Posted by randfish

Keyword research, when done right, is a fairly complex process. Uncovering new keywords and appraising their value should involve a robust toolkit, a multitude of different sources, and a great deal of thoughtfulness.

In today’s Whiteboard Friday, Rand shares a strategic and straightforward 4-step process (including a passel of tools to check out) for discovering and prioritizing the best keywords for your SEO campaigns.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re chatting about keyword research and a step-by-step process to choose and prioritize the best possible keywords that we can for your SEO campaigns.

So let’s get started with…

Step one: Use multiple sources to get keyword suggestions

The first thing that a lot of folks do is they only use a single source. They go to AdWords for example, or maybe they’ll go to Suggest. Or possibly they’ll start with SEMrush, which has an awesome corpus and database, but it’s sort of based on a single source. My strong suggestion is a lot of the sources have only one type of data in them and you want to combine them.

The five or six that I really like are, first off, AdWords is a great source. They’re, generally speaking, commercially focused terms. AdWords knows that people want to buy those keywords for pay-per-click search, and so they try and include commercial terms that people are actually going to convert on. They hide a lot of stuff that frankly Google feels like is not going to get people the conversions they’re looking for, because the problem is if you buy the wrong keywords, you don’t blame yourself for poor keyword targeting, you blame Google for sending you bad traffic. So AdWords has hidden some of those things. They’ll show them to you if you type them directly in, but not otherwise.

Suggest, you can go to Google Suggest and in fact, Google related searches — which are at the bottom of the search versus the top in the bar as you type — those both give variance and/or searches that people who search for this also performed.

Then you’ll see there are a lot of tools out there. SEMrush is by far the most popular one — and, in my opinion, a really, really good one, too — for a keyword to rankings graph. Essentially what this is saying is, “Here are keywords that the pages that rank for the keyword you gave us also rank for,” or same thing at the domain level. It’s creating and mapping those things so that you can get broader terms than you ordinarily would have with just these other methods. That’s pretty cool.

Another one that’s very, very cool and very sophisticated, that some SEOs are doing, is topic modeling-based keywords. This is essentially saying, “Hey, show me terms and phrases that co-occur on lots of documents, high quality documents hopefully, with the term or phrase that I’m targeting.” You can find those through tools like AlchemyAPI. It’s a little challenging to use, but there you go.

Bunch of tools, SEMrush and AdWords. You can use Google Search for a bunch of these. Ubersuggest to get some of those suggestions. KeywordTool.io actually has a number of these inside it. SpyFu is similar to SEMrush. AlchemyAPI helps you with topic modeling.

Then — somewhat self-promotionally, and I apologize for that — but Keyword Explorer, which Moz just launched this week and which we’re pretty excited about. I was actually the product architect for that. So I’m feeling quite excited and very proud of my team. Keyword Explorer, shamelessly, has all of these in there. I think our topic modeling is actually a little better than AlchemyAPI’s. I think our keyword to rankings graph is almost as good, maybe in some cases better, maybe in some cases not as good as what SEMrush has. We also get suggestion-related, real time, and then we obviously have a big corpus that we’ve got from AdWords too.

Step two: Select keywords that match multiple types of search intent

I’ve done my keyword suggestions. I’ve got all of these. Now, I need to pick which keywords from these suggestion lists am I actually going to try targeting. To do that, it’s not really a tool-based thing, although you certainly could use something like a Google Doc or Excel, or a Google Spreadsheet, or you could do it right inside some of these tools. KeywordTool.io and Keyword Explorer both have like an “Add this to my list” type of feature. AdWords does too.

But what I want to do is match multiple types of search or intent based on your content and keyword goals. So this has little to do with what the keywords actually say and more to do with, “What am I trying to accomplish with my SEO and with my content?”

For example, let’s say I’m an online coffee bean roaster and seller. Maybe I’m independent. I have a location, but I also want to sell my beans and my grounds and accessories online, which is awesome. There are some keywords that are going to match with my goal of direct conversion. People are likely looking for this because they want to buy it, and I want to be in front of them when they’re looking to buy it. Those are the keywords like “coffee beans online,” “buy coffee beans,” “coffee accessories,” “stovetop espresso machine,” getting more specific.

Then, I’m also looking at doing some strategic content to target folks early in the buying stage, like before they actually think, “Oh, I’m going to buy from them.” I just want them to have an association with us. I want anyone who’s interested in coffee — coffee aficionados, researchers, people who are passionate about the topic — to find me and have an association with my brand. In order to do that, I might target keywords like “flavors of coffee beans,” “best independent coffee roasters in the US,” “home barista resources.”

People aren’t going to convert on these keywords. “Best home coffee techniques.” I’m trying to learn. I’m trying to get help. I’m trying to get content, not necessarily buy directly.

Then I might in my content strategy have some idea that, “Hey, I also want to target coffee influencers.” People who are influential in this world. It could be journalists and bloggers, people who write for magazines, and folks who are very popular on Twitter or Facebook or have popular Instagram accounts. I want them to be aware of us.

So I might go after things like “barista competitions.” Barista competitions, if I have a big list of those, well, lots of baristas and folks who run coffee shops are going to be looking for that. I can influence them, get in their head, get them to know my brand. “Coffee shop awards,” same thing.

“Worldwide coffee bean wholesale cost comparison,” aha, this is going to the suppliers and the coffee bean buyers around the world and looking at price trends and tracking. That’s some of that data that a lot of those folks might have. Probably a small audience, but very influential people.

“How to open a new coffee shop,” aha, now I’m targeting coffee entrepreneurs who are also potential influencers for me.

These lists won’t apply to all of your efforts. Your efforts are going to be determined by your specific strategic goals, but you should make keyword lists and match those up to all the keywords you see here so that you know what types of things you’re trying to do with those keywords. I would encourage you, if you’re doing this, to make a different list for each one of those.

Step three: Collect keyword metrics and sort/filter/prioritize them based on goals

This is where we have to get very, very data-driven, because I want to do is I want to take all the keywords in each of the lists that I have and I want to get the metrics for them so I can prioritize properly. So what I’ve done here is I’ve taken a list of keywords. I have: my volume, how much are they searched for; difficulty, how hard will it be to rank in the organic results; click-through rate opportunity, meaning what other features are in the search results — images, news boxes, ads, videos up at the top, instant answers, knowledge graph on the right-hand side that’s going to draw clicks away from my potential to get searchers to click on my result.

I need click-through rate opportunity in my scoring. Otherwise, I might be biased to keywords that look great but in fact get very little click-through rate.

Importance, this is essentially my personal priority, and it’s something where it’s not a metric that comes from anywhere else. I use it internally. I know, for example, that “coffee beans online” is a very, very important keyword because it directly relates to what I’m selling. It’s the first thing I’m offering, so I’m going to put it at a 10 out of 10, versus maybe “how to open a coffee shop,” which looked at some content marketing that I might do in the future, but it’s not a high priority right now for me from an importance standpoint.

Then all of these metrics, so it’s like this metric combined with this metric combined with this metric should give me some form of potential. I want to come up with an algorithm. You could come up with your own, or you could use one of the tools. Tools like KeywordTool.io and Keyword Explorer have an algorithm that combines these types of scores to give you a consistent one for potential. The idea is I want high volume, low difficulty, strong click-through rate opportunity, and high importance. That should give me a good potential score. Then, hopefully what I can do is just sort by this potential metric, and now I get my prioritized list of keywords.

If you don’t take this data-driven approach, you can wind up just in a world of hurt where you’re targeting the wrong keywords and not being as intelligent as you could be. You can do this with something like AdWords and then an export to Excel or to Google Spreadsheets. You can do this with a tool like WordStream, who does a great job of it particularly for paid search, and you can leverage some of that for organic too. Like I said, KeywordTool.io. Obviously, Excel and Google Spreadsheets. Then Keyword Explorer does this right inside the tool as well.

Step four: Determine keyword targeting & new content creation needs & priorities.

Now what I want to do is I want to determine my keyword targeting and my new content creation needs and the priority of those processes.

So after I look at this, I might refactor a few things and say, “Wow, you know what. That is pretty strong. Even though I set it as a low importance, I’m kind of interested. I’m more interested in this ‘how to open a coffee shop’ than I was previously, based on the metrics that I saw there, the opportunity I think I’ve got.”

So here’s my prioritized list.

• (A) I’m going to start by optimizing my homepage for “coffee beans online.” I’ve decided that’s the best keyword that I can possibly target on there. That’s what I’m going after.
• (B) I want to create a new coffee accessories page. Maybe I didn’t have one before. I see that that’s a high opportunity and high potential keyword. I want it. I need to create a new page. Now, I also need to go get inventory relationships established with all my accessory providers so that I can actually ship folks that stuff.
• (C) I’ve decided that I really like that “how to open a coffee shop,” and I want to create a guide. That’s going to be one of my key content marketing pieces and, therefore, I’m going to go interview 10 successful coffee entrepreneurs, folks who’ve opened some successful shops. Then I’m going to assemble some content, build a survey, target 500 coffee shops in the U.S. — maybe that I already have relationships with or that I don’t — so that I can get a survey of data back. I’ll outreach to each one individually, or I’ll have my SEO content person do that. Now, I’m going to create that guide based on the feedback that I get from there. Now, it’s data-driven, and I have a bunch of people who are likely to help support it because they’ve contributed to it.
• (D) Finally, I might say, “Hey, I really like that ‘best independent coffee roaster.’ That keyword looks real strong to me. I want to target that one too.” That’s also going to go into my content marketing efforts, so I’m going to establish some criteria for that one. I’m going to do some research, and I’m going to send out awards to the winners after we pick those through whatever process we decide.

This is a phenomenal way to go through keyword research and keyword targeting to get the content and the optimization priorities that you need for SEO. I think if you choose the right data and the right tools, you use multiple sources, you intelligently build the right kinds of lists, you use metrics to prioritize, are data-driven rather than just pure intuition, and you prioritize your work based on this, you can have phenomenal success.

All right, everyone, look forward to your feedback and comments. Certainly, if you haven’t given Keyword Explorer a spin yet, I’d encourage you to do so. I think it’s pretty cool, but obviously, there are lots of good competitors out there too, and you can check them out as well.

Hope to see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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Posted by purna_v

[Estimated read time: 13 minutes]

Disappointingly, this isn’t one of those doom-and-gloom articles proclaiming that SEO/PPC is dead. Instead, we’ll look at how voice search will shake things up for us digital marketers and examine all the wonderful things that can come from it.

But first, here’s a question for you.

If you wanted to find out who Microsoft’s current CEO is, what would you search for if….

a) You were on your computer and typed in your search phrase?

OR

b) You were talking into your phone using a digital personal assistant such as Siri or Cortana?

If you’re like the vast majority of folks today, your answer would be a shorter phrase like “Microsoft CEO” for the former. For the latter question, you’d have been far more likely to have used natural language such as “Who is the CEO of Microsoft?”

Without even being conscious of the fact, you’ve altered your search behavior for voice vs. text.

We all do it.

Search is finally growing up. Take the latest announcements from Microsoft (my employer) at their recent Build event. Microsoft CEO Satya Nadella talked about a world where “human language is the UI layer” and developers build for “conversational canvases,” a new term applied to any app where people are conversing, from email to chat to SMS.

Slack, too, has written about “conversational offices” where computer systems — such as expense reporting software — are made more convenient and user-friendly via an interface we can talk to.

All those times you’ve wished for a better way to understand intent and personalize more effectively? Natural language could be the key.

Voice-activated technology is going to switch things up for us marketers, in many beneficial ways. That’s what I’m going to cover here. Specifically, I want to dig into voice search.

What do I mean by voice search?

When I say “voice search” I’m referring to your smartphone or desktop computer that has a digital personal assistant or an entry point that uses voice, like Google’s microphone or Amazon’s Echo.

In most cases, if you’re using a personal assistant and activating with your voice, you’re doing some kind of voice search. And that is the element of voice command I’ll be referring to.

I’ll cover the three big questions:

• Who’s actually using voice search?
• How is it different from text input?
• What can you do to prepare for these differences?

Who’s using voice search?

Most of us reading this article are likely to be regular users of digital personal assistants.

In one of the very few studies published on the topic, Thrive Analytics showed a compelling number of people using digital personal assistants:

We’d expect the high volume of 18 to 43 year olds, since statistically they fall into the early adopters bucket. But to me, the higher usage numbers for 44+ age ranges were pretty surprising. Perhaps it could have something to do with usability? Tiny screens and even tinier buttons can be difficult to navigate — voice search is easier.

The Thrive Analytics study was from late 2014 and, given the speed at which this technology is advancing, the adoption numbers have grown dramatically.

It appears we’re all feeling less silly talking into our phones and are rushing to embrace the convenience of these digital personal assistants. According to a survey conducted in October 2015 by MindMeld, most folks only just started using voice search and voice commands within the 6 months prior to when the survey was conducted.

Recently at SMX West, Google’s Director of Conversational Search Behshad Behzadi presented a keynote on how Google is approaching voice search. Behzadi shared that Google has seen the ratio of voice search growing much faster than text search.

He attributed that in part to the fact that people are increasingly comfortable using speech commands, and also because of the quality of results.

Today, Google’s speech recognition error rate is only 8%, down from ~25% just two short years ago. As a result, they’ve seen people use more natural sentences instead of query language, such as “What’s the weather like in Paris?” vs. “weather Paris.”

What are we using voice search for?

This is the big question — what are we using it for? This graph shows the general use of voice search, from a Northstar Mobile Voice study. Why do you think so many people are asking for directions? Are we all lost?

Maybe we need an assistant to help us out in life.

Which brings us to Google’s prediction for the future of search. In his talk, Behzadi said they believed the future of search was “an ultimate mobile assistant that helps you with your daily life so you can focus on the things that matter.”

Interesting and quite possibly true.

It just so happens that at Microsoft we have one of these — with Windows 10 launching this past summer with Cortana. Thus, I bring you amazing (IMHO) data on what people are using Cortana for.

As a slightly humorous aside: Cortana’s top search is “Who is Bill Gates?” I think it’s because people are expecting a jokey answer.

Early news articles about Cortana really enjoyed the fact that she answered the question, “Who’s your daddy?” with a witty response about Bill Gates. We like funny and witty, don’t we? So we ask the question “Who is Bill Gates?” expecting her to say “He’s my daddy.”

But that’s not how Cortana plays the game! She means business. Here’s how she answers the question:

How voice search is growing

One-third of all Cortana queries come from voice.

We cannot measure which queries coming into a search engine are coming from text input and which are coming from voice input. But we can measure what queries via Cortana are happening from text and which from voice — because Cortana is part of the Windows 10 operating system.

This data was pulled in November, just three months after Windows 10 launched, and already 33% of queries are coming from voice. This is incredible!

I’m very interested in getting another look at this data in a few months, when we’re one year out from the launch of Cortana on the desktop, making voice search super accessible around the world.

Where it impacts us digital advertisers is how this relates to searches.

We all know that voice searches have results in SERPs. Interestingly, a voice search query can sometimes indirectly lead to a SERP with ads being served as well.

Are your ads showing up as a result of a voice search query? This is the reason we need to pay attention.

How voice search differs from text and what you can do about it

Okay, we’ve seen that voice is here to stay and it keeps growing, so let’s explore the five most important ways voice and text search differ.

1. Query length

The first thing we think about is query length, right? They must be different. We pulled data for query length for Cortana searches and compared that with query length for general text searches.

Not surprisingly, query length for text searches is pretty short, about 2 words. We’re using computer language – it’s not a sentence, it’s the most direct route to express our intent.

Then we looked at query length for voice search.

What you can see is that the successful voice searches, the ones that get the most volume, impressions and clicks, are the ones with 3 words in the keyword or query.

This was a little unexpected.

I thought the query length for voice searches would be significantly longer than for text-based searches. But again, we’ve just started learning how to use voice search. We ran these tests 10 months ago, and I expect a follow-up would show longer query length for speech.

The younger generation — like my son — are more comfortable using natural language. Here’s a great example the brilliant Tom Anthony shared at SMX Munich this March of voice searches his daughter had done:

Notice the degree of self-selection and specificity. We’re all going to be trained to search like this one day.

Take action:

Most likely you’re already targeting 1–2 word keywords, such as

• Bahamas
• Bahamas air fare
• Bahamas vacation
• Bahamas vacation packages
• Bahamas travel

Pro Tip: Test out adding longer, more voice-friendly keywords such as:

• Cost for air fare to Bahamas
• Bahamas vacation info
• Best Bahamas vacation package
• Cheapest Bahamas travel
• Bahamas travel guide

While broad or phrase match targeting may help account for these longer keywords, it’s not necessarily conversational and thus may not cover the ways people search with voice.

2. Question words

Voice search differs from text search in the usage of question phrases.

When you type a search, you use computer language — “Bahamas vacation deals,” for example. When you speak a search, you use your own language, such as “Who has the best deals on Bahamas vacation packages?”

Just like in our “Microsoft CEO” vs. “Who is the CEO of Microsoft?” example.

We’ve seen a growth in question phrases year over year:

Take action:

Try adding some relevant question keyword phrases to your keyword list as a test.

For example, for a company that sold vacations in the Bahamas, some relevant ones could be:

• What is the cost for air fare to Bahamas?
• How much does it cost to fly to the Bahamas?
• Where can I find Bahamas vacation info?
• What’s the best Bahamas vacation package?
• When is the best time to travel to the Bahamas?

You could also consider negating out irrelevant question phrases, such as:

• Who lives in the Bahamas?
• What time is it in the Bahamas?

3. Stronger intent

This might be the most important difference of them all, since natural language shows intent more strongly.

If I were to do a search for “digital camera,” you’d have no idea whether I wanted to buy one, have one repaired, or was simply looking for stock images of cameras.

While we digital marketers think we can draw some conclusions based on these words, we actually have no idea if this searcher wants to buy or is doing research.

Here’s where the natural language usage within conversational search changes everything.

The type of question asked can reveal the degree of intent:

This has real consequences on bids and creative. I can bid higher for question phrases with the highest likelihood of action, e.g. “Where’s my nearest Microsoft store?” vs. “What does the Microsoft store sell?”

Finally, getting detailed insights into intent can prove extremely effective from both an ROAS as well as conversion rate standpoint.

Take action:

• Identify your highest value question phrases
• Optimize for these keywords and also adjust bids up for these terms

You could also consider tailoring the ad copy and landing page more specifically towards the highest-value questions asked.

I’d also recommend including filler words in your questions:

The more matches you have, the more likely your ad will show on a voice search that includes words like “a” and “me” and “for.”

4. Impact on local

Mobile voice search is three times more likely to be local-based than text search. This is closely related to the fact that most smartphone searches are also local.

What does this mean for local businesses?

It means you need to sharpen your approach, because voice search is rapidly becoming the way your customers will find you.

Take action:

If you have a local physical presence, it’s even more critical that you refine your strategy because you have a lot more to gain by getting this right.

Get smart with keywords relevant to your local searcher:

• Are there landmarks you need to call out, such as “in old city” or the stadiums or anything else significant that will be a cue for your searcher?
• What are the local places of interest that matter to your company?
• How do folks describe your neighborhood in natural speak?

5. More quick answers and quick action

Voice search will continue to trigger more quick answers in the SERPs. This is because of those question words we saw earlier — those question words are closely related to local searches. For example, “Where is the best Thai food near me?” and “Where can I rent a car today?”

These are distinctly local searches and they trigger ads in the SERP that allow the user to act without going to a web page.

You can see reviews, a phone call button, and a “book now” button. Users don’t have to come to your website to complete their intention.

This will have a strong impact on crowd-sourced sites, such as Yelp and TripAdvisor, where it’s your company’s responsibility to update hours and phone info, as well as to monitor and respond appropriately to customer reviews.

Take action

Make it a priority to keep your local listing, your business listing, and your crowd-sourced sites updated and active. These sites have a great deal of power when the search doesn’t leave the SERP.

For example, is your address correct? What about your hours and your phone number? Are there customer reviews you need to manage?

It’s worth the time to keep these all spiffy and up-to-date.

Let’s recap the five core differences:

TL; DR? Here are the five core ways conversational and text search differ.

1. Voice has longer queries
2. Natural language means more question phrases
3. Natural language reveals intent clearly
4. Voice search has high local value;
5. And greatly impacts 3rd-party listings

What’s next?

Looking into the future, one thing is certain. We. Will. Adapt. Voice search will be adopted.

We’ve proven time and again that we can be trained — think about the first time you learned to swipe using an iPhone. Or the way we learned to take selfies… I resisted for as long as I could before joining the dark side.

Another development that will have an impact on voice search will be the Internet of Things. Between wearables and common household objects, we’ll be communicating more with them using voice commands.

One of the most critical expectations we’ll develop from this specific use of technology is the expectation that it will anticipate our needs. This is called predictive response.

Let’s think about that in action.

Your phone can capture and communicate signals about you. Let’s say I’m walking around Seattle and I decide I’m feeling a little hungry. I’ll ask Cortana or Google Now, and she will know that it’s breakfast time and that I’m on foot. She’ll also know that it’s a little cold and rainy.

If I asked her for the nearest cafe, she’d respond with an answer that factors all that in. She’d even cross-reference this with my love for cappuccinos to find me the nearest coffee shop that sells cappuccinos with plenty of indoor seating so I can be warm and dry.

Better still, with the new chatbot technology, my digital personal assistant could even suggest I might like to book a table and communicate with the table booking bot to have my table booked.

We’re happy to give up more personal information to these personal assistants because of the convenience they provide. This additional data could be helpful when it comes to targeting and personalizing ads in the future.

It’s also inevitable that there will be a rush to monetize.

Between the tech giants like Google, Microsoft, Facebook, or others, someone is going to figure this out. Already we can see articles talking about Google working on conversational shopping in the SERPs.

We’re poised to see this industry take a seismic shift. It’s exciting and exhilarating most of all because we can be a part of the change.

We’re not being handed brand new technology (think iPhone when it first came out), but more so that we have a hand in what is seen as normal, what we can accept and expect, how we as advertisers can be even more effective with intent and personalization and targeting. We can shape this together.

Why not use your voice? Share your thoughts in the comments below.

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Posted by gmehrguth[Estimated read time: 5 minutes] Every small business owner needs tools to get their marketing campaigns off the ground. Frankly, too many of these tools are only for enterprise-level businesses or require a budget that doesn’t alwa… Continue reading →

Posted by evolvingSEO

[Estimated read time: 24 minutes]

Marketers: Add podcast promotion to your skill set

Sure. This post is for podcasters.

Hi Podcasters. You may find the below interesting, perhaps educational — and I hope you leave your insights for the Moz Community in the comments below (I’ll be reading and replying to all of them).

But even if you never plan on having your own podcast, this post is for you, too! I see the marketing of podcasts will being an important addition to any marketer’s skill set in 2016 and beyond.

So below, we’ll examine iTunes ranking factors, lay out promotional strategies I’ve used to grow listeners in my first 6 weeks of podcasting, and I’ll transparently reveal all of my podcast’s metrics.

Before I show you this, though, let’s look at exactly how much podcasts are growing.

The “Serial” effect.

To grasp the magnitude, we zoom out and look at the trends.

Since Edison Research began tracking statistics in 2008, podcasting saw the largest YoY growth of monthly listeners in early 2016. Listeners jumped from 17% to 21%.

That’s now 21% of the US population, compared to only 9% in 2008. Estimates expect that percentage to grow even more.

Yes, you are witnessing the Serial Effect: accelerated growth of a medium led by mass popularity of the best produced product in podcasting to date.

Ways to consume podcasts are growing, too

Not surprisingly, app developers have jumped on board — and the paths to discovery are growing.

As a podcaster or marketer, you should want to look at this from a search perspective. iTunes (partially a search engine) is likely the top discovery channels for podcasts. Many other players like Sticher, Player.fm, and even Google (just announced) have a core search functionality for discovery.

And Google just announced they’ll show podcasts in search results in the Android Google App.

How long before this carries into all of Google search?

How’s the data available to podcasters?

Meager at best.

Apple doesn’t disclose search volume. There’s conflating ideas of what a “download” actually means. There’s no engagement metrics (i.e.: you can’t tell how long people actually listen to an episode).

Because of that (and my lack of extreme nerd-ness, I only have moderate nerd-ness) this post has NO fancy charts or big-data graphs. But my hope is to relate my experience with podcasting SEO thus far, to bring value to the marketing community at large.

Keep in mind: this post is from the perspective of a two-person podcasting team, running it as a side project at Evolving SEO, with a combined total of only about 12 hours per week.

Buckle up.

---

I. iTunes rankings

What are the “paths” to discovering podcasts in iTunes?

It’s first important to understand the different nuances and places of “ranking” within iTunes.

In other words — these are the places you can show up in iTunes.

Curated lists vs. searching

The biggest distinction I have learned — and you need to know — is lists versus search rankings. “Ranking” factors for each may be quite different.

• List Rankings are NOT attached to a search keyword, because no search happens. Found via clicks and navigating through the site.
• Search Rankings are impacted by keywords, because the user types a search into the search bar. Found via performing a search.

The podcast “home page” lists

This is the “holy grail” of what Podcasters talk about when trying to break into “new and noteworthy.” Supposedly if you get listed here, your downloads skyrocket, you make tons of cash, and you sit on a beach in the Bahamas.

Category lists

This includes:

• New & Noteworthy for the Category
• What’s Hot for the Category
• All Podcasts for the Category

Though not the “home page,” it’s still generally quite advantageous to rank here. Lists function by clicking into the category list — not by running a search:

Subcategory lists

The UX in iTunes (desktop) is weird here, because you can’t drill down from a category into subcategories. You have to find a show in the subcategory, and use the breadcrumbs to back out of it into the subcategory page:

Now we’re in the Business > Careers subcategory:

As you can see, it still has “New and Noteworthy” and “What’s Hot.” I should note, in the Podcast App, it’s much easier to drill into subcategories.

Related podcasts

iTunes will show “related” podcasts in three ways:

• More by Channel
  • If you publish more than one show.
  • Publish multiple shows to show up here.
• Top Podcasts in Category
  • Basically this looks like the Top 200 category list.
  • So you need to break into the Top 200 list for your category to show up here.
• Listeners Also Subscribed to
  • This seems to be the only “related” functionality based upon user behavior (like Amazon’s “people also bought”).
  • You need to get more subscribers in iTunes to show up here.

Podcast search results

This is the true “search engine” area of iTunes. These seem to operate quite differently than lists.

Here is the “first page” result for “marketing”:

The main point to takeaway here is that there are a variety of discovery paths within the iTunes store, and you should be aware and optimize for all of them.

What are possible iTunes podcast ranking factors?

Below, I’m going to list a large variety of possible ranking factors and some anecdotal, instinctual thoughts of my own — as well as references to other opinions.

Again, this is one view and set of hypotheses for how rankings might work within iTunes. I welcome opposing thoughts or discussion.

Number of new subscribers in last week

In the middle of writing this post I stumbled upon episode 421 of Podcast Answer Man. Admittedly, it threw me a HUGE curveball. Rob Walch claims to know the exact algorithm for iTunes List rankings. Yeah, I’m not kidding.

Rob says:

“The top 200 list is number of new subscribers in the last seven days with a weighted average of 24, 48, and 72 hours.

The actual algorithm is: (Day1x4 + D2x3 + D3x2 + D4 + D5 + D6 + D7) / 13″

You can go listen to the excerpt of that episode and Cliff’s follow-up explanation for how this algo works.

Again, this is the top 200 for each category (Business, Arts, Education etc). I do NOT think this is for ranking in searches.

• List or Search Rankings: This likely affects list rankings, not search.
• Likely Factor: I think likely, but would just like to see some example data to back it up.
• Influenceable: Indirectly; there’s a lot of things you can do to promote getting subscriptions.
• Data Available: Supposedly yes, in Feedburner, but I’m just not seeing anything in my account yet.
• My Advice: You should be trying to grow subscribers anyway, so of course this is an important area.

Keywords in show feed

This includes the following areas:

• Show Name
• Artist Name
• Episode Titles
• Episode Description

By the way, you can read a TON on podcast keyword placement suggestions on Pat Flynn’s Podcasting Tutorial. It’s pretty basic though. Put your keywords in those places, without being spammy.

• List or Search Rankings: This impacts search rankings (not list).
• Likely Factor: I say yes. It’s quite obvious iTunes ranked my show based upon words I used.
• Influenceable: Yes. You can control, edit, and update any of this text at any time. It takes about 12–24 hours tops for iTunes to pick up the updates.
• Data Available: Yes, we can publicly see all text available in any Podcast feed. This makes it easier to study.
• My Advice: Similar to traditional SEO, definitely optimize your show with keywords. See Pat’s tutorial for more specifics advice on that.

Total number of plays/downloads

This is a very common factor many podcasters will cite as having influence on ranking.

To clarify, “downloads” can be misleading — it refers to any streaming play or actual download of an episode, as reported by podcast hosting services like Libsyn (the host I use).

Nielson’s Hot Pod states:

“We’re about a year and a half into this podcast-renaissance racket, but even with all this talk, a download still doesn’t necessarily mean a download, and an impression still doesn’t necessarily mean an impression.”

As far as I understand, I haven’t seen download numbers affected at all by length of engagement. One could listen to the first 10 seconds of an episode and it still registers as a “download” (I’ve tested this myself).

• Likely Factor: No. Apple does not have access to my Libsyn stats of total downloads.
• Influenceable: Indirectly (unless you use Fiverr or something).
• Data Available: Only privately, or if podcasters willingly share their download numbers.
• My Advice: Of course you want to get listens or downloads. But consider these numbers proxy/relative metrics at best. And certainly don’t try to boost thinking they impact rankings.

NOTE: Downloads are often the go-to numbers used when sponsorships are purchased. See Tim Ferris’ post or EOFire’s great guide on sponsorships.

Are you beginning to see how download numbers are pretty muddy too?

Review acquisition

This is one of the most hotly debated ranking factors for podcasts. The idea is that the more reviews you get and the faster, the more likely you are to hit “New and Noteworthy.”

• Likely Factor: In my opinion, unfortunately, yes. Although some may strongly disagree. And I respect Daniel’s opinion. I’m just not sold on reviews being off the table as a ranking factor. Perhaps they don’t affect Top Lists, but do affect search rankings.
  • And maybe some people are gaming iTunes rankings for no actual reason, and I’m misreading this as a correlation. More on that below.
• Influenceable: Yes. Unfortunately. As you’ll see below, fake reviews are plentiful.
• Data Available: Yes, you can see at any time how many reviews any episode has, when they were left and how many stars (out of five) were given. There could be sub-factors to just pure number of reviews, such as:
  • Quality of reviews
  • Velocity of reviews
  • Who leaves them (kind of like a Yelp Elite user review has more weight).
• My Advice: I’m in the camp of “earn your reviews organically.” As of writing this I only have 10 reviews, while other shows that came out around the same time have 50+. I haven’t asked a single person for a review, but that’s my personal choice.

Cover art

Many podcasters have claimed that the quality of your cover art impacts rankings. They state that an iTunes editor will be more likely to place you into New and Noteworthy.

• Likely Factor: My opinion, no. I know many will disagree — but design quality is subjective, in a way. And I’ve seen many shows with what I would call “ugly” cover art ranking just fine. This may help you if iTunes wants to hand-choose you for the homepage. Also, this is not a scaleable ranking factor.
• Influenceable: Yes— hire a good designer 🙂
• Data Available: Subjectively.
• My Advice: You should aim to have great cover art no matter what (ok ok, I know mine is just OK, I made it myself, and we’re working on a very lean/agile budget, remember?) 🙂

Launching with 2–3+ episodes at once

This seems to be commonly cited among podcasters — including Tim Ferris, in his exceptional article about building his podcast (it’s great, you should read it). But I’m not sure I can agree.

• Likely Factor: I’m going to go against a lot of the podcasting community on this one and say — I’m highly skeptical. I think the idea is that you have a small window of time after launching to rank, and you’ll “miss out” otherwise. I’m just not seeing evidence of this. My show didn’t rank for much in week #1, but 7–10 days later after I had 3–4 episodes posted it did start to rank for things, yet I posted episodes one at a time.
• Influenceable: Yes. You can upload as many episodes as you want, whenever you want.
• Data Available: Sort of. We can look at newly launched podcasts, and try to parse those launching with only one episode from those that launch with three or more — and note ranking differences. So it’s hard to say if this effect is correlation or causation. And I’m afraid many are seeing correlating evidence on this one. For example, perhaps more episodes will result in more reviews, which then results in higher rankings. In which case the directive should be “get more reviews!” Even with one episode.
• My Advice: You may want to consider launching with 3+ episodes, so when new people discover your show, they are more enticed to subscribe.

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II. My promotion strategy

HUGE DISCLAIMER: There was so much more I wish we could have done. With extra resources (time and/or budget) I’m confident we could break into the “New and Noteworthy” section.

Also, I have no intention of “gaming” rankings to break into “New and Noteworthy.” I want the answer to “how would an average guy, with no fancy tricks, rank naturally in iTunes?”

1. Produce an exceptional product

This sounds like an empty platitude, but let me break it down for you. Here are a few core standards I wanted to adhere to from the beginning:

a.) Ask the guests unique questions

We’re running a guest interview-format show. Therefore, the questions are everything.

How do you ensure you’re asking unique questions? Two ways:

• Listen to or read at least 2–3 recent interviews your guest has given. Avoid repeating questions they’ve already been asked.
• Reference very recent tweets or articles the guest has written, especially on newer topics. Chances are no one else has had the chance to ask about them yet.

I can see our strategy working. Jen Slegg had this to say:

If we’re not asking at least 2–3 questions our guest has never heard before, we’re not doing our job — and we’re not going to have a show that stands out.

b.) Read 1-star reviews of other podcasts to learn what NOT to do

I know that’s a long heading… so let me show you an example.

The following are some 1-star reviews of other marketing podcasts:

I read through hundreds of bad reviews of other podcasts. I started to see common things to avoid, such as:

• Make the intros short and sweet, and get right into the meat of the show. Listeners are not very tolerant of longwinded intros (note: I’ve worked on improving this, especially episodes 11 and on!)
• Don’t “banter” and small-talk, especially not at the beginning. People are VERY turned off by the typical “radio jock” DJ you may have heard on radio stations in the ’80s and ’90s.
• Make the sound quality as good as possible. People complain a lot about unbalanced volume levels, inaudible guests, and just generally bad sound. Don’t hurt people’s ears!
• Don’t trick people. There’s a big trend in podcasting to just pile in the names of “famous” entrepreneurs to try to rank for searches of their name. People hate this. It’s disingenuous.

c.) Strive for professional audio quality

Poor audio quality in a podcast should be the same criminal offense as having illegible fonts on your blog. It creates cognitive friction that distracts from your content.

Fortunately, I have experience with audio production; if you don’t, I highly recommend you get help in this area.

Here are a few of the trade secrets I’ve been using.

• Use Compression — Most basic music software will have a compression plugin (including Garageband). Essentially, it evens out the high/low volumes, eliminating spikes and brings up the softer sounds. (There was a tool called “Levelator” which you could use, but it’s been discontinued).
• Use a Gate — A “gate” is a way to eliminate lower volume extraneous noises, like fans humming, an echo-y room (like my office), sniffling, etc. This has been my secret weapon to really clean up the show.

And I have to say, for not having the most fancy and expensive equipment and setup, our show sounds pretty good. It’s something I’m super proud of.

There’s LOTS more we’re doing to strive for a best-in-class show, but those have been the top three focus areas.

2. Run targeted Facebook ads

I have a Facebook Ad consultant running ads for clients, so we set a campaign up for the podcast episode in which I interviewed Brian Dean. I figured leveraging a pretty known name in the industry would attract some clicks and interest on this particular episode.

This was our targeting:

• Locations: Australia, UK, Ireland, US
• Ages: 22–50
• Languages: English (UK or US)
• Interests: Amy Porterfield, KissMetrics, Neil Patel, Moz (marketing software), Smart Passive Income with Pat Flynn or Derek Halpern
• Must match interests: Podcasts
• Budget: $200

We tested a number of text/image combinations, but these were the two “winners”:

I think these won in CTR simply because the messaging is specific and intriguing.

Ad 1 Stats:

• Reach: 14,151
• Website Clicks: 746
• Cost: $0.17
• Spent: $123.14

Ad 2 Stats:

• Reach: 7,963
• Website Clicks: 263
• Cost: $0.21
• Spent: $55.63

We also tested other images of Brian, but that one performed the best by far.

It’s tough to tell exactly how many plays we got from ad traffic, but it looks like about 30% of Facebook ad traffic resulted in a “download.”

In other words, it cost about $1.00 per download.

3. Create an organic network effect

Besides spending $200 on Facebook, we had no budget allocated; just time and effort. This means doing every little thing you can to create a cumulative effect.

a.) Update your email signature

Tons of people see my emails every day. These impressions add up and matter over time:

Now you have my phone number 🙂

b.) Send personal emails to highly relevant people

This is truly the power of one in practice. Yes, I’ll take the time to personally email a small handful of people who I think might enjoy the show. I don’t ask them to review it or share it. These are people I already know pretty well, not cold emails.

For instance, Jake, who asked me about Podcasts almost a year ago.

We had a short conversation at that time, but I remembered the chain and followed up:

This is an excerpt of his reply:

I also remembered Borja Obeso had me as a guest on the Rebel Growth Podcast — and I had been emailing with him and let him know about it:

He then voluntarily shared it:

No. None of this is earth shattering. But repeat small actions like this dozen or hundred’s of times and they add up.

Besides, I’m just building/continuing relationships in the process — which is even better.

c.) Share in seemingly irrelevant places

A podcast has a much wider appeal than my SEO services. This means I can share my podcast in places I’d never be talking about SEO services. Like Instagram.

I pretty much use it as a photographer:

But I figured, why not just share a photograph per usual and announce it in the copy of the post?

Luckily, this photo got the most likes I’ve ever received — and this the most visibility.

And it actually worked:

Yes, that’s ONE person telling me they downloaded the Podcast. It’s small. But it’s one more person listening to the show. Remember, those add up. Cumulative effects.

d.) Swap small talk for “Hey, we started a podcast!”

How does your typical meeting begin?

“How are you?”
“How’s the weather there?”
“What’d you do this weekend”?

Snooze.

Because I probably talk to and/or meet 100+ different people per month, I have used these opportunities in the last 6 weeks to switch up my default answer from “good” or “cold” or “here’s some boring activity we did you don’t care about” to:

“Great! One exciting thing, we just launched our marketing podcast and it seems to be going well.”

Sometimes there’s an awkward pause, because an actual conversation is so shocking to some people.

But 85% of the time I sense an interest. In which case, I drop them a link in a chat or an email.

Results?

That person ended up leaving a review, too.

This is just two examples, but it happened many many times — just by telling people as you go through your day.

Again, this sort of “word of mouth” promotion is possible by the very nature of a podcast — it has a wide reach and appeal.

4. Be a guest on other podcasts

When you think about it, the people you should be trying to get in front of are podcast listeners. Not all people interested in marketing will want to consume information in audio format. But if you can be a guest on a podcast in a related field, you’re more likely to attract new listeners, because they’re already in the podcasting ecosystem.

I only had limited opportunity to do this, as I was the guest on Talking Drupal last week, but will be hoping to do this more in the future.

Yes, I’m available to be on any podcast talking about SEO. Interested? Tweet me </plug>.

5. Interview guests who have audiences

I think this is a given and in fact it’s a pretty known “trick of the trade” in podcasting. Look at the success of shows like Entrepreneur on Fire, School of Greatness and Mixery. These shows are practically built on the following of the guests (and the hosts to some degree).

Now… I will NEVER have a guest on I’m not excited about or who won’t bring real value, just for the sake of siphoning their audience. But I’m well aware of the fact some guests may have a sizable influence.

Take the show I did with Everette Taylor. All I did was put out one tweet and his audience did the rest:

And Ross Simmonds’ tweet with Everette’s RT took it even further:

(Yeah, some Twitter bots jacked up those numbers a bit)

And again, I reiterate, there are plenty of people I could have on my show with “influence,” but I’d opt to have someone that makes for a great interview any day over “influence” alone.

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III. Goals & results

First, before I show results, I have a few things in mind we’re looking to achieve:

Goal KPIs

• To hit “New and Noteworthy” in our subcategory, and category (I doubt the home page is possible with our limited resources and the 2016 competition)
• To rank in iTunes search for some general keywords like “SEO,” “marketing,” “growth hacking,” and some guest names like “Brian Dean,” etc.

Goal show metrics

• Downloads — I’m shooting to hit 10,000–30,000+ downloads per episode within six weeks from the date they’re posted. There’s no consistent industry agreement on how many downloads you need to monetize (see here and here and here) but the 10,000–30,000 mark seems common. I’m NOT saying we’ll definitely take sponsors, but I figure if we’re “sponsor-worthy” we’re “monetization-worthy” in one way or another.

Business goals

• Monetization — As noted, I am not set on how we monetize, but this would be a great result for the hours, effort, and energy we put into a free show.
• New service / Product opportunities — Again, nothing I’m dead set on, but open to what happens. We may be in the position to train other companies on how to produce audio content, or to have this be on offshoot media company producing a variety of audio content.

So how are we doing so far? It’s been 36 days since we launched, so we’re relatively young, but I’m seeing promising results thus far.

General show stats

(As of 4/28/2016)

• Episodes posted: 13
• Reviews received: 11
• Total “Downloads”: 2,708

iTunes rankings

I didn’t do this very “scientifically.” I don’t know how to track iTunes rankings automatically, so I just jumped in and took screenshots every few days.

Here’s some rankings in chronological order:

Day 2

By day 2, we were “indexed” in iTunes and showing up for long-tail searches like “digital marketing experts”:

I doubt anyone searches that, but I was basically just checking that it showed up at all.

Day 3

I was pleasantly surprised to see us ranking for “seo” — albeit position #51 — only 3 days in:

I also quickly realized I would need to improve the cover art, as the font was WAY too small.

I was even more happily surprised to see we ranked #6 for “growth hacking” by day 3.

Sadly, we didn’t actually have any content about growth hacking yet. I suspect we ranked for it simply because it’s in our show title.

By day 3 we also ranked for “Brian Dean”:

Day 9

Yeah, I know… what happened to days 4–8? Well by Day 9, we ranked even better for “Brian Dean”:

Day 12

In trying some other searches, I noticed we ranked pretty well for “slideshare”:

This was due to episode four with Ross Simmonds, which was mostly about SlideShare, so it was in the show title.

Day 20

I know, I know, we’ve skipped 8 more days. Anyway, I’m still not ranking for the terms I think will bring the most value, like “marketing”:

I should not, at this point, as search result like this only has 100 slots. If you’re not in the top 100, you’re not there at all. That would be me (not there).

We ARE, however, moving up the spots for “SEO,” now at position #27:

Day 28

Finally. We made it into “New and Noteworthy” for the sub-category of Marketing and Management:

Could we have done this sooner and ranked higher with the application of additional “tactics”? Sure. I could have directly asked people for reviews and subscriptions. But I really wanted to see what the natural progressions of rankings would be without this influence.

Day 30

We then finally made it into “New and Noteworthy” in the main category of Business. Well, sort of. Ranking in the 15th row is there, but that’s basically like the 10th page of Google:

Beyond day 30

We tend to hover around the position 30 range for “New and Noteworthy” in Marketing & Management:

Also, currently rankings are:

• 29 for “seo”
• Not in top 100 for “marketing”
• 3 for “everette taylor”
• 4 for “growth hacking”
• 18 for “content marketing”
• 67 for “digital marketing”
• 81 for “analytics”

iTunes ranking hacks

Throughout the course of doing this, I noticed a series of loopholes — if one had the desire to pursue them.

Rank #1 by post-dating your episodes

Now, I’m not sure if this is being done on purpose, but here’s how you show up #1 in your category:

If you look at his episodes, they are post-dated. So apparently this section is ranked chronologically:

Rank for almost any keyword by being popular

There’s not much keyword targeting going on here:

This show has nothing to do with marketing, but ranked #2 (at the time of my search) for “marketing.” Perhaps it had a marketing episode at one point.

There’s no apparent filtering or de-ranking for fake reviews

Do these reviews by user names “dghdb76” or “ghn dgd56” look real to you?

Yeah, me neither.

However, this show (I didn’t want to call it out) has dozens (maybe hundreds at this point) of fake reviews. It ranks exceptionally well. iTunes does nothing to filter them out.

I’m not 100% sure the reviews are causing the rankings, but if the reviews are gamed, wouldn’t you assume the subscriptions are as well?

“REALLY THIS PODCAST IS AN EXCELENT.” <— seriously?

Podcast show metrics — our results

Just like normal SEO, rankings mean nothing if they don’t translate to marketing and business outcomes. Which is why we can look at my iTunes rankings all we want, but I’m more interested in downloads.

First, here are my total “downloads” as of 4/20/2016:

Remember. My GOAL is 10,000+ downloads per episode within 6 weeks of when they post. So for example, #3 with Brian Dean would have more like 9,000+ downloads by now.

So yeah, we’re just getting started.

Here’s the growth of downloads day by day. As you can see, it’s been a nice steady trend upwards so far:

Each spike is generally a day when a new episode posts, or when it gets some extra sharing on social media.

What’s cool is Libsyn also provides some nice data around user agents — here are the agents most used to play my show thus far:

Though not a “goal” metric, it is nice to see a nice variety of agents and diversity of places people listen to the show.

Business results

This is where it gets interesting. Sure, metrics are great, but I’m paying extra attention to those “serendipitous” things most people might miss.

I mentioned the long term goals of monetization and additional business opportunities. Of course 44 days in is pretty fast for that, but I can specifically point to other business results due to the podcast.

Having a podcast makes writers more receptive to you

I occasionally reply to HARO inquiries. I noticed that when I started putting that I was a podcast host, it helped warm up writers to me a bit more. I think it’s less intimidating than “agency owner.”

This is an example of one of a few placements that came as the result:

People perceive you differently

I can hear it in their voices. When I’m on a call and I tell a client “we launched a podcast,” you hear that like “ohhhhhh,” as if they’re impressed. I think podcasting can have this effect right now, because they still have a perception of “status,” like authoring a book.

If you want to stand out, podcasting is a great route, but not the only one. It’s the idea of doing something “real companies do.”

Instead of just being any other SEO agency or consultant, suddenly we have an extra badge of credibility. This can lead to a client having more confidence/trust in our ability to make decisions and set strategies for them — leading to more success.

Relationship building leads to business outcomes

I can cite two very concrete examples of business outcomes since interviewing about 20 people (we record the episodes a few weeks ahead of time):

• A new client — Someone I interviewed referred a small project to us a week later.
• A placement in a high-profile publication — Someone else I interviewed invited me to contribute content to a high-profile site in the tech/marketing industry. Since I have not done much of this, it opens the door to an opportunity of more exposure and doing so again in the future. (Note: this content has not been posted as of yet). Writing for higher profile sites beyond just the SEO industry has been a passive goal for a while.

Running an interview-format podcast has opened the doors to a TON of relationship building and networking that I normally wouldn’t be doing from Worcester, MA. 🙂

Podcasting impacts your website rankings & traffic

I spent most of this post focusing on ranking in iTunes for the sake of getting more podcast downloads. But your podcast can feed back into your website performance.

Remember, podcast episodes are posted to your website, so all of that content lives on your domain too. This means I could eventually rank for some target terms like:

People will search for podcasts in Google by category, so this is another source of traffic and discovery.

You also get a link from Apple. Despite being nofollowed, I think this still must convey something to Google.

Combine niches to create a new niche & stand out

There are tons of SEOs. And there are LOTS of podcasters.

But there are NOT many podcasting SEOs.

This sounds like a cheap gimmick, but honestly, I only realized it in hindsight. Here’s a concrete example.

How many non-SEO podcasters would have noticed the dilemma in Google Play’s email here?

Or how many SEOs would have received that email without having a podcast themselves?

However, now being in “both worlds,” it’s an opportunity to spot something happening in one industry relevant to another — and be the source of interesting news or information.

As an SEO or marketer, “niche” down into something and you’ll spot TONS of information you can share between the two worlds, providing value to both, and helping you to stand out.

The future of “standing out” is combining disciplines in new ways.

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IV. Lessons learned & takeaways

Patience

I’m only 44 days into podcasting. I realize I could be employing “tactics” (tricks?) to break into New and Noteworthy. I am aware of other podcasts that have received MORE downloads, reviews, listens, and praise than mine in the same amount of time.

But, I refuse to employ such tricks, so I’m willing to be more patient to let those results come more naturally.

Make a popular show iTunes wants to rank

Just like Google, iTunes want to rank popular/quality podcasts — not make your podcast popular.

Back in about 2006–2012, you could just put a decent show up in iTunes, rank in New and Noteworthy, and be set. But now, you can’t depend on iTunes alone to make your show a success. You have to put in the work, especially if you’re not going to use tricks.

Should you optimize for iTunes rankings? Of course. But you’ll have to market your podcast outside of iTunes as well.

Competition is heating up

We come full circle.

There are real media companies — with budgets and brand equity — pouring into the podcasting space every day. I’m not saying it’s too late to have a widely popular podcast. I’m still planning on it.

But check it out: this is New and Noteworthy, April 24th, 2016. Look. At. All. The. BRANDS.

Out of the top 27 podcasts in iTunes, there are these 12 brands:

• Entertainment Weekly
• Earwolf (a Podcasting Network)
• Apple
• Dean & DeLuca
• FOX Sports
• ABC News
• Digg
• New York Daily News
• Women’s Health
• New Hampshire Public Radio
• Sports Illustrated
• ESPN

Yes, folks, being successful at podcasting has evolved into real marketing.

But with monthly listeners growing fast as well, there’s still opportunity.

The true variable of success is the quality of the product.

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Chat with me.

Comments? Questions? Disagreements?

I will reply to ALL below.

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Posted by randfish

A year ago, in April of 2015, I pitched a project internally at Moz to design and launch a keyword research tool, one of the few areas of SEO we’ve never comprehensively tried to serve. The pitch took effort and cajoling (the actual, internal pitch deck is available here), but eventually received approval, with one big challenge… We had to do it with a team already dedicated to the maintenance and development of our rankings collections and research tools. This project wouldn’t get additional staffing — we had to find a way to build it with only the spare bandwidth of this crew.

Sure, we didn’t have the biggest team, or the ability to work on the project free from our other obligations, but we had grit. We had passion. We wanted to prove ourselves to our fellow Mozzers and to our customers. We had pride. And we desperately wanted to build something that wasn’t just “good enough,” but was truly great. Today, I think we’ve done that.

Meet our new keyword research tool, Keyword Explorer:

If you want to skip hearing about it and just try it out, head on over. You can run 2 free searches/day without even logging in, another 5 with a free community account, and if you’re a Pro subscriber, you’ve already got access. For those who want to learn more, read on!

The 5 big, unique features of Keyword Explorer

Keyword Explorer (which we’ve taken to calling “KWE” for short) has lots of unique features, metrics, and functionality, but the biggest ones are pretty obvious and, we believe, highly useful:

1. KWE takes you all the way through the keyword research process — from discovering keyword ideas to getting metrics to building a list, filtering the keywords on it, and prioritizing which ones to target based on the numbers that matter.
2. KWE features metrics essential to the SEO process — two you’re familiar with — Volume and Difficulty — and three that are less familiar: Opportunity, Importance, and Potential. Opportunity estimates the relative CTR of the organic web results on a SERP. Importance is a metric you can modify to indicate a keyword that’s more or less critical to your campaign/project. And Potential is a combination of all the metrics built to help you prioritize a keyword list.
3. Our volume score is the first volume estimation metric we know of that goes beyond what AdWords reports. We do that using Russ Jones’ volume bucket methodology and adding in anonymized clickstream data from ~1 million real searchers in the US. From there, Russ has built a model that predicts the search volume range a keyword is likely to have with ~95% accuracy.
4. Keyword suggestions inside KWE come from almost all the sources we saw SEOs accessing manually in their research processes — Keyword Planner data, Google Suggest, Related Searches, other keywords that the ranking pages also ranked for, topic-modeling ideas, and keywords found from our clickstream data. All of these are available in KWE’s suggestions.
5. Import and export functionality are strongly supported. If you’ve already got a list of keywords and just want KWE’s metrics, you can easily upload that to us and we’ll fetch them for you. If you like the KWE process and metrics, but have more you want to do in Excel, we support easy, powerful, fast exports. KWE is built with power users in mind, so go ahead and take advantage of the tool’s functionality however works best with your processes.

These five are only some of the time-saving, value-adding features in the tool, but they are, I think, enough to make it worthwhile to give Keyword Explorer a serious look.

A visual walkthrough

As an experiment, I’ve created a visual, slide-by-slide walkthrough of the tool. If you’d rather *see* vs. read the details, this format might be for you (Slideshare’s embedding is having issues today, but you can find the presentation on their site).

And, for those of you who prefer video, we made a short, 2 minute demo of the tool in that format, too:

Of course, there’s a ton of nuance and complexity in a product like this, and given Moz’s dedication to transparency, you can find all of that detail in the more thorough explanation below.

Keyword Explorer’s metrics

KWE’s metrics are among the biggest data-driven advances we’ve made here at Moz, and a ton of credit for that goes to Dr. Pete Meyers and Mr. Russ Jones. Together, these two have crafted something extraordinary — unique metrics that we’ve always needed for SEO-based keyword research, but never had before. Those include:

Keyword volume ranges

Nearly every keyword research tool available uses a single source for volume data: Google AdWords’ Keyword Planner. We all know from studying it that the number AdWords provides is considerably off from reality, and last year, Moz’s Russ Jones was able to quantify those discrepancies in his blog post: Keyword Planner’s Dirty Secrets.

Since we know that Google’s numbers don’t actually have precision, but do indicate a bucket, we realized we could create ranges for volume and be significantly more accurate, more of the time. But, that’s not all… We also have access to anonymized clickstream data here at Moz, purchased through a third-party (we do NOT collect or use any of our own user data via, for example, the MozBar), that we were able to employ in our new volume ranges.

Using sampling, trend data, and the number of searchers and searches for a given keyword from the clickstream, combined with AdWords’ volume data, we produced a volume range that, in our research, showed ~95% accuracy with the true impression counts Google AdWords would report for a keyword whose ad showed during a full month.

We’re pretty excited about this model and the data it produces, but we know it’s not perfect yet. As our clickstream data grows, and our algorithm for volume improves, you should see more and more accurate ranges in the tool for a growing number of keywords. Today, we have volume data on ~500mm (half a billion) English-language search queries. But, you’ll still see plenty of “no data” volume scores in the tool as we can access considerably more terms and phrases for keyword suggestions (more on suggestion sources below).

NOTE: KWE uses volume data modeled on the quantity of searches in the US for a given term/phrase (global English is usually 1.5-3X those numbers). Thus, while the tool can search any Google domain in any country, the volume numbers will always be for US-volume. In the future, we hope to add volume data for other geos as well.

An upgraded, more accurate Keyword Difficulty score

The old Keyword Difficulty tool was one of Moz’s most popular (it’s still around for another month or so, but will be retired soon in favor of Keyword Explorer). But, we knew it had a lot of flaws in its scoring system. For Keyword Explorer, we invested a lot of energy in upgrading the model. Dr. Pete, Dr. Matt Peters, myself, and Russ had 50+ reply email threads back and forth analyzing graphs, suggesting tweaks, and tuning the new score. Eventually, we came up with a Keyword Difficulty metric that:

• Has far more variation than the old model — you’ll see way more scores in the 20s and 30s as well as the 80s and 90s than the prior model, which put almost every keyword between 50–80.
• Accounts for pages that haven’t yet been assigned a PA score by using the DA of the domain.
• Employs a smarter, CTR-curve model to show when weaker pages are ranking higher and a page/site may not need as much link equity to rank.
• Adjusts for a few domains (like Blogspot and Wordpress) where DA is extremely high, but PA is often low and the inherited domain authority shouldn’t pass on as much weight to difficulty.
• Concentrates on however many results appear on page 1, rather than the top 20 results.

This new scoring model matches better with my own intuition, and I think you’ll find it vastly more useful than the old model.

As you can see from one of my lists above (for Haiku Deck, whose board I joined this year), the difficulty ranges are considerably higher than in the past, and more representative of how relatively hard it would be to rank in the organic results for each of the queries.

A true Click-Through Rate Opportunity score

When you look at Google’s results, it’s pretty clear that some keywords are worthy of pursuit in the organic web results, and some are not. To date, no keyword research tool we know of has attempted to accurately quantify that, but it’s a huge part of determining the right terms and phrases to target.

Once we had access to clickstream data, we realized we could accurately estimate the percent of clicks on a given search result based on the SERP features that appeared. For example, a classic, “ten-blue-links” style search result had 100% of click traffic going to organic results. Put a block of 4 AdWords ads above it, though, and that dropped by ~15%. Add a knowledge graph to the right-hand side and another ~10% of clicks are drawn away.

It would be crazy to treat the prioritization of keywords with loads of SERP features and little CTR on the organic results the same as a keyword with few SERP features and tons of organic CTR, so we created a metric that accurately estimates Click-Through-Rate (CTR), called “Opportunity.”

The search above for “Keanu” has an instant answer, knowledge graph, news results, and images (further down). Hence, its Opportunity Score is a measly 37/100, which means our model estimates ~37% of clicks go to the organic results.

But, this search, for “best free powerpoint software” is one of those rare times Google is showing nothing but the classic 10 blue links. Hence, its Opportunity Score is 100/100.

If you’re prioritizing keywords to target, you need this data. Choosing keywords without it is like throwing darts with a blindfold on — someone’s gonna get hurt.

Importance scores you can modify

We asked a lot of SEOs about their keyword research process early in the design phases of Keyword Explorer and discovered pretty fast that almost everyone does the same thing. We put keyword suggestions from various sources into Excel, get metrics for all of them, and then assign some type of numeric representation to each keyword based on our intuition about how important it is to this particular campaign, or how well it will convert, or how much we know our client/boss/team desperately wants to rank for it.

That self-created score was then used to help weight the final decision for prioritizing which terms and phrases to target first. It makes sense. You have knowledge about keywords both subjective and objective that should influence the process. But it needs to do so in a consistent, numeric fashion that flows with the weighting of prioritization.

Hence, we’ve created a toggle-able “Importance” score in Keyword Explorer:

After you add keywords to a list, you’ll see the Importance score is, by default, set to 3/10. We chose this number to make it easy to increase a keyword’s importance by 3X and easy to bring it down to 1/3rd. As you modify the importance value, overall Keyword Potential (below) will change, and you can re-sort your list based on the inputs you’ve given.

For example, in my list above, I set “free slideshow software” to 2/10, because I know it won’t convert particularly well (the word “free” often does not). But, I also know that churches and religious organizations love Haiku Deck and find it hugely valuable, so I’ve bumped up the importance of “worship presentation software” to 9/10.

Keyword Potential

In order to prioritize keywords, you need a metric that combines all the others — volume, difficulty, opportunity, and importance — with a consistent, sensible algorithm that lets the best keywords rise to the top. In Keyword Explorer, that metric is “Potential.”

Sorting by Potential shows me keywords that have lots of search volume, relatively low difficulty, relatively high CTR opportunity, and uses my custom importance score to push the best keywords to the top. When you build a list in Keyword Explorer, this metric is invaluable for sorting the wheat from the chaff and identifying the terms and phrases with the most promise.

Keyword research & the list building process

Keyword Explorer is built around the idea that, starting from a single keyword search, you can identify suggestions that match your campaign’s goals and include them in your list until you’ve got a robust, comprehensive set of queries to target.

List building is easy — just select the keywords you like from the suggestions page and use the list selector in the top right corner (it scrolls down as you do) to add your chosen keywords to a list, or create a new list:

Once you’ve added keywords to a list, you can go to the lists page to see and compare your sets of keywords:

Each individual list will show you the distribution of metrics and data about the keywords in it via these helpful graphs:

The graphs show distributions of each metric, as well as a chart of SERP features to help illustrate which types of results are most common in the SERPs for the keywords on your list:

For example, you can see in my Rock & Grunge band keywords, there’s a lot of news results, videos, tweets, and a few star reviews, but no maps/local results, shopping ads, or sitelinks, which makes sense. Keyword Explorer is using country-level, non-personalized, non-geo-biased results, and so some SERPs won’t match perfectly to what you see in your local/logged-in results. In the future, we hope to enable even more granular location-based searches in the tool.

The lists themselves have a huge amount of flexibility. You can sort by any column, add, move, or delete in bulk, filter based on any metric, and export to CSV.

If your list gets stale, and you need to update the metrics and SERP features, it’s just a single click to re-gather all the data for every keyword on your list. I was particularly impressed with that feature; to me it’s one of the biggest time-savers in the application.

Keyword Explorer’s unique database of search terms & phrases

No keyword research tool would be complete without a massive database of search terms and phrases, and Keyword Explorer has just that. We started with a raw index of over 2 billion English keywords, then whittled that down to the ~500 million highest-quality ones (we collapsed lots of odd suggestions we found via iterative crawls of AdWords, autosuggest, related searches, Wikipedia titles, topic modeling extractions, SERPscape — via our acquisition last year — and more) into those we felt relatively confident had real volume).

Keyword Explorer’s suggestions corpus features six unique filters to get back ideas. We wanted to include all the types of keyword sources that SEOs normally have to visit many different tools to get, all in one place, to save time and frustration. You can see those filters at the top of the suggestions page:

The six filters are:

1. Include a Mix of Sources
   • This is the default filter and will mix together results from all the others, as well as ideas crawled from Google Suggest (autocomplete) and Google’s Related Searches.
2. Only Include Keywords With All of the Keyword Terms
   • This filter will show only suggestions that include all of the terms you’ve entered in the query. For example, if you entered “mustache wax” this filter would only show suggestions that contain both the word “mustache” and the word “wax.”
3. Exclude Your Query Terms to Get Broader Ideas
   • This filter will show only suggestions that do not include your query terms. For example, if you entered “mustache wax,” suggestions might include “facial grooming products” or “beard oil” but nothing with either “mustache” or “wax.”
4. Based on Closely Related Topics
   • This filter uses Moz’s topic modeling algorithm to extract terms and phrases we found on many web pages that also contained the query terms. For example, keywords like “hair gel” and “pomade” were found on many of the pages that had the words “mustache wax” and thus will appear in these suggestions.
5. Based on Broadly Related Topics and Synonyms
   • This filter expands upon the topic modeling system above to include synonyms and more broadly related keywords for a more iterative extraction process and a wider set of keyword suggestions. If “Closely Related Topics” suggestions are too far afield for what you’re seeking, this filter often provides better results.
6. Related to Keywords with Similar Results Pages
   • This filter looks at the pages that ranked highly for the query entered and then finds other search terms/phrases that also contained those pages. For example, many pages that ranked well for “mustache wax” also ranked well for searches like “beard care products” and “beard conditioner” and thus, those keywords would appear in this filter. We’re big fans of SEMRush here at Moz, and this filter type shows suggestions very similar to what you’d find using their competitive dataset.

Some of my favorite, unique suggestions come from the “closely related topics” filter, which uses that topic modeling algorithm and process. Until now, extracting topically related keywords required using something like Alchemy API or Stanford’s topic modeling software combined with a large content corpus, aka a royal pain in the butt. The KWE team, mostly thanks to Erin, built a suitably powerful English-language corpus, and you can see how well it works:

NOTE: Different filters will work better and worse on different types of keywords. For newly trending searches, topic modeling results are unlikely to be very good, and on longer tail searches, they’re not great either. But for head-of-demand-curve and single word concepts, topic modeling often shows really creative lexical relationships you wouldn’t find elsewhere.

SERPs Analysis

The final feature of Keyword Explorer I’ll cover here (there are lots of cool nooks and crannies I’ve left for you to find on your own) is the SERPs Analysis. We’ve broadened the ability of our SERP data to include all the features that often show up in Google’s results, so you’ll see a page much more representative of what’s actually in the keyword SERP:

Holy smack! There’s only 3 — yes, THREE — organic results on page one for the query “Disneyland.” The rest is sitelinks, tweets, a knowledge graph, news listings, images — it’s madness. But, it’s also well-represented in our SERPs Analysis. And, as you can see, the Opportunity score of “7” effectively represents just how little room there is for organic CTR.

Over time, we’ll be adding and supporting even more features on this page, and trying to grab more of the metrics that matter, too (for example, after Twitter pulled their tweet counts, we had to remove those from the product and are working on a way to get them back).

Yes, you can buy KWE separately (or get it as part of Moz Pro)

Keyword Explorer is the first product in Moz Pro to be available sold separately. It’s part of the efforts we’ve been making with tools like Moz Local, Followerwonk, and Moz Content to offer our software independently rather than forcing you to bundle if you’re only using one piece.

If you’re already a Moz Pro subscriber, you have access to Keyword Explorer right now! If you’re not a subscriber and want to try it out, you can run a few free queries per day (without list building functionality though). And, if you want to use Keyword Explorer on its own, you can buy it for $600/year or $1,800/year depending on your use.

The best part of Keyword Explorer — we’re going to build what you want

There’s lots to like in the new Keyword Explorer, but we also know it’s not complete. This is the first version, and it will certainly need upgrades and additions to reach its full potential. That’s why, in my opinion, the best part of Keyword Explorer is that, for the next 3–6 months, the team that built this product is keeping a big part of their bandwidth open to do nothing but make feature additions and upgrades that YOU need.

It was pretty amazing to have the team’s schedule for Q2 and Q3 of 2016 make the top priority “Keyword Explorer Upgrades & Iterations.” And, in order to take advantage of that bandwidth, we’d love to hear from you. We have dozens (maybe hundreds) of ideas internally of what we want to add next, but your feedback will be a huge part of that. Let us know through the comments below, by tweeting at me, or by sending an email to Rand at Moz.com.

A final note: I want to say a massive thanks to the Keyword Explorer team, who volunteered to take on much more than they bargained for when they agreed to work with me 🙂 Our fearless, overtime-investing, never-complaining engineers — Evan, Kenny, David, Erin, Tony, Jason, and Jim. One of the best designers I’ve ever worked with — Christine. Our amazingly on-top-of-everything product manager — Kiki. Our superhero-of-an-engineering-manager — Shawn. Our bug-catching SDETs — Uma and Gary. Our product marketing liaison — Brittani. And Russ & Dr. Pete, who helped with so many aspects of the product, metrics, and flow. You folks all took time away from your other projects and responsibilities to make this product a reality. Thank you.

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