Pinterest is the hottest young site on the internet. In the past six months, the social sharing tool has gone from effectively non-existent to one of the top 100 sites on the web (and is on track to break into Alexa’s Top 50).
Pinterest’s traffic charts aren’t hockey sticks– they’re rocket ships. In our experience, when traffic is growing that sharply there is often something even more amazing going on under the hood. We wanted to see if the usage and engagement numbers for Pinterest were as remarkable as its traffic and gain insights into exactly what was driving growth. Unfortunately, the company has kept very quiet when it comes to its data.
Tired of waiting, we took things into our own hands using some clever scripting and our secret sauce for analytics: RJMetrics. A full report is below, but here a few highlights from our findings:
- Pinterest is retaining and engaging users as much as 2-3x as efficiently as Twitter was at a similar time in its history.
- Pins link to a tremendously large universe of sites. Etsy is the most popular source of pin content, but it only represents about 3% of pins.
- Over 80% of pins are re-pins, demonstrating the tremendous virality at work in the Pinterest community. To contrast, a study done at a similar time in Twitter’s history showed that only about 1.4% of tweets were retweets.
- The quality of the average new user (as defined by their level of engagement and likelihood to remain active) is high but declining. Users who have joined in recent months are 2-3x less active during their first month than the users that came before them.
How We Did It
We wrote some simple scripts to identify random users who joined at varying times in the company’s history and download their complete history of pins to conduct cohort analysis. We also pulled several hundred thousand additional pins from the general user population. All told, we ended up with a database of nearly one million pins.
Thanks to our old friend the central limit theorem, we’re confident that our sizable random samples are representative of the greater population they were pulled from. We should caveat, however, that there is always a risk of sampling bias. Since Pinterest doesn’t use auto-incrementing IDs, we had to get creative about identifying random users and pins. We identified user names based on common dictionary words and then expanded to general-population pins by guessing at ID numbers in numeric proximity to the pins of those core users.
We loaded this raw data into RJMetrics and were able to conduct the following analysis in about 15 minutes. If you’d like to give it a try with your own company’s data, RJMetrics is offering free 30-day trials for a limited time.
Content: What’s Being Pinned?
On Pinterest, every pin ties back to an external link. We used RJMetrics to extract the top-level domain of those links for the pins in our sample. What we found was a pretty tremendous long-tail effect. In our sample of about a million pins, over 100,000 distinct source domains existed. The twenty most prominent are shown below by percent of pins.
The most popular domain was Etsy.com, which powered just over 3% of pins. Close behind was google.com, although almost all Google links point to Google Image Search, which is technically misattributed content from other 3rd party domains. Flickr (2.5%), Tumblr (1.1%), and weheartit.com (1.0%) round out the top 5, after which no domain represents more 1% of pins.
Virality: Re-Pins and Tools
We were able to break out the population of pins based on how those pins were posted to Pinterest. We were expecting a high percentage from pinmarklet, a browser bookmarklet that allows users to pin content from any website with one click. However, what we found was astonishing.
Remarkably, over 80% of pins are re-pins. This is evidence of the impressive level of virality at work in the Pinterest community. Pinterest is truly an ecosystem of sharing. To contrast, a study done by Hubspot at a similar point in Twitter’s history showed that only about 1.4% of tweets were retweets.
User Engagement: Cohort Analysis
Cohort Analysis is a powerful tool that allows us to study different groups of users at identical points in time in their lifecycles, regardless of when they actually joined the site. It’s a great way of getting an “apples to apples” look at newer vs. older users to see how their engagement stacks up.
In the chart below, each line represents a cohort and each cohort is a group of customers who made their first pin in a specific month. For example, the June 2011 cohort consists of users who made their first pin in June 2011. The line itself shows the “average cumulative pins made per cohort member.” So, the “Month 1” data point for the June 2011 cohort shows us how many items were pinned in June 2011 by users who joined in June 2011. The “Month 2” data point on that same line shows us how many pins had been made by the average user in that cohort by the end of July 2011, and so on.
For most companies, even highly successful ones, cohort charts like these show lines that steadily decay toward a more horizontal slope over time. This happens because there is some natural attrition rate with which users simply stop using the site, causing the incremental engagement of the average user to drop off.
That is definitely not the case with Pinterest.
These lines show little to no decay whatsoever. Their slopes remain consistent, indicating a net attrition rate of close to 0%. This either means that no one who starts using Pinterest ever stops or– more likely– that users who continue to use Pinterest become so much more engaged over time that their activities fully make up for those of any users who leave.
To explore which of these two scenarios is playing out, we changed a few options in RJMetrics and ran the cohort analysis below:
This weekly cohort analysis shows the percentage of distinct users from some recent cohorts who come back to pin again in each of the first 8 weeks of their life cycle. As you can see, between 40% and 60% of users are still actively pinning even as far out as week 8. This may seem like a steep drop-off, but for a consumer internet business it’s exceptionally good.
To provide some context, I want to compare this data to a similar analysis I conducted on Twitter in 2009. Twitter was at a similar point in its life cycle (growing tremendously and about a year into its existence). See the chart below:
Twitter’s decay rate was twice that of Pinterest, with user activity (measured by tweets) rapidly plummeting to around 20% before stabilizing.
Growing Pains: Quality Decay
With every fast-growing consumer startup I’ve profiled, an increase in media coverage inevitably corresponds to a huge spike in the number of registered users and a drop-off in the quality of the average user (as defined by their level of engagement and likelihood to remain active). Pinterest is no exception.
As shown above, the average new user who has joined Pinterest in the past few months is using the site substantially less than their counterparts from months in the past. I speculate that this is caused by flocks of curious onlookers who are outside of Pinterest’s core audience registering accounts and failing to get engaged. In the long-term, this could potentially represent a challenge to the company maintaining the remarkable engagement metrics we’ve seen so far.
Conclusion
Pinterest demonstrates some of the strongest user engagement, retention, and virality metrics I have ever seen in an online business. The company has found tremendous success among its core demographic, and the potential reach of its appeal will be tested in the coming months as attention from broader audiences continues to increase.
If the company’s performance to date is any indication, however, it will surely be a start-up to watch in 2012 and beyond.
Nice work.
I do think the repin-phenomenon can be attributed to the fact that Pinterest is still invite-only. Many people’s experience begin with a “network” already set up to explore.
Also, I don’t think “retweets” on Twitter is a fair comparison. “Retweet” wasn’t an official option on Twitter until after the cited study. “Retweets” were done manually, even though various Apps built in the functionality at this point. Pinterest clearly wants you to “repin.” Twitter didn’t think about “retweets” until the community demanded it.
Interesting stuff. A minor point on the Top Source Domains and Average Pins charts: put the domains on the Y axis an the percentages on the X. That would save us having to twist our heads to one side to read them.
Also, replace the pie charts with bar charts. Saves space as is easier to read.
Thanks.
Cool analysis, RJ! I’d be interested to see a pin category distribution similar to the domain distibution. And also maybe (definitely) a graph of pin category vs signup date.
Thanks for the data
I’m curious why you expected most pins to come from the pinmarklet. The majority of my pins were re-pinned from someone else.
@Mark: True, Pinterest is invite-only, but you can request an invite from Pinterest if you don’t already know a current user. I do agree with you regarding the comparison between repins and retweets in that Pinterest was designed with repinning in mind.
Thanks for this, it is straight-up gorgeous! I’d be interested to know how much payoff places like Etsy are getting from their own Pinterest accounts.
Fascinating figures, thank you so much for posting them! I just started with Pinterest so seeing the analysis is quite illuminating.
And of course now I have to go repin this…
Good analysis, are there any available APIs for the data?
Great survey. Thanks. As a new and very active Pinterest user (using it to share futurehacking concepts) my experience is that it needs much development. I regularly update certain pins (not a good word) but repinners are still showing the obsolete version. Why can’t I scroll through my pins? Why can’t comments be edited? (This drives me nuts.) Why is navigation so poor? Why can’t I see lists of Followers and Following as I can on Twitter? Pinterest could do with a big dollop of UX. I’m hoping someone will copy the good bits of Pinterest (another bad name) and add the features that Pinterest has omitted. Best wishes from Bristol, UK. Jack
I am very certain I’m going to able to put so much to use from here!!ty
Why isn’t there a category for mobile pins (i.e. pictures)?
Great post, Pinterest definitely allows great content to go viral. What we’ve found interesting is that it appears that people are more likely to follow boards than people.
I’m curious about whether users are more likely to follow boards or other people… Any analytics on this?
This data, while a nice start, barely scrapes the surface of Pinterest. Taking into the account the demos of users and how it is driving trends in the market place and social atmosphere is a level I’d like to understand. For example, nail polish and nail design. I’m sure this industry and brands such as Opi and Sally Hansen has seen a an uptick in sales due to Pinterest. Even though there is no direct traffic to their sites.
I’ve used pinterest to optimize my site and the result was amazing my site was jumped from #234 to #9 in few weeks time.
The trick is we must got our website pinned and repinned by many people this is the hardest part. Most of pinterest users won’t doing repin when they aren’t like what we pinned.
I do simple thing to outsource it on fiverr and got my site pinned by 75 people, I don’t know how can he did it just search by typing pinterest on fiverr and you will find it on the TOP. Many other seller offer pinterest service on fiverr but in my experience they can’t make my website increase in SEO. I don’t know why.
As I know currently pinterest is best for SEO for these reason:
1. Once our website pinned it has 3 backlinks counts
2. Google interest in social media signal so it will not tagged as links farm
3. Currently pinterest links are dofollow even the image
4. Even not support anchor text (except the url link), it’s still perfect for placing our keywords in description. Google will READ it!!
5. You need to ping the links of your pins to the to get your website increase in SEO
6. Obama The President and Mark Zuckerberg now pinning on Pinterest lol.
Love your analytics here! Do you have any plans to update this? Pinterest is a fast moving topic. I am following it closely and like many involved with Pinterest for brands, I am very interested in analytics. Would love to stay in touch with you. Nice link back from ClickZ/Mashable’s June 11 article. I just left this comment there:
“Nice post Heidi. This is very clearly RJ Metrics data and I appreciate the link to their excellent February article but I think in the spirit of all we are learning about making clear attributions from working with Pinterest – that including their name with each chart is always a good idea – even in small type so that the reference doesn’t get lost as it moves around the web. An updated RJ Metrics’ image source graph would hopefully show some shift as people attempt to be more careful in sourcing images. WeHeartIt is absolutely one of the worst sources I have seen as I have yet to find an image pinned from there where I could discern the creator of the image. Great to see Anthropologie in that early list. They have gone a significant step further by adding the PinIt button to each SKU on their site. I showed an Anthropologie slide to demonstrate this during our Pinterest for Big Brands Case Studies session also at BlogWorld New Media Expo (Social Media Business Summit) New York.”
nice work,
I like the cohort analysis. This is crazy how there is no decay for Pinterest, especially when you compare to Twitter. That clearly show the incredible potential of this tool for marketers.
Vincent
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I have got this guide from pinterest traffic fever “How to get 1 million pinterest followers” Unlike what have claimed i only got about 2k pinterest followers, BTW i have found a free link for this guide if you want it is at , pinterestboardfollowers.com
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