Is IP Address A Google Ranking Factor? via @sejournal, @kristileilani

Does the IP address of your website’s server affect your rankings in search results? According to some sources around the internet, your IP address is a ranking signal used by Google.

But does your IP address have the potential to help or harm your rankings in search? Continue reading to learn whether IP addresses are a Google ranking factor.

The Claim: IP Address As A Ranking Factor

Articles on the internet from reputable marketing sites claim that Google has over 200 “known” ranking factors.

These lists often include statements about flagged IP addresses affecting rankings or higher-value links because they are from separate C-class IP addresses.

IP address from hubspotScreenshot from HubSpot.com, June 2022

Fortunately, these lists sparked numerous conversations with Google employees about the validity of IP addresses as ranking factors in Google’s algorithm.

[Ebook:] The Complete Guide To Google Ranking Factors

The Evidence Against IP Address As A Ranking Factor

In 2010, Matt Cutts, former head of Google’s webspam team, was asked if the ranking of a client’s website would be affected by spammy websites on the same server.

His response:

“On the list of things that I worry about, that would not be near the top. So I understand, and Google understands that shared web hosting happens. You can’t really control who else is on that IP address or class c subnet.”

Ultimately, Google decided if they took action on an IP address or Class C subnet, the spammers would just move to another IP address. Therefore, it wouldn’t be the most efficient way to tackle the issue.

Cutts did note a specific exception, where an IP address had 26,000 spam sites and one non-spammy site that invited more scrutiny but reiterated that this was an exceptional outlier.

In 2011, a tweet from Kaspar Szymanski, another former member of Google’s webspam team, noted that Google has the right to take action when free hosts have been massively spammed.

In 2016, during a Google Webmaster Central Office Hours, John Mueller, Search Advocate at Google, was asked if having all of a group’s websites on the same c block of IP addresses was a problem.

He answered:

“No, that’s perfectly fine. So that’s not something where you artificially need to buy IP address blocks to just shuffle things around.

And especially if you are on a CDN, then maybe you’ll end up on an IP address block that’s used by other companies. Or if you’re on shared hosting, then these things happen. That’s not something you need to artificially move around.”

In March 2018, Mueller was asked if an IP change with a different geo-location would affect SEO. He responded:

“If you move to a server in a different location? Usually not. We get enough geotargeting information otherwise, e.g., from the TLD & geotargeting settings in Search Console.”

A few months later, Mueller replied to a tweet asking if Google still counted bad neighborhoods as a ranking signal and if a dedicated IP was necessary.

“Shared IP addresses are fine for search! Lots of hosting / CDN environments use them.”

In October 2018, Mueller was asked if the IP address location mattered for a site’s rankings. His response was simply, “Nope.”

A few tweets later, within the same Twitter thread, another user commented that IP addresses mattered regarding backlinks. Mueller again responded with a simple “Nope.”

In June 2019, Mueller received a question about Google Search Console showing a website’s IP address instead of a domain name. His answer:

“Usually, getting your IP addresses indexed is a bad idea. IP addresses are often temporary.”

He suggested that the user ensure the IP address redirects to their domain.

A few months later, when asked if links from IP addresses were bad, Mueller tweeted:

“Links from IP addresses are absolutely fine. Most of the time, it means the server wasn’t set up well (we canonicalized to the IP address rather than the hostname, easy to fix with redirects & rel=canonical), but that’s just a technical detail. It doesn’t mean they’re bad.”

In early 2020, when asked about getting links from different IP addresses, Mueller said that the bad part was the user was making the backlinks themselves – not the IP addresses.

Then, in June, Mueller was asked what happens if a website on an IP address bought links. Would there be an IP-level action taken?

“Shared hosting & CDNs on a single IP is really common. Having some bad sites on an IP doesn’t make everything on that IP bad.”

In September, during a discussion about bad neighborhoods affecting search rankings, Mueller stated:

“I’m not aware of any ranking algorithm that would take IPs like that into account. Look at Blogger. There are great sites that do well (ignoring on-page limitations, etc.), and there are terrible sites hosted there. It’s all the same infrastructure, the same IP addresses.”

In November, Gary Illyes, Chief of Sunshine and Happiness at Google, shared a fun fact.

“Fun fact: changing a site’s underlaying infrastructure like servers, IPs, you name it, can change how fast and often Googlebot crawls from said site. That’s because it actually detects that something changed, which prompts it to relearn how fast and often it can crawl.”

While it’s interesting information, it seems to impact crawling and not ranking. Crawling is, of course, required to rank, but crawling is not a ranking factor.

In 2021, a Twitter user asked if IP canonicalization could positively affect SEO. Meuller replied:

“Unless folks are linking to your site’s IP address (which would be unexpected), this wouldn’t have any effect on SEO.”

Later in December, when asked if an IP address instead of a hostname looks unusual when Google evaluates a link’s quality, Meuller stated, “Ip addresses are fine. The internet has tons of them.”

If you’re worried about your IP address or hosting company, the consensus seems to be: Don’t worry.

Get More Google Ranking Factor Insights.

Our Verdict: IP Address Is Not A Ranking Factor Anymore

Is IP Address A Google Ranking Factor?

Maybe in the past, Google experimented with IP-level actions against spammy websites.

But it must have found this ineffective because we are not seeing any confirmation from Google representatives that IP addresses, shared hosting, and bad neighborhoods are a part of the algorithm.

Therefore, we can conclude for now that IP addresses are not a ranking factor.


Featured Image: Paulo Bobita/Search Engine Journal

Ranking Factors: Fact Or Fiction? Let’s Bust Some Myths! [Ebook]

Transitioning From Excel To Python: Essential Functions For SEO Data Analysis via @sejournal, @williamjnye

Learning to code, whether with PythonJavaScript, or another programming language, has a whole host of benefits, including the ability to work with larger datasets and automate repetitive tasks.

But despite the benefits, many SEO professionals are yet to make the transition – and I completely understand why! It isn’t an essential skill for SEO, and we’re all busy people.

If you’re pressed for time, and you already know how to accomplish a task within Excel or Google Sheets, then changing tack can feel like reinventing the wheel.

When I first started coding, I initially only used Python for tasks that I couldn’t accomplish in Excel – and it’s taken several years to get to the point where it’s my defacto choice for data processing.

Looking back, I’m incredibly glad that I persisted, but at times it was a frustrating experience, with many an hour spent scanning threads on Stack Overflow.

This post is designed to spare other SEO pros the same fate.

Within it, we’ll cover the Python equivalents of the most commonly used Excel formulas and features for SEO data analysis – all of which are available within a Google Colab notebook linked in the summary.

Specifically, you’ll learn the equivalents of:

  • LEN.
  • Drop Duplicates.
  • Text to Columns.
  • SEARCH/FIND.
  • CONCATENATE.
  • Find and Replace.
  • LEFT/MID/RIGHT.
  • IF.
  • IFS.
  • VLOOKUP.
  • COUNTIF/SUMIF/AVERAGEIF.
  • Pivot Tables.

Amazingly, to accomplish all of this, we’ll primarily be using a singular library – Pandas – with a little help in places from its big brother, NumPy.

Prerequisites

For the sake of brevity, there are a few things we won’t be covering today, including:

  • Installing Python.
  • Basic Pandas, like importing CSVs, filtering, and previewing dataframes.

If you’re unsure about any of this, then Hamlet’s guide on Python data analysis for SEO is the perfect primer.

Now, without further ado, let’s jump in.

LEN

LEN provides a count of the number of characters within a string of text.

For SEO specifically, a common use case is to measure the length of title tags or meta descriptions to determine whether they’ll be truncated in search results.

Within Excel, if we wanted to count the second cell of column A, we’d enter:

=LEN(A2)
LEN formula excelScreenshot from Microsoft Excel, November 2022

Python isn’t too dissimilar, as we can rely on the inbuilt len function, which can be combined with Pandas’ loc[] to access a specific row of data within a column:

len(df['Title'].loc[0])

In this example, we’re getting the length of the first row in the “Title” column of our dataframe.

len function python
Screenshot of VS Code, November, 2022

Finding the length of a cell isn’t that useful for SEO, though. Normally, we’d want to apply a function to an entire column!

In Excel, this would be achieved by selecting the formula cell on the bottom right-hand corner and either dragging it down or double-clicking.

When working with a Pandas dataframe, we can use str.len to calculate the length of rows within a series, then store the results in a new column:

df['Length'] = df['Title'].str.len()

Str.len is a ‘vectorized’ operation, which is designed to be applied simultaneously to a series of values. We’ll use these operations extensively throughout this article, as they almost universally end up being faster than a loop.

Another common application of LEN is to combine it with SUBSTITUTE to count the number of words in a cell:

=LEN(TRIM(A2))-LEN(SUBSTITUTE(A2," ",""))+1

In Pandas, we can achieve this by combining the str.split and str.len functions together:

df['No. Words'] = df['Title'].str.split().str.len()

We’ll cover str.split in more detail later, but essentially, what we’re doing is splitting our data based upon whitespaces within the string, then counting the number of component parts.

word count PythonScreenshot from VS Code, November 2022

Dropping Duplicates

Excel’s ‘Remove Duplicates’ feature provides an easy way to remove duplicate values within a dataset, either by deleting entirely duplicate rows (when all columns are selected) or removing rows with the same values in specific columns.

Excel drop duplicatesScreenshot from Microsoft Excel, November 2022

In Pandas, this functionality is provided by drop_duplicates.

To drop duplicate rows within a dataframe type:

df.drop_duplicates(inplace=True)

To drop rows based on duplicates within a singular column, include the subset parameter:

df.drop_duplicates(subset='column', inplace=True)

Or specify multiple columns within a list:

df.drop_duplicates(subset=['column','column2'], inplace=True)

One addition above that’s worth calling out is the presence of the inplace parameter. Including inplace=True allows us to overwrite our existing dataframe without needing to create a new one.

There are, of course, times when we want to preserve our raw data. In this case, we can assign our deduped dataframe to a different variable:

df2 = df.drop_duplicates(subset='column')

Text To Columns

Another everyday essential, the ‘text to columns’ feature can be used to split a text string based on a delimiter, such as a slash, comma, or whitespace.

As an example, splitting a URL into its domain and individual subfolders.

Excel drop duplicatesScreenshot from Microsoft Excel, November 2022

When dealing with a dataframe, we can use the str.split function, which creates a list for each entry within a series. This can be converted into multiple columns by setting the expand parameter to True:

df['URL'].str.split(pat='/', expand=True)
str split PythonScreenshot from VS Code, November 2022

As is often the case, our URLs in the image above have been broken up into inconsistent columns, because they don’t feature the same number of folders.

This can make things tricky when we want to save our data within an existing dataframe.

Specifying the n parameter limits the number of splits, allowing us to create a specific number of columns:

df[['Domain', 'Folder1', 'Folder2', 'Folder3']] = df['URL'].str.split(pat='/', expand=True, n=3)

Another option is to use pop to remove your column from the dataframe, perform the split, and then re-add it with the join function:

df = df.join(df.pop('Split').str.split(pat='/', expand=True))

Duplicating the URL to a new column before the split allows us to preserve the full URL. We can then rename the new columns:🐆

df['Split'] = df['URL']

df = df.join(df.pop('Split').str.split(pat='/', expand=True))

df.rename(columns = {0:'Domain', 1:'Folder1', 2:'Folder2', 3:'Folder3', 4:'Parameter'}, inplace=True)
Split pop join functions PythonScreenshot from VS Code, November 2022

CONCATENATE

The CONCAT function allows users to combine multiple strings of text, such as when generating a list of keywords by adding different modifiers.

In this case, we’re adding “mens” and whitespace to column A’s list of product types:

=CONCAT($F$1," ",A2)
concat Excel
Screenshot from Microsoft Excel, November 2022

Assuming we’re dealing with strings, the same can be achieved in Python using the arithmetic operator:

df['Combined] = 'mens' + ' ' + df['Keyword']

Or specify multiple columns of data:

df['Combined'] = df['Subdomain'] + df['URL']
concat PythonScreenshot from VS Code, November 2022

Pandas has a dedicated concat function, but this is more useful when trying to combine multiple dataframes with the same columns.

For instance, if we had multiple exports from our favorite link analysis tool:

df = pd.read_csv('data.csv')
df2 = pd.read_csv('data2.csv')
df3 = pd.read_csv('data3.csv')

dflist = [df, df2, df3]

df = pd.concat(dflist, ignore_index=True)

SEARCH/FIND

The SEARCH and FIND formulas provide a way of locating a substring within a text string.

These commands are commonly combined with ISNUMBER to create a Boolean column that helps filter down a dataset, which can be extremely helpful when performing tasks like log file analysis, as explained in this guide. E.g.:

=ISNUMBER(SEARCH("searchthis",A2)
isnumber search ExcelScreenshot from Microsoft Excel, November 2022

The difference between SEARCH and FIND is that find is case-sensitive.

The equivalent Pandas function, str.contains, is case-sensitive by default:

df['Journal'] = df['URL'].str.contains('engine', na=False)

Case insensitivity can be enabled by setting the case parameter to False:

df['Journal'] = df['URL'].str.contains('engine', case=False, na=False)

In either scenario, including na=False will prevent null values from being returned within the Boolean column.

One massive advantage of using Pandas here is that, unlike Excel, regex is natively supported by this function – as it is in Google sheets via REGEXMATCH.

Chain together multiple substrings by using the pipe character, also known as the OR operator:

df['Journal'] = df['URL'].str.contains('engine|search', na=False)

Find And Replace

Excel’s “Find and Replace” feature provides an easy way to individually or bulk replace one substring with another.

find replace ExcelScreenshot from Microsoft Excel, November 2022

When processing data for SEO, we’re most likely to select an entire column and “Replace All.”

The SUBSTITUTE formula provides another option here and is useful if you don’t want to overwrite the existing column.

As an example, we can change the protocol of a URL from HTTP to HTTPS, or remove it by replacing it with nothing.

When working with dataframes in Python, we can use str.replace:

df['URL'] = df['URL'].str.replace('http://', 'https://')

Or:

df['URL'] = df['URL'].str.replace('http://', '') # replace with nothing

Again, unlike Excel, regex can be used – like with Google Sheets’ REGEXREPLACE:

df['URL'] = df['URL'].str.replace('http://|https://', '')

Alternatively, if you want to replace multiple substrings with different values, you can use Python’s replace method and provide a list.

This prevents you from having to chain multiple str.replace functions:

df['URL'] = df['URL'].replace(['http://', ' https://'], ['https://www.', 'https://www.’], regex=True)

LEFT/MID/RIGHT

Extracting a substring within Excel requires the usage of the LEFT, MID, or RIGHT functions, depending on where the substring is located within a cell.

Let’s say we want to extract the root domain and subdomain from a URL:

=MID(A2,FIND(":",A2,4)+3,FIND("/",A2,9)-FIND(":",A2,4)-3)
left mid right ExcelScreenshot from Microsoft Excel, November 2022

Using a combination of MID and multiple FIND functions, this formula is ugly, to say the least – and things get a lot worse for more complex extractions.

Again, Google Sheets does this better than Excel, because it has REGEXEXTRACT.

What a shame that when you feed it larger datasets, it melts faster than a Babybel on a hot radiator.

Thankfully, Pandas offers str.extract, which works in a similar way:

df['Domain'] = df['URL'].str.extract('.*://?([^/]+)')
str extract PythonScreenshot from VS Code, November 2022

Combine with fillna to prevent null values, as you would in Excel with IFERROR:

df['Domain'] = df['URL'].str.extract('.*://?([^/]+)').fillna('-')

If

IF statements allow you to return different values, depending on whether or not a condition is met.

To illustrate, suppose that we want to create a label for keywords that are ranking within the top three positions.

Excel IFScreenshot from Microsoft Excel, November 2022

Rather than using Pandas in this instance, we can lean on NumPy and the where function (remember to import NumPy, if you haven’t already):

df['Top 3'] = np.where(df['Position'] <= 3, 'Top 3', 'Not Top 3')

Multiple conditions can be used for the same evaluation by using the AND/OR operators, and enclosing the individual criteria within round brackets:

df['Top 3'] = np.where((df['Position'] <= 3) & (df['Position'] != 0), 'Top 3', 'Not Top 3')

In the above, we’re returning “Top 3” for any keywords with a ranking less than or equal to three, excluding any keywords ranking in position zero.

IFS

Sometimes, rather than specifying multiple conditions for the same evaluation, you may want multiple conditions that return different values.

In this case, the best solution is using IFS:

=IFS(B2<=3,"Top 3",B2<=10,"Top 10",B2<=20,"Top 20")
IFS ExcelScreenshot from Microsoft Excel, November 2022

Again, NumPy provides us with the best solution when working with dataframes, via its select function.

With select, we can create a list of conditions, choices, and an optional value for when all of the conditions are false:

conditions = [df['Position'] <= 3, df['Position'] <= 10, df['Position'] <=20]

choices = ['Top 3', 'Top 10', 'Top 20']

df['Rank'] = np.select(conditions, choices, 'Not Top 20')

It’s also possible to have multiple conditions for each of the evaluations.

Let’s say we’re working with an ecommerce retailer with product listing pages (PLPs) and product display pages (PDPs), and we want to label the type of branded pages ranking within the top 10 results.

The easiest solution here is to look for specific URL patterns, such as a subfolder or extension, but what if competitors have similar patterns?

In this scenario, we could do something like this:

conditions = [(df['URL'].str.contains('/category/')) & (df['Brand Rank'] > 0),
(df['URL'].str.contains('/product/')) & (df['Brand Rank'] > 0),
(~df['URL'].str.contains('/product/')) & (~df['URL'].str.contains('/category/')) & (df['Brand Rank'] > 0)]

choices = ['PLP', 'PDP', 'Other']

df['Brand Page Type'] = np.select(conditions, choices, None)

Above, we’re using str.contains to evaluate whether or not a URL in the top 10 matches our brand’s pattern, then using the “Brand Rank” column to exclude any competitors.

In this example, the tilde sign (~) indicates a negative match. In other words, we’re saying we want every brand URL that doesn’t match the pattern for a “PDP” or “PLP” to match the criteria for ‘Other.’

Lastly, None is included because we want non-brand results to return a null value.

np select PythonScreenshot from VS Code, November 2022

VLOOKUP

VLOOKUP is an essential tool for joining together two distinct datasets on a common column.

In this case, adding the URLs within column N to the keyword, position, and search volume data in columns A-C, using the shared “Keyword” column:

=VLOOKUP(A2,M:N,2,FALSE)
vlookup ExcelScreenshot from Microsoft Excel, November 2022

To do something similar with Pandas, we can use merge.

Replicating the functionality of an SQL join, merge is an incredibly powerful function that supports a variety of different join types.

For our purposes, we want to use a left join, which will maintain our first dataframe and only merge in matching values from our second dataframe:

mergeddf = df.merge(df2, how='left', on='Keyword')

One added advantage of performing a merge over a VLOOKUP, is that you don’t have to have the shared data in the first column of the second dataset, as with the newer XLOOKUP.

It will also pull in multiple rows of data rather than the first match in finds.

One common issue when using the function is for unwanted columns to be duplicated. This occurs when multiple shared columns exist, but you attempt to match using one.

To prevent this – and improve the accuracy of your matches – you can specify a list of columns:

mergeddf = df.merge(df2, how='left', on=['Keyword', 'Search Volume'])

In certain scenarios, you may actively want these columns to be included. For instance, when attempting to merge multiple monthly ranking reports:

mergeddf = df.merge(df2, on='Keyword', how='left', suffixes=('', '_october'))
    .merge(df3, on='Keyword', how='left', suffixes=('', '_september'))

The above code snippet executes two merges to join together three dataframes with the same columns – which are our rankings for November, October, and September.

By labeling the months within the suffix parameters, we end up with a much cleaner dataframe that clearly displays the month, as opposed to the defaults of _x and _y seen in the earlier example.

multi merge PythonScreenshot from VS Code, November 2022

COUNTIF/SUMIF/AVERAGEIF

In Excel, if you want to perform a statistical function based on a condition, you’re likely to use either COUNTIF, SUMIF, or AVERAGEIF.

Commonly, COUNTIF is used to determine how many times a specific string appears within a dataset, such as a URL.

We can accomplish this by declaring the ‘URL’ column as our range, then the URL within an individual cell as our criteria:

=COUNTIF(D:D,D2)
Excel countifScreenshot from Microsoft Excel, November 2022

In Pandas, we can achieve the same outcome by using the groupby function:

df.groupby('URL')['URL'].count()
Python groupbyScreenshot from VS Code, November 2022

Here, the column declared within the round brackets indicates the individual groups, and the column listed in the square brackets is where the aggregation (i.e., the count) is performed.

The output we’re receiving isn’t perfect for this use case, though, because it’s consolidated the data.

Typically, when using Excel, we’d have the URL count inline within our dataset. Then we can use it to filter to the most frequently listed URLs.

To do this, use transform and store the output in a column:

df['URL Count'] = df.groupby('URL')['URL'].transform('count')
Python groupby transformScreenshot from VS Code, November 2022

You can also apply custom functions to groups of data by using a lambda (anonymous) function:

df['Google Count'] = df.groupby(['URL'])['URL'].transform(lambda x: x[x.str.contains('google')].count())

In our examples so far, we’ve been using the same column for our grouping and aggregations, but we don’t have to. Similarly to COUNTIFS/SUMIFS/AVERAGEIFS in Excel, it’s possible to group using one column, then apply our statistical function to another.

Going back to the earlier search engine results page (SERP) example, we may want to count all ranking PDPs on a per-keyword basis and return this number alongside our existing data:

df['PDP Count'] = df.groupby(['Keyword'])['URL'].transform(lambda x: x[x.str.contains('/product/|/prd/|/pd/')].count())
Python groupby countifsScreenshot from VS Code, November 2022

Which in Excel parlance, would look something like this:

=SUM(COUNTIFS(A:A,[@Keyword],D:D,{"*/product/*","*/prd/*","*/pd/*"}))

Pivot Tables

Last, but by no means least, it’s time to talk pivot tables.

In Excel, a pivot table is likely to be our first port of call if we want to summarise a large dataset.

For instance, when working with ranking data, we may want to identify which URLs appear most frequently, and their average ranking position.

pivot table ExcelScreenshot from Microsoft Excel, November 2022

Again, Pandas has its own pivot tables equivalent – but if all you want is a count of unique values within a column, this can be accomplished using the value_counts function:

count = df['URL'].value_counts()

Using groupby is also an option.

Earlier in the article, performing a groupby that aggregated our data wasn’t what we wanted – but it’s precisely what’s required here:

grouped = df.groupby('URL').agg(
     url_frequency=('Keyword', 'count'),
     avg_position=('Position', 'mean'),
     )

grouped.reset_index(inplace=True)
groupby-pivot PythonScreenshot from VS Code, November 2022

Two aggregate functions have been applied in the example above, but this could easily be expanded upon, and 13 different types are available.

There are, of course, times when we do want to use pivot_table, such as when performing multi-dimensional operations.

To illustrate what this means, let’s reuse the ranking groupings we made using conditional statements and attempt to display the number of times a URL ranks within each group.

ranking_groupings = df.groupby(['URL', 'Grouping']).agg(
     url_frequency=('Keyword', 'count'),
     )
python groupby groupingScreenshot from VS Code, November 2022

This isn’t the best format to use, as multiple rows have been created for each URL.

Instead, we can use pivot_table, which will display the data in different columns:

pivot = pd.pivot_table(df,
index=['URL'],
columns=['Grouping'],
aggfunc='size',
fill_value=0,
)
pivot table PythonScreenshot from VS Code, November 2022

Final Thoughts

Whether you’re looking for inspiration to start learning Python, or are already leveraging it in your SEO workflows, I hope that the above examples help you along on your journey.

As promised, you can find a Google Colab notebook with all of the code snippets here.

In truth, we’ve barely scratched the surface of what’s possible, but understanding the basics of Python data analysis will give you a solid base upon which to build.

More resources:


Featured Image: mapo_japan/Shutterstock

What 2022 SEO Shifts Could Mean For 2023 & Beyond [Webinar] via @sejournal, @lorenbaker

Have you ever felt overwhelmed by Google’s seemingly constant algorithm updates? If so, you’re certainly not alone.

Many SEO professionals are reeling from Google’s whirlwind of a year, with eight confirmed and several unconfirmed updates that have dropped in 2022.

And with so much volatility in search this past year, it can often feel like you’re scrambling to keep up.

But what does the chaos of 2022 mean for 2023? Can we expect more updates? Will we see more testing?

How can you get on the front end of Google’s new rollouts and make sure you’re prepared for the changes to come?

How can you adapt your SEO strategy to keep it fresh and relevant?

For SEO pros looking to get ahead of the curve, our next webinar focuses on how to handle frequent algorithm changes and market shifts.

Join Pat Reinhart, VP of Customer Success at Conductor, for an in-depth recap of this year’s biggest SEO insights, as well as expert predictions for what 2023 may hold.

Key Takeaways From This Upcoming Google Algorithm Webinar

  • What a crazy 2022 for Google means for 2023.
  • How the growth of social media search will impact strategy next year.
  • What the popularity of visual search will mean going forward.

Trends To Watch For In 2023

As technology continues to evolve and new digital trends emerge, the SEO community must quickly adapt.

With image search becoming more prominent and Google starting to prioritize short-form videos on mobile SERPs, visual content is predicted to make a major impact on search rankings, going forward.

Between the rise of social media and the explosion of short-form video content, there are several factors expected to have a major impact on SEO in 2023.

Not only are people sharing more on social platforms now, but an increasing amount of people are relying on social media search to find what they’re looking for online.

This trend, plus the growing popularity of visual search, should be key considerations in your SEO strategy for next year.

Discover more insights on how these trends could affect SEO next year by signing up for this webinar.

Optimize Your SEO Strategy

If you struggled to keep up with this year’s frequent search engine updates, the SEO predictions you’ll discover in this webinar could be a game-changer for your business.

If you want to stay competitive in 2023, it’s time to take action and start optimizing your SEO strategy.

Register for this webinar and learn more about how Google’s recent past will inform the future.

6 Ways To Engage Your Organic Search Traffic On Social Media via @sejournal, @GaryLHenderson

It can feel like it takes forever to build an online audience of people who actually want to read what you post, engage in your content, and actually buy the products and services you offer – especially when trying to grow organically.

Organic growth can sometimes take months or even years to reach a profitable point.

The crazy thing is most creators and business owners are still waiting on Google to hopefully bring another person to their website or page.

But what if there were a way to fix that problem?

What if there were a better and faster way to engage your organic search traffic and your social media content all at the same time?

Luckily, there is!

We created this simple six-step process to engage your organic search traffic on social media and drastically expand your organic search reach using Facebook lookalike audiences.

  • Step 1: Perform keyword research.
  • Step 2: Create a piece of content (for this example, it will be a blog).
  • Step 3: Get some organic traffic to that piece of content.
  • Step 4: Set up your social media pixel and pixel the people who read the content article.
  • Step 5: Create a Facebook lookalike audience.
  • Step 6: Serve social media ads to that audience.

The steps may seem a bit much, especially if you’re new to organic growth. But don’t worry; this blog will break it down for you.

Step 1: Perform Keyword Research

Most people starting out with keyword research already have a few keywords or phrases they think will for their business or niche. These could be keywords related to their business or brand, like [best books to read for business] or [what foods cause inflammation?].

Keyword research (keywords) or the specific words and phrases that you and your ideal audience are using related to your products, services, industry, etc.

These highly specific seed topics are very important and a great place to start.

Many times the content you want to create and rank for and what your audience is actually typing in the search bar are likely completely different.

Which is one of the most pivotal reasons to perform keyword research in the first place.

If people aren’t searching for it, then why waste time creating it in the first place?

The smartest way to avoid this is to find the exact words and phrases your ideal customers are currently searching for on Google and other major search engines.

Figuring this out isn’t as complicated as it sounds. There are a handful of keyword research tools that can help.

For example, we use Ahrefs to research the phrase, [how to get followers on Instagram].

ahrefs search data for how to get followers on instagramScreenshot from Ahrefs, October 2022

You can see in the image above how many people are searching for this key phrase and the other relatable parent topics related to it.

When creating content for search engines, it’s essential to create content that answers one question at a time.

It’s okay to elaborate on that question, even up to a few thousand words. But don’t confuse one article with too many questions and topics.

For example, you could take these short-term and long-term keywords and write a blog post on each topic (of course, when it makes sense for your business).

If it doesn’t make sense to write a topic on each of those questions and the keywords are too relatable, then maybe it makes more sense to use this set of keywords as an H1 or H2 heading instead in the same blog post, which will also play a significant factor in search engine rankings.

Step 2: Create A Piece Of Content

Now that you understand the importance of finding the right keywords to use in your content marketing strategy, it is time to create a blog post.

When writing a blog, it is essential to remember that the goal is to get new readers to your blog consistently, which will eventually lead to a sale.

It’s also to get readers and engagement on the blog, so signals are sent to social media and the search engines to help your article get first-page rankings and rank in the first 10 blog posts on Google.

Again, this is where keyword research comes into play.

Make sure to read every blog on the first page of Google related to your keyword research. When doing so, make sure that your article outperforms each one of those blog posts or is found more valuable.

When performing keyword research correctly, it takes no time to get top rankings in Google because you know what people are searching for and how frequently they are searching for it.

Once your blog post is published on your website, it is time to wait for some people to read and engage with it.

Step 3: Get Organic Traffic

The only thing you have to do in this step is to wait for some organic traffic to trickle in; the goal is to have around 1,000 people. If 1,000 seems like too many, try to have at least 100.

Over time when the piece of content you created starts to get search results, you can set up a pixel (this is the next step) and begin running social media ads to hack the process and get more eyeballs on your content faster.

However, let me start by saying this may not be as simple as it sounds – this is the step where most businesses get stuck and don’t know how to grow reasonably.

Most creators, businesses, and companies understand how a simple marketing funnel works, but what they don’t understand is how to continuously get newly qualified people throughout every piece of the marketing funnel.

Even so, most businesses don’t understand how to successfully intertwine multiple platforms and use social media to grow their organic search traffic or vice versa.

People have created all these great pieces of content, but they don’t understand how to use that awesome content to take them to the next level.

People don’t have enough time to create new content every single day. The pressure of having to come up with new ideas every day, film videos, or write a 2,500-word blog post often times leads to burnout.

And when you are using multiple platforms, that’s where this marketing strategy comes into play.

You have to understand how to track every person who touches your content, from the first touch to the last.

Studies have shown that it usually takes a person seven interactions or touches with a business before making a purchase.

To know how many times a person interacts with your content, it is critical to have a pixel placed on your website for accurate data tracking, leading to the next step.

Step 4: Set Up Social Media Pixel

Once you have published your blog post and have a small or large amount of traffic engaging with your content, it is time to set up your social media pixel on your website.

how to set up a pixelScreenshot by author, October 2022

If you are unfamiliar with a pixel, here is the definition.

A pixel is a few lines of code that you copy into the header section of your website.

It works by placing and triggering cookies to track users as they interact with your website and your Facebook ads.

The pixel serves two primary purposes:

  • To remarket to someone who has visited one of your pages.
  • To know which pages they have visited and to track and see if someone has completed the desired action, whatever that may be.

What the pixel does, in essence, is allow Facebook to track its audience on our platform; we are essentially giving Facebook access to our tracking.

If you are unsure how to create a Facebook pixel and add the Facebook Pixel to your website, follow this two-part process:

Part 1: Create A Facebook Pixel

  • Go to Events Manager.
  • Click Connect Data Sources and select Web.
  • Select Facebook Pixel and click Connect.
  • Add your Pixel Name.
  • Enter your website URL to check for easy setup options.
  • Click Continue.

Part 2: Add The Facebook Pixel To Your Website

Once you’ve created your pixel, you’re ready to put the Facebook pixel code on your website.

There are a few different options on how you can set this part up:

  • You can manually add pixel code to a website.
  • Use a partner integration.
  • Use email instructions.

Once the tracking is in place and you fully understand your target audience’s patterns, you can begin implementing the R3MAT strategy, showing the right message to the right person at the right time with the right expectations.

Once you have your social media pixel set up, it’s time to move to the next step.

Step 5: Create A Lookalike Audience

Did you know that Facebook can predict if you are pregnant before you know you’re pregnant? Or that Facebook can tell if you’re cheating on your partner? Or that you’re going to get a divorce?

It can track every scroll up or down, a swipe of the finger, every heart, repost, retweet, and knows every person, business, and profile you interact with.

Seems pretty scary, right?

But here’s where that becomes super powerful.

Facebook has an option where you can create a lookalike audience based on its tracking abilities to reach new people who are most likely to be interested in your business because they’re similar to your best existing customers.

You can create a group of people with similar likes, interests, and demographics to those already interacting with your website.

Here is how to create a Facebook Lookalike Audience:

  • Go to your Audiences.
  • Click the Create Audience dropdown and choose Lookalike Audience.
  • Choose your source notes:
    • A source can be a customer audience not created with your pixel data, mobile app data, or fans of your page.
    • Consider using 1,000 to 50,000 of your best customers based on lifetime value, transaction value, total order size, or engagement.
  • Choose the country/countries where you’d like to find a similar set of people.
  • Choose your desired audience size with the slider.
  • Click Create Audience.
how to create a custom audienceScreenshot from Facebook, October 2022

Creating this audience allows any business to create a small subset of people you can talk to any way you choose.

You can now show this audience relevant ads, move them through the sales funnel, build your relationship with them, and build your reach and frequency.

All of this is possible because Facebook is watching so many little data points all of the time.

Facebook continuously collects information about what you buy, who you search for or friend, what websites you visit, and the accounts you follow and unfollow.

Plus, thousands of other bits of personal information are gathered from public records and your social media activity.

Step 6: Serve Audience The Social Media Ads

The final step is to show relevant ads to your new lookalike audience that you just created.

To keep this process going, make sure you are consistently showing your lookalike audience(s) new relevant content that meets them at every point in their buyers’ journey.

Meaning you will hit them with new or recycled content (and the kind your audience likes to engage with) at the awareness stage, consideration stage, and decision stage of the buyers’ journey.

When you complete this six-step process, you are officially taking your organic search and lighting it on fire.

Conclusion

Make sure you continue to repeat this simple six-step process to engage your organic search traffic on social media over and over to see the best results.

Repeat everything from performing new keyword research to creating new content and setting up your new pixel to running new ads to the piece of content to a saved or new audience.

This doesn’t mean you must change what’s working, but maybe take a few clips out of your existing content and show that to your audience.

Break larger pieces of content down into smaller segments to create new pieces of micro-content out of your current existing content.

More Resources:


Featured Image: oatawa/Shutterstock

Why Everyone In Your Business Wins With SEO via @sejournal, @HelenPollitt1

We know that there are many reasons to focus on SEO from a commercial standpoint.

Working on your company’s SEO can help raise the quality of your website, your brand reputation, and your conversions.

But what about the impact on your team?

Having a good SEO strategy in place can actually benefit your company in other ways.

Colleagues’ jobs can be made easier.

They may be equipped with new skills.

It may even help prove the worth of their work.

How SEO Can Positively Impact Other Marketing Channels

There are many important ways in which SEO can impact other marketing channels.

But let’s take a look at how it can help those teams meet their personal and team goals.

Collaboration

A good SEO strategy will never be in isolation from other marketing channels.

Pay-per-click (PPC) advertising, for instance, goes hand-in-hand with SEO. Both channels’ leads need to talk to each other, or there’s going to be a financial impact.

The benefits go beyond money saving, though. SEO is a far-reaching specialism.

We need input on many other teams’ work: brand marketing, CRM, and paid media, to name a few. Through this, SEO can help to unify projects.

SEO professionals tend to need to be involved in anything that could affect the performance of the website – from brand positioning to content creation.

As such, SEO pros can be key stakeholders in marketing campaigns.

We help to ensure consistency in messaging and audience, both on-site and off.

Traffic And Visibility

SEO can assist with bringing a lot more users to your company’s digital assets, which, in turn, allows channels such as email marketing to promote sign-ups, or ecommerce managers to alert customers to offers.

Without the steady traffic of organic search, it can be hard for other marketing channels to gain enough of an initial audience for their campaigns to flourish.

Organic traffic is often one of the largest generators of traffic to a website.

When colleagues are looking to carry out user experience (UX) or conversion rate optimization (CRO) experiments, they will need a significant enough flow of traffic to be able to declare their experiment concluded.

SEO can be one of the ways qualified traffic is sent to those experiments without the additional cost of PPC or social media campaigns.

Ideation

The data gathered through SEO can also be very helpful in giving other marketing channels a place to start with their own campaign ideation.

Through the Google Trends data into trending topics, your editorial team can understand what subjects to cover that will be of interest to your target audience.

The seasonality of your industry shown through the peaks and troughs of search term usage can indicate to your wider marketing team the impact their campaigns may have at different times of the year.

A quick search engine results pages (SERP) analysis can yield lots of information about what social posts or videos competitors are producing.

The reserved spaces in the search results for videos, images, news, and social media can be a goldmine of ideas for other marketing teams that they may not think to check.

Brand Reputation Management

SEO pros can help improve and maintain brand reputation.

Often, when a search is carried out for a company name, the first page of the search results is a mix of brand-owned and third-party websites. Because of this, SEO professionals have a huge impact on what visitors see when they are searching for a brand.

Negative Google Business Profile (GBP) reviews or a poor Tripadvisor score may be visible on the front page of the SERPs if a brand is having trouble with its online reputation.

SEO pros can work to bring owned properties up the search results for branded search terms, as well as work with customer success teams to respond to negative reviews.

This can help to make the branded search results more neutral (or even positive) for the brand.

How SEO Research Can Help Beyond Driving Traffic

SEO experts have to cover a lot of bases with their work.

They need to understand how the technology of the website they are working on impacts its performance. There is a requirement to understand how user behavior changes over time. They have to be ready to capitalize on trends.

As a result, SEO pros are in a great position to be able to share their knowledge with other teams outside of the marketing department.

Ideas For New Products

Research into search terms potential visitors are using can sometimes reveal new revenue streams or product ideas.

When conducting keyword research for your industry, you may well discover that there is a lot of interest in an idea or topic that is very related to your current product offering.

This insight can be shared with product teams to help them explore interest in new products.

This research can also be used to test the interest in a product in new markets.

For example, if your or a client’s business is considering expanding internationally, then research carried out by SEO pros can indicate receptiveness to a product in the new country.

Competitor analysis carried out by SEO professionals will often look at where there are gaps in the search market that competitors are filling.

This data can give product teams insight into how other relevant companies are better meeting the needs of your shared audience.

It can also show where there is little or no significant competition for a new product or service.

Help Reduce Workload Of Customer Support

Speaking to the customer service team is often touted as a great source of topic ideas for SEO pros. However, finding out what questions and concerns the customer service team is working with daily can go beyond an article for the company blog.

Find out common customer issues now and provide resources online to alleviate those concerns.

This is especially beneficial to customer service teams that field many calls every day, and have long hold times.

It isn’t just for the benefit of getting more organic traffic to the website. It could be the difference between a happy or unhappy customer.

SEO professionals can optimize this content so it directly meets the needs of searchers looking for those answers. This makes the answer easier to find and stops them from having to call a customer service line.

It can also give SEO pros an understanding of what might appear as a “People Also Asked” question in relation to your brand if it is asked a lot, and therefore probably searched a lot.

Creating content that answers those frequently asked questions can help your customer success team’s workload, and also enable your site to be a possible contender for the People Also Asked result if one is provided.

SEO Skills Can Help Other Teams

It can be fairly obvious to see how SEO will impact other marketing channels and vice versa. However, have you stopped to consider quite how broad the impact of SEO is?

The skills involved in good SEO can have a much wider effect.

Sales

SEO is all about understanding our audience’s needs and how they go about solving their problems.

Through keyword research, we have a clear view of what our target market is looking for in relation to our products or services.

This information is incredibly valuable to sales teams.

It is a level of data they may not be able to access themselves, yet it provides great insight into the problems and concerns their customers are looking to solve.

Consider creating regular reports to your, or your client’s, sales teams that detail trending topics and frequently asked questions.

This data could help them to identify new hooks or solutions that will be directly relevant to your market.

Content Creation

This one might seem obvious.

We know SEO relies heavily on quality content creation – the data we can pull for keywords alone helps to ensure copy that’s more relevant to searchers.

But how can SEO help copywriters?

With the myriad of tools at our disposal, SEO experts can gain insights into trending topics, predict seasonal interests, and understand how to make copy resonate with readers.

All of this is very valuable to content creators.

Editorial Teams

Consider your editorial teams – they want to be creating content for your blog or video channel that will be found by new audiences.

SEO pros can help with that greatly, from recommending important search phrases to use, to video optimization to help them be more visible on Google Search and YouTube.

Product Copy

Beyond editorial, SEO can assist with ensuring product copy and service details are targeted to the language readers are wanting to see.

Keyword search data and competitive analysis can give insight into what features and information readers are interested in and therefore need to be highlighted.

SEO experts can also help copywriters to understand how search engines perceive the relevancy of their copy to their target audience’s needs.

After all, the likes of Google have spent considerable time and money ensuring the pages they rank will meet the needs of searchers. There is a lot of insight SEO pros can provide on what relevancy looks like.

Using SEO To Reinforce The Value Of Other Teams’ Work

One big way SEO can positively impact the work of other departments is by showing the value their work brings to SEO.

They will have their own metrics and key performance indicators (KPIs) they use to demonstrate the effectiveness of what they do.

SEO, however, is another channel they may be affecting – and proving the benefit of their work to the success of SEO is a great way of encouraging closer collaboration.

There will be several ways in which you can quickly identify the impact of other teams’ work on SEO.

Traffic

Sometimes changes are made to websites, and the teams involved don’t know how to measure their success.

Increases in search visibility or organic traffic to those pages can be a good indicator that the change was a successful one.

Conversion Rate

SEO isn’t just about driving traffic to a website; that traffic needs to be converting.

Demonstrate to the teams involved that changes to the website have yielded a much higher conversion rate for organic traffic.

This can help to solidify the value of the work they have carried out.

Crawling And Indexation

Changes the engineering team has made to the website can drastically hinder or improve its ability to be crawled.

Crawl stats can detail the improvement in volume or type of pages being crawled. They can also show the reduction in cruft pages being crawled.

It can be a good analysis to demonstrate the success of recent development changes. Similarly, look at how pages are being indexed over time.

Seeing that the right ones are indexed (and the wrong ones aren’t) can be a success indicator for recent development changes.

Page Speed

This is a metric that most developers are probably keeping an eye on themselves.

However, it can be a good one to share with those that aren’t.

Improving page speed can be a positive change for SEO purposes and user experience.

Conclusion

SEO has a very obvious benefit to companies. More traffic, more leads or sales, and more revenue.

Beyond this, SEO can help other departments of a business be more efficient.

As SEO pros, we shouldn’t be afraid to provide insight to other teams.

It might be valuable to them and can help them to demonstrate their own successes to the broader organization.

More resources: 


Featured Image: PeopleImages.com – Yuri A/Shutterstock

Finance Marketing: How To Form A Successful Content Strategy via @sejournal, @sejournal

As a financial service business, you’re facing a unique set of challenges when it comes to creating content.

  1. Finance isn’t a particularly glamorous or entertaining subject to write about, which can make it tough to engage your readers.
  2. There are heavy regulations and strict guidelines in Google results that limit what you can say, as well as how you can say it.

So, how can you overcome these challenges to form an effective content strategy?

How do you create finance content that’s responsible and accurate yet still compelling and convincing?

Our new ebook, Content Marketing For Finance, walks you through how you can develop a content strategy that respects the rigorous demands of the financial space while truly connecting with your target audience.

“Audience is at the heart of every content marketing strategy and should always be kept top of mind,” writes author Chandal Nolasco da Silva.

Download your copy and learn how to meet your customers at each stage of their journey and create the kind of content that consistently converts.

What’s Inside This Finance Content Marketing Ebook?

This pocket guide has all the insights you need to navigate the ins and outs of content marketing within the finance industry.

Topics covered include:

  • Content marketing principles, best practices, and how to apply them specifically to finance.
  • Solutions to the unique challenges of finance marketing: slow adaptation to change, difficulty getting buy-in for digital efforts, and managing complex content and content marketing in an industry with high scrutiny on advertising.
  • Key marketing channels for finance and how to use them effectively.

Key Takeaways:

The contents of this marketing ebook can help you navigate complex issues, such as the:

  • Very long sales cycles in the B2B space, as well as the long delays at the bottom of the funnel. The finance industry has been notoriously slow to digitize, so new products and services are dealing with slow movers that are resistant to change.
  • Stark reality of required due diligence processes with lots of different stakeholders involved. There can be complications with regulators, operational delays, reference checks, or other risk-reduction processes involved. These are increasingly important and lengthy, depending on the institution or firm size involved.
  • Fact that sometimes traditional channels don’t perform as well as they do in other industries; instead, more traditional ways of doing business, like in-person meetings, are sometimes better. Money is involved, after all.

If you’re a financial service professional looking to step up your content strategy for 2023, download the ebook now!

Finance Marketing: How To Form A Successful Content Strategy

How To Combine SEO & PPC Keyword Strategies For More Effective ROI via @sejournal, @seomonitor

At Estudio34, we have a powerful mix between SEO and PPC, which helps us be more effective at optimizing spending and targeting.

So, start by building a communication plan before creating your next digital strategy. Focus on leveraging some of the learnings from one another.

Step 2: Define The SEO & PPC Problem To Solve

First, you and your teams should ask yourselves:

  • Are we paying for PPC traffic that we could have secured through SEO?
  • Are we multiplying the effect of growing traffic by doubling up the results of PPC and SEO in tandem?
  • Would I achieve the same conversions if I didn’t cover searches on both channels?
  • Is my conversion rate for the same query higher on PPC or SEO?

Once everyone from your SEO and PPC teams has provided answers, it will be easy to create the perfect roadmap of keywords for each team.

An Example Of How To Overcome Keyword Overlap In SEO & PPC

Sometimes, it’s easier to learn by example, so let’s travel through a real marketing problem that we had to solve.

In this instance, a grocery retail client had a simple yet very common problem: a high dependency on branded and non-branded terms in their paid campaigns.

The client’s objective was to leverage their SEO efforts in order to reduce exposure on paid channels.

The hypothesis was that if you target key PPC terms you could easily get organic visibility for, you could stop bidding on them and consequently stop cannibalizing SEO through paid search.

It is worth stating that, in our case, there was a huge dependency on branded terms. As you may have experienced, spending on PPC keywords for which you have good organic rankings can make good business sense to protect coverage on a more crowded SERP.

In order to illustrate it in a very simplistic manner, this is how PPC keyword targeting versus SEO would normally be set:

The SEO Strategy

We try to define specific terms (AKA: chunky middle, even long tail), and we move towards broader terms (AKA: Generics), thus grouping many keywords in buckets (groups in SEOmonitor).

Ex.: Wooden toy kitchen: Global Search Volume 11.4K

The PPC Strategy

We try to define broader terms (AKA: broad match), and we move towards specific terms (AKA: exact match), thus grouping many keywords in buckets (AdGroups).

Ex.: Wooden toys OR Toys: Global Search Volume 53.5K

The Result

You can see that one will be more specific (PPC) over time, whilst the other is specific from day one but relies on getting good visibility in order to harness any impact.

The next thing to uncover is what happens when you have good visibility (rankings) for it.

Step 3: Try The Estudio34 Method

These steps are the real, proven pathways to how the Estudio34 team combined SEO and PPC data to improve their search visibility while optimizing budgets for both channels.

Step 3.1: Identify Where & How Cannibalization Occurs

Once you’ve made it to this method, you and your PPC team should be actively communicating and sharing data.

Without actively collaborating with your PPC team, you might not even be aware of cannibalization issues.

In this context, cannibalization refers to SEO and PPC targeting the same keywords and competing for traffic instead of being leveraged together. When that happens, search results might include your own competing landing pages, which can lead to lower conversions or dispersed traffic.

Where Does Cannibalization Often Occur?

PPC teams might bid on terms without knowing the SEO side. Or SEO professionals might inherit this structure from day one without realizing it’s happening.

Because the point of this strategy is to benefit cross-channel through keyword overlap, we started the analysis from paid keywords to then cross-reference with SEO data.

How We Stopped SEO & PPC Keyword Cannibalization

First, we pulled a list of PPC terms that were generating clicks and no conversions over a period of three months – this allows you to group them by search queries (SQR report).

Note that the timeframe may differ from business to business due to the volume of data and actual spending in the given period. You should test with date ranges to see how many terms meet the criteria. You don’t want to be swamped in rows of data, but rather have actionable and measurable options.

To solve the “not provided” issue and get conversion data at the keyword level, our team at Estudio34 leveraged SEOmonitor’s Organic Traffic module. SEOmonitor brings all the keyword data from Search Console enriched with sessions and conversions from Analytics by using their common ground: the landing page.

Once we had the hit list from the PPC team, we uploaded these to the rank tracker as new keywords.

How To Combine SEO & PPC Keyword Strategies For More Effective ROIImage by Estudio34 using SEOmonitor.com’s keyword groups, November 2022

We recommend doing this in a separate group, mainly because the visibility for the group can be measured and excluded from potential forecasts if needed.

Next, it was time to identify overlaps.

Step 3.2: Filter Out Search Terms That Rank In The Top 3

For our case, we looked at keywords in position 3 or above.

We did it manually as we didn’t want new terms to be added unless we said so, but in SEOmonitor, you can set smart groups, meaning that anything that falls into your filtering option will be automatically added and updated.

How To Combine SEO & PPC Keyword Strategies For More Effective ROIImage by Estudio34 using SEOmonitor.com’s advanced filters and Smart groups, November 2022

Step 3.3: Filter Out Keywords With Ads

We continued our filtering in SEOmonitor’s rank tracker so as to leave out keywords that also have an ad showing for them.

Theoretically, this check is unnecessary because we pulled out the terms from PPC campaigns.

However, it’s good to know in case you need to do it the other way around. Bear in mind that certain terms may not be picked up in some instances as it depends on your aggressive bidding and when the tool snapshots the SERPs.

How To Combine SEO & PPC Keyword Strategies For More Effective ROIImage by Estudio34 using SEOmonitor.com’s advanced filters, November 2022

Over time, you’ll also get Seasonality, and SERP Features Visibility details.

These are incredibly useful because whatever terms you decide to test may well have no impact if, seasonally speaking, they are not relevant.

How To Combine SEO & PPC Keyword Strategies For More Effective ROIImage by Estudio34 using SEOmonitor.com’s search and SERP data, November 2022

Step 3.4: Test Your New Keywords

Start by defining the landing page for which a certain query ranks.

The landing page will help determine how much traffic was coming to it organically and thus if it increases or decreases. Likewise, we can assess conversions that may have been generated from that landing page. Note that we are making concessions, as there are cases where a landing page may be serving the discovery phase purely, so conversions may not affect the overall result.

Now, you can start testing.

You may be tempted to pause campaigns to see the impact on organic traffic. However, this is not advised, mainly because you could be affecting your top line. How you go about it can help mitigate any risk associated with revenue loss.

Target individual keyword testing by:

  • Adding these keywords as negative keywords on an exact match basis on your campaign or campaigns (subject to how these are configured).
  • Running this for 7 to 14 days. Again, subject to the volume of data previously mentioned, this may have to be longer.

Because we have the organic traffic to the ranking URL, we have a snapshot of the before and after effects of negatively excluding keywords from PPC campaigns.

Compare the following for the timeframe tested versus the previous period: 

  • Traffic from PPC to the landing page in question.
  • Traffic from SEO to the landing page in question.
  • CVR for landing page per channel: PPC and SEO.
  • Revenue/Transactions or Goals from both channels.

Look for patterns like:

  • Improved return on ad spend (ROAS) in your paid campaigns. This is because the terms excluded were supposedly not converting but were generating clicks (a consideration to be taken into account is that these may have been for discovery purposes, thus low conversion).
  • SEO traffic increases — that should be the right trajectory if the overlap was indeed helping PPC.
  • Conversions. This one can swing either way. The ultimate check is higher conversions. However, for some terms of landing pages, conversion rate and thus conversions may decrease. Why? Because you are capturing SEO traffic but it might not convert as well as when Paid was active. That can be your exception, so doubling up could make sense, or simply PPC would perform great on its own.

What to do based on the previous patterns:

Retain the excluded terms if all three instances are met positively – meaning:

  • More SEO traffic.
  • Better ROAS (as you decrease spend).
  • Higher SEO conversions.
  • Same total or more (PPC + SEO) conversions.

If there are what-ifs involved and the client has concerns, here’s what to do:

Tackle concerns with an actual agreed-upon action plan.

As a means of mitigating potential sales loss, the first question to ask is if SEO traffic converts worse than when targeting the query on paid. Our recommended action was to revert back to that term and dig into specifics: Are the landing pages the exact same? What can be taken from the paid campaign to improve UX on the SEO page?

This is where the second benefit of this activity comes to play: leveraging the on-page optimization and clear targeting of a landing page used in PPC to target an SEO term and landing page, as follows:

  • Content on the paid landing page was better focused at conversions.
  • Ad copy can serve meta descriptions.
  • Ad copy titles can help the meta titles for CTR (be careful here because it may affect ranking fluctuations).
  • The wrong page was ranking for the term at hand, meaning paid search told us what landing page would be better suited.
  • You do need to double up, but only on certain times or days of the week, based on which stage of the process you’re in.

With this client, we learned that the best results came from switching the exact terms that included the brand. Mainly because they had a competitive cost and good conversion rates.

With generic terms, the results were a mixed bag. Yet it’s reasonable to state that on expensive terms, if you have good SEO, it will be an almost certain win.

Step 3.5: Evaluate The Results

For this client, we targeted a test with 1,300 terms with an average cost per click of 0.12 euros. Generating 20,000 clicks over the two weeks tested saved around 4,800 euros per month.

SEOmonitor Can Help You Zero-In On SEO Performance

As we saw from Smith and the team at Estudio34, taking an integrated approach to SEO and PPC might be useful for data-driven experiments and cutting waste on both channels through:

  • Understanding keyword overlapping and cannibalizing results.
  • Learning what works best in each channel and optimizing the other (specific terms, landing pages, meta descriptions, etc.).
  • Being mindful of how and when to leverage a specific tactic.

With SEOmonitor’s data granularity (daily ranks for desktop and mobile as standard) and solution to the not provided, the agency could zero in on SEO performance and understand every change.

Plus, having advanced filtering capabilities, they could set up a mix of groupings to track carefully.

This is just one of the many ways SEO professionals leverage SEOmonitor to be more effective in their workflows.

Join us, and agencies like Estudio34, in our quest to help SEO professionals focus on what matters.

Google Answers If Splitting A Long Article Could Result In Thin Content via @sejournal, @martinibuster

In a Google Search Office Hours video, Googler Lizzi Sassman answered a question about thin content, clarifying a common misperception about what thin content really is.

Thin Content

The word thin means lacking thickness or width.

So when we hear the term “thin content” it’s not uncommon to think of thin content as a webpage with not much content on it.

The actual definition of thin content is more along the lines of content that lacks any added value.

Examples are a cookie cutter page that barely differs from other pages, and even a webpage that is copied from a retailer or manufacturer with nothing additional added to it.

Google’s Product Review Update weeds out, among other things, thin pages consisting of review pages that are only product summaries.

The hallmark qualities of thin pages is that they lack originality, are barely different from other pages and/or do not offer any particular added value.

Doorway pages are a form of thin content. These are webpages designed to rank for specific keywords. An example can be pages created to rank for a keyword phrase and different city names, where all the pages are virtually the same except for the names of the cities.

Are Short Articles Thin Content?

The person asking the question wanted to know if splitting up a long article into shorter articles would result in thin content.

This is the question asked:

“Would it be considered thin content if an article covering a lengthy topic was broken down into smaller articles and interlinked?”

Lizzi Sassman answered:

“Well, it’s hard to know without looking at that content.

But word count alone is not indicative of thin content.

These are two perfectly legitimate approaches: it can be good to have a thorough article that deeply explores a topic, and it can be equally just as good to break it up into easier to understand topics.

It really depends on the topic and the content on that page, and you know your audience best.

So I would focus on what’s most helpful to your users and that you’re providing sufficient value on each page for whatever the topic might be.”

Splitting a Long Article Into Multiple Pages

What the person asking the question may have been asking is if was okay to split one lengthy topic across multiple pages that are interlinked, which is called pagination.

With pagination, a site visitor clicks to the next page to keep reading the content.

The Googler assumed that the person asking the question was splitting a long article into shorter articles devoted to the multiple topics that the lengthy article covered.

The non-live nature of Google’s new version of SEO office-hours didn’t allow the Googler to ask a follow-up question to verify if she was understanding the question correctly.

In any case, pagination is a fine way to break up a lengthy article.

Google Search Central has a page about pagination best practices.

Citation

Listen to the Google SEO Office Hours video at the 12:05 minute mark

Google: Links Have Less Impact Today Than In The Past via @sejournal, @martinibuster

In a Google SEO office hours video, a Googler answered a question about backlinks and rankings and offered the interesting fact that backlinks have less impact as a ranking signal than it used to in the past.

Backlinks Ranking Signal

Links and anchor text signals made Google a better search engine than the competition when it was first introduced.

SEO used to primarily be about optimizing titles, headings, and content with keywords.

After Google became important it was realized that links were the key to better rankings.

Whole industries rose to service the need for links, such as web directories and link selling brokers.

Various link building techniques also came to be such as reciprocal linking, comment spam, forum spam and so on.

Google largely lost the war against link spam. The turning point was 2012 with the introduction of the Penguin algorithm, as well as other updates to Google’s infrastructure (Hummingbird) which allowed Google to do increasingly massive amounts of link related ranking functions.

Today we are at a point where Google is able to rank links in such a way that low quality links are discarded.

Links continue to be an important ranking factor but it has been a mystery as to how much impact links have today.

John Mueller speculated recently that links may begin playing a decreasing role in ranking, saying:

“…it’s something where I imagine, over time, the weight on the links at some point will drop off a little bit as we can figure out a little bit better how the content fits in within the context of the whole web.”

Backlinks Have Less Impact Today

It is interesting to hear a Googler say that links have less impact today because it was understood that the reduction in importance was something in the future.

But perhaps the key point to keep in mind is that the strength of the link signal is being compared to when Google first started.

The remark about links came about from a question about why Google still uses backlinks and if link building campaigns are not allowed.

This is the question:

“Why does Google keep using backlinks as a ranking factor if link building campaigns are not allowed?

Why can’t Google find other ranking factors that can’t be easily manipulated like backlinks?”

Google’s answer:

“There are several things to unpack here.

First, backlinks as a signal has a lot less significant impact compared to when Google Search first started out many years ago.

We have robust ranking signals, hundreds of them, to make sure that we are able to rank the most relevant and useful results for all queries.”

That is definitely true, links have a lot less impact today than when Google first started, mainly because less kinds of links (like directory links, paid links) have the ability to impact search rankings.

It’s unclear if the Googler was making a reference to more than just the kinds of links that still have an impact.

The Googler continued:

“Second, full link building campaigns, which are essentially link spam according to our spam policy.

We have many algorithms capable of detecting unnatural links at scale and nullify them.

This means that spammers or SEOs spending money on links truly have no way of knowing if the money they spent on link building is actually worth it or not, since it’s really likely that they’re just wasting money building all these spammy links and they were already nullified by our systems as soon as we see them.”

Links and Site Promotion Are Still Important

Links have a function that goes beyond just ranking. Google discovers webpages through links.

Google’s own documentation not only cites links as how Google discovers web pages, it encourages publishers to promote their sites.

The documentation says:

“Google also finds pages through links from other pages. Learn how to encourage people to discover your site by Promoting your site.

…Chances are, there are a number of sites that cover topic areas similar to yours. Opening up communication with these sites is usually beneficial. Hot topics in your niche or community could spark additional ideas for content or building a good community resource.”

The quantity of links pointing to a site still indicates how important a site is.

The linking patterns that are created from natural links helps Google to understand what a site is about as well through the resulting link graph.

Follow Up Questions

The Googlers statements seem to require follow up questions.

  • Did the Googler mean that links that Google uses for ranking have less impact than in the past?
  • What about link building campaigns that are centered on telling others about a site and asking for a link, are those considered spam?
  • When the Googler referenced “link building campaigns” were they talking about campaigns to pay for guest posts or link insertions into existing articles?

The answers given are good starting points but this new format for the Google office hours is not conducted live.

That means there is no way to ask follow up questions, which makes some of the answers less useful.

Citation

Featured image by Shutterstock/Asier Romero

Listen to the Google Office Hours at the 6:08 minute mark

Google: Disavowing Random Links Flagged By Tools Is A Waste Of Time via @sejournal, @martinibuster

Google’s John Mueller answered a question about using the link disavow tool and offered a tip about the best way to use it, specifically mentioning links flagged by tools.

Although this tool was introduced ten years ago there is still much confusion as to the proper use of it.

Link Disavow Tool

The link disavow tool was introduced by Google in October 2012.

The disavow tool followed in the wake of the Penguin Algorithm from May 2012, which ushered in a period of unprecedented chaos in the search marketing community because so many people were buying and selling links.

This period of openly buying and selling links came to a stop on May 2012 when the Penguin algorithm update was released and thousands of websites lost rankings.

Getting paid links removed was a huge pain for because they had to request removal from every site, one by one.

There were so many link removal requests that some site owners started charging a fee to remove the links.

The SEO community begged Google for an easier way to disavow links and in response to popular demand Google released the Link Disavow tool on October 2012 for the express purpose of disavowing spam links that a site owner was responsible for.

The idea of a link disavow tool was something that had been kicking around for many years, at least since 2007.

Google resisted releasing that tool until after the Penguin update.

Google’s official announcement from October 2012 explained:

“If you’ve been notified of a manual spam action based on “unnatural links” pointing to your site, this tool can help you address the issue.

If you haven’t gotten this notification, this tool generally isn’t something you need to worry about.”

Google also offered details of what kinds of links could trigger a manual action:

“We send you this message when we see evidence of paid links, link exchanges, or other link schemes that violate our quality guidelines.”

John Mueller Advice on Link Disavow Tool

Mueller answered a question about disavowing links to a domain property and as a side note offered advice on the proper use of the tool.

The question asked was:

“The disavow feature in Search Console is currently unavailable for domain properties. What are the options then?”

John Mueller answered:

“Well, if you have domain level verification in place, you can verify the prefix level without needing any additional tokens.

Verify that host and do what you need to do.”

Then Mueller added an additional comment about the proper way to use the link disavow tool.

Mueller continued his answer:

“Also, keep in mind that disavowing random links that look weird or that some tool has flagged, is not a good use of your time.

It changes nothing.

Use the disavow tool for situations where you actually paid for links and can’t get them removed afterwards.”

Toxic Link Tools and Random Links

Many third party tools use proprietary algorithms to score backlinks according to how spammy or toxic the tool company feels they are.

Those toxicity scores may accurately rank how bad certain links appear to be but they don’t necessarily correlate with how Google ranks and uses links.

Toxic link tool scores are just opinions.

The tools are useful for generating an automated backlink review, especially when they highlight negative links that you thought were good.

However, the only links one should be disavowing are the links one knows are paid for or are a part of a link scheme.

Should You Believe Anecdotal Evidence of Toxic Links?

Many people experience ranking losses and when checking their backlinks are shocked to discover a large amount of extremely low quality webpages linking to their websites.

Naturally it’s assumed that this is the reason for the ranking drops and a never-ending cycle of link disavowing commences.

In those cases it may be useful to consider that there is some other reason for the change in rankings.

One case that stands out is when someone came to me about a negative SEO attack. I took a look at the links and they were really bad, exactly as described.

There were hundreds of adult themed spam links with exact match anchor text on unrelated adult topics pointing to his website.

Those backlinks fit the definition of a negative SEO attack.

I was curious so I privately contacted a Googler by email.
They emailed me back the next day and confirmed that negative SEO was not the reason why the site had lost rankings.

The real cause for the loss of rankings was that the site was affected by the Panda algorithm.

What triggered the Panda algorithm was low quality content that the site owner had created.

I have seen this many times since then, where the real problem was that the site owner was unable to objectively review their own content so they blamed links.

It’s helpful to keep in mind that what seems like the obvious reason for a loss in rankings is not necessarily the actual reason, it’s just the easiest to blame because it’s obvious.

But as John Mueller said, disavowing links that a tool has flagged and that aren’t paid links is not a good use of time.

Citation

Featured image by Shutterstock/Asier Romero

Listen to the Google SEO Office Hours video at the 1:10 minute mark