was not meta, rather, it was used by Pinterest to provide suggestions for searches and related pins.
How did it occur?
Step 1: The Search is Clicked
I started with a general keyword in the input bar. Pinterest began suggesting terms, and as it was doing so, I called the browser’s developer console and analyzed the requests being issued.
Step 2: Look at the Network Activity
I opened the “Network” section of the developer tools and put a filter for the search type of activity. There was one endpoint that stood out the most. The endpoint had a response payload that was JSON formatted, and the data contained in it had a number of fields that were marked up with other numbers that could be classed as search volumes.
Step 3: Understanding the JSON Response
After some trial and error, I started to analyze which parameters generated results for different searches. I found certain fields which I believed defined the metrics for user engagement and search volume.
Step 4: Validating the Information
To validate my conclusion, I compared the obtained numbers with external keyword explore tools. I was astonished by the accuracy of the search volumes from the company’s concealed API data.
It is similar to finding a well hidden door in a known room. The ability to use this information for content optimization was staggering.
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The Methodology: Finding Pinterest Keywords Step by Step
For those looking to get your hands dirty, below is a comprehensive account of my work:
1. Get the Right Tools
Browser Developer Tools: Check the “Network” tab in the Chrome or Firefox Developer Tools. It is was useful for grabbing the API calls.
JSON viewer: A reader extension for JSON makes reading difficult data structures much simpler.
Keyword Research Tools: Ahrefs, SEMrush, and Ubersuggest are great tools when you want to confirm the data that you have collected.
2. Start by Searching
Begin with a broader keyword relating to the niche you are working in.
Type it in, and allow Pinterest to complete the phrase and suggest the related terms.
Note down the suggestions which are prompted as you type and remember to pause.
3. Review the API Calls
Click F12 or simply right-click the page and select “Inspect” to enable the developer tools in your browser.
Afterward, click on the “Network” tab.
Refresh Pinterest and keep an eye out for the API calls currently in use.
You’ll want to search for JSON outputs that contain recommendations or keywords in their metadata.
4. Find the Search Volume Parameter
Not all pieces of information will be useful. Rather, focus on the numerical values which may indicate search volume.
Look to see if these figures have patterns during several searches.
If you have identified what you think is the correct field, write down the parameter name.
5. Obtain and Keep Data
For every suggestion from your keywords, obtain the data regarding the volume of search in association with them.
Establish a spreadsheet where you store your keywords and their volume of search for easy access.
Test that data over time with a variety of keywords to make sure it consistently plausible. Then, adjust your methods accordingly.
6. Confirm Your Results
Use keyword analytical tools already present to confirm the search volumes obtained are legitimate and accurate.
After normalization, revisit and adjust your methods if you find mismatches.
When everything is verified, these numbers can help you adjust your content as needed to focus more on keywords with less competition but more local volume and skip the high competitive words.
Let us analyze the changes in my Content Strategy due to the Real-World Impact due to this discovery further.
As soon as I verified Pinterest was discreetly providing search volume data for its keywords, I applied the information for the blog and social media as follows:
Improved Content Targeting
Content Relevance: I was able to customize my blog posts and pins because I was aware of which keywords had a high search volume and interest amongst the target audience.
Niche Focus: There were a few more niche keywords that I had completely overlooked. These were very specific and narrow topics and resulted in more engagement which was a hidden opportunities these gems provided to me.
Competitive Advantage: I was able to outperform my competition with generic keyword research tools because I had a unique set of data to rely on.
Enhanced SEO and Engagement
Pin Optimization: I used high-volume keywords in the board titles and pin descriptions. The outcome was increased visibility and more repins.
Traffic Boost: The repinned optimized pins brought in a lot of viewers and traffic to my site which was a new peak.
Analytics Driven Adjustments: I made sure to continuously track performance and adjusted my strategy to refine it after gaining further insights from both the hidden Pinterest data and external analytics tools.
Case Study Description
My homemade home decoration post on my blog was initially focused on general keywords. However, after applying the hidden Pinterest keyword data, I edited the blog post to accommodate high volume, niche keywords. The post was able to achieve a 50% increase in organic traffic and 30% increase in engagement on Pinterest within weeks. This case study is a great example of how well informed decisions can lead to positive achieving results.
Possible Challenges and Their Solutions
Though it was a EUREKA moment for me, there were a few challenges that I overcame. Here are some of the pitfalls I faced along with the solutions: and how to avoid them:
1. Different Data Sets
Challenge: There was some inconsistency in the API responses. This caused some of the keywords to have a varying amount of search volume.
Solution: Use more than one tool and try and look for trends over the course of a year instead of relying on just 1 data, especially on inconsistent data.
2. Changes to the Platform
Challenge: There are no notes on changes made to the underlying data structure and API for Pinterest.
Solution: Regularly change your methods and keep up with social changes where these common discoveries can be discussed.
3. Hidden Data Over Dependence
Challenge: If you solely depend on the hidden data from Pinterest, you may not have the right amount of data in regards to trends on overall search.
Tip: It is recommended to take a multi-source approach. This means merging data from Pinterest with Google Trends information or information gleaned from traditional SEO instruments to create an all-encompassing strategy.
The Future of Pinterest Keyword Research
This revelation has led me to realize how much potential is present in platforms people often neglect. Pinterest, in the same way as many newer search engines does, has multiple layers of suppressed essential information waiting for a curious person to delve deep into it. With further time spent refining our methods and tools shapes, here’s what I envision far ahead: technology
Active Social Listening
Increased Transparency: Recent changes in API technology as well as engagement will boost the desire for transparency from platforms like Pinterest. In the near future, we may begin to see a raised number of tools built for such purposes or partnerships actively engaged in working with this data.
Developer Communities: As the amount of marketers and developers disclosing their findings rises, so too will the collective intelligence base which is available, and this will have a positive impact on everyone engaged in digital marketing.
AI and Machine Learning
New Technology: The capacity to analyze large amounts of hidden data in real time the AI tools already have and, hopefully in the nearest future, will equip them with understanding the nuances behind keyword trends.
Predictive Trends: Just imagine an instrument that, aside from supplying you with the current search volumes, predicts in real time which trends will become popular next.
Worse Targeting Approaches
It is not easy to optimize every piece of content for better performance, but when content creators such as writers or bloggers receive assistance, there is greater flexibility to make changes.
According to these websites, agencies and brands are more effective at engaging and driving conversions with their targeted campaign using the data provided.
Conclusion: Acknowledge the Possibilities
When I discovered secret Pinterest keywords with actual search volumes, it was not only a technological advancement but a brilliant and wholesome shift in how I approached digital content. It showed how fascinated I can get by just looking below the surface.
It’s not enough to just work in digital marketing, content writing or SEO. We need to write more deeply. Every layer of your preferred platforms needs to be peeled away, and in the end, you might be able to gain insights that provide the advantage you’re seeking.
I cannot help myself. I have set out on a mission to discover concealed data in other platforms. I do not know where it will take me, but I remain super excited about the journey of continuously discovering greater possibilities.
Here’s raising a toast to make results that matter out of the data that confides in silence. Happy discovering!
