New figures show that marketers spent $479 million on podcasts ads last year, and are projected to spend over $1 billion by 2021.
These figures are from the Interactive Advertising Bureau (IAB), and PwC, and reported on by eMarketer.
In an analysis of the US podcast advertising industry, it was found that self-reported podcast advertising revenues grew 34% in 2018. It’s predicted that revenue will grow 42% this year.
Lauren Fisher, the principal analyst at eMarketer, speaks on the growth of podcasts and the value they provide to listeners:
“Podcasts are one of the fastest-growing, if not the fastest-growing category within digital audio.
Performance marketers and brands are recognizing the value in reaching consumers who aren’t just tuning in to tune out—they’re tuning in to actively be entertained or engage their minds. And that’s a mindset advertisers increasingly want to be a part of.”
The report from eMarketer includes additional data on the current state of podcasts.
A (Relatively) Small But Passionate Audience
It’s projected that 76.4 million people, or a quarter of the US population, will listen to a podcast this year.
While podcast listeners still represent a minority of the population, surveys have found that most are listening to several podcasts a week.
“In a March 2019 survey by Edison Research and digital audio technology and advertising company Triton Digital, a fifth (21%) of podcast listeners said they listened to four to five podcasts a week, and even more (31%) said they listened to six or more podcasts a week.”
Here are some additional data included in the report:
Over 70% of podcast ads are bought by brands in the direct-to-consumer (D2C) market.
Ads read by the podcast host are most preferred, making up 63.3% of ads in 2018.
Pre-produced ads made up 35% of last year’s podcast ads
Most (65.7%) podcast ad revenue in 2018 went to news/politics/current events, comedy, business, education, and arts & entertainment podcasts.
You can think of Tobiko as a kind of anti-Yelp. Launched in 2018 by Rich Skrenta, the restaurant app relies on data and expert reviews (rather than user reviews) to deliver a kind of curated, foodie-insider experience.
A new Rich Skrenta project. Skrenta is a search veteran with several startups behind him. He was one of the founders of DMOZ, a pioneering web directory that was widely used. Most recently Skrenta was the CEO of human-aided search engine Blekko, whose technology was sold to IBM Watson in roughly 2015.
At the highest level, both DMOZ and Blekko sought to combine human editors and search technology. Tobiko is similar; it uses machine learning, crawling and third-party editorial content to offer restaurant recommendations.
Betting on expert opinion. Tobiko is also seeking to build a community, and user input will likely factor into recommendations at some point. However, what’s interesting is that Skrenta has shunned user reviews in favor of “trusted expert reviews” (read: critics).
Those expert reviews are represented by a range of publisher logos on profile pages that, when clicked, take the user to reviews or articles about the particular restaurant on those sites. Where available, users can also book reservations. And the app can be personalized by engaging a menu of preferences. (Yelp recently launched broad, site-wide personalization itself.)
While Skrenta is taking something of a philosophical stand in avoiding user reviews, his approach also made the app easier to launch because expert content on third-party sites already existed. Community content takes much longer to reach critical mass. However, Tobiko also could have presented or “summarized” user reviews from third-party sites as Google does in knowledge panels, with TripAdvisor or Facebook for example.
Tobiko is free and currently appears to have no ads. The company also offers a subscription-based option that has additional features.
Why we should care. It’s too early to tell whether Tobiko will succeed, but it provocatively bucks conventional wisdom about the importance of user reviews in the restaurant vertical (although reading lots of expert reviews can be burdensome). As they have gained importance, reviews have become somewhat less reliable, with review fraud on the rise. Last month, Google disclosed an algorithm change that has resulted in a sharp decrease in rich review results showing in Search.
Putting aside gamesmanship and fraud, reviews have brought transparency to online shopping but can also make purchase decisions more time-consuming. It would be inaccurate to say there’s widespread “review fatigue,” but there’s anecdotal evidence supporting the simplicity of expert reviews in some cases. Influencer marketing can be seen as an interesting hybrid between user and expert reviews, though it’s also susceptible to manipulation.
About The Author
Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.
When used creatively, XPaths can help improve the efficiency of auditing large websites. Consider this another tool in your SEO toolbelt.
There are endless types of information you can unlock with XPaths, which can be used in any category of online business.
Some popular ways to audit large sites with XPaths include:
In this guide, we’ll cover exactly how to perform these audits in detail.
What Are XPaths?
Simply put, XPath is a syntax that uses path expressions to navigate XML documents and identify specified elements.
This is used to find the exact location of any element on a page using the HTML DOM structure.
We can use XPaths to help extract bits of information such as H1 page titles, product descriptions on ecommerce sites, or really anything that’s available on a page.
While this may sound complex to many people, in practice, it’s actually quite easy!
How to Use XPaths in Screaming Frog
In this guide, we’ll be using Screaming Frog to scrape webpages.
Screaming Frog offers custom extraction methods, such as CSS selectors and XPaths.
It’s entirely possible to use other means to scrape webpages, such as Python. However, the Screaming Frog method requires far less coding knowledge.
(Note: I’m not in any way currently affiliated with Screaming Frog, but I highly recommend their software for web scraping.)
Step 1: Identify Your Data Point
Figure out what data point you want to extract.
For example, let’s pretend Search Engine Journal didn’t have author pages and you wanted to extract the author name for each article.
What you’ll do is:
Right-click on the author name.
In the dev tools elements panel, you will see your element already highlighted.
Right-click the highlighted HTML element and go to Copy and select Copy XPath.
At this point, your computer’s clipboard will have the desired XPath copied.
Step 2: Set up Custom Extraction
In this step, you will need to open Screaming Frog and set up the website you want to crawl. In this instance, I would enter the full Search Engine Journal URL.
Go to Configuration > Custom > Extraction
This will bring up the Custom Extraction configuration window. There are a lot of options here, but if you’re looking to simply extract text, match your configuration to the screenshot below.
Step 3: Run Crawl & Export
At this point, you should be all set to run your crawl. You’ll notice that your custom extraction is the second to last column on the right.
When analyzing crawls in bulk, it makes sense to export your crawl into an Excel format. This will allow you to apply a variety of filters, pivot tables, charts, and anything your heart desires.
3 Creative Ways XPaths Help Scale Your Audits
Now that we know how to run an XPath crawl, the possibilities are endless!
We have access to all of the answers, now we just need to find the right questions.
What are some aspects of your audit that could be automated?
Are there common elements in your content silos that can be extracted for auditing?
What are the most important elements on your pages?
The exact problems you’re trying to solve may vary by industry or site type. Below are some unique situations where XPaths can make your SEO life easier.
1. Using XPaths with Redirect Maps
Recently, I had to redesign a site that required a new URL structure. The former pages all had parameters as the URL slug instead of the page name.
This made creating a redirect map for hundreds of pages a complete nightmare!
So I thought to myself, “How can I easily identify each page at scale?”
After analyzing the various page templates, I came to the conclusion that the actual title of the page looked like an H1 but was actually just large paragraph text. This meant that I couldn’t just get the standard H1 data from Screaming Frog.
However, XPaths would allow me to copy the exact location for each page title and extract it in my web scraping report.
In this case I was able to extract the page title for all of the old URLs and match them with the new URLs through the VLOOKUP function in Excel. This automated most of the redirect map work for me.
With any automated work, you may have to perform some spot checking for accuracy.
2. Auditing Ecommerce Sites with XPaths
Sometimes, stakeholders will need product level audits on an ad hoc basis. Sometimes this covers just categories of products, but sometimes it may be the entire site.
Using the XPath extraction method we learned earlier in this article, we can extract all types of data including:
And much more
This can help identify products that may be lacking valuable information within your ecommerce site.
The cool thing about Screaming Frog is that you can extract multiple data points to stretch your audits even further.
3. Auditing Blogs with XPaths
This is a more common method for using XPaths. Screaming Frog allows you to set parameters to crawl specific subfolders of sites, such as blogs.
However, using XPaths, we can go beyond simple meta data and grab valuable insights to help identify content gap opportunities.
Categories & Tags
One of the most common ways SEO professionals use XPaths for blog auditing is scraping categories and tags.
This is important because it helps us group related blogs together, which can help us identify content cannibalization and gaps.
This is typically the first step in any blog audit.
This step is a bit more Excel-focused and advanced. How this works, is you set up an XPath extraction to pull the body copy out of each blog.
Fair warning, this may drastically increase your crawl time.
Whenever you export this crawl into Excel, you will get all of the body text in one cell. I highly recommend that you disable text wrapping, or your spreadsheet will look terrifying.
Next, in the column to the right of your extracted body copy, enter the following formula:
In this formula, A1 equals the cell of the body copy.
To scale your efforts, you can have your “keyword” equal the cell that contains your category or tag. However, you may consider adding multiple columns of keywords to get a more accurate and robust picture of your blogging performance.
Over the almost 16-years of covering search, specifically what Googlers have said in terms of SEO and ranking topics, I have seen my share of contradictory statements. Google’s ranking algorithms are complex, and the way one Googler explains something might sound contradictory to how another Googler talks about it. In reality, they are typically talking about different things or nuances.
Some of it is semantics, some of it is being literal in how one person might explain something while another person speaks figuratively. Some of it is being technically correct versus trying to dumb something down for general practitioners or even non-search marketers to understand. Some of it is that the algorithm can change over the years, so what was true then has evolved.
Does it matter if something is or is not a ranking factor? It can be easy to get wrapped up in details that end up being distractions. Ultimately, SEOs, webmasters, site owners, publishers and those that produce web pages need to care more about providing the best possible web site and web page for the topic. You do not want to chase algorithms and racing after what is or is not a ranking factor. Google’s stated aim is to rank the most relevant results to keep users happy and coming back to the search engine. How Google does that changes over time. It releases core updates, smaller algorithm updates, index updates and more all the time.
For SEOs, the goal is to make sure your pages offer the most authoritative and relevant content for the given query and can be accessed by search crawlers.
When it is and is not a ranking factor. An example of Googlers seeming to contradict themselves popped this week.
Gary Illyes from Google said at Pubcon Thursday that content accuracy is a ranking factor. That raised eyebrows because in past Google has seemed to say content accuracy is not a ranking factor. Last month Google’s Danny Sullivan said, “Machines can’t tell the ‘accuracy’ of content. Our systems rely instead on signals we find align with relevancy of topic and authority.” One could interpret that to mean that if Google cannot tell the accuracy of content, that it would be unable to use accuracy as a ranking factor.
Upon closer look at the context of Illyes comments this week, it’s clear he’s getting at the second part of Sullivan’s comment about using signals to understand “relevancy of topic and authority.” SEO Marie Haynes captured more of the context of Illyes’ comment.
Illyes was talking about YMYL (your money, your life) content. He added that Google goes through “great lengths to surface reputable and trustworthy sources.”
He didn’t outright say Google’s systems are able to tell if a piece of content is factually accurate or not. He implied Google uses multiple signals, like signals that determine reputations and trustworthiness, as a way to infer accuracy.
So is content accuracy a ranking factor? Yes and no. It depends if you are being technical, literal, figurative or explanatory. When I covered the different messaging around content accuracy on my personal site, Sullivan pointed out the difference, he said on Twitter “We don’t know if content is accurate” but “we do look for signals we believe align with that.”
It’s the same with whether there is an E-A-T score. Illyes said there is no E-A-T score. That is correct, technically. But Google has numerous algorithms and ranking signals it uses to figure out E-A-T as an overall theme. Sullivan said on Twitter, “Is E-A-T a ranking factor? Not if you mean there’s some technical thing like with speed that we can measure directly. We do use a variety of signals as a proxy to tell if content seems to match E-A-T as humans would assess it. In that regard, yeah, it’s a ranking factor.”
You can see the dual point Sullivan is making here.
The minutiae. When you have people like me, who for almost 16 years, analyze and scrutinize every word, tweet, blog post or video that Google produces, it can be hard for a Google representative to always convey the exact clear message at every point. Sometimes it is important to step back, look at the bigger picture, and ask yourself, Why is this Googler saying this or not saying that?
Why we should care. It is important to look at long term goals, and as I said above, not chase the algorithm or specific ranking factors but focus on the ultimate goals of your business (money). Produce content and web pages that Google would be proud to rank at the top of the results for a given query and other sites will want to source and link to. And above all, do whatever you can to make the best possible site for users — beyond what your competitors produce.
About The Author
Barry Schwartz is Search Engine Land’s News Editor and owns RustyBrick, a NY based web consulting firm. He also runs Search Engine Roundtable, a popular search blog on SEM topics.