SEO
How to Put a $ Value on Your Content
The formula for calculating ROI is so simple that I’ll share it right here, in the article introduction:
((Return from content − cost of content) / cost of content) * 100If your content marketing generated $10,000 in sales and cost $2,000 to create, that’s an ROI of 400%:
(($10,000 - $2,000) / $2,000) * 100 = 400%Although the math is simple, actually doing this exercise in real life is tricky, for a few reasons. The most important: it’s pretty hard to put a dollar value on every single benefit of your content marketing.
I’ll explain why, and then show you 3 practical methods for quickly working out your content marketing ROI.
If you want to talk convincingly about ROI to your boss or your clients, it helps to understand these three points:
If all of your content marketing is outsourced from freelancers or agencies, it’s relatively easy to work out how much it costs: it’s the amount they bill you.
If you have an entirely in-house team, with team members dedicating 100% of their effort to content, costs are similarly straightforward: it’s their salaries.
But things can get a little complicated if you source content from multiple sources (like a combination of freelancers, agencies, and in-house team members), or if multiple people contribute to your content in relatively small ways (like a designer dedicating a third of their time to content, and two thirds to product marketing).
But this is still simple compared to our next complication:
The most obvious benefit of content marketing: it attracts new customers. We can theoretically add up all the new customers who found and bought our product because of our content marketing, and work out how much money they spent (I explain how in the next section).
But content has lots of other benefits that are less easy to measure. It can:
- Encourage upsells and expansion. By sharing product tips and new use cases, content can provide the nudge needed to turn free users into power users, or “Lite” plan customers into “Advanced” plan users—like My 5 Favorite Ahrefs Use Cases for Content Marketers.
- Save money on customer support. Content can help answer customer questions before they become support queries, like the many guides we’ve published to help users understand how metrics like Traffic Value are calculated, and how they can be used.
- Build brand recognition and affinity. Content can give your brand a voice, sharing the motivations and beliefs that underpin the products or services you sell. We generally like to buy from companies we respect, so “brand affinity” can make a real difference to the bottom line.
- Makes paid search advertising more effective. Sending paid search traffic to articles instead of “traditional” landing pages can reduce the cost of clicks (something we’ve done for articles like our guide to keyword research).
- Help other pages perform better. A page that generates a ton of backlinks but no sales (like our list of SEO statistics) can still contribute to revenue by helping other “money” pages rank better for their target keywords.
Many of these benefits are virtually invisible—how do you measure support queries that content stopped from existing?—but very real. No matter how you calculate ROI, there’s a good chance you’ll be undervaluing its impact.
Which brings us to our next complication:
Working out the role content played in a sale is called “attribution”, and it’s pretty tricky to pin down.
Did someone convert because of an article or in spite of it? When they read multiple articles, which had the biggest impact? If someone buys because of an advert, should we still credit the blog post they read beforehand?
Customer journeys are also rarely as straightforward as we’d hope. One person might read 50 articles and never buy anything; another might read a single article, disappear for a year, and immediately buy. What role did content play in those journeys?
There are different ways of measuring attribution to help with some of this uncertainty:
- First-touch attribution credits the first piece of content a visitor engages with before converting.
- Last-touch attribution credits the last piece of content.
- Multi-touch attribution tries to credit every piece of content that was involved in the buying process.
But in all cases, attribution is never perfect: we just can’t measure every interaction someone has with our content.
In a perfect world, we would know exactly how much revenue each and every blog post generated for our business. To calculate ROI this way, we can use a formula as follows:
Return from content marketing = (New customers from content * ACV)
To work this out, we need to calculate the number of new customers generated by our content in a given period. If you don’t know this figure, you’ll need to set up some kind of conversation tracking in software like Google Analytics, allowing you to track the number of people that complete a desired action on your blog post (like filling in a form or starting a free trial)
In most cases, visitors won’t buy directly from your blog post, so you’ll need to track:
- The number of conversions generated by your content (e.g. free trial signups or demo requests), and
- The number of those conversions that went on to become paying customers.
In the image below, we can see which pages visitors land on before purchasing a product. We can also see the conversion rate and the revenue attributed to the conversions:
Next, we need to calculate ACV: average customer value. This refers to the typical amount that customers spend with our company over the course of their relationship with us.
If we sell one product, and most customers buy just once, our ACV will be the price of our product. If we offer multiple products or add-ons, and customers buy regularly or set up subscriptions, then our ACV will be a lot higher.
Let’s assume that our conversion analysis shows that we had 1,000 free trial signups from our content in February, and 100 of those free trials became paying customers. If our ACV is $2,000, we can plug these numbers into our formula to calculate a return from content of $200,000:
(New customers from content * ACV) = 100 * $2,000 = $200,000This method is the gold standard of ROI calculations, but (because of the problems mentioned above) calculating ROI like this can be extremely complicated.
At the other end of the spectrum, here’s a quick and easy method that takes about 30 seconds using Ahrefs:
Return from content marketing = (monthly traffic value * content lifetime in months)
Instead of working out how much revenue we’ve generated from our content, this method estimates how much money we’ve saved by ranking organically for keywords instead of paying for advertising.
In Ahrefs, you can estimate the Traffic Value of any article—the amount it would cost to generate the same traffic via Google Ads, instead of SEO.
Below, we can see that it would cost an estimated ~$44k to “replace” the traffic to our list of free SEO tools using ads:
If we add up the traffic value of all the pages in our blog, we have an estimated monthly traffic value of $790,000:
Put another way, if we used paid advertising to get the same amount of visits from the same keywords, we’d need to spend around $790,000 on ads, each and every month.
Most content is useful for longer than a single month, so we can multiply this monthly traffic value by the expected useful “lifetime” of our content. If we use two years as a starting point, that gives us a lifetime traffic value of $18,960,000:
(Monthly traffic value * content lifetime) = $790,900 * 24-months = $18,960,000We have over 2,000 blog articles at Ahrefs, and we were probably never going to spend $19 million on paid advertising. But this calculation allows you to assign a dollar value to your content in a matter of seconds. It’s particularly useful if your company recently switched from a heavy reliance on paid advertising to content marketing, letting you show off the money you’ve saved from the switch.
Let’s wrap up with a best-of-both-worlds approach, very similar to how we calculate ROI at Ahrefs:
Return from content = (% of signups attributed to content * total signup revenue)
Whenever a new customer signs up for Ahrefs, we ask them a question: Where did you hear about us?
Their answer is piped into a dedicated Slack channel, #registrations, which gives us a live feed of new signups and, crucially, how they discovered Ahrefs. Sam, our VP of Marketing, regularly uses this feed to work out the percentage of total signups that can be attributed to his YouTube content.
If I head to #registrations and run a search for signups that mentioned “youtube”, we can see over 34,000 people that directly attributed their discovery of Ahrefs to Sam’s video content:
We can use this to estimate content marketing ROI: if 33% of all respondents in a given month attribute their signing up to YouTube, it would be fairly reasonable to assume that 33% of all signups came from YouTube, and that 33% of all new revenue should be attributed to our video content efforts.
If we assume a theoretical monthly revenue of $300,000, and that 1,000 of a total 3,000 signups could be attributed to “YouTube”, we can plug these values into our formula for a return on content of $100,000:
(33% of signups attributed to content * $300,000) = $100,000This method will underreport the number of signups generated (people might misspell YouTube, or say “videos” instead, or most likely, not answer the question at all). The relationship between new signups and new revenue might also be more complicated than we assume here (if you have lots of free users, for example).
But it has the benefit of making it easy to compare to other marketing channels. If I search for “google” in the same #registration channel, I see 94,000 mentions—bigger than Sam’s 34,000 YouTube mentions:
(Although he’s definitely catching up…)
Final thoughts
There are tons of ways to measure content marketing ROI, and none of them are perfect. But for practical purposes, they don’t need to be.
Metrics, like content marketing ROI, are most useful as directional indicators. Instead of obsessing over perfect calculations, it’s better to choose a simple methodology, stick to it consistently, and see how it changes over time.
SEO
YouTube Extends Shorts To 3 Minutes, Adds New Features
YouTube expands Shorts to 3 minutes, adds templates, AI tools, and the option to show fewer Shorts on the homepage.
- YouTube Shorts will allow 3-minute videos.
- New features include templates, enhanced remixing, and AI-generated video backgrounds.
- YouTube is adding a Shorts trends page and comment previews.
SEO
How To Stop Filter Results From Eating Crawl Budget
Today’s Ask An SEO question comes from Michal in Bratislava, who asks:
“I have a client who has a website with filters based on a map locations. When the visitor makes a move on the map, a new URL with filters is created. They are not in the sitemap. However, there are over 700,000 URLs in the Search Console (not indexed) and eating crawl budget.
What would be the best way to get rid of these URLs? My idea is keep the base location ‘index, follow’ and newly created URLs of surrounded area with filters switch to ‘noindex, no follow’. Also mark surrounded areas with canonicals to the base location + disavow the unwanted links.”
Great question, Michal, and good news! The answer is an easy one to implement.
First, let’s look at what you’re trying and apply it to other situations like ecommerce and publishers. This way, more people can benefit. Then, go into your strategies above and end with the solution.
What Crawl Budget Is And How Parameters Are Created That Waste It
If you’re not sure what Michal is referring to with crawl budget, this is a term some SEO pros use to explain that Google and other search engines will only crawl so many pages on your website before it stops.
If your crawl budget is used on low-value, thin, or non-indexable pages, your good pages and new pages may not be found in a crawl.
If they’re not found, they may not get indexed or refreshed. If they’re not indexed, they cannot bring you SEO traffic.
This is why optimizing a crawl budget for efficiency is important.
Michal shared an example of how “thin” URLs from an SEO point of view are created as customers use filters.
The experience for the user is value-adding, but from an SEO standpoint, a location-based page would be better. This applies to ecommerce and publishers, too.
Ecommerce stores will have searches for colors like red or green and products like t-shirts and potato chips.
These create URLs with parameters just like a filter search for locations. They could also be created by using filters for size, gender, color, price, variation, compatibility, etc. in the shopping process.
The filtered results help the end user but compete directly with the collection page, and the collection would be the “non-thin” version.
Publishers have the same. Someone might be on SEJ looking for SEO or PPC in the search box and get a filtered result. The filtered result will have articles, but the category of the publication is likely the best result for a search engine.
These filtered results can be indexed because they get shared on social media or someone adds them as a comment on a blog or forum, creating a crawlable backlink. It might also be an employee in customer service responded to a question on the company blog or any other number of ways.
The goal now is to make sure search engines don’t spend time crawling the “thin” versions so you can get the most from your crawl budget.
The Difference Between Indexing And Crawling
There’s one more thing to learn before we go into the proposed ideas and solutions – the difference between indexing and crawling.
- Crawling is the discovery of new pages within a website.
- Indexing is adding the pages that are worthy of showing to a person using the search engine to the database of pages.
Pages can get crawled but not indexed. Indexed pages have likely been crawled and will likely get crawled again to look for updates and server responses.
But not all indexed pages will bring in traffic or hit the first page because they may not be the best possible answer for queries being searched.
Now, let’s go into making efficient use of crawl budgets for these types of solutions.
Using Meta Robots Or X Robots
The first solution Michal pointed out was an “index,follow” directive. This tells a search engine to index the page and follow the links on it. This is a good idea, but only if the filtered result is the ideal experience.
From what I can see, this would not be the case, so I would recommend making it “noindex,follow.”
Noindex would say, “This is not an official page, but hey, keep crawling my site, you’ll find good pages in here.”
And if you have your main menu and navigational internal links done correctly, the spider will hopefully keep crawling them.
Canonicals To Solve Wasted Crawl Budget
Canonical links are used to help search engines know what the official page to index is.
If a product exists in three categories on three separate URLs, only one should be “the official” version, so the two duplicates should have a canonical pointing to the official version. The official one should have a canonical link that points to itself. This applies to the filtered locations.
If the location search would result in multiple city or neighborhood pages, the result would likely be a duplicate of the official one you have in your sitemap.
Have the filtered results point a canonical back to the main page of filtering instead of being self-referencing if the content on the page stays the same as the original category.
If the content pulls in your localized page with the same locations, point the canonical to that page instead.
In most cases, the filtered version inherits the page you searched or filtered from, so that is where the canonical should point to.
If you do both noindex and have a self-referencing canonical, which is overkill, it becomes a conflicting signal.
The same applies to when someone searches for a product by name on your website. The search result may compete with the actual product or service page.
With this solution, you’re telling the spider not to index this page because it isn’t worth indexing, but it is also the official version. It doesn’t make sense to do this.
Instead, use a canonical link, as I mentioned above, or noindex the result and point the canonical to the official version.
Disavow To Increase Crawl Efficiency
Disavowing doesn’t have anything to do with crawl efficiency unless the search engine spiders are finding your “thin” pages through spammy backlinks.
The disavow tool from Google is a way to say, “Hey, these backlinks are spammy, and we don’t want them to hurt us. Please don’t count them towards our site’s authority.”
In most cases, it doesn’t matter, as Google is good at detecting spammy links and ignoring them.
You do not want to add your own site and your own URLs to the disavow tool. You’re telling Google your own site is spammy and not worth anything.
Plus, submitting backlinks to disavow won’t prevent a spider from seeing what you want and do not want to be crawled, as it is only for saying a link from another site is spammy.
Disavowing won’t help with crawl efficiency or saving crawl budget.
How To Make Crawl Budgets More Efficient
The answer is robots.txt. This is how you tell specific search engines and spiders what to crawl.
You can include the folders you want them to crawl by marketing them as “allow,” and you can say “disallow” on filtered results by disallowing the “?” or “&” symbol or whichever you use.
If some of those parameters should be crawled, add the main word like “?filter=location” or a specific parameter.
Robots.txt is how you define crawl paths and work on crawl efficiency. Once you’ve optimized that, look at your internal links. A link from one page on your site to another.
These help spiders find your most important pages while learning what each is about.
Internal links include:
- Breadcrumbs.
- Menu navigation.
- Links within content to other pages.
- Sub-category menus.
- Footer links.
You can also use a sitemap if you have a large site, and the spiders are not finding the pages you want with priority.
I hope this helps answer your question. It is one I get a lot – you’re not the only one stuck in that situation.
More resources:
Featured Image: Paulo Bobita/Search Engine Journal
SEO
Ad Copy Tactics Backed By Study Of Over 1 Million Google Ads
Mastering effective ad copy is crucial for achieving success with Google Ads.
Yet, the PPC landscape can make it challenging to discern which optimization techniques truly yield results.
Although various perspectives exist on optimizing ads, few are substantiated by comprehensive data. A recent study from Optmyzr attempted to address this.
The goal isn’t to promote or dissuade any specific method but to provide a clearer understanding of how different creative decisions impact your campaigns.
Use the data to help you identify higher profit probability opportunities.
Methodology And Data Scope
The Optmyzr study analyzed data from over 22,000 Google Ads accounts that have been active for at least 90 days with a minimum monthly spend of $1,500.
Across more than a million ads, we assessed Responsive Search Ads (RSAs), Expanded Text Ads (ETAs), and Demand Gen campaigns. Due to API limitations, we could not retrieve asset-level data for Performance Max campaigns.
Additionally, all monetary figures were converted to USD to standardize comparisons.
Key Questions Explored
To provide actionable insights, we focused on addressing the following questions:
- Is there a correlation between Ad Strength and performance?
- How do pinning assets impact ad performance?
- Do ads written in title case or sentence case perform better?
- How does creative length affect ad performance?
- Can ETA strategies effectively translate to RSAs and Demand Gen ads?
As we evaluated the results, it’s important to note that our data set represents advanced marketers.
This means there may be selection bias, and these insights might differ in a broader advertiser pool with varying levels of experience.
The Relationship Between Ad Strength And Performance
Google explicitly states that Ad Strength is a tool designed to guide ad optimization rather than act as a ranking factor.
Despite this, marketers often hold mixed opinions about its usefulness, as its role in ad performance appears inconsistent.
Our data corroborates this skepticism. Ads labeled with an “average” Ad Strength score outperformed those with “good” or “excellent” scores in key metrics like CPA, conversion rate, and ROAS.
This disparity is particularly evident in RSAs, where the ROAS tends to decrease sharply when moving from “average” to “good,” with only a marginal increase when advancing to “excellent.”
Screenshot from author, September 2024Interestingly, Demand Gen ads also showed a stronger performance with an “average” Ad Strength, except for ROAS.
The metrics for conversion rates in Demand Gen and RSAs were notably similar, which is surprising since Demand Gen ads are typically designed for awareness, while RSAs focus on driving transactions.
Key Takeaways:
- Ad Strength doesn’t reliably correlate with performance, so it shouldn’t be a primary metric for assessing your ads.
- Most ads with “poor” or “average” Ad Strength labels perform well by standard advertising KPIs.
- “Good” or “excellent” Ad Strength labels do not guarantee better performance.
How Does Pinning Affect Ad Performance?
Pinning refers to locking specific assets like headlines or descriptions in fixed positions within the ad. This technique became common with RSAs, but there’s ongoing debate about its efficacy.
Some advertisers advocate for pinning all assets to replicate the control offered by ETAs, while others prefer to let Google optimize placements automatically.
Image from author, September 2024Our data suggests that pinning some, but not all, assets offers the most balanced results in terms of CPA, ROAS, and CPC. However, ads where all assets are pinned achieve the highest relevance in terms of CTR.
Still, this marginally higher CTR doesn’t necessarily translate into better conversion metrics. Ads with unpinned or partially pinned assets generally perform better in terms of conversion rates and cost-based metrics.
Key Takeaways:
- Selective pinning is optimal, offering a good balance between creative control and automation.
- Fully pinned ads may increase CTR but tend to underperform in metrics like CPA and ROAS.
- Advertisers should embrace RSAs, as they consistently outperform ETAs – even with fully pinned assets.
Title Case Vs. Sentence Case: Which Performs Better?
The choice between title case (“This Is a Title Case Sentence”) and sentence case (“This is a sentence case sentence”) is often a point of contention among advertisers.
Our analysis revealed a clear trend: Ads using sentence case generally outperformed those in title case, particularly in RSAs and Demand Gen campaigns.
Image from author, September 2024(RSA Data)
Image from author, September 2024(ETA Data)
Image from author, September 2024(Demand Gen)
ROAS, in particular, showed a marked preference for sentence case across these ad types, suggesting that a more natural, conversational tone may resonate better with users.
Interestingly, many advertisers still use a mix of title and sentence case within the same account, which counters the traditional approach of maintaining consistency throughout the ad copy.
Key Takeaways:
- Sentence case outperforms title case in RSAs and Demand Gen ads on most KPIs.
- Including sentence case ads in your testing can improve performance, as it aligns more closely with organic results, which users perceive as higher quality.
- Although ETAs perform slightly better with title case, sentence case is increasingly the preferred choice in modern ad formats.
The Impact Of Ad Length On Performance
Ad copy, particularly for Google Ads, requires brevity without sacrificing impact.
We analyzed the effects of character count on ad performance, grouping ads by the length of headlines and descriptions.
Image from author, September 2024
Image from author, September 2024(RSA Data)
Image from author, September 2024
Image from author, September 2024(ETA Data)
Image from author, September 2024
Image from author, September 2024(Demand Gen Data)
Interestingly, shorter headlines tend to outperform longer ones in CTR and conversion rates, while descriptions benefit from moderate length.
Ads that tried to maximize character counts by using dynamic keyword insertion (DKI) or customizers often saw no significant performance improvement.
Moreover, applying ETA strategies to RSAs proved largely ineffective.
In almost all cases, advertisers who carried over ETA tactics to RSAs saw a decline in performance, likely because of how Google dynamically assembles ad components for display.
Key Takeaways:
- Shorter headlines lead to better performance, especially in RSAs.
- Focus on concise, impactful messaging instead of trying to fill every available character.
- ETA tactics do not translate well to RSAs, and attempting to replicate them can hurt performance.
Final Thoughts On Ad Optimizations
In summary, several key insights emerge from this analysis.
First, Ad Strength should not be your primary focus when assessing performance. Instead, concentrate on creating relevant, engaging ad copy tailored to your target audience.
Additionally, pinning assets should be a strategic, creative decision rather than a hard rule, and advertisers should incorporate sentence case into their testing for RSAs and Demand Gen ads.
Finally, focus on quality over quantity in ad copy length, as longer ads do not always equate to better results.
By refining these elements of your ads, you can drive better ROI and adapt to the evolving landscape of Google Ads.
Read the full Ad Strength & Creative Study from Optmyzr.
More resources:
Featured Image: Sammby/Shutterstock
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