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66 Content Marketing Statistics for 2022

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66 Content Marketing Statistics for 2022


According to a recent study, only 10% of marketers don’t use content marketing (spoiler alert). So for the remaining majority of marketers, and perhaps the unconvinced minority, we’ve curated, vetted, and categorized a list of up-to-date statistics that will help you make the best of 2022.

In this article, we’ll highlight the following:

Top content marketing statistics

Here are the most interesting content marketing statistics we think you should know.

  1. 82% of marketers are actively investing in content marketing, 10% report not using content marketing, and 8% are unsure if their company uses content marketing (HubSpot).
  2. 43% of B2B marketers have a documented content marketing strategy, and 60% of the most successful B2B marketers have a documented content marketing strategy (Content Marketing Institute).
  3. 69% of marketers actively invest time in SEO (HubSpot).
  4. 60% of marketers report that content marketing generates demand/leads. In addition, 70% of marketers say that content marketing helps to educate the audience, and 60% say that it helps build loyalty with existing clients/customers (CMI).
  5. Video is the primary form of marketing media being created in 2021, followed by blogs (used by more than half of marketing teams), then infographics (HubSpot).
  6. 73% of people admit to skimming blog posts, while 27% consume them thoroughly (HubSpot).
  7. 71% of marketers say that targeting strategic keywords is their top SEO tactic  (HubSpot).
  8. 51% of the businesses that invest in content marketing publish content every day (The Manifest).
  9. Although 32% of respondents say they are overwhelmed by the amount of content available, a majority (44%) say they typically consume three to five pieces of content before engaging with a vendor (DemandGen).
  10. 69% of respondents prefer to learn about a product or service from a short video. 18% prefer to read a text-based article, website, or post. 4% prefer to view an infographic. 3% prefer to download an ebook or manual. 3% prefer to attend a webinar or pitch. 2% prefer to receive a sales call or demo (Wyzowl).
  11. 81% of marketers view content as a core business strategy (CMI).

Content marketing strategy statistics

As you can see in the previous section, most successful content marketers have a documented content strategy. Here are some statistics to inspire your strategy.

  1. The top three primary goals of creating content are boosting sales, building relationships with customers, and increasing brand awareness (eMarketer).
  2. Content marketing generates over 3x as many leads as outbound marketing and costs 62% less (Demand Metric).
  3. 72% of the most successful marketers in North America measure the ROI of their content marketing (eMarketer).

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B2B content marketing statistics

Here’s what B2B marketers say about their content marketing efforts.

  1. Only 4% of B2B marketers don’t plan to develop a content marketing strategy (CMI).
  2. 87% of B2B marketers prioritize the audience’s informational needs over the organization’s sales/promotional messages (CMI).
  3. Content creation is the most outsourced content marketing activity among B2B marketers (CMI).
  4. The top three organic content distribution channels used by B2B marketers are social media, email, and their organization’s blog/website (CMI).
  5. LinkedIn is used by 96% of B2B content marketers (CMI).
  6. Only 28% of B2B marketers don’t use paid content distribution channels (CMI).
  7. 78% of B2B marketers employ keyword research for SEO while creating content (CMI).

B2C content marketing statistics

Let’s see how answers given by B2C content marketers compare to their B2B counterparts.

  1. Only 6% of B2C marketers don’t plan to develop a content marketing strategy (CMI).
  2. Content creation is the most outsourced content marketing activity among B2C marketers (CMI).
  3. The top three organic content distribution channels used by B2C marketers are social media, email, and their organization’s blog/website (CMI).
  4. The top three most often used content formats by B2C marketers are blog posts/short articles, email newsletters, and videos (CMI).
  5. B2C marketers who use at least two organic social media platforms report that Facebook (59%) and Instagram (21%) produce the best overall content marketing results (CMI).
  6. Only 28% of B2C marketers don’t use paid content distribution channels (CMI).
  7. 73% of B2C marketers employ keyword research for SEO while creating content (CMI).

Organic search statistics

As our collected statistics have already proven, most content marketers do keyword research and invest in SEO. In other words, they invest in organic search. Let’s see what else we can find about this marketing channel.

  1. 90.63% of pages get no organic search traffic from Google (Ahrefs).
    90.63% of pages get no organic search traffic from Google
  2. 68% of online experiences begin with a search engine (Brightedge).
  3. 71% of B2B researchers start their research with generic search instead of branded search (Google).
  4. 53% of shoppers say they always do research before a purchase to ensure they are making the best possible choice (Google).
  5. Only 5.7% of pages will rank in the top 10 search results within a year of publication (Ahrefs).
  6. Almost two-thirds of global online search comes from mobile devices (Perficient).
  7. 69% of marketers actively invest in SEO (HubSpot).
  8. The top three most often used metrics for SEO are keyword ranking, organic traffic, and time spent on page (HubSpot).
  9. Generally speaking, the more backlinks a page has, the more organic traffic it gets from Google (Ahrefs).
  10. The average #1 ranking page will also rank in the top 10 for nearly 1,000 other relevant keywords (Ahrefs).
    Most top-ranking pages also rank for hundreds of other keywords
  11. There’s no correlation between Flesch Reading Ease scores and ranking positions (Ahrefs).
    There's no correlation between flesch reading ease scores and ranking positions

Handpicked statistics for this cornerstone of many content strategies.

  1. People rarely read online. They’re far more likely to scan than read word for word. They simply want to pick out the information that is most pertinent to their current needs (Nielsen).
  2. 70% of people rather get information from blogs than traditional advertisements (Demand Metric).
  3. To date, there are more than 600 million blogs out of 1.9 billion websites in the world. Their authors account for over 6 million blog posts daily, or over 2.5 billion annually (hosting tribunal).
  4. How-to articles are the most popular content formats (77%), followed by news and trends (49%), and guides and ebooks (47%) (Statista).
  5. Only one-third of bloggers regularly check their blogs’ traffic analytics (Statista).
  6. Engagement starts to drop for posts with a reading time longer than seven minutes (Medium).
    Peoples' attention drops when a post is too long

As reported by Hubspot, video is the primary form of marketing media being created in 2021. It seems that video marketing is no longer an option.

  1. 70% of viewers bought from a brand after seeing it on YouTube (Google).
  2. 79% of people say they’ve been convinced to buy or download a piece of software or app by watching a video (Wyzowl).
  3. 50.9% of B2B decision-makers use YouTube to research purchases (Hootsuite).
  4. YouTube is the second-most visited website in the U.S. by organic traffic (Ahrefs).
  5. YouTube reaches more 18- to 49-year-olds in an average week than all cable TV networks combined (Google).
  6. Video viewers say relating to their passions is 3X more important than content featuring famous actors (Google).
  7. Video viewers say relating to their passions is 1.6X more important than content with high production quality (Google).
  8. 86% of businesses use video as a marketing tool (Wyzowl).
  9. 91% of marketers feel the pandemic has made video more important for brands (Wyzowl).
  10. 96% of people have watched an explainer video to learn more about a product or service (Wyzowl).
  11. 85% of people want to see more videos from brands in 2021 (Wyzowl).
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Brands like Slack, Shopify, and Basecamp have already invested in creating a branded podcast. These statistics show that marketers should at least consider advertising on podcasts.

  1. Podcast ad spending in the U.S. is expected to reach $1.74B in 2022, a 23% increase from 2021 (Statista).
  2. 57% of Americans listen to podcasts (Edison Research).
  3. 80% of podcast listeners listen to all or most of each episode (Podcast Insights).
  4. Weekly podcast listeners tune in to an average of eight podcasts per week (Edison Research).
  5. Each week in America, there are more podcast listeners than Netflix account holders (Edison Research).

Other interesting statistics

Is visual content important? Is there something like the best day to publish? How do people decide what link to click? Find out below.

  1. People following directions with text and illustrations do 323% better than people following directions without illustrations (W.H Levie, H.Lentz).
  2. The majority of marketers surveyed say that visual content is a key component of their marketing strategy. 64% say that visuals are either essential or very important. Only 9.6% don’t require visuals for their content marketing (Venngage).
  3. There’s no “best day” to publish a new piece of content. Social shares are distributed evenly among posts published on different days of the week (Backlinko).
  4. The average time a reader allocates a newsletter after opening it is only 51 seconds. Participants of the study fully read only 19% of newsletters (Nielsen).
  5. When deciding which links to click on the web, users choose those with the highest information scent, which is a mix of cues they get from the link label, the context in which the link is shown, and their prior experiences (Nielsen).
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Final thoughts

I hope you’ve found valuable insight in the above collection of statistics. After all, it’s always a good idea to look for data-driven answers to your marketing hypotheses.

But let’s remember that it’s wise to take any statistic with a grain of salt. Statistics are generalizations of only a portion of the reality around us. Also, they aren’t methodologically sound all of the time: small sample sizes, p‑hacking, and spurious correlations are quite common.

So if you’ve just read a piece of data that contradicts your professional marketing experience, don’t throw away your content strategy just yet. Instead, dig deeper.

Finally, if you want to learn more about content marketing, we’ve got a few guides ready for you:

Got questions? Ping me on Twitter.





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Are Contextual Links A Google Ranking Factor?

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Are Contextual Links A Google Ranking Factor?


Inbound links are a ranking signal that can vary greatly in terms of how they’re weighted by Google.

One of the key attributes that experts say can separate a high value link from a low value link is the context in which it appears.

When a link is placed within relevant content, it’s thought to have a greater impact on rankings than a link randomly inserted within unrelated text.

Is there any bearing to that claim?

Let’s dive deeper into what has been said about contextual links as a ranking factor to see whether there’s any evidence to support those claims.

The Claim: Contextual Links Are A Ranking Factor

A “contextual link” refers to an inbound link pointing to a URL that’s relevant to the content in which the link appears.

When an article links to a source to provide additional context for the reader, for example, that’s a contextual link.

Contextual links add value rather than being a distraction.

They should flow naturally with the content, giving the reader some clues about the page they’re being directed to.

Not to be confused with anchor text, which refers to the clickable part of a link, a contextual link is defined by the surrounding text.

A link’s anchor text could be related to the webpage it’s pointing to, but if it’s surrounded by content that’s otherwise irrelevant then it doesn’t qualify as a contextual link.

Contextual links are said to be a Google ranking factor, with claims that they’re weighted higher by the search engine than other types of links.

One of the reasons why Google might care about context when it comes to links is because of the experience it creates for users.

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When a user clicks a link and lands on a page related to what they were previously looking at, it’s a better experience than getting directed to a webpage they aren’t interested in.

Modern guides to link building all recommend getting links from relevant URLs, as opposed to going out and placing links anywhere that will take them.

There’s now a greater emphasis on quality over quantity when it comes to link building, and a link is considered higher quality when its placement makes sense in context.

One high quality contextual link can, in theory, be worth more than multiple lower quality links.

That’s why experts advise site owners to gain at least a few contextual links, as that will get them further than building dozens of random links.

If Google weights the quality of links higher or lower based on context, it would mean Google’s crawlers can understand webpages and assess how closely they relate to other URLs on the web.

Is there any evidence to support this?

The Evidence For Contextual Links As A Ranking Factor

Evidence in support of contextual links as a ranking factor can be traced back to 2012 with the launch of the Penguin algorithm update.

Google’s original algorithm, PageRank, was built entirely on links. The more links pointing to a website, the more authority it was considered to have.

Websites could catapult their site up to the top of Google’s search results by building as many links as possible. It didn’t matter if the links were contextual or arbitrary.

Google’s PageRank algorithm wasn’t as selective about which links it valued (or devalued) over others until it was augmented with the Penguin update.

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Penguin brought a number of changes to Google’s algorithm that made it more difficult to manipulate search rankings through spammy link building practices.

In Google’s announcement of the launch of Penguin, former search engineer Matt Cutts highlighted a specific example of the link spam it’s designed to target.

This example depicts the exact opposite of a contextual link, with Cutts saying:

“Here’s an example of a site with unusual linking patterns that is also affected by this change. Notice that if you try to read the text aloud you’ll discover that the outgoing links are completely unrelated to the actual content, and in fact, the page text has been “spun” beyond recognition.”

A contextual link, on the other hand, looks like the one a few paragraphs above linking to Google’s blog post.

Links with context share the following characteristics:

  • Placement fits in naturally with the content.
  • Linked URL is relevant to the article.
  • Reader knows where they’re going when they click on it.

All of the documentation Google has published about Penguin over the years is the strongest evidence available in support of contextual links as a ranking factor.

See: A Complete Guide to the Google Penguin Algorithm Update

Google will never outright say “contextual link building is a ranking factor,” however, because the company discourages any deliberate link building at all.

As Cutts adds at the end of his Penguin announcement, Google would prefer to see webpages acquire links organically:

“We want people doing white hat search engine optimization (or even no search engine optimization at all) to be free to focus on creating amazing, compelling web sites.”

Contextual Links Are A Ranking Factor: Our Verdict

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Contextual links are probably a Google ranking factor.

A link is weighted higher when it’s used in context than if it’s randomly placed within unrelated content.

But that doesn’t necessarily mean links without context will negatively impact a site’s rankings.

External links are largely outside a site owner’s control.

If a website links to you out of context it’s not a cause for concern, because Google is capable of ignoring low value links.

On the other hand, if Google detects a pattern of unnatural links, then that could count against a site’s rankings.

If you have actively engaged in non-contextual link building in the past, it may be wise to consider using the disavow tool.


Featured Image: Paulo Bobita/Search Engine Journal





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Is It A Google Ranking Factor?

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Is It A Google Ranking Factor?


Latent semantic indexing (LSI) is an indexing and information retrieval method used to identify patterns in the relationships between terms and concepts.

With LSI, a mathematical technique is used to find semantically related terms within a collection of text (an index) where those relationships might otherwise be hidden (or latent).

And in that context, this sounds like it could be super important for SEO.

Right?

After all, Google is a massive index of information, and we’re hearing all kinds of things about semantic search and the importance of relevance in the search ranking algorithm.

If you’ve heard rumblings about latent semantic indexing in SEO or been advised to use LSI keywords, you aren’t alone.

But will LSI actually help improve your search rankings? Let’s take a look.

The Claim: Latent Semantic Indexing As A Ranking Factor

The claim is simple: Optimizing web content using LSI keywords helps Google better understand it and you’ll be rewarded with higher rankings.

Backlinko defines LSI keywords in this way:

“LSI (Latent Semantic Indexing) Keywords are conceptually related terms that search engines use to deeply understand content on a webpage.”

By using contextually related terms, you can deepen Google’s understanding of your content. Or so the story goes.

That resource goes on to make some pretty compelling arguments for LSI keywords:

  • Google relies on LSI keywords to understand content at such a deep level.”
  • LSI Keywords are NOT synonyms. Instead, they’re terms that are closely tied to your target keyword.”
  • Google doesn’t ONLY bold terms that exactly match what you just searched for (in search results). They also bold words and phrases that are similar. Needless to say, these are LSI keywords that you want to sprinkle into your content.”

Does this practice of “sprinkling” terms closely related to your target keyword help improve your rankings via LSI?

The Evidence For LSI As A Ranking Factor

Relevance is identified as one of five key factors that help Google determine which result is the best answer for any given query.

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As Google explains is its How Search Works resource:

“To return relevant results for your query, we first need to establish what information you’re looking forーthe intent behind your query.”

Once intent has been established:

“…algorithms analyze the content of webpages to assess whether the page contains information that might be relevant to what you are looking for.”

Google goes on to explain that the “most basic signal” of relevance is that the keywords used in the search query appear on the page. That makes sense – if you aren’t using the keywords the searcher is looking for, how could Google tell you’re the best answer?

Now, this is where some believe LSI comes into play.

If using keywords is a signal of relevance, using just the right keywords must be a stronger signal.

There are purpose-build tools dedicated to helping you find these LSI keywords, and believers in this tactic recommend using all kinds of other keyword research tactics to identify them, as well.

The Evidence Against LSI As A Ranking Factor

Google’s John Mueller has been crystal clear on this one:

“…we have no concept of LSI keywords. So that’s something you can completely ignore.”

There’s a healthy skepticism in SEO that Google may say things to lead us astray in order to protect the integrity of the algorithm. So let’s dig in here.

First, it’s important to understand what LSI is and where it came from.

Latent semantic structure emerged as a methodology for retrieving textual objects from files stored in a computer system in the late 1980s. As such, it’s an example of one of the earlier information retrieval (IR) concepts available to programmers.

As computer storage capacity improved and electronically available sets of data grew in size, it became more difficult to locate exactly what one was looking for in that collection.

Researchers described the problem they were trying to solve in a patent application filed September 15, 1988:

“Most systems still require a user or provider of information to specify explicit relationships and links between data objects or text objects, thereby making the systems tedious to use or to apply to large, heterogeneous computer information files whose content may be unfamiliar to the user.”

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Keyword matching was being used in IR at the time, but its limitations were evident long before Google came along.

Too often, the words a person used to search for the information they sought were not exact matches for the words used in the indexed information.

There are two reasons for this:

  • Synonymy: the diverse range of words used to describe a single object or idea results in relevant results being missed.
  • Polysemy: the different meanings of a single word results in irrelevant results being retrieved.

These are still issues today, and you can imagine what a massive headache it is for Google.

However, the methodologies and technology Google uses to solve for relevance long ago moved on from LSI.

What LSI did was automatically create a “semantic space” for information retrieval.

As the patent explains, LSI treated this unreliability of association data as a statistical problem.

Without getting too into the weeds, these researchers essentially believed that there was a hidden underlying latent semantic structure they could tease out of word usage data.

Doing so would reveal the latent meaning and enable the system to bring back more relevant results – and only the most relevant results – even if there’s no exact keyword match.

Here’s what that LSI process actually looks like:

Image created by author, January 2022

And here’s the most important thing you should note about the above illustration of this methodology from the patent application: there are two separate processes happening.

First, the collection or index undergoes Latent Semantic Analysis.

Second, the query is analyzed and the already-processed index is then searched for similarities.

And that’s where the fundamental problem with LSI as a Google search ranking signal lies.

Google’s index is massive at hundreds of billions of pages, and it’s growing constantly.

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Each time a user inputs a query, Google is sorting through its index in a fraction of a second to find the best answer.

Using the above methodology in the algorithm would require that Google:

  1. Recreate that semantic space using LSA across its entire index.
  2. Analyze the semantic meaning of the query.
  3. Find all similarities between the semantic meaning of the query and documents in the semantic space created from analyzing the entire index.
  4. Sort and rank those results.

That’s a gross oversimplification, but the point is that this isn’t a scalable process.

This would be super useful for small collections of information. It was helpful for surfacing relevant reports inside a company’s computerized archive of technical documentation, for example.

The patent application illustrates how LSI works using a collection of nine documents. That’s what it was designed to do. LSI is primitive in terms of computerized information retrieval.

Latent Semantic Indexing As A Ranking Factor: Our Verdict

Latent Semantic Indexing (LSI): Is It A Google Ranking Factor?

While the underlying principles of eliminating noise by determining semantic relevance have surely informed developments in search ranking since LSA/LSI was patented, LSI itself has no useful application in SEO today.

It hasn’t been ruled out completely, but there is no evidence that Google has ever used LSI to rank results. And Google definitely isn’t using LSI or LSI keywords today to rank search results.

Those who recommend using LSI keywords are latching on to a concept they don’t quite understand in an effort to explain why the ways in which words are related (or not) is important in SEO.

Relevance and intent are foundational considerations in Google’s search ranking algorithm.

Those are two of the big questions they’re trying to solve for in surfacing the best answer for any query.

Synonymy and polysemy are still major challenges.

Semantics – that is, our understanding of the various meanings of words and how they’re related – is essential in producing more relevant search results.

But LSI has nothing to do with that.


Featured Image: Paulo Bobita/Search Engine Journal





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What Is a Google Broad Core Algorithm Update?

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What Is A Google Broad Core Algorithm Update?


When Google announces a broad core algorithm update, many SEO professionals find themselves asking what exactly changed (besides their rankings).

Google’s acknowledgment of core updates is always vague and doesn’t provide much detail other than to say the update occurred.

The SEO community is typically notified about core updates via the same standard tweets from Google’s Search Liaison.

There’s one announcement from Google when the update begins rolling out, and one on its conclusion, with few additional details in between (if any).

This invariably leaves SEO professionals and site owners asking many questions with respect to how their rankings were impacted by the core update.

To gain insight into what may have caused a site’s rankings to go up, down, or stay the same, it helps to understand what a broad core update is and how it differs from other types of algorithm updates.

After reading this article you’ll have a better idea of what a core update is designed to do, and how to recover from one if your rankings were impacted.

So, What Exactly Is A Core Update?

First, let me get the obligatory “Google makes hundreds of algorithm changes per year, often more than one per day” boilerplate out of the way.

Many of the named updates we hear about (Penguin, Panda, Pigeon, Fred, etc.) are implemented to address specific faults or issues in Google’s algorithms.

In the case of Penguin, it was link spam; in the case of Pigeon, it was local SEO spam.

They all had a specific purpose.

In these cases, Google (sometimes reluctantly) informed us what they were trying to accomplish or prevent with the algorithm update, and we were able to go back and remedy our sites.

A core update is different.

The way I understand it, a core update is a tweak or change to the main search algorithm itself.

You know, the one that has between 200 and 500 ranking factors and signals (depending on which SEO blog you’re reading today).

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What a core update means to me is that Google slightly tweaked the importance, order, weights, or values of these signals.

Because of that, they can’t come right out and tell us what changed without revealing the secret sauce.

The simplest way to visualize this would be to imagine 200 factors listed in order of importance.

Now imagine Google changing the order of 42 of those 200 factors.

Rankings would change, but it would be a combination of many things, not due to one specific factor or cause.

Obviously, it isn’t that simple, but that’s a good way to think about a core update.

Here’s a purely made up, slightly more complicated example of what Google wouldn’t tell us:

“In this core update, we increased the value of keywords in H1 tags by 2%, increased the value of HTTPS by 18%, decreased the value of keyword in title tag by 9%, changed the D value in our PageRank calculation from .85 to .70, and started using a TF-iDUF retrieval method for logged in users instead of the traditional TF-PDF method.”

(I swear these are real things. I just have no idea if they’re real things used by Google.)

For starters, many SEO pros wouldn’t understand it.

Basically, it means Google may have changed the way they calculate term importance on a page, or the weighing of links in PageRank, or both, or a whole bunch of other factors that they can’t talk about (without giving away the algorithm).

Put simply: Google changed the weight and importance of many ranking factors.

That’s the simple explanation.

At its most complex form, Google ran a new training set through their machine learning ranking model and quality raters picked this new set of results as more relevant than the previous set, and the engineers have no idea what weights changed or how they changed because that’s just how machine learning works.

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(We all know Google uses quality raters to rate search results. These ratings are how they choose one algorithm change over another – not how they rate your site. Whether they feed this into machine learning is anybody’s guess. But it’s one possibility.)

It’s likely some random combination of weighting delivered more relevant results for the quality raters, so they tested it more, the test results confirmed it, and they pushed it live.

How Can You Recover From A Core Update?

Unlike a major named update that targeted specific things, a core update may tweak the values of everything.

Because websites are weighted against other websites relevant to your query (engineers call this a corpus) the reason your site dropped could be entirely different than the reason somebody else’s increased or decreased in rankings.

To put it simply, Google isn’t telling you how to “recover” because it’s likely a different answer for every website and query.

It all depends on what everybody else trying to rank for your query is doing.

Does every one of them but you have their keyword in the H1 tag? If so then that could be a contributing factor.

Do you all do that already? Then that probably carries less weight for that corpus of results.

It’s very likely that this algorithm update didn’t “penalize” you for something at all. It most likely just rewarded another site more for something else.

Maybe you were killing it with internal anchor text and they were doing a great job of formatting content to match user intent – and Google shifted the weights so that content formatting was slightly higher and internal anchor text was slightly lower.

(Again, hypothetical examples here.)

In reality, it was probably several minor tweaks that, when combined, tipped the scales slightly in favor of one site or another (think of our reordered list here).

See also  What Is a Google Broad Core Algorithm Update?

Finding that “something else” that is helping your competitors isn’t easy – but it’s what keeps SEO professionals in the business.

Next Steps And Action Items

Rankings are down after a core update – now what?

Your next step is to gather intel on the pages that are ranking where your site used to be.

Conduct a SERP analysis to find positive correlations between pages that are ranking higher for queries where your site is now lower.

Try not to overanalyze the technical details, such as how fast each page loads or what their core web vitals scores are.

Pay attention to the content itself. As you go through it, ask yourself questions like:

  • Does it provide a better answer to the query than your article?
  • Does the content contain more recent data and current stats than yours?
  • Are there pictures and videos that help bring the content to life for the reader?

Google aims to serve content that provides the best and most complete answers to searchers’ queries. Relevance is the one ranking factor that will always win out over all others.

Take an honest look at your content to see if it’s as relevant today as it was prior to the core algorithm update.

From there you’ll have an idea of what needs improvement.

The best advice for conquering core updates?

Keep focusing on:

  • User intent.
  • Quality content.
  • Clean architecture.
  • Google’s guidelines.

Finally, don’t stop improving your site once you reach Position 1, because the site in Position 2 isn’t going to stop.

Yeah, I know, it’s not the answer anybody wants and it sounds like Google propaganda. I swear it’s not.

It’s just the reality of what a core update is.

Nobody said SEO was easy.

More resources:


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