Tag Archive | "DataDriven"

"Study Finds:" How Data-Driven Content Marketing Builds Links and Earns Press Mentions

Posted by KristinTynski

In 2019, high-authority links remain highly correlated with rankings. However, acquiring great links is becoming increasingly difficult. Those of you who operate publications of any variety, especially those who enjoy high domain authority, have likely received several link building requests or offers like this each day:

“Please link to my suspect site that provides little or no value.”

“Please engage in my shady link exchange.”

“I can acquire 5 links of DA 50+ for $ 250 each.”

Or maybe slightly more effectively:

“This link is broken, perhaps you would like to link here instead.”

“You link to X resource, but my Y resource is actually better.”

This glut of SEOs who build links through these techniques above have been consistently eroding the efficacy of this style of little-to-no-value ad outreach link building. In the past, perhaps it was possible to convert 2% of outreach emails of this style to real links. Now, that number is more like 0.2 percent.

Link building outreach has become glorified email spam—increasingly ignored and decreasingly effective. And yet, high-authority links remain one of the single most important ranking factors.

So where do we go from here?

Let’s start with a few axioms.

The conclusion: Leveraging data journalism to tell newsworthy stories re-enables effective promotion of content via outreach/pitching. Doing so successfully results in the acquisition of high domain authority links that enjoy the potential for viral syndication. Overall data journalism and outreach represents one of the only remaining scaleable high-authority link building strategies.

How can I leverage data journalism techniques to earn coverage?

To answer this question, I conducted my own data journalism project about the state of data journalism-driven link building! (Meta, I know.)

The primary goal was to understand how major publications (the places worth pitching content) talk about data journalism findings from external sources. By understanding how data journalism is covered, we lay the groundwork for understanding what types of data journalism, themes, and strategies for outreach can be most effective for link building.

We pulled 8,400 articles containing the text “study finds.” This keyword was used as a heuristic for finding data-driven news stories created by outside sources (not done internally by the news publication themselves). We then supplemented these articles with additional data, including links built, social shares, and Google’s Machine Learning topic categorization.

The categories derived by Google’s classifier can have multiple tiers based on the keywords in the article titles, giving us four ways to show the results within each category: The main topic area (containing all relevant subcategories), just the first subcategory, just the second subcategory, and just the third subcategory.

Which outlets most frequently cover data-driven stories from external pitches?

Let’s begin by taking a look at which top-tier news outlets cover “study finds” (AKA, any project pitched by an outside source that ran a survey or study that had “findings”).

For companies conducting studies, they hope to win press coverage for, these top sites are prime targets, with editorial guidelines that clearly see outside pitches of study findings as attractive.

It’s not surprising to see science-based sites ranking at the top, as they’re inherently more likely to talk about studies than other publications. But sites like The Independent, Daily Mail, The Guardian, CNN, Washington Post, and NBC News all ranked highly as well, providing great insight into which established, trusted news sources are willing to publish external research.

Which topic areas do these publishers write about most?

Diving a little deeper, we can explore which topics are covered in these publications that are associated with these external studies, providing us insight into which verticals might be the best targets for this strategy.

There are many unique insights to be gleaned from the following charts depending on your niche/topical focus. This data can easily be used as a pitching guide, showing you which publishers are the most likely to pick up and cover your pitches for the findings of your study or survey.

Here is a view of the overall category and subcategory distribution for the top publishers.

As you can see, it’s…a lot. To get more actionable breakdowns, we can look at different views of the topical categories. The categories derived by Google’s classifier can have multiple tiers based on the keywords in the article titles, giving us several ways to show the results within each category.

You can explore the Tableau sheets to get into the nitty-gritty, but even with these views, a few more specialized publications, like InsideHigherEd.com and blogs.edweek.org, emerge.

Which topic areas drive the most links?

Press mentions are great, but syndication is where data journalism and content-based outreach strategy really shines. I also wanted to understand which topic areas drive link acquisition. As it turns out, some topics are significantly better at driving links than others.

Note that the color of the bar charts is associated with volume of sharing by topic—the darker the bar on the chart, the higher it was shared. With this additional sharing data, it’s plain to see that while links and social shares are highly correlated, there are some categories that are top link builders but do not perform as well on social and vice versa.

This next set of data visualizations again explore these topic areas in detail. In each batch, we see the median number of links built as an overall category aggregate and then by each category.

Which domains generate the most links when they pick up a data-driven story?

Another interesting question is which domains overall result in the largest number of links generated for “study finds” stories. Below is that ranking, colored by the median number of total shares for that domain.

Notice that while The Independent ranked supreme in the earlier graph about including the most “study finds” pieces, they don’t appear at all on this graph. Sites like The Guardian, CNN, The Washington Post, and NBC News, however, score highly on both, meaning they’re probably more likely to publish your research (relatively speaking, since all high-authority sites are tough to get coverage on), and if you’re successful, you’re probably more likely to get more syndicated links as a result.

Which topic areas are the most evergreen?

Now, let’s look at each category by BuzzSumo’s “evergreen score” to see what kind of content will get you the most bang for your buck.

The evergreen score was developed by BuzzSumo to measure the number of backlinks and social shares an article receives more than a month after it’s published.

When you’re considering doing a study and you want it to have lasting power, brainstorm whether any of these topics tie to your product or service offering, because it appears their impact lingers for longer than a month:

What this all means

Link building through data-driven content marketing and PR is a predictable and scalable way to massively impact domain authority, page authority, and organic visibility.

Always consider:

1. Which publishers make sense to pitch to?

  • Do they often cover external studies?
  • Do they cover topics that I write about?
  • Does their coverage lead to a high volume of syndicated links?

2. Does my topic have lasting power?

To really make the most of your content and outreach strategy, you’ll need to incorporate these tips and more into your content development and pitching.

In previous articles on Moz I’ve covered:

These ideas and methodologies are at the heart of the work we do at Fractl and have been instrumental in helping us develop best practices for ideation, content creation, and successful outreach to press. Pulling on each of these levers (and many others), testing, and accumulating data that can then be used to refine processes is what begins to make a real impact on success rates and allows you to break through the noise.

If you want to discuss the major takeaways for your industry, feel free to email me at kristin@frac.tl.

Did anything surprise you in the data? Share your thoughts below!

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Search Trends: Are Compound Queries the start of the Shift to Data-Driven Search?

Posted by Tom-Anthony

The Web is an ever-diminishing aspect of our online lives. We increasingly use apps, wearables, smart assistants (Google Now, Siri, Cortana), smart watches, and smart TVs for searches, and none of these are returning 10 blue links. In fact, we usually don’t end up on a website at all.

Apps are the natural successor, and an increasing amount of time spent optimising search is going to be spent focusing on apps. However, whilst app search is going to be very important, I don’t think it is where the trend stops.

This post is about where I think the trends take us—towards what I am calling “Data-Driven Search”. Along the way I am going to highlight another phenomenon: “Compound Queries”. I believe these changes will dramatically alter the way search and SEO work over the next 1-3 years, and it is important we begin now to think about how that future could look.

App indexing is just the beginning

With
App Indexing Google is moving beyond the bounds of the web-search paradigm which made them famous. On Android, we are now seeing blue links which are not to web pages but are deep links to open specific pages within apps:


This is interesting in and of itself, but it is also part of a larger pattern which began with things like the answer box and knowledge graph. With these, we saw that Google was shifting away from sending you somewhere else but was starting to provide the answer you were looking for right there in the SERPs. App Indexing is the next step, which moves Google from simply providing answers to enabling actions—allow you to
do things.

App Indexing is going to be around for a while—but here I want to focus on this trend towards providing answers and enabling actions.

Notable technology trends

Google’s mission is to build the “ultimate assistant”—something that anticipates your needs and facilitates fulfilling them. Google Now is just the beginning of what they are dreaming of.

So many of the projects and technologies that Google, and their competitors, are working on are converging with the trend towards “answers and actions”, and I think this is going to lead to a really interesting evolution in searches—namely what I am calling “Data-Driven Search”.

Let’s look at some of the contributing technologies.

Compound queries: query revisions & chained queries

There is a lot of talk about conversational search at the moment, and it is fascinating for many reasons, but in this instance I am mostly interested in two specific facets:

  • Query revision
  • Chained queries

The current model for multiple queries looks like this:

You do one query (e.g. “recipe books”) and then, after looking at the results of that search, you have a better sense of exactly what it is you are looking for and so you refine your query and run another search (e.g. “vegetarian recipe books”). Notice that you do two distinct searches—with the second one mostly completely separate from the first.

Conversational search is moving us towards a new model which looks more like this, which I’m calling the
Compound Query model:

In this instance, after evaluating the results I got, I don’t make a new query but instead a
Query Revision which relates back to that initial query. After searching “recipe books”, I might follow up with “just show me the vegetarian ones”. You can already do this with conversational search:

Example of a “Query Revision”—one type of Compound Query

Currently, we only see this intent revision model working in conversational search, but I expect we will see it migrate into desktop search as well. There will be a new generation of searchers who won’t have been “trained” to search in the unnatural and stilted keyword-oriented that we have. They’ll be used to conversational search on their phones and will apply the same patterns on desktop machines. I suspect we’ll also see other changes to desktop-based search which will merge in other aspects of how conversational search results are presented. There are also other companies working on radical new interfaces, such as
Scinet by Etsimo (their interface is quite radical, but the problems it solves and addresses are ones Google will likely also be working on).

So many SEO paradigms don’t begin to apply in this scenario; things like keyword research and rankings are not compatible with a query model that has multiple phases.

This new query model has a second application, namely
Chained Queries, where you perform an initial query, and then on receiving a response you perform a second query on the same topic (the classic example is “How tall is Justin Bieber?” followed by “How old is he?”—the second query is dependent upon the first):

Example of a Chained Query—the second type of Compound Query

It might be that in the case of chained queries, the latter queries could be converted to be standalone queries, such that they don’t muddy the SEO waters quite as much as as queries that have revisions. However, I’m not sure that this necessarily stands true, because every query in a chain adds context that makes it much easier for Google to accurately determine your intent in later queries.

If you are not convinced, consider that in the example above, as is often the case in examples (such as the Justin Bieber example), it is usually clear from the formulation that this is explicitly a chained query. However—there are chained queries where it is not necessarily clear that the current query is chained to the previous. To illustrate this, I’ve borrowed an example which Behshad Behzadi, Director of Conversational Search at Google, showed at SMX Munich last month:

Example of a “hidden” Chained Query—it is not explicit that the last search refers to the previous one.

If you didn’t see the first search for “pictures of mario” before the second and third examples, it might not be immediately obvious that the second “pictures of mario” query has taken into account the previous search. There are bound to be far more subtle examples than this.

New interfaces

The days of all Google searches coming solely via a desktop-based web browser are already long since dead, but mobile users using voice search are just the start of the change—there is an ongoing divergence of interfaces. I’m focusing here on the
output interfaces—i.e., how we consume the results from a search on a specific device.

The primary device category that springs to mind is that of wearables and smart watches, which have a variety of ways in which they communicate with their users:

  • Compact screens—devices like the Apple Watch and Microsoft Band have compact form factor screens, which allow for visual results, but not in the same format as days gone by—a list of web links won’t be helpful.
  • Audio—with Siri, Google Now, and Cortana all becoming available via wearable interfaces (that pair to smart phones) users can also consume results as voice.
  • Vibrations—the Apple Watch can give users directions using vibrations to signal left and right turns without needing to look or listen to the device. Getting directions already covers a number of searches, but you could imagine this also being useful for various yes/no queries (e.g. “is my train on time?”).

Each of these methods is incompatible with the old “title & snippet” method that made up the 10 blue links, but furthermore they are also all different from one another.

What is clear is that there is going to need to be an increase in the forms in which search engines can respond to an identical query, with responses being adaptive to the way in which the user will consume their result.

We will also see queries where the query may be “handed off” to another device: imagine me doing a search for a location on my phone and then using my watch to give me direction. Apple already has “Handover”which does this in various contexts, and I expect we’ll see the concept taken further.

This is related to Google increasingly providing us with encapsulated answers, rather than links to websites—especially true on wearables and smart devices. The interesting phenomenon here is that these answers don’t specify a specific layout, like a webpage does.
The data and the layout are separated.

Which leads us to…

Cards

Made popular by Google Now, cards are prevalent in both iOS and Android, as well as on social platforms. They are a
growing facet of the mobile experience:

Cards provide small units of information in an accessible chunk, often with a link to dig deeper by flipping a card over or by linking through to an app.

Cards exactly fit into the paradigm above—they are more concerned with the data you will see and less so about the way in which you will see it. The same cards look different in different places.

Furthermore, we are entering a point where you can now
do more and more from a card, rather than it leading you into an app to do more. You can response to messages, reply to tweets, like and re-share, and all sorts of things all from cards, without opening an app; I highly recommend this blog post which explores this phenomenon.

It seems likely we’ll see Google Now (and mobile search as it
becomes more like Google Now) allowing you to do more and more right from cards themselves—many of these things will be actions facilitated by other parties (by way of APIs of schema.org actions). In this way Google will become a “junction box” sitting between us and third parties who provide services; they’ll find an API/service provider and return us a snippet of data showing us options and then enable us to pass back data representing our response to the relevant API.

Shared screens

The next piece of the puzzle is “shared screens”, which covers several things. This starts with Google Chromecast, which has popularised the ability to “throw” things from one screen to another. At home, any guests I have over who join my wifi are able to “throw” a YouTube video from their mobile phone to my TV via the Chromecast. The same is true for people in the meeting rooms at Distilled offices and in a variety of other public spaces.

I can natively throw a variety of things: photos, YouTube videos, movies on Netflix etc., etc. How long until that includes searches? How long until I can throw the results of a search on an iPad on to the TV to show my wife the holiday options I’m looking at? Sure we can do that by sharing the whole screen now, but how long until, like photos of YouTube videos, the search results I throw to the TV take on a new layout that is suitable for that larger screen?

You can immediately see how this links back to the concept of cards and interfaces outlined above;
I’m moving data from screen to screen, and between devices that provide different interfaces.

These concepts are all very related to the concept of “fluid mobility” that Microsoft recently presented in their Productivity Future Vision released in February this year.

An evolution of this is if we reach the point that some people have envisioned, whereby many offices workers, who don’t require huge computational power, no longer have computers at their desks. Instead their desks just house dumb terminals: a display, keyboard and mouse which connect to the phone in their pockets which provides the processing power.

In this scenario, it becomes even more usual for people to be switching interfaces “mid task” (including searches)—you do a search at your desk at work (powered by your phone), then continue to review the results on the train home on the phone itself before browsing further on your TV at home.

Email structured markup

This deserves a quick mention—it is another data point in the trend of “enabling action”. It doesn’t seem to be common knowledge that you can use
structured markup and schema.org markup in emails, which works in both Gmail and Google Inbox.

Editor’s note: Stay tuned for more on this in tomorrow’s post!

The main concepts they introduce are “highlights” and “actions”—sound familiar? You can define actions that become buttons in emails allowing people to confirm, save, review, RSVP, etc. with a single click right in the email.

Currently, you have to apply to Google for them to whitelist emails you send out in order for them to mark the emails up, but I expect we’ll see this rolling out more and more. It may not seem directly search-related but if you’re building the “ultimate personal assistant”, then merging products like Google Now and Google Inbox would be a good place to start.

The rise of data-driven search

There is a common theme running through all of the above technologies and trends, namely data:

  • We are increasingly requesting from Search Engines snippets of data, rather than links to strictly formatted web content
  • We are increasingly being provided the option for direct action without going to an app/website/whatever by providing a snippet of data with our response/request

I think in the next 2 years small payloads of data will be the new currency of Google. Web search won’t go away anytime soon, but large parts of it will be subsumed into the data driven paradigm. Projects like Knowledge Vault, which aims to dislodge the Freebase/Wikipedia (i.e. manually curated) powered Knowledge Graph by
pulling facts directly from the text of all pages on the web, will mean mining the web for parcels of data become feasible at scale. This will mean that Google knows where to look for specific bits of data and can extract and return this data directly to the user.

How all this might change the way users and search engines interact:

  1. The move towards compound queries will mean it becomes more natural for people to use Google to “interact” with data in an iterative process; Google won’t just send us to a set of data somewhere else but will help us sift through it all.
  2. Shared screens will mean that search results will need to be increasingly device agnostic. The next generation of technologies such as Apple Handover and Google Chromecast will mean we increasingly pass results between devices where they may take on a new layout.
  3. Cards will be one part of making that possible by ensuring that results can rendered in various formats. Users will become more and more accustomed to interacting with sets of cards.
  4. The focus on actions will mean that Google plugs directly into APIs such that they can connect users with third party backends and enable that right there in their interface.

What we should be doing

I don’t have a good answer to this—which is exactly why we need to talk about it more.

Firstly, what is obvious is that lots of the old facets of technical SEO are already breaking down. For example, as I mentioned above, things like keyword research and rankings don’t fit well with the conversational search model where compound queries are prevalent. This will only become more and more the case as we go further down the rabbit hole. We need to educate clients and work out what new metrics help us establish how Google perceive us.

Secondly, I can’t escape the feeling that APIs are not only going to increase further in importance, but also become more “mainstream”. Think how over the years ownership of company websites started in the technical departments and migrated to marketing teams—I think we could see a similar pattern with more core teams being involved in APIs. If Google wants to connect to APIs to retrieve data and help users do things, then more teams within a business are going to want to weigh in on what it can do.

APIs might seem out of the reach and unnecessary for many businesses (exactly as websites used to…), but structured markup and schema.org are like a “lite API”—enabling programmatic access to your data and even now to actions available via your website. This will provide a nice stepping stone where needed (and might even be sufficient).

Lastly, if this vision of things does play out, then much of our search behaviour could be imagined to be a sophisticated take on faceted navigation—we do an initial search and then sift through and refine the data we get back to drill down to the exact morsels we were looking for. I could envision “Query Revision” queries where the initial search happens within Google’s index (“science fiction books”) but subsequent searches happen in someone else’s, for example Amazon’s, “index” (‘show me just those with 5 stars and more than 10 reviews that were released in the last 5 years’).

If that is the case, then what I will be doing is ensuring that Distilled’s clients have a thorough and accurate “indexes” with plenty of supplementary information that users could find useful. A few years ago we started worrying about ensuring our clients’ websites have plenty of unique content, and this would see us worrying about ensuring they have a thorough “index” for their product/service. We should be doing that already, but suddenly it isn’t going to be just a conversion factor, but a ranking factor too (following the same trend as many other signals, in that regard)

Discussion

Please jump in the comments, or tweet me at @TomAnthonySEO, with your thoughts. I am sure many of the details for how I have envisioned this may not be perfectly accurate, but directionally I’m confident and I want to hear from others with their ideas.

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The 6-Step Process to Building Better Relationships With a Data-Driven Approach to Outreach

golden retriever puppy running alongside an English bulldog

Outreach is the art of connecting with bloggers or authors and building relationships through social media, email, or other online channels.

It’s a subject near and dear to my heart.

Earlier this year, I spoke about this topic at Authority Intensive, sharing the insights I learned while down in the trenches — building outreach teams from scratch, and seeing them lose opportunities to gain substantial visibility because of a lack of data-driven research and improper targeting.

Truly effective outreach is based upon deep research, relationship-building skills, and a fundamental understanding of SEO

To form the relationships you want, you need to customize each outreach campaign.

Unfortunately, outreach campaigns often fail when content marketers only perform surface-level research.

Here are six essential tips for conducting thorough outreach research that creates a foundation for ongoing, strong relationships.

1. Review outreach fundamentals

Data-driven research helps you identify relationships that are mutually beneficial.

There are several consistent, fundamental components of outreach execution:

  • Time
  • Data
  • Conversations
  • Relationship Maintenance
  • Value-Add

But one element is especially easy to neglect: Using data to hyper-target potential relationships.

When you perform outreach correctly, you form a mutually beneficial relationship.

2. Assess your value-add

The first question you should ask yourself when working on outreach is: “What’s your value-add?”

Notice the phrase “your value-add” rather than “their value-add.” This slight mental shift is an extremely important part of outreach.

You need to offer valuable information, including, but not limited to:

  • Original data and studies. Provide proprietary industry or consumer data, or studies in the form of stand-alone content.
  • Unique expertise. How can you help through Q&A sessions, live blogging, interviews, etc?
  • Exclusive resources. To appeal to a publisher or blogger, offer an information page that complements their research or interests.
  • Supplementary help. To initiate a relationship, present the assets you can contribute other than content.

3. Identify potential relationships

I heard somewhere that everybody on this planet is separated by only six other people. I find it extremely comforting that we’re so closely connected.

But building meaningful connections is not easy. You have to find the right six people to make the right connections.

Some teams fail because they search Google to find relevant publishers or bloggers — that’s basically busy work.

The best place to start is with the actual data from your website or your client’s website. Review:

  • Backlinks and mentions. Backlinks help you find authors or publishers who have covered you in the past. Mentions reveal discussions about your brand.
  • Competitors’ backlinks. Take advantage of tools like Majestic SEO to dig through their backlinks and mentions. Since you have similar audiences, use these sources to create a list of publishers or bloggers to contact.

Once you have a list of author and publisher websites, you should also mine:

  • Backlinks of the publishers’ websites. This will help you identify who shares their content.
  • Backlinks of those backlinks. This will help you identify their extended audience.
  • Authority metrics on the publications. Determine domain authority, citation trust, and citation flow scores of both small and large websites to help you decide who to work with.

The goal at this point is to make a large list that you can whittle down with the tools listed at the end of this post.

4. Learn about authors

Notice I wrote “authors” — not publishers, not the editorial staff. Authors.

Since you’re going to build relationships with authors, take time to understand them. Find out:

  • Who are they?
  • Where are they from?
  • Where did they go to school?
  • Where do they write?
  • What topics do they love to cover?
  • What are their interests outside of their industries?
  • Are they active on one particular network over another?
  • What are their temperaments?
  • What topics or brands do they love or hate?
  • How well does their content perform socially and organically?

In the screenshot below, I’ve pulled an example that shows basic data about an author who writes for The Next Web. You see URLs of posts he wrote for the specific publication, social metrics, and organic metrics, such as number of referring domains and backlinks.

Author Data Example

The data gives an overall view of whether or not the content performed well, or if specific topics resonated with the audience. Next, I usually check out comment engagement.

There are multiple tools that you can use to aggregate this information. BuzzSumo has quickly become my favorite tool because it allows you to view metrics and segment your search by types of content, specific authors, or URLs.

BuzzSumo Search

BuzzSumo also allows you to view metrics about other posts from that author, and SharedCount is a tool that quickly pulls social metrics. I use Majestic SEO to pull backlinks and referring domains.

BuzzSumo Authors

5. Make your cold market warm

Relationships always start out cold, but that doesn’t mean they can’t quickly become lukewarm with a little bit of effort.

You can find ways to genuinely connect with different authors, even if you don’t have any type of potential collaboration in mind.

Focus on building relationships that are both personal and professional:

  • Connect through social networks and blog post comments.
  • Share their content that you find interesting.
  • Talk about non-business topics.
  • Meet in real life at a conference or event — just make plans ahead of time so you are not relying on happenstance.

6. Drive success

Once you collaborate on a project with a particular author or publisher, your job isn’t done. Contribute to the success of the content.

Different techniques and strategies depend on individual situations, but here are a few examples.

Share across relevant networks

Find specific communities interested in the content produced from your collaboration. Do you know other authors who may want to share the content?

An author may find it useful to reference your research in an upcoming blog post or in a round-up post she shares with her audience or email list.

Paid social

You can boost a post on Facebook after you share the link. It’s inexpensive, and it helps get more eyeballs on the post, which can also result in more shares or organic links. 

Below is a screenshot of an example from one of my own previous local campaigns.

Facebook Boost Example

Discuss future collaborations

Suggest other ways you may be able to contribute content. When you provide unique value as an expert on a topic, you help the author with his or her editorial calendar.

What not to do

Relationships are delicate, so I’m going to arm you with several crucial tips to make sure you keep your relationships strong:

Don’t ask for multiple links

Some authors work for publications that have strict guidelines regarding links in content or author bios. Be respectful of that. Links should provide extra value and, of course, be relevant to the content.

Don’t cut off communication

Avoid a “said it and forget it” relationship. Remember what I said about building a personal and professional relationship. Treat it as such, and don’t neglect or end a relationship after a promise has been delivered.

Don’t offer multiple publishers the same article

This should be self-explanatory, especially if you promised exclusive content. Be careful not to break trust.

Don’t assume you know their audience

If there’s anything authors or publications hate, it’s having an outside party claim that their own content is perfect for a publication’s audience. If appropriate, reference other posts on their website that are similar to your proposed topic, but make sure you let them decide whether or not it’s the right fit.

Tool recommendations

I am a tool freak. I use a lot of them.

For the sake of not overwhelming you, I’ll share some of the key tools I use when putting together outreach research:

  • Majestic SEO — backlinks, backlink volume and metrics, mentions, and topical exploration.
  • NerdyData — a source code search engine that is limited without a paid subscription, but fun for sleuthing backlinks and mentions.
  • Open Site Explorer — backlink and mention exploration tools.
  • SharedCount — a free way to pull social metrics on bulk URLs.
  • BuzzSumo — social metrics for content and author sleuthing.
  • BuzzStream — an outlet for relationship building and PR.
  • Meshfire — tracks conversations and recommends who to follow and engage with to broaden your social relationships and opportunities.

[Editor's note: And don't forget, Scribe allows you to do in-depth keyword and social research right from the comfort of your WordPress dashboard.]

As a bonus, I’ve also put together an outreach research spreadsheet you can duplicate. 

It’s not an extensive tracking system, but it’s a great starting place that you can customize as you perform your own outreach research.

Over to you …

Have your current outreach techniques produced successes or failures?

How do you ensure that your relationships are mutually beneficial?

Let’s go over to Google+ and continue the discussion!

Editor’s note: If you found this post useful, we recommend that you also check out 5 Ways Listening to Community Data Can Expand Your Content Marketing Strategy by Shannon Byrne.

Flickr Creative Commons Image via Douglas Sprott.

About the Author: Selena’s (caffeine induced) data-driven research and diverse execution experience allows her to create custom organic search strategies to help clients reach their goals. You can find her speaking at conferences, training, advising businesses, or focusing on SEO strategy consulting, content strategy, and social activation for events with her company, Orthris. You can contact her through her personal website, or via @selenavidya on Twitter.

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APIs for Data-Driven Marketers

Posted by Dr. Pete

Data is everywhere, and companies are virtually climbing over each other to give it away. If you’re a data-driven content marketer, data is opportunity, but accessing that data can take some technical know-how. This is a guide to APIs, one of the key methods for accessing 3rd-party data, and also a mini-directory of some of the most useful APIs currently available to marketers.

What Is an API?

Let’s start with the official definition – API stands for “Application Programming Interface”. Sorry, I’m not the one who lets engineers name things. Put simply, an API is a way to let you talk to a 3rd-party application, usually either to retrieve data or update that application. We’re going to focus primarily on the first use (retrieving data), and it looks something like this:

Simple API Diagram (Send Request, Get Data)

The API itself isn’t really a box floating in space, so much as a chunk of code that acts as a gatekeeper. That code helps translate the third party’s data into something you can read, and it makes sure that only authorized users can access the data (a process called “authentication”).

Why Should I Care?

There are hundreds of applications on the market that collect useful data, and many of them are making that data available for free or very cheaply. You can use that data to do original research, create unique content or even build your own applications. If you’d rather stick to beet farming, well then that’s cool, too.

Where Do I Start?

Here’s the bad news – APIs are far from standardized, and you’re going to have to understand data structures and write some code. This is not a how-to manual so much as an overview of what’s out there that can help you decide if the world of APIs is right for you. There are some bright spots on the horizon – tools and sites that make programming APIs easier – and I’ll cover some of those at the end.

Following is a list of hand-selected APIs (I’ll do my best not to play favorites, and our competitors are on the list), broken down into a few industry categories, and alphabetical within each category. For each API, I’ll provide a main link, a documentation link (documentation can be way too hard to find), a brief description of what’s available in that API, and whether or not there’s a free version. APIs are split into five sections:

  1. APIs for SEO
  2. APIs for PPC
  3. APIs for Social
  4. Miscellaneous APIs
  5. API Support Tools

The last section covers sites and tools that can help you if you're new to APIs, new to programming, or just are hunting for something that's not on this list.


(1) APIs for SEO

This section contains APIs for organic SEO data, including keyword research and link profiling.

Bing Search (Docs)

The Bing search API allows you to integrate Bing search results and search data directly into your applications, including web search, images, news, videos, related search, and spelling suggestions.

Free Version?  YES, but rate-limited.


Majestic SEO (Docs)

The Majestic API includes a wide range of link metrics, including full back-link lists, discovery dates for links, anchor text, redirection information, and ACRank. Some features are limited to the paid version.

Free Version?  YES, but limited functionality.


Raven Tools (Docs)

The Raven Tools API lets customers access and update account and campaign information. It can also be used to access link data from your Raven campaigns.

Free Version?  NO, paid accounts only.


SEOmoz Mozscape (Docs)

SEOmoz's API has access to proprietary metrics, including MozRank, Domain Authority, and Page Authority, as well as link metrics such as linking root domains and anchor text data.

Free Version?  YES, but rate-limited.


WordStream Keyword Tool (Docs)

WordStream's Keyword Tool API lets you access WordStream's keyword volume metrics, along with related keywords and structured keyword suggestions.

Free Version?  YES, but rate-limited.


(2) APIs for PPC

The following APIs provide access to major ad platforms, including Google, Bing, and Facebook.

Bing Ads API (Docs)

While primarily a campaign management platform, the Bing Ads API does have access to useful data, including keword volume and keyword suggestions/opportunities.

Free Version?  YES, but authorization required.


Facebook Ads API (Docs)

The Facebook Ads API provides access to managing Facebook campaigns, as well as statistics about Facebook keyword searches and audience segments.

Free Version?  YES, but authorization required.


Google AdWords API (Docs)

Like Bing, the Google AdWords API is mainly for campaign management and building AdWords apps, but it also the only portal to Google keyword volume data. Getting authorized can be a long process.

Free Version?  YES, but authorization required.


SEMRush API (Docs)

The SEMRush API has a number of tools for both organic and paid search campaigns, but where it really shines is in competitive analysis, especially for paid search.

Free Version?  NO, starts at $ 15/month.


(3) APIs for Social

These APIs can access a wealth of information from major social networks and social aggregators.

Facebook Graph (Docs)

Facebook's "Graph" API is the primariy interface to building Facebook-based apps, updating Facebook accounts, and accessing Facebook social graph data. There are other, secondary Facebook APIs.

Free Version?  YES, but rate-limited.


FollowerWonk (Docs)

FollowerWonk's Social Authority API scores Twitter users on a 1-100 scale, for simple influence scoring and comparisons (Note: FollowerWonk is a part of SEOmoz).

Free Version?  YES, but rate-limited.


Gnip (Docs)

Gnip provides an enterprise-level API with "firehose" and filtered streams for Twitter, Facebook, Google+, YouTube, and more. Pricing is custom and is aimed at large-scale applications.

Free Version?  YES, but trial only.


Google+ (Docs)

The official Google+ API allows you to manage accounts, build apps, and access to data from user profiles, posts, and comments. It includes some limited search capability.

Free Version?  YES, but rate-limited.


Klout (Docs)

The Klout API provides access to Klout's aggregate social metrics, including Klout score, influencers, influence graphs, and topics of influence.

Free Version?  YES, but rate-limited.


PeerIndex (Docs)

PeerIndex is another social aggregator, and their API provides data on multiple influence metrics, including activity, authority, and audience scores.

Free Version?  YES, but rate-limited.


SharedCount (Docs)

The SharedCount API lets you access sharing stats on a number of platforms, including Facebook, Twitter, Google+, Reddit, LinkedIn, Digg, Delicious, StumbleUpon, and Pinterest.

Free Version?  YES, but rate-limited.


Topsy (Docs)

The Topsy Otter API is an alternative source for Twitter data, including a number of useful search functions – search by keyword, by links mentioned, by popluar stories on a domain, etc.

Free Version?  YES, but rate-limited.


Twitter (Docs)

The official Twitter RESTful API includes many tools for account management and data gathering, including individual tweet and user data, follower stats, and a variety of search options.

Free Version?  YES, but rate-limited.


(4) Miscellaneous APIs

Here are some other useful APIs, including Google products, analytics, and text processing.

AlchemyAPI (Docs)

AlchemyAPI provides a Natural Language Processing engine to perform tasks such as sentiment analysis, named entity extraction, author extraction, and topic categorization.

Free Version?  YES, but rate-limited.


Google Analytics API (Docs)

The Google Analytics API is a full-featured system to manage GA accounts and profiles, customize tracking codes, and to access and export analytics data.

Free Version?  YES, but authorization required.


Google Places API (Docs)

The Google Places API allows you to access the entire family of Google local data, including Google Maps, Google+ Local, and Google Places search.

Free Version?  YES, but authorization required.


PageSpeed Insights (Docs)

PageSpeed Insights is a Google Developer tool for website performance analysis. The PageSpeed API allows access to PageSpeed scores and recommendations.

Free Version?  YES, but authorization required.


Repustate (Docs)

The Repustate API provides access to a number of advanced algorithms, including sentiment analysis, social media monitioring, and predictive analytics.

Free Version?  YES, but rate-limited.


(5) API Support Tools

If you're new to APIs, this section can help get you started or find APIs outside the scope of this post.

CodeAcademy API Track

CodeAcademy is a resource for learning programming concepts and languages. The API track has specific online courses designed to help you learn API coding.

Free Version?  YES.


Mashape (Docs)

Mashape is an API marketplace that allows you to access over 2,000 APIs from a single account. Mashape also lets you distribute and monetize your own APIs.

Free Version?  YES, depending on the API.


ProgrammableWeb

ProgrammableWeb is a directory of over 9,000 APIs on a wide variety of topics. ProgrammableWeb has its own API, that allows you to access their search database.

Free Version?  YES.


SEER Interactive SEO Toolbox (Docs)

SEER's all-in-one interactive toolbox lets you access multple APIs via Excel, including Google Analytics, SEOmoz, Majestic, Raven, Twitter, and Klout.

Free Version?  YES, but rate-limited.


SEOGadget Excel API Extensions (Docs)

The SEOGadget API extension for Excel allows you to easily call link data from Excel spreadsheets, including SEOmoz, Majestic, and additional SEOGadget data.

Free Version?  YES, but rate-limited.


What Are Your Favorites?

While I don't intend this to be an exhaustive list of APIs, I'll try to keep the post up to date with the most useful APIs for marketers (assuming that people are interested). So, feel free to share your favorite data-collection APIs in the comments.

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How to Cultivate a Data-Driven Marketing Team

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Data: You can’t live with it, and you can’t live without it. At least, that’s how a lot of marketers feel. In fact, the affair between marketers and their data is often somewhat of a love-hate relationship.

Data can help you be a much more successful, analytical marketer who makes decisions based on facts rather than hunches. But wrangling together all that data — and then properly analyzing it? It can give you quite a headache, and frankly, it can get pretty overwhelming at times.

But if you’re fearful of data, you’re not alone. According to a study reported by eMarketer and conducted by 33Across, 91% of survey respondents are concerned about driving ROI from “big data,” 73% are concerned about integrating cross-channel data, and 70% are concerned about making sense of all the data coming at them. That’s a whole lot of concern right there.

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But even though data can come with its challenges, successful marketers understand that it’s a necessary evil, and most even learn to love data because it makes them better marketers. When I first started working at HubSpot 4 years ago, I’ll admit I wasn’t the most analytically-minded person. But boy, has that changed. So be empowered, marketers! Learning how to be truly data-driven can be extremely rewarding, helping you be more effective and achieve much better marketing results. And in this post, we’ll give you 11 tips to help you cultivate an entire team’s worth of data-driven marketers. That’s some powerful stuff!

1) Put the Right Analytics in Place

It’s no wonder data can be such a headache — you need to have the right tools in place to collect it! And for many marketers, their analytics live in silos, making it difficult to compare data and metrics across channels. For example, you might have analytics for your email marketing over here; social media marketing analytics over there, there … and there; and blog analytics hanging out in an entirely different place. Furthermore, if you don’t have this data connected to your customer relationship management (CRM) system, you’re also missing out on some extremely valuable closed-loop analytics that can truly report on the ROI of each individual marketing channel — and your marketing strategy as a whole. You can imagine how all of this disconnected and incomplete data can make things awfully difficult to handle.

So if you’re not happy with your current marketing analytics solution and its ability to integrate all your marketing data, searching for a new solution is a great place to start. To guide you through the process of selecting the perfect marketing analytics solution for your needs, check out our blog post on the subject, which highlights important questions you should ask potential analytics providers (including HubSpot!) before making a purchase.

 

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2) Assign Specific Metrics to Individual Marketers

Now that you have a reliable, integrated, and all-encompassing analytics tool in place, use it to its fullest potential. Measure everything you can possibly measure. Believe us, as a data-driven marketing team, we know there really is no shortage of metrics you can track — just check out this introductory marketing analytics ebook for some great ideas to get you started.

The best way to divvy up the measurement work is to hold individual members (or teams, if your marketing department is on the larger side) accountable for specific metrics. Identify the most important metrics you’ll use to measure the success of each particular marketing channel (our ebook actually does the work for you), and prioritize them by importance. Then assign the tracking and managing of these metrics to individual team members. For example, you might assign your social media manager/team with the task of monitoring high-priority metrics such as customers, leads, and visits generated from social media overall; as well as those same metrics segmented by individual social network; and even more granular metrics like engagement per social network (think “likes,” comments, shares, etc.). Not only will this ensure you have all your important metrics covered, but it will also hold your teams accountable for regularly keeping track of and reporting them.

3) Establish Benchmarks

What are your company’s typical email clickthrough rates? How many “Likes” do you generally get on an individual Facebook post? What is your average landing page conversion rate? Setting benchmarks helps you not only understand what your business’ marketing “norms” are, but it also gives you a standard that you can work toward meeting — and exceeding — incrementally. That being said, setting benchmarks is easier said than done. How are you supposed to know what “good” is to begin with?

There are a couple of ways to approach this. First, you could do some research to see if there are any established industry marketing benchmarks out there to compare yourself to. This can give you a general sense of how others in the industry are faring, and how you stack up in comparison. More likely, however, you’ll probably want to establish benchmarks that are specific to your own business and industry. This is where your analytics come into play. Once you’ve had some time (say, a few months) for your analytics to marinate, you can start to notice and record general patterns in the performance of your individual marketing metrics. Use those as your initial benchmarks, and make it a priority to improve those benchmarks over time.

4) Set Metrics-Driven Goals

Now that you’ve some set benchmarks for your business’ marketing, you can establish metrics-driven goals. Each marketer (or team) in your marketing department should not only be responsible for tracking and reporting on their key metrics, but they should also be assigned specific goals to achieve. How else will you know if your marketing is successful if you don’t know what “success” is? In other words, setting goals helps you define success for your marketing.

The goals you set for your marketers will depend on a number of factors, but should mainly be based on the overarching goals of your business. This will likely involve meeting with your company’s management team to determine your business’ growth projections so you can understand how Marketing fits into this bigger picture. For example, if your company is looking to grow by 5% in revenue in the following quarter, you’ll need to figure out how many leads you’ll need to generate in order to close 5% more customers or revenue. Based on this overall goal, you can then start to assign individual team goals based on those marketing channels’ benchmarks. In other words, if you know that your email marketing typically contributes 20% of your business’ overall new leads and your blog contributes 10%, you’d logically assign a larger overall leads goal for your email marketing team than you would your blogging team.

To help you with your goal-setting, download our free calculator for determining your monthly traffic and leads goals.

5) Report on Progress Toward Goals Regularly

Don’t just set and forget your goals. Make it a priority for individual marketers to base their strategies and tactics on the monthly goals they’re required to meet by reporting on their progress regularly. Do you hold weekly and monthly marketing meetings? At HubSpot, we report on the progress of our most important marketing metrics (such as traffic, leads, and the status of our marketing SLA) at our weekly team meetings. And tracking traffic and leads is easy to do in HubSpot’s software, where all you have to do is input your lead generation goal to easily track the number of leads you generate each day, week, month, or year.

 

Dashboard goals resized 600

 

We also have longer monthly meetings during which each individual team reports on their month over month progress and more niche metrics like email unsubscribe rate, social media reach, or blog subscriber growth.

In addition to reporting on these metrics within your marketing team, share a monthly marketing report that highlights the results of individual teams — and the marketing department as a whole — with the rest of your company. Not only will this keep your team more accountable for being data-driven (you want those metrics to look good, right?), but it will also prove to the rest of the company that Marketing does way more than the stereotypical party planning and arts and crafts all day.

6) Back up Marketing Decisions With Data

This may seem like a no-brainer, but if you refer back to the chart at the beginning of this post, it’s a little less surprising. You’re collecting all this marketing data, sure, but you need to actually do something with it. In other words, to really be a data-driven marketer, you can’t just collect and report on the data. You need to actually use that data to drive your marketing decisions. This requires you to hone your analytical skills. It requires some critical thinking and problem solving.

For example, let’s say you’ve been doing social media marketing for several months because that’s what you’ve thought you needed to do. But now that you’re actually tracking the success of your social media marketing with your marketing analytics tool, you realize that there are certain social media channels that just aren’t performing for you. Maybe you’ve been spending equal amounts of time on Facebook and Pinterest, yet your analytics are telling you that Facebook has 5X the ROI of Pinterest. Wouldn’t it make sense for you to reallocate some — or all — of the time you’re investing in Pinterest to Facebook? By using data to back up your marketing decisions, you’ll not only make smarter decisions, but you’ll also improve your marketing results!

Learn how to think more analytically by checking out this post about nine terrific ways to make your marketing analytics actionable.

7) Find Ways to Measure “Unmeasurable” Things

Truly data-driven marketers find ways to measure seemingly “unmeasurable” things. For example, one of the teams in HubSpot’s marketing department is the Brand & Buzz team, which is responsible for HubSpot’s branding. And you can imagine how measuring something like branding isn’t really as cut and dry as measuring something like leads generated from social media, or the clickthrough rate of email marketing, right? But that doesn’t mean our Brand and Buzz team is exempt from being analytical. So they measure things such as direct traffic to the HubSpot website and branded search term volume.

Furthermore, one of the challenges our Product Marketing team has is making sure people realize that HubSpot sells software. In other words, they need to figure out people’s perception of what HubSpot. Not exactly an easy feat. As you can imagine, measuring their progress toward achieving this goal isn’t something you can just take a look at a dashboard to gauge. So they administer brief, multiple choice surveys of our audience placed on various thank-you pages for our non-software related marketing offers such as educational ebooks and webinars. This survey simply asks respondents to select what HubSpot does. Their goal is to increase the number of people who select “software” vs. other things like “services” or “marketing content.”

8) Reward Record-Setting Achievements

One of the best ways to get your marketing team on board with a data-driven culture is to incentivize them. Consider giving out a monthly award for the member of your marketing team that achieves the most impressive record-crushing results based on their specific metrics-driven goals. On HubSpot’s marketing team, for example, we identify a marketing “champion” every month, who gets to attend a Champions Dinner hosted by one of HubSpot’s executives and attended by other “champions” from other departments.

And don’t stop at just incentivizing those record-setting achievements with tangible rewards. Recognize them publicly in front of the entire company, too. Sometimes the most rewarding incentive for your employees is public recognition of their hard work. You should also keep track of employees’ individual metrics-driven achievements and incorporate them into your annual review process.

9) Use Data in Content Creation

The benefits of data in marketing don’t have to be limited to your marketing analytics or making better marketing decisions. Data can also be used in a number of other ways in your marketing, such as improving your marketing content, including blog posts, ebooks, and other written collateral. In fact, incorporating a little data can go a long way, making your content much more high-quality, credible, authoritative, and interesting. Just be sure you’re selecting trustworthy data and properly attributing it to the original sources.

There are quite a few ways you can go about spicing up your marketing content with data. Some techniques include demonstrating change/consistency over time, providing benchmarks, showing connection/correlation, proving a point, emphasizing why readers should care, backing up opinions, showing discrepancies, including social proof, showing success, offering clarity, showing scale, highlighting original data, and portraying data visually. To learn more about how to use any of these above techniques, read our comprehensive post on using data in your marketing content.

 

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10) Leverage A/B Testing

The savviest data-driven marketers are always looking to get better data and to improve how the analytics look for the metrics they’re responsible for. And what’s one of the best ways to improve the looks of your data? Optimize your marketing with A/B testing, that’s what!

A/B testing enables you to experiment with how different variables affect things like traffic, clickthrough rates, and conversion rates, and allows you to optimize your marketing efforts using the variables that contribute to the best results. Luckily, there’s no shortage of variables you can test in your marketing, and you can also conduct A/B tests in practically every one of your marketing assets. Check out our complete ebook on A/B testing to get started.

11) Share Data-Driven Research With the Rest of Your Team/Business

If you’re doing all that A/B testing we recommended in our last tip, chances are you’re going to come away from those tests with a bunch of great takeaways about what works — and what doesn’t — for your particular business and its audience. Don’t hoard that data … share it!

At the very least, the rest of the members of your marketing team could probably really benefit from those lessons learned. It will make them better marketers, and it will also probably teach them a thing or two about how your prospects respond to different marketing tactics. Encourage members of your marketing team to present lessons learned from specific A/B test they’ve run during your weekly marketing meetings so everyone can benefit.

Chances are, the rest of your business — even departments outside of Marketing — might appreciate this insight into your marketing lessons, too. At HubSpot, we have a popular internal wiki, which the marketing team often uses to share the results and lessons from its A/B tests with the rest of the company. Marketing members also regularly present at meetings in other departments to share valuable marketing insights. Not only is sharing these results educational to them, but it also shows them that the marketing department doesn’t just sit on our butts and act on hunches. No sirree! Marketing regularly tests its tactics and acts on proven data to make its decisions. This is sure to boost the R-E-S-P-E-C-T of your marketing team, and it will probably even contribute to more marketing buy-in. And who doesn’t want that?

In what other ways can you cultivate a data-driven marketing team?

Image Credit: RecycledStarDust



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