How to use data stories for SEO
How to use data stories for SEO
Data stories aren't even specifically in the domain of SEO, as many organizations/websites generally use data stories to build authority, but here's how to maximize them.
This week’s newsletter is sponsored by the Digital PR agency Search Intelligence, which uses PR methods to grow a link portfolio and North Star Inbound, a recommended agency for penalty recovery. See their case studies linked in the newsletter.
Links are less potent for SEO than just a few years ago, but they will likely always be a requirement for SEO success, even if it’s just a brand signal. While AI can contextualize and value content, there will still always be a need for external authority validation. The best signals for this authority will be links from “popular” sites as scored by traffic, engagement, and their own inbound links.
As a result, many link-building tactics might become obsolete as the algorithms advance; however, using data to craft exciting content to bait links will always be valuable.
Data Stories for SEO
Data stories aren't even specifically in the domain of SEO, as many organizations/websites generally use data stories to build authority. At their core, a presidential opinion poll or an analysis of economic activities are just data stories.
[SPONSORED by Search Intelligence]
Digital PR link building works, but only after you've done these things.
Are you only relying on Digital PR for links?
↳ It probably won't work.
Are you creating average content, with the hope that Digital PR will do the job anyway?
↳ It probably won't work.
Are you ignoring search intent, with the hope that Digital PR will boost the site anyway?
↳ It probably won't work.
The upper limit of data stories is a mass media poll that predicts the likelihood of a specific event (elections, for example), while the lower limit is some cobbled-together statistics in a blog post to attract links. While most data story ideas strive for that upper limit, they usually end up closer to the lower limit in output and results because of one fatal flaw: the creators missed the mark on being interesting.
Focus more on the story than the data
The goal for any story, data or not, is to be as attractive as possible, thereby gaining follow-on activity like engagement and links. An uninteresting story supported by data is still a bland story.
To share some ideas on how to build a successful data story initiative, I will break down my favorite attempt.
Toilets for links and links for toilets
In 2015 while I was living in Singapore, I saw a sign on a bathroom wall from an organization called “The Restroom Association of Singapore” encouraging people to take a survey about……restrooms.
I visited the survey link, and it was an absolutely awful survey. It defied every best practice for survey creation and was atrociously boring.
Out of pure curiosity, I contacted the organization to meet its founder. The founder was a fascinating person with an extreme passion for clean bathrooms.
He achieved his goal of cleaner public restrooms by leveraging the public to score their bathrooms in a survey and then awarding the cleanest in a ceremony attended by the local media and government.
Sensing a possible opportunity for a collaboration that might benefit my APAC growth goals for SurveyMonkey, I proposed that SurveyMonkey could help him improve the quality of his survey with a request that I could also insert some of my own questions that were not on his typical list.
Make a boring survey interesting
This is where the data story comes in. I knew that some media would be reading the survey results, so I had to make it interesting enough that media not on the original distribution list would want to cover it too.
Once we started the survey planning process, I discovered that I had incorrectly assumed that this organization had an extensive distribution list for the survey. They relied on their website and a small email list to complete their survey, which didn’t have enough responses to make this an excellent viral story.
I set up a Facebook campaign with my colleagues on our paid media teams to gather responses to the survey. For some reason, having a picture of a toilet led to great performance, and we got hundreds of results for a low price. :)
This leads to the first important point about data stories:
You need a channel to gather data; if you don’t have one, use paid social.
To make this an exciting story, interesting data was needed. Rather than doing what most people do when using a survey for a data study, which is waiting until the results come to find the “viral” nuggets, I decided what I wanted those viral data points to be first.
I found stories with much social engagement by doing Google searches on past viral stories about bathrooms. Rather than reinventing the wheel, I ensured that my survey would have similar results. While the other viral stories might have had nothing to do with Singaporeans’ views on bathrooms, the same ideas resonate with humans worldwide.
Know what attractions attention
Everyone has the same reactions to gross findings or a sense of identification for knowing that they are “normal.”
For example, two ideas that I found from my Google searches were that there was a sense of surprise at how many people took work calls in the bathroom and that many people actually dropped their phones in the toilet.
All I had to do was make sure that I asked these particular questions in my survey, and I was guaranteed to have data points that people wanted to share.
This leads to the second recommendation for data stories:
Start with the end in mind - the story you want to tell and then get it.
There are obviously many more best practices here (and reach out if you want to hear more), but I want to share one more idea.
I was fortunate to have learned a lot about survey creation during my time at SurveyMonkey. One of my favorite tools was using crosstabs. A crosstab is essentially when you slice responses by answers; the more you slice, the more interesting the data can get.
(It’s helpful to have a lot of responses for cross tabs because the more you slice, the smaller the response count gets).
Cross tabs make things interesting
Based on my research, I already knew which data point would interest readers, and I was confident that cross-tabs would make it even more enjoyable. Again, rather than wait until the results came in to see what was interesting, I pre-decided what would be interesting and ensured that my survey would support those cross-tabs.
For example, gender wasn’t relevant for the overall survey, but I knew that being able to slice gross bathroom behavior by gender would make a headline that much more interesting.
Additionally, mobile device type was irrelevant for a survey about bathroom cleanliness, but knowing which device was more likely to splash in the bowl would be a great headline.
Once the results came in, they were exactly as I had expected them to be. The only thing I didn’t have before launching the survey was the actual stats. Since I already knew it would be interesting, I pre-shopped the results to journalists before they were in.
Interest in covering the survey was unanimous, and my data story was a massive success in media mentions and SEO backlinks (which I cared less about). The story was picked up by most media in Singapore and even had coverage in Indonesia and Malaysia.
While not every topic is as viral as weird bathroom behaviors, I believe these steps are relevant in any vertical, and I have also been equally successful with boring topics.
To recap:
Use social media to gather responses. The responses don't need to be statistically significant, but they must be a big enough pool for the media to trust the results. Five hundred responses might not meet the statistical significance bar, but five hundred people with a particular opinion are enough for a media headline.
Start with the end in mind, and know the stat you want to gather. It’s ok to lead the survey taker if it’s just for a media story AND it is real.
Ask questions that will make for exciting cross-tabs. Consider how each question will combine with other questions to generate interesting results.
Reach out if I can help you think through your data story efforts.
[Sponsored by North Star Inbound ]
This is the exact playbook we ran for a dental client.
In a few short months, the results was:
$139,801 in revenue.
Old SEO playbook:
Create 1000s of pages and rank for millions of keywords.
Alienate users with mass-produced content.
Buy links, run link exchanges, scale your guest posting to boost your rankings so more people can check out the bad mass-produced pages.
New SEO playbook:
Create 100 pages that are best in class, help users solve their problems, honestly present various solutions, and position you as a great option.
Keep those pages up to date be refreshing content regularly.
Create original research and thought leadership content that builds your brand while attracting journalists who want to write about your content.
People who find your pages organically immediately feel served by the content and develop a positive association with your brand. They convert at a higher level or place you on a shortlist.
Get your New SEO Playbook.