Becoming an Industry Thought Leader: Advanced Techniques for Finding the Best Places to Pitch Guest Posts

Posted by KristinTynski

If you’re involved in any kind of digital PR — or pitching material to writers to expand your brand awareness and build strong ties-in — then you know how hard it can be to find a good dwelling for your content.

I’m about to share the process you can use to identify the best, highest ROI publishers for structure consistent, mutually beneficial guest affixing relationships with.

This knowledge has been invaluable in understanding which publishings have the best reach and authority to other known vertical/ niche professionals, to enable you to share your own expert within these audience communities.

Before we is starting, there’s a caveat: If you aren’t willing to develop genuine dream leader, this process won’t work for you. The qualification for success here is having a piece of content that is new, sensational, and most likely data-driven.

Now let’s get to the good stuff.

Not all publications are equal

Guest posting can increase awareness of your firebrand, originate connect government, and eventually generate prepared induces. However, that only happens if you pick publishers that have ๐Ÿ˜› TAGEND The trust of your target audience.Topical relevant and authority.Sufficiently massive invasion in readership amongst existing powers in your niche/ horizontal.

A large-hearted capture numerous fall into is not properly prioritizing their client affixing programme along these three important metrics.

To situated such a strategy into framework, I’ll furnish a detailed methodology for understanding the “thought leadership” space of two different horizontals. I’ll also include actionable tips for developing a prioritized list of targets for triumphing guest smudges or pillars with your gunman content.

It all starts with BuzzSumo

We use BuzzSumo data as the starting point for developing these interactive constituents. For this section, the focus will be on looking at data drew from their Influencer and Shared Links APIs.

Let’s begin by looking at the data we’re after in the regular user interface. On the Influencers tab, we start by selecting a keyword most representative of the overall niche/ industry/ vertical we want to understand. We’ll start with “SEO.”

The list of influencers here should already be sorted, but feel free to shrink it down by applying filters. I recommend meeting sure your final roll has 250 -5 00 influencers as a minimum to be comprehensive.

Next, and most importantly, we want to get the links’ shared data for each of these influencers. This will be the data we use to build our system visualizations to truly understand the publishers in the opening that are likely to be the highest ROI sits for guest affixing.

Below you can see the visual readout for one influencer.

Note the delivery of websites Gianluca Fiorelli (@ gfiorelli1) most often links to on Twitter. These areas( and their percentages) will be the data we used to support our visualization.

Pulling our data programmatically

Thankfully, BuzzSumo has an excellent and instinctive API, so it’s relatively easy to attract and aggregate all of the data we need. I’ve included a link to my script in Github for those who would like to get it on themselves.

In general, it does the following address ๐Ÿ˜› TAGEND Generates the first page of influencers for the devoted keyword, which is about 50. You can either modernize the write to iterate through sheets or precisely update the page number it pulls from within the script and concatenate the production folders after the fact. For each influencer, it makes another API call and gets all of the aggregated Top Domains shared data for each influencer, which is the same as the data you see in the above pie chart visualization. Aggregates all the data and exports to a CSV. Teach from the data

Once we have our data in the format Gephi prefers for network visualizations( sample edge file ), we are ready to start exploring. Let’s start with our data from the “SEO” search, for which I drew the domain sharing data for the top 400 influencers.

A few mentions ๐Ÿ˜› TAGEND The roundabouts are called nodes. All pitch-black nodes are the influencer’s Twitter details. All other colored nodes are the websites. The size of the nodes is based on Page Rank. This isn’t the Google Page Rank number, but instead the Page Rank within this graph alone. The large the node, the more definitive( and popular) that website is within the entire graph. The dyes of the nodes are based on a modularity algorithm in Gephi. Nodes with same join graphs generally have the same color.

What can we learn from the SEO influencer graph?

Well, the diagram is relatively evenly gave and cohesive. This indicates that the websites and blogs that are shared most frequently are well known by the entire community.

Additionally, there are a few examples of clusters outside the primary collection( the middle of the graph ). For instance, we verify a Local SEO cluster at the 10 p.m. statu on the left hand side. We can also experience a National Press cluster at the 6-7 p. m. arrangement on the bottom and a French Lingo knot at the 1-2 p.m. arrangement at the top right.

Ultimately, Moz, Search Engine Journal, Search Engine Roundtable, Search Engine Land are great gambles when developing and fostering guest posting liaisons.

Note that one of the purposes of the complication with this data has to do with publishing volume. The three largest nodes are also some of the most prolific, necessitating there are more overall an opportunity for clauses to earn Tweets and other social media mentions from industry influencers. You could refining of the data further by normalizing each site by content publishing work to find publishers who publish much less frequently and still enjoy disproportionate visibility within the industry.

Webmasters.Googleblog.com is a good example of this. They publicize 3 to 4 times a month, and more because of their influence in the industry, they’re still one of the largest and most central nodes. Of course, this becomes smell yielded it is the only public expression of Google for our manufacture.

Another important thing to notice is the prominence of both YouTube and SlideShare. If you haven’t hitherto recognise the importance and reach of these platforms, perhaps this is the proof you need. Video content and slip decks are highly shared in the SEO community by top influencers.

Difference between SEO and content commerce influencer graphs

What can we learn from the Content Marketing influencer graph?

For starters, it appears rather different overall from the SEO influencer graph; it’s much less cohesive and seems to have many more separate assembles. This could indicate that the content publishing globe for material marketing is perhaps little grown-up, with more fragmentation and fewer central informants for destroying content commerce referred content. It could also be situations where content commerce is descriptive of more than SEO and that different clusters are publishers that focus more on one type of content marketing vs. another( same to what we saw with the local SEO cluster in the previous example ).

Instead of 3 to 5 similarly sized marketplace presidents, here we read one behemoth, Content Marketing Institute, a testament to both the authorities concerned of that firebrand and the massive sum of the information contained they write.

We can also watch various specific collections. For speciman, the “SEO blogs” cluster in off-color at the 8-9 p. m. place and the more general sell blogs like Hubspot, MarketingProfs, and Social Media Examiner in light-green and mauve at the 4-5 p. m. standing.

The general business top-tier press areas seem relatively influential in this space as well, including Forbes, Entrepreneur, Adweek, Tech Crunch, Business Insider, Inc ., which we didn’t see as much in the SEO example.

YouTube, again, is extremely important, even more so than in the SEO example.

Is it worth noting?

If you’re previously deep in an manufacture, the visualization results of this process are unlikely to shock you. As someone who’s been in the SEO/ content marketing industry for 10 times, the diagrams are roughly what I expected, but there certainly were some surprises.

This process will be most valuable to you when you are new to an industry or are working within a new horizontal or niche. Abusing the python code I joined and BuzzSumo’s incredible API and data offers the opportunity to gain a late visual known of the favorite situates of industry mulled presidents. This knowledge acts as a basis for strategic planning toward identifying top publishers with your own guest content.

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