How Intel Optimizes Pinterest For Maximum Engagement
At SMX East, a team from Intel outlined the company's research on Pinterest and how it affected its strategy. Columnist Benjamin Spiegel discusses what they learned and shares key takeaways for marketers.
With 100 million monthly active users, Pinterest is a powerful and rapidly growing platform for marketers. A session presented at last week’s SMX East by Intel’s Laura Ann Mitchell and Scott Jaworski, titled, “Why Intel Investments in SEO Paid Dividends on Pinterest,” discussed the following:
- The company’s data-driven approach to a Pinterest strategy.
- How to optimize campaigns for maximum engagement in Pinterest.
Mitchell manages SEO for Intel, while Jaworski is global social media and digital strategist for the company. The session highlighted some inspirational (and highly actionable) insights on creating engaging content on Pinterest.
First of all, I have to say that Mitchell is an incredible presenter. (I had the pleasure of presenting alongside her at last year’s SMX West on “Life After Not Provided.”) She is factual and inspiring, and she really knows her topics well.
She also never fails to highlight the work her agency is doing. (Agencies always appreciate that show of support.)
Mitchell and Jaworski delivered the session as a team, which shows how truly integrated search and social are at Intel. They delivered their story with tremendous energy.
Mitchell began with some interesting facts about Pinterest, from the platform and Pew Research, the first being that Pinterest has reached its 100 million active user milestone. Pinterest’s announcement of this figure last month was the first time ever that it had shared its user size, which amplified the platform’s growing importance.
We also learned that:
- Pinterest users are 71 percent female.
- Of its members, 27 percent use Pinterest daily.
- 93 percent of pinners have made an online purchase in the last six months.
- Pinterest’s US male user base increased 73 percent in 2014.
One of the most important components of Intel’s strategy on Pinterest was to clearly define its objective: “Drive brand awareness and affinity by telling a visual story of technology, innovation, and inspiration.”
The team started with the premise that Pinterest is a search engine, then asked the question: “How can insights from SEO help to drive engagement on Pinterest?”
The Intel team performed extensive research around visibility and engagement factors inside Pinterest to find answers. They analyzed the top 25 pins for more than 4,500 keywords, leading to an impressive data set of:
- 110,000+ Pins
- 19,000+ Pinners
- 9,000+ Domains
- 4M+ Re-Pins
- 800k Likes
- 15k+ Comments
As some might have expected, the main performance factors for Pinterest are the pinners, pins, boards and the domains hosting the image. The researchers explored each of these factors and tested some assumptions and theories.
Pinner Factors
What is the impact that the pinners’ metrics have on the performance of the actual pin? Which perform better, pins from pinners…
- With more pins?
- With more followers?
- That are following other pinners?
- That pin content from many domains?
- With many boards?
Interestingly, out of all of these factors, only the first two apply. Their results showed that 80 percent of pins ranking in the first row come from pinners with more than 1,400 total pins, and pinners with first-row ranking pins have an average of 229k followers (36 percent higher than pinners with pins in rows 2–4).
Pin Factors
Next, the team highlighted the pin-related factors that affected the performance of the pins. They looked at pins…
- With more re-pins.
- With more likes.
- With more comments.
- That use rich pins.
Their analysis showed that all of these factors affected a pin’s performance.
Pins ranking in the first row have dramatically higher re-pins (87 percent), likes (93 percent) and comments (220 percent ) than Pins in rows 2–4, and 50 percent of the #1-ranking pins were rich pins.
Therefore, Intel recommends:
- Using rich pins.
- Optimizing the source URL.
- Avoiding pinning duplicate content.
Board Factors
Intel’s team also highlighted some of the findings when it comes to the effect boards have on a pin’s performance. Which perform better?
- Boards with more pins?
- Group boards?
- Certain board names?
It turns out that the Pinterest algorithm for Search for Boards appears to be heavily weighted for exact match of the keyword in the board name. Therefore, the Intel team recommends that marketers:
- Align boards with Pinterest categories.
- Create boards that align with specific events or holidays.
- Create inspirational boards.
Domain Factors
The Intel team identified some domains that are the most pinned and re-pinned. They are:
- YouTube
- Etsy
- Amazon
- CNet
- Engadget
- Mashable
- BuzzFeed
- Flickr
Given that Intel is a tech company, this list is skewed toward technology, but this research could be applied to all kinds of categories.
The team then shared some of the resulting strategies and the playbooks they created based on the findings, with impressive results: 48 percent increase in average monthly engaged viewers and a whopping 364 percent increase in average monthly viewers.
Key Learnings We Can All Apply
A key takeaway from the Intel team’s presentation was that insights from search drive value well beyond the boundaries of the traditional search engine results page. As shown by Mitchell and Jaworski:
- A marketing organization structure that facilitates the sharing of insights across disciplines enables rapid innovation.
- Focusing on the user reveals new ways to meet our audience where they are.
I am looking forward to applying some of the learnings they shared to our clients’ Pinterest projects.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
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