MARKETING
The Beginner’s Guide to Keyword Density
When you’re writing SEO-optimized content, how many keywords are enough? How many are too many? How do you know? And what happens if Google and other search engines determine your site is “stuffed” with keywords?
In our beginner’s guide to keyword density, we’ll cover the basics, dig into why it matters, and offer functional formulas and simple tools that can make sure your keyword strategies are working as intended.
What is keyword density?
Keyword density — also called keyword frequency — is the number of times a specific keyword appears on a webpage compared to the total word count. It’s often reported as a percentage or a ratio; the higher the value, the more your selected keyword appears on your page.
Why Keyword Density Matters
Keywords are a critical part of your SEO strategy .
Along with relevant content and optimized website design, ranking for the right keywords helps your site stand out from the crowd — and get closer to the top of search engine results pages (SERPs).
So it’s no surprise that a substantial amount of SEO advice centers on keywords: Doing your research can help you select and rank for top-performing keywords in your market, in turn boosting user engagement and increasing total sales.
Why? Because keywords drive searches. When users go looking for products or services, they’ll typically use a keyword that reflects their general intent, and expect search engines to serve up relevant results.
While tools like Google now take into account factors such as geographical area and page
authority — defined in part by the number of visitors to your webpage and in part by “dofollow” links from reputable sites that link back to your page — keywords remain a critical factor in website success.
The caveat? You can’t simply “stuff” as many keywords as possible into your content and expect reliable results.
This practice is called keyword stuffing, and it’s a black-hat SEO practice that can lead to penalization and even full-on removal from the SERPs.
What is keyword stuffing?
Keyword stuffing is the practice of writing low-quality content with a higher-than-average frequency of the same keyword. The purpose of keyword stuffing is to trick search engines, i.e. Google, to rank your page higher in the search engine results pages. This black-hat tactic no longer works.
During the wild west days of the first search engines, brands and SEO firms would write low-value content and cram it with keywords and keyword tags, along with links to similarly-stuffed pages on the same site. Not surprisingly, visitors grew frustrated and search engine providers realized they needed a better approach.
Now, keyword stuffing has the opposite effect — search engines will penalize the page rankings of sites that still choose to keyword stuff.
By the Numbers: The Keyword Density Formula
How do you calculate keyword density? The formula is straightforward: Divide the number of times a keyword is used on your page by the total number of words on the page.
Here’s an easy example: Your page has 1,000 words and your keyword is used 10 times. This gives:
10 / 1000 = .001
Multiply this by 100 to get a percentage, which in this case is 1%.
There’s also another formula sometimes used to assess keyword usage: TF-IDF, which stands for “term frequency-inverse document frequency”. The idea here is to assess the frequency of a keyword on specific pages (TF) against the number of times this word appears across multiple pages on your site (IDF). The result helps determine how relevant your keyword is for specific pages.
While TF is straightforward, it’s easy to get sidetracked by IDF. Here, the goal is to understand the rarity of your keyword across multiple documents. IDF is measured in values between 0 and 1 — the closer to 0, the more a word appears across your pages. The closer to 1, the more it appears on a single page and no others.
This is the “inverse” nature of the calculation: lower values mean more keyword use.
Consider this formula in practice. Applied to very common words such as “the” or “but”, the TD-IDF score will approach zero. Applied to a specific keyword, the value should be much closer to 1 — if not, you may need to reconsider your keyword strategy.
What is good keyword density?
While there are no hard and fast rules for keyword density beyond always-relevant “don’t keyword stuff” advice, many SEOs recommend using approximately 1-2 keyword for every 100 words of copy. That factors in to about 1-2% keyword density.
Your content may perform similarly with slightly more or slightly less, but general wisdom holds that Google and other search engines respond well to keyword density around 0.5%.
It’s also worth remembering the value of keyword variants — words and phrases that are similar, but not identical, to your primary keyword. Let’s say your website sells outdoor lighting solutions. While your highest-value keyword for SERPs is “outdoor lighting”, stuffing as many uses of this keyword into as many pages as possible will reduce rather than improve overall SEO.
Instead, consider keyword variants; terms that are close to your primary keyword but not an exact copy. In the case of “outdoor lighting”, variants such as “garden lighting”, “patio lighting”, “deck lighting” or “landscape lighting” can help your page rank higher without running afoul of keyword-stuffing rules.
Not sure what variants make the most sense for your website? Use the “searches related to” section at the bottom of Google’s SERP for your primary keyword. Here’s why: Google has put significant time and effort into understanding intent, so the “searches related to” section will show you similar terms to your primary keyword.
Keyword Density Tools
While you can do the math on keyword density yourself by calculating the total word and keyword counts across every page on your website, this can quickly become time- and resource-intensive as your website expands and page volumes increase.
Keyword density tools help streamline this process. Potential options include:
1. SEO Review Tools Keyword Density Checker
This free tool is browser-based — simply input your site URL or page text, then complete the “I’m not a robot” captcha to perform a keyword density check. While this tool doesn’t offer the in-depth analytics of other options on the list, it’s a great way to get an overview of current keyword density.
Why We Like It
SEO Review Tool’s keyword density checker includes a color warning for keywords with an abnormally high level of appearance, so you can easily see which ones you need to pare down. It also gives you a breakdown of the keywords by word-number and allows you to exclude certain phrases.
2. SEOBook Keyword Density Analyzer
Similar to the tool above, the SEOBook Keyword Density Analyzer is free — but it does require an account to use. Along with basic keyword density reports, this tool also lets you search for your target keyword in Google, pull data for five of the top-ranked pages using the same keyword, then analyze them to see how your keyword stacks up.
Why We Like It
The SEOBook keyword density analyzer allows you to include meta information and exclude “stop words,” which tend to appear often in a text (like “does,” “a,” “the,” and so forth). You can also set a minimum word length. That gives you the ability to only include words that meet a certain character count criteria.
3. Copywritely Keyword Density Checker
Copywritely’s keyword density checker shows your top keywords by density, and color codes terms that come up often. This tool is a bit more limited than the others in that it doesn’t give you an option to exclude stop words, not does it give you an option to include meta descriptions. But it is a great starter tool.
Why We Like It
Copywritely’s simplicity and user-friendliness makes it a good option if you’re looking for a quick, at-a-glance keyword density check. You then have the option of signing up for a Copywritely account to check and correct errors.
4. Semrush’s On-Page SEO Checker
Semrush’s powerful on-page SEO checker includes a keyword density checker, named “keyword phrase usage” within the tool. Along with keyword density assessment, the tool includes automated SEO checkups and reports, assessments for titles and metadata, backlink prospecting tools, and in-depth site crawls, scans, and reports. It also helps you compare your keyword density with your competition’s. It does come at a premium price, starting at $119.95/month.
Why We Like It
Semrush isn’t just a keyword density checker, but a powerful SEO tool that can help you with all aspects of on-page SEO, including competitive comparison. You can learn how many times competitors user certain keywords. You can then get closer to their performance levels by adhering to the industry standard.
Key(words) to the Kingdom
Want to improve your SERP position and boost site impact? Start with strong keywords.
The caveat? Keyword balance is key to search success. By finding — and regularly assessing — the keyword density of both specific pages and your site at scale, it’s possible to boost relevant SEO impact and avoid the ranking pitfalls of overly-dense keyword distribution.
Editor’s note: This post was originally published in December 2020 and has been updated for comprehensiveness.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
Introduction
With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.
Types of YouTube Ads
Video Ads
- Description: These play before, during, or after a YouTube video on computers or mobile devices.
- Types:
- In-stream ads: Can be skippable or non-skippable.
- Bumper ads: Non-skippable, short ads that play before, during, or after a video.
Display Ads
- Description: These appear in different spots on YouTube and usually use text or static images.
- Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).
Companion Banners
- Description: Appears to the right of the YouTube player on desktop.
- Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.
In-feed Ads
- Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.
Outstream Ads
- Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.
Masthead Ads
- Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.
YouTube Ad Specs by Type
Skippable In-stream Video Ads
- Placement: Before, during, or after a YouTube video.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Action: 15-20 seconds
Non-skippable In-stream Video Ads
- Description: Must be watched completely before the main video.
- Length: 15 seconds (or 20 seconds in certain markets).
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
Bumper Ads
- Length: Maximum 6 seconds.
- File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
- Resolution:
- Horizontal: 640 x 360px
- Vertical: 480 x 360px
In-feed Ads
- Description: Show alongside YouTube content, like search results or the Home feed.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Headline/Description:
- Headline: Up to 2 lines, 40 characters per line
- Description: Up to 2 lines, 35 characters per line
Display Ads
- Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
- Image Size: 300×60 pixels.
- File Type: GIF, JPG, PNG.
- File Size: Max 150KB.
- Max Animation Length: 30 seconds.
Outstream Ads
- Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
- Logo Specs:
- Square: 1:1 (200 x 200px).
- File Type: JPG, GIF, PNG.
- Max Size: 200KB.
Masthead Ads
- Description: High-visibility ads at the top of the YouTube homepage.
- Resolution: 1920 x 1080 or higher.
- File Type: JPG or PNG (without transparency).
Conclusion
YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
A deeper dive into data, personalization and Copilots
Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.
To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.
Dig deeper: Salesforce piles on the Einstein Copilots
Salesforce’s evolving architecture
It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?
“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”
Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”
That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.
“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.
Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”
Let’s learn more about Einstein Copilot
“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.
For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”
Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”
It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”
What’s new about Einstein Personalization
Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?
“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”
Finally, trust
One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.
“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”
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