Marketing goals can be defined as broad, long-term outcomes that a company wants to achieve via marketing efforts.
Setting clear marketing goals is important, as this can effectively focus your team on a shared vision. But the thing is, you need to choose your goals carefully. Otherwise, you may waste a lot of time on things that bring poor results or even undermine your past efforts.
In this article, we’ve curated a short list of strategic goals that are worth considering in any marketing strategy, along with some ideas on how you can measure them:
- Improve product satisfaction
- Grow organic traffic
- Generate leads
- Establish thought leadership
- Increase brand awareness
- Increase revenue
Any successful marketing needs to be founded on a good product that satisfies existing market demand. Otherwise, none of your marketing efforts will “stick.” Meaning, no matter how you promote the product, you will fail to convince your audience and build sustainable growth.
Conversely, a product that users are willing to use, buy, and recommend to others will reinforce all marketing activities. In fact, a lot of successful companies have grown solely or mainly via word-of-mouth recommendations sparked by the remarkable value of their products (e.g., Whatsapp, Tesla).
To set yourself on the right path of improving product satisfaction, you need to achieve product-market fit.
Once you know you’re in the right market with the right kind of product, you can start delighting your users with useful features and a great user experience. Keep in mind that even seemingly simple product improvements can go a long way.
We have finally released this long overdue SEO metric:
🔥 Traffic potential 🔥
Because pages don’t rank in Google for just a single keyword. They also rank for all the different variations of that keyword and get search traffic from them. https://t.co/a0ehTT5WJV pic.twitter.com/zQAXCaQTYj
— Tim Soulo (@timsoulo) November 12, 2021
How to measure
You can measure product satisfaction in two ways: ask your users what they think or gather relevant data from product usage.
In surveys, you should ask all kinds of questions that help you understand how well your product satisfies users’ needs. You can also use tried and tested methods like the popular and uncomplicated Net Promoter Score (NPS) survey.
This survey comprises just one question: “How likely are you to recommend [product] to a friend or colleague?” The answers are given on a 10-point scale.
You can find multiple tools online that will help you distribute the survey and calculate your NPS (e.g., Hotjar, Survicate).
If you’re running an online service, consider measuring product satisfaction with product analysis tools (also called product intelligence tools) like Mixpanel or Amplitude. They work by gathering data from your users’ in-app behavior and allowing you to analyze the data to gain insights from it.
For example, by measuring how often your users reach out for particular features inside your product, you can see whether those features bring value or not. Then, you can discard unused features based on real data or conduct experiments (e.g., tweaking your features or making them more visible).
User retention (or cohort retention) is a metric used for measuring the ability to keep customers over a specified period of time.
If your customers go as quickly as they come, this is usually a huge red flag (with some exceptions, e.g., e‑commerce). If you’re not operating in a niche where a short usage period is natural, low user retention is a sign that:
- Users don’t find what you’ve promised in your marketing communication.
- Your product delivers the promise, but your competitors do a better job.
In these scenarios, it’s likely you’re wasting money and brand equity by providing something people are not willing to stay with. So you need to improve your product fast.
That said, even if you have the best product on the market, the so-called customer churn (i.e., when customers stop using your product) is a natural phenomenon to some extent. The key here is to determine whether you have a healthy retention rate.
Organic traffic, also called organic search traffic, refers to the visitors who come to your website via the non-paid search results from a search engine (e.g., Google, DuckDuckGo).
To take advantage of the organic traffic potential from search engines, you need to publish content based on search demand and the business value of a particular topic (the so-called SEO content).
That way, whenever someone searches for a solution via a search engine, they will find your content and, consequently, your brand and product.
Here are the top reasons why you should join the majority of marketers who invest in creating SEO content to grow organic traffic:
- SEO content can influence and even drive the entire marketing funnel.
- Such content brings almost free, continuous traffic.
- Compounding effects. A blog post written years ago can get you traffic now and into the future as long as you rank high.
- How much your organic traffic grows depends more on content quality and creativity rather than budget.
- The flywheel effect: Content marketing done right can be a self-reinforcing mechanism that helps you get results more easily as you go along.
Let me just add that this is not some hypothesis. At Ahrefs, we’ve been systematically developing search engine optimized articles and videos, and the articles alone bring us approximately 384K organic visits every month.
How to measure
We can recommend two types of tools here.
Firstly, measuring organic traffic is best done via Google Search Console (GSC). This is a free tool that gives the most accurate organic traffic data. GSC will show you the number of clicks coming from Google Search, Discover, or News. It’ll also show you the number of times your content has been displayed by Google (i.e., impressions):
While GSC does a great job of providing these simple metrics, it lacks features and data for comprehensive organic traffic analysis.
For example, while GSC will show you up to 1K keywords and up to 1K backlinks, Ahrefs Webmaster Tools will show you that and many more data points without any limits.
To sum up, you can use GSC for measuring organic traffic and other more advanced SEO tools for SEO analysis and finding growth opportunities.
To put things simply, the more leads you generate, the more revenue you make. This is because every lead is a potential customer. However, not every lead will become a customer, so you need a lot more leads to get your desired number of customers.
A lead is anyone who has expressed interest in a product or service by sharing their contact information (e.g., email address) with a company in exchange for some kind of value (e.g., free ebook, free tool, weekly email newsletter with educational materials).
More often than not, potential customers are not instantly ready to buy. This is especially when they have little or no acquaintance with your brand.
When there is a lot of competition in the market, your potential customers are likely to do some research and compare you to others before they make a purchase. Moreover, if your product is complex and/or expensive, people need to make sure the product will solve their problem or will be worth their money and effort.
This is where lead generation comes in. When a person gives you their contact information, you gain an opportunity to contact them directly in the future. You can use that opportunity to nurture your relationship with them to a point where they are ready to buy.
To generate leads, you will need three things:
- Traffic – In other words, visitors coming through your marketing channels.
- Offer – The value you are going to provide in exchange for contact information (e.g., free ebook).
- Lead capture – A form where people can submit their contact information (e.g., name, phone number, email address).
How to measure
How you measure your lead generation depends on your offer. This can be the number of newsletter subscribers, trial sign-ups, app downloads, or whatever else you are planning to provide.
The simplest way to measure incoming leads is via the same tool you use to capture your leads. For example, our email capture form uses Mailchimp’s functionality. It’s the same app we use to monitor the number of leads and send a weekly newsletter to people who signed up.
You can also aggregate your data in a business intelligence software like Google Data Studio or Klipfolio. Then view the data next to other important metrics for quick insights, such as the conversion rate from leads to customers.
In marketing, thought leadership is demonstrating your brand has expertise in its area of business. Effective thought leadership creates a belief among your target audience that your solutions are the best.
Through effective thought leadership, you become an authority in your industry—that status reinforces every message you send out. And so, in the classic conundrum of whether the messenger is more important than the message, you can actually have both.
The more sophisticated and technically oriented the market, the more thought leadership counts. A good example of this is the electric car market. Tesla is an undisputed thought leader in this area. That’s why it surpasses sales of other established car brands with larger advertising budgets. In fact, Tesla is famous for its anti-advertising attitude.
We don’t buy advertising
— Elon Musk (@elonmusk) April 29, 2019
How to measure
Measuring your progress in becoming a thought leader depends on where you share your ideas. Here, we’ll show examples of two effective channels and their respective metrics.
A backlink is a link on one website that links to another website. Backlinks act as votes. Even Google thinks so, treating backlinks as one of the most important ranking factors.
And so if you publish content that gets this kind of vote, you’re on the right track of becoming an authority in your industry. This is because people are digitally voting for what you say, resulting in direct traffic from those pages and higher search engine rankings.
To illustrate, one of the widely discussed subjects in the SEO community is building links through outreach. Our CMO, Tim Soulo, has joined the conversation with an article called I Just Deleted Your Outreach Email. And NO, I Don’t Feel Sorry, which explains how to do effective outreach that doesn’t feel like spam.
That article alone got over 2K backlinks (aka digital votes).
And just a quick reminder—sharing ideas through such articles brings customers:
Speaking engagements come in different shapes and sizes. These can be either big industry events like BrightonSEO (with some 4K attendees) or more cozy settings with smaller audiences like podcast interviews.
What they all have in common is getting attention from industry professionals and even industry authorities. So the more you speak at those events, the more likely you are to reach people with your ideas (and your name) and become an authority in your niche.
With speaking engagements, you can put your name on the map, attract followers to your social media channels, and communicate with these followers directly later on.
Once you have more budget, you can even up the ante by creating your own conference, especially if you want to popularize an original concept. That’s what Hubspot has done with the term “inbound marketing” and its INBOUND event.
A brand is a central concept in marketing, and it’s been this way for decades. This is because brands have powerful effects on consumers:
- A brand makes recognizing the product as easy as remembering the word or the shape of a logo.
- A brand evokes associations with positive experiences.
- A brand allows for rationalizing the cost of the product.
Building brand awareness increases the odds of consumers associating your brand or product with a specific need.
Just think about it. Starbucks is one of the most valuable brands in the world. For millions of people, Starbucks is the synonym of coffee. So essentially, it isn’t an exaggeration to say its business relies on a mental association between a logo and a need for coffee. That’s how powerful brand awareness is.
And the amazing part is, however absurd this may sound, the Starbucks logo has nothing to do with coffee. Starbucks has even dropped the word “coffee” from the logo.
How to measure
Measuring brand awareness is the domain of specialized research companies. A common method for measuring it is through surveys. However, this option has its flaws: It’s expensive and time-consuming.
Alternatively, you can gauge the overall trend of your brand awareness yourself using online tools. The only caveat is this method will give more accurate estimations for online businesses than the predominantly offline ones.
You can also use a keyword research tool to discover the search volume of your brand name. The reason is this: If your brand awareness increases, more people will want to buy from you and look up your brand on the web.
For example, if you use Ahrefs’ Keywords Explorer, you can just plug in your brand name and instantly get:
- The number of estimated monthly searches for a specific country (and globally).
- A graph of monthly searches plotted in time that offers quick insights into trends.
You can also easily measure your performance against your competitors’ (technically, this kind of comparison is called measuring the share of voice).
If you’re not an Ahrefs user or just need a point of reference without the search volume data, you can use Google Trends to gauge interest in branded queries.
So far, we’ve discussed rather indirect ways to increase revenue. Now, we’ll discuss three ideas for increasing revenue directly.
The first way is revising your pricing. If you have solid reasons for thinking you’re not charging enough for the value you provide, you can try to increase prices. Even a price increase of a few percent can result in significant returns if multiplied by hundreds or even thousands of new customers. Word of advice: A good practice here is to keep the original price for any existing customers.
A seemingly counterintuitive way (also quite risky) to increase your profits is through lowering prices (e.g., penetration pricing, loss leader strategy). This can lower the barrier enough for the arrival of new customers (you can even win your competitors’ customers this way).
Recommended reading: How to Increase SaaS Prices the Right (and Profitable) Way
The second way is adding new services and/or products. For instance, a dog food brand decides to expand its assortment by offering dog accessories like toys, dog care products, or beddings. It can even create special product bundles and call it “new dog owner essentials.”
The third way is cross-selling and upselling. Cross-selling means suggesting other products in addition to the chosen product. Upselling suggests a more expensive version of the chosen product.
Let’s learn from the best here. When you’re shopping for a new iMac, you will first see a standard price for the product:
Then you will be offered an array of upsell options:
Followed by an even wider array of cross-selling suggestions:
How to measure
The easiest way to measure revenue is to measure the number and the value of sales. But a lot of companies also need to measure recurring revenue from subscriptions, the revenue growth rate, and the value of each new customer.
Monthly recurring revenue (MRR) measures how much you’re earning each month through recurring contracts (i.e., subscriptions).
MRR = number of subscribers on a monthly plan * average revenue per user
For annual plans, you have to divide the plan price by 12 and then multiply by the number of customers on that plan.
For example: If you have 700 customers on a $9 per month plan and 100 customers on a $97 yearly plan, your MRR will be:
(700 x $9) + ($97/12 x 100) = $7,108 MRR
If you want to track annual recurring revenue (ARR) as well, all you need to do is multiply MRR by 12.
In our example, that is:
$7,108*12 = $85,296 ARR
Revenue growth rate
Revenue growth rate measures the month-over-month percentage increase in revenue. This metric is an indicator of how quickly your company is growing.
You can measure the revenue growth rate for any period you need: weeks, months, or years.
Let’s say you want to measure the annual growth rate compared to the previous year. The formula for that will be:
(revenue year 2 — revenue year 1) / revenue year 1 x 100 = revenue growth rate (%)
In our example, that is:
($170,592 — $85,296) / $85,296 x 100 = 100% revenue growth rate
Customer lifetime value
Customer lifetime value (CLV) is the total worth of a customer to a business over the whole period of their relationship. CLV can also be used as a predictive metric of how much revenue each new customer will bring on average.
There are multiple models of calculating CLV. Without going into too much detail about each alternative, here’s a fairly simple formula to calculate CLV:
customer lifetime value = average order value x purchase frequency rate x average customer lifetime
- Average order value is your total revenue divided by the number of purchases.
- Purchase frequency rate is the total number of purchases divided by the number of customers.
- Average customer lifetime is the number of days between the first and last purchase date, divided by 365.
Marketing goals, by nature, are usually grand and ambitious. Hence, they can be quite intimidating.
But no worries. You can overcome that problem by setting achievable goals and breaking your overarching goal into smaller bits. You can see how it’s done in practice using SEO goals as an example in the below article:
Got questions? Ping me on Twitter.
Are Contextual Links A Google Ranking Factor?
Inbound links are a ranking signal that can vary greatly in terms of how they’re weighted by Google.
One of the key attributes that experts say can separate a high value link from a low value link is the context in which it appears.
When a link is placed within relevant content, it’s thought to have a greater impact on rankings than a link randomly inserted within unrelated text.
Is there any bearing to that claim?
Let’s dive deeper into what has been said about contextual links as a ranking factor to see whether there’s any evidence to support those claims.
The Claim: Contextual Links Are A Ranking Factor
A “contextual link” refers to an inbound link pointing to a URL that’s relevant to the content in which the link appears.
When an article links to a source to provide additional context for the reader, for example, that’s a contextual link.
Contextual links add value rather than being a distraction.
They should flow naturally with the content, giving the reader some clues about the page they’re being directed to.
Not to be confused with anchor text, which refers to the clickable part of a link, a contextual link is defined by the surrounding text.
A link’s anchor text could be related to the webpage it’s pointing to, but if it’s surrounded by content that’s otherwise irrelevant then it doesn’t qualify as a contextual link.
Contextual links are said to be a Google ranking factor, with claims that they’re weighted higher by the search engine than other types of links.
One of the reasons why Google might care about context when it comes to links is because of the experience it creates for users.
When a user clicks a link and lands on a page related to what they were previously looking at, it’s a better experience than getting directed to a webpage they aren’t interested in.
Modern guides to link building all recommend getting links from relevant URLs, as opposed to going out and placing links anywhere that will take them.
There’s now a greater emphasis on quality over quantity when it comes to link building, and a link is considered higher quality when its placement makes sense in context.
One high quality contextual link can, in theory, be worth more than multiple lower quality links.
That’s why experts advise site owners to gain at least a few contextual links, as that will get them further than building dozens of random links.
If Google weights the quality of links higher or lower based on context, it would mean Google’s crawlers can understand webpages and assess how closely they relate to other URLs on the web.
Is there any evidence to support this?
The Evidence For Contextual Links As A Ranking Factor
Evidence in support of contextual links as a ranking factor can be traced back to 2012 with the launch of the Penguin algorithm update.
Google’s original algorithm, PageRank, was built entirely on links. The more links pointing to a website, the more authority it was considered to have.
Websites could catapult their site up to the top of Google’s search results by building as many links as possible. It didn’t matter if the links were contextual or arbitrary.
Google’s PageRank algorithm wasn’t as selective about which links it valued (or devalued) over others until it was augmented with the Penguin update.
Penguin brought a number of changes to Google’s algorithm that made it more difficult to manipulate search rankings through spammy link building practices.
In Google’s announcement of the launch of Penguin, former search engineer Matt Cutts highlighted a specific example of the link spam it’s designed to target.
This example depicts the exact opposite of a contextual link, with Cutts saying:
“Here’s an example of a site with unusual linking patterns that is also affected by this change. Notice that if you try to read the text aloud you’ll discover that the outgoing links are completely unrelated to the actual content, and in fact, the page text has been “spun” beyond recognition.”
A contextual link, on the other hand, looks like the one a few paragraphs above linking to Google’s blog post.
Links with context share the following characteristics:
- Placement fits in naturally with the content.
- Linked URL is relevant to the article.
- Reader knows where they’re going when they click on it.
All of the documentation Google has published about Penguin over the years is the strongest evidence available in support of contextual links as a ranking factor.
Google will never outright say “contextual link building is a ranking factor,” however, because the company discourages any deliberate link building at all.
As Cutts adds at the end of his Penguin announcement, Google would prefer to see webpages acquire links organically:
“We want people doing white hat search engine optimization (or even no search engine optimization at all) to be free to focus on creating amazing, compelling web sites.”
Contextual Links Are A Ranking Factor: Our Verdict
Contextual links are probably a Google ranking factor.
A link is weighted higher when it’s used in context than if it’s randomly placed within unrelated content.
But that doesn’t necessarily mean links without context will negatively impact a site’s rankings.
External links are largely outside a site owner’s control.
If a website links to you out of context it’s not a cause for concern, because Google is capable of ignoring low value links.
On the other hand, if Google detects a pattern of unnatural links, then that could count against a site’s rankings.
If you have actively engaged in non-contextual link building in the past, it may be wise to consider using the disavow tool.
Featured Image: Paulo Bobita/Search Engine Journal
Is It A Google Ranking Factor?
Latent semantic indexing (LSI) is an indexing and information retrieval method used to identify patterns in the relationships between terms and concepts.
With LSI, a mathematical technique is used to find semantically related terms within a collection of text (an index) where those relationships might otherwise be hidden (or latent).
And in that context, this sounds like it could be super important for SEO.
If you’ve heard rumblings about latent semantic indexing in SEO or been advised to use LSI keywords, you aren’t alone.
But will LSI actually help improve your search rankings? Let’s take a look.
The Claim: Latent Semantic Indexing As A Ranking Factor
The claim is simple: Optimizing web content using LSI keywords helps Google better understand it and you’ll be rewarded with higher rankings.
Backlinko defines LSI keywords in this way:
“LSI (Latent Semantic Indexing) Keywords are conceptually related terms that search engines use to deeply understand content on a webpage.”
By using contextually related terms, you can deepen Google’s understanding of your content. Or so the story goes.
That resource goes on to make some pretty compelling arguments for LSI keywords:
- “Google relies on LSI keywords to understand content at such a deep level.”
- “LSI Keywords are NOT synonyms. Instead, they’re terms that are closely tied to your target keyword.”
- “Google doesn’t ONLY bold terms that exactly match what you just searched for (in search results). They also bold words and phrases that are similar. Needless to say, these are LSI keywords that you want to sprinkle into your content.”
Does this practice of “sprinkling” terms closely related to your target keyword help improve your rankings via LSI?
The Evidence For LSI As A Ranking Factor
Relevance is identified as one of five key factors that help Google determine which result is the best answer for any given query.
As Google explains is its How Search Works resource:
“To return relevant results for your query, we first need to establish what information you’re looking forーthe intent behind your query.”
Once intent has been established:
“…algorithms analyze the content of webpages to assess whether the page contains information that might be relevant to what you are looking for.”
Google goes on to explain that the “most basic signal” of relevance is that the keywords used in the search query appear on the page. That makes sense – if you aren’t using the keywords the searcher is looking for, how could Google tell you’re the best answer?
Now, this is where some believe LSI comes into play.
If using keywords is a signal of relevance, using just the right keywords must be a stronger signal.
There are purpose-build tools dedicated to helping you find these LSI keywords, and believers in this tactic recommend using all kinds of other keyword research tactics to identify them, as well.
The Evidence Against LSI As A Ranking Factor
“…we have no concept of LSI keywords. So that’s something you can completely ignore.”
There’s a healthy skepticism in SEO that Google may say things to lead us astray in order to protect the integrity of the algorithm. So let’s dig in here.
First, it’s important to understand what LSI is and where it came from.
Latent semantic structure emerged as a methodology for retrieving textual objects from files stored in a computer system in the late 1980s. As such, it’s an example of one of the earlier information retrieval (IR) concepts available to programmers.
As computer storage capacity improved and electronically available sets of data grew in size, it became more difficult to locate exactly what one was looking for in that collection.
Researchers described the problem they were trying to solve in a patent application filed September 15, 1988:
“Most systems still require a user or provider of information to specify explicit relationships and links between data objects or text objects, thereby making the systems tedious to use or to apply to large, heterogeneous computer information files whose content may be unfamiliar to the user.”
Keyword matching was being used in IR at the time, but its limitations were evident long before Google came along.
Too often, the words a person used to search for the information they sought were not exact matches for the words used in the indexed information.
There are two reasons for this:
- Synonymy: the diverse range of words used to describe a single object or idea results in relevant results being missed.
- Polysemy: the different meanings of a single word results in irrelevant results being retrieved.
These are still issues today, and you can imagine what a massive headache it is for Google.
However, the methodologies and technology Google uses to solve for relevance long ago moved on from LSI.
What LSI did was automatically create a “semantic space” for information retrieval.
As the patent explains, LSI treated this unreliability of association data as a statistical problem.
Without getting too into the weeds, these researchers essentially believed that there was a hidden underlying latent semantic structure they could tease out of word usage data.
Doing so would reveal the latent meaning and enable the system to bring back more relevant results – and only the most relevant results – even if there’s no exact keyword match.
Here’s what that LSI process actually looks like:
And here’s the most important thing you should note about the above illustration of this methodology from the patent application: there are two separate processes happening.
First, the collection or index undergoes Latent Semantic Analysis.
Second, the query is analyzed and the already-processed index is then searched for similarities.
And that’s where the fundamental problem with LSI as a Google search ranking signal lies.
Google’s index is massive at hundreds of billions of pages, and it’s growing constantly.
Each time a user inputs a query, Google is sorting through its index in a fraction of a second to find the best answer.
Using the above methodology in the algorithm would require that Google:
- Recreate that semantic space using LSA across its entire index.
- Analyze the semantic meaning of the query.
- Find all similarities between the semantic meaning of the query and documents in the semantic space created from analyzing the entire index.
- Sort and rank those results.
That’s a gross oversimplification, but the point is that this isn’t a scalable process.
This would be super useful for small collections of information. It was helpful for surfacing relevant reports inside a company’s computerized archive of technical documentation, for example.
The patent application illustrates how LSI works using a collection of nine documents. That’s what it was designed to do. LSI is primitive in terms of computerized information retrieval.
Latent Semantic Indexing As A Ranking Factor: Our Verdict
While the underlying principles of eliminating noise by determining semantic relevance have surely informed developments in search ranking since LSA/LSI was patented, LSI itself has no useful application in SEO today.
It hasn’t been ruled out completely, but there is no evidence that Google has ever used LSI to rank results. And Google definitely isn’t using LSI or LSI keywords today to rank search results.
Those who recommend using LSI keywords are latching on to a concept they don’t quite understand in an effort to explain why the ways in which words are related (or not) is important in SEO.
Relevance and intent are foundational considerations in Google’s search ranking algorithm.
Those are two of the big questions they’re trying to solve for in surfacing the best answer for any query.
Synonymy and polysemy are still major challenges.
Semantics – that is, our understanding of the various meanings of words and how they’re related – is essential in producing more relevant search results.
But LSI has nothing to do with that.
Featured Image: Paulo Bobita/Search Engine Journal
What Is a Google Broad Core Algorithm Update?
Google’s acknowledgment of core updates is always vague and doesn’t provide much detail other than to say the update occurred.
The SEO community is typically notified about core updates via the same standard tweets from Google’s Search Liaison.
There’s one announcement from Google when the update begins rolling out, and one on its conclusion, with few additional details in between (if any).
This invariably leaves SEO professionals and site owners asking many questions with respect to how their rankings were impacted by the core update.
To gain insight into what may have caused a site’s rankings to go up, down, or stay the same, it helps to understand what a broad core update is and how it differs from other types of algorithm updates.
After reading this article you’ll have a better idea of what a core update is designed to do, and how to recover from one if your rankings were impacted.
So, What Exactly Is A Core Update?
First, let me get the obligatory “Google makes hundreds of algorithm changes per year, often more than one per day” boilerplate out of the way.
In the case of Penguin, it was link spam; in the case of Pigeon, it was local SEO spam.
They all had a specific purpose.
In these cases, Google (sometimes reluctantly) informed us what they were trying to accomplish or prevent with the algorithm update, and we were able to go back and remedy our sites.
A core update is different.
The way I understand it, a core update is a tweak or change to the main search algorithm itself.
You know, the one that has between 200 and 500 ranking factors and signals (depending on which SEO blog you’re reading today).
What a core update means to me is that Google slightly tweaked the importance, order, weights, or values of these signals.
Because of that, they can’t come right out and tell us what changed without revealing the secret sauce.
The simplest way to visualize this would be to imagine 200 factors listed in order of importance.
Now imagine Google changing the order of 42 of those 200 factors.
Rankings would change, but it would be a combination of many things, not due to one specific factor or cause.
Obviously, it isn’t that simple, but that’s a good way to think about a core update.
Here’s a purely made up, slightly more complicated example of what Google wouldn’t tell us:
“In this core update, we increased the value of keywords in H1 tags by 2%, increased the value of HTTPS by 18%, decreased the value of keyword in title tag by 9%, changed the D value in our PageRank calculation from .85 to .70, and started using a TF-iDUF retrieval method for logged in users instead of the traditional TF-PDF method.”
(I swear these are real things. I just have no idea if they’re real things used by Google.)
For starters, many SEO pros wouldn’t understand it.
Basically, it means Google may have changed the way they calculate term importance on a page, or the weighing of links in PageRank, or both, or a whole bunch of other factors that they can’t talk about (without giving away the algorithm).
Put simply: Google changed the weight and importance of many ranking factors.
That’s the simple explanation.
At its most complex form, Google ran a new training set through their machine learning ranking model and quality raters picked this new set of results as more relevant than the previous set, and the engineers have no idea what weights changed or how they changed because that’s just how machine learning works.
(We all know Google uses quality raters to rate search results. These ratings are how they choose one algorithm change over another – not how they rate your site. Whether they feed this into machine learning is anybody’s guess. But it’s one possibility.)
It’s likely some random combination of weighting delivered more relevant results for the quality raters, so they tested it more, the test results confirmed it, and they pushed it live.
How Can You Recover From A Core Update?
Unlike a major named update that targeted specific things, a core update may tweak the values of everything.
Because websites are weighted against other websites relevant to your query (engineers call this a corpus) the reason your site dropped could be entirely different than the reason somebody else’s increased or decreased in rankings.
To put it simply, Google isn’t telling you how to “recover” because it’s likely a different answer for every website and query.
It all depends on what everybody else trying to rank for your query is doing.
Does every one of them but you have their keyword in the H1 tag? If so then that could be a contributing factor.
Do you all do that already? Then that probably carries less weight for that corpus of results.
It’s very likely that this algorithm update didn’t “penalize” you for something at all. It most likely just rewarded another site more for something else.
Maybe you were killing it with internal anchor text and they were doing a great job of formatting content to match user intent – and Google shifted the weights so that content formatting was slightly higher and internal anchor text was slightly lower.
(Again, hypothetical examples here.)
In reality, it was probably several minor tweaks that, when combined, tipped the scales slightly in favor of one site or another (think of our reordered list here).
Finding that “something else” that is helping your competitors isn’t easy – but it’s what keeps SEO professionals in the business.
Next Steps And Action Items
Rankings are down after a core update – now what?
Your next step is to gather intel on the pages that are ranking where your site used to be.
Conduct a SERP analysis to find positive correlations between pages that are ranking higher for queries where your site is now lower.
Try not to overanalyze the technical details, such as how fast each page loads or what their core web vitals scores are.
Pay attention to the content itself. As you go through it, ask yourself questions like:
- Does it provide a better answer to the query than your article?
- Does the content contain more recent data and current stats than yours?
- Are there pictures and videos that help bring the content to life for the reader?
Google aims to serve content that provides the best and most complete answers to searchers’ queries. Relevance is the one ranking factor that will always win out over all others.
Take an honest look at your content to see if it’s as relevant today as it was prior to the core algorithm update.
From there you’ll have an idea of what needs improvement.
The best advice for conquering core updates?
Keep focusing on:
- User intent.
- Quality content.
- Clean architecture.
- Google’s guidelines.
Finally, don’t stop improving your site once you reach Position 1, because the site in Position 2 isn’t going to stop.
Yeah, I know, it’s not the answer anybody wants and it sounds like Google propaganda. I swear it’s not.
It’s just the reality of what a core update is.
Nobody said SEO was easy.
Featured Image: Ulvur/Shutterstock
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