For example, take the topic of compound interest.
Over the last 4,000 years, it’s been expressed on Babylonian clay tablets, in medieval manuscripts, in printed mathematical tables, and in thousands of online blog posts.
Some of the earliest compound interest tables in written format (source).
Sure, the format has changed beyond recognition. But the concept hasn’t moved an inch.
It’s as evergreen a topic as it gets. Yet the right approach to it today isn’t to “publish once and forget it.”
Evergreen content remains relevant long past its original publication date and is built around a topic with consistent, lasting demand.
The classic example holds up: “how to tie a tie” is evergreen because the demand is consistent and the answer hasn’t changed.
A post about last week’s football scores is not evergreen; interest in the topic recurs, but the content expires quickly.
But here’s where the traditional definition breaks down.
How evergreen content has changed in modern SEO
Let’s take compound interest, arguably one of the most evergreen topics in existence. Nobody is adding new chapters to compound interest or reworking the formula.
And yet, look at the bottom of Wikipedia’s compound interest page:
The most authoritative online source on a 4,000-year-old concept was updated three months ago.
Now look at the broader competitive picture for the same keyword. Google’s top 20 results for “compound interest” were (on average) updated within the last 10 months. The freshest was updated four days ago.
There is not a single page in the top results that has been left completely untouched since originally published, not even for one of the most stable topics in human history.
This isn’t because compound interest changed. It’s because the competitive and algorithmic environment around it did.
That’s the distinction worth understanding, and where most evergreen content strategies go wrong.
Understanding why evergreen content needs ongoing maintenance, rather than being a one-time investment, requires understanding how both Google and AI search systems treat freshness.
Google has formally distinguished between queries that deserve fresh results and those that don’t since 2007, when Amit Singhal first described Query Deserves Freshness (QDF) — a model that identifies when a topic is “hot” and boosts fresh content accordingly.
Evergreen topics, by technical definition, are where QDF doesn’t fire.
Consistent, flat demand is the opposite of what triggers the freshness boost. That’s part of what makes them valuable, as you’re not racing a news cycle.
But the 2024 Google API leak confirmed that Google still tracks freshness on stable topics through multiple page-level signals:
- bylineDate — the authored or published date
- syntacticDate — the date embedded in the URL
- semanticDate — the date referenced in on-page content
- lastGoodClick — last time a user clicked and stayed
Separately, the leak revealed that irregularly updated content receives the lowest storage priority in Google’s infrastructure. This means that stale pages are deprioritized before ranking signals even come into play. A cosmetic date change without substantive improvement won’t move the needle.
For AI search, the preference for fresh content is even more pronounced.
Seer Interactive’s analysis found that 85% of AI Overview citations come from content published in the last two years.
Ahrefs’ own data found that AI-cited content is 25.7% fresher on average than content that only ranks organically.
The nuance worth knowing: this freshness bias is strongest for queries that imply recency. For stable, informational queries without time anchors (the kind that evergreen content targets), research across 485,000+ ChatGPT citations found that authoritative, established sources still win.
Freshness and authority together are the combination that improves visibility in both traditional and AI search.
Most content strategies treat “evergreen” as a publishing decision: write it once, leave it alone. It isn’t. It’s a topic strategy. And most definitions miss this by conflating the topic with the content built on top of it.
They’re not the same thing.
An evergreen topic is one where the semantic core (the fundamental answer, mechanism, or concept) is stable over time.
Compound interest is semantically stable.
It has survived 4,000 years of economic systems, currencies, religions (the Catholic Church actively tried to suppress it), mathematical revolutions, and digital finance, and the core principle hasn’t changed.
“Best AI writing tools” is not semantically stable. The correct answer changes every few months as the landscape shifts and new tools emerge.
Evergreen content is what you build on top of an evergreen topic. But as with Wikipedia’s updated page, evergreen content requires active maintenance to continue performing well in SEO, not because the concept changes, but because the competition and digital landscape around it do.
Our own data backs this up.
An Ahrefs study of one million URLs found that the average #1 ranking page is 5 years old, and 72.9% of pages in Google’s top 10 are more than 3 years old.
Old content can absolutely win, but almost none of it got there by being left alone. The pages holding top positions have accumulated links, trust, and engagement signals over time, while being actively updated to stay competitive.
That’s why in modern search, evergreen is a topic-selection strategy, not a publishing approach.
Choosing evergreen topics is a decision you make during keyword research. Maintaining evergreen content is an ongoing operational commitment. Both are required for ongoing success.
Finding the right topic is only the first decision. What follows (how you build the content, position it, and maintain it over time) determines whether it actually compounds in value or slowly loses ground to competitors who are more deliberate about it.
Here’s the full process, from topic selection to long-term maintenance.
Step 1: Find a topic with long-term, stable, or recurring search demand
Finding evergreen topics means identifying consistent, stable demand. These are topics people search for regardless of what’s trending. Not every topic that looks stable actually is.
Some are in a slow decline.
Others are genuinely stable, sitting in what the search demand lifecycle describes as the plateau phase, where growth has leveled off into durable, predictable demand. That’s your target zone.
To find evergreen topic opportunities, search for a broad term related to your niche in Keywords Explorer and check out the trends graph in the Overview report.
For each candidate topic, look for trends that indicate sustained or growing interest over time. A flat line over a long period is ideal, indicating consistent demand.
Ad hoc spikes suggest the topic is tied to news cycles or hype and is unlikely to be suitable for evergreen content.
Check out our post on The 7 Phases of the Search Demand Lifecycle for more patterns, trends in graphs, and guidance on whether your chosen topic is suitable for your evergreen strategy.
Step 2: Apply the semantic stability test
Semantic stability is a concept borrowed from AI research that turns out to be one of the best lenses for evaluating evergreen topics. We observed it in action in a recent data study when looking at how consistent AI Overview responses are over time.
My colleague, Louise Linehan, found that AI Overview responses change every 2 days:
But, they have a remarkably high semantic consistency with a 0.95 cosine similarity score:
In other words, the content in the response changes frequently, but the underlying message or topic doesn’t.
This same concept can apply to how you choose evergreen topics. Look for topics where the underlying information or message doesn’t change frequently.
Start by asking:
- Is the fundamental information likely to be the same in five years?
- Has it largely been the same for the last 5+ years?
- Is it independent of specific tools, platforms, people, or trends that could change?
If the answer or information required to cover a topic changes quickly, then it’s not evergreen for a long-term SEO strategy, even if search demand is stable over time.
For example, “How to use [specific tool]” topics are a common trap. They can often look stable in keyword data:
But decay fast when the tool changes its UI, gets acquired, or loses market share to emerging competitors. Google search results shift a lot in the process, too, promoting newer content that’s more relevant to the topic:
So, before you commit to a topic, it’s worth testing whether its core answer is truly stable.
A quick test is to search them in ChatGPT, Claude, or Perplexity without enabling web search.
Caption: Searching a topic in ChatGPT without web search enabled. A confident, accurate answer drawn from training knowledge is a strong signal the topic is semantically stable.
If the AI accurately answers based on its training knowledge (without retrieving live sources), that’s a strong signal that the topic is semantically stable. LLMs store stable conceptual knowledge in their weights and rely on live retrieval for things that change.
For SEO, it’s worth adding these topics to your strategy only if you can also gain traffic from them.
For many topics, people will still want to verify information from human creators, read more in-depth, or act on specific recommendations, which is why even AI-native topics can still drive traffic.
You can easily see the traffic potential for any topic in Keywords Explorer.
Step 3: Figure out how often to update content to keep it evergreen
Before creating anything, understand how often the content that’s already visible in search results gets updated.
Every topic has a content refresh rate, the cadence at which top-ranking pages are updated to stay fresh and competitive. It varies significantly:
- High: financial products, software comparisons, AI tool guides. Monthly or quarterly updates are usually required
- Medium: SEO guides, marketing tactics, industry how-tos. Annual or biannual refreshes are usually sufficient
- Low: foundational concepts, mathematical principles, skills-based how-tos. Update when examples or statistics age, not on a fixed schedule
I like to use Darren Shaw’s free Freshness Distance Calculator to find the refresh rate for any topic. Enter your keyword, and it pulls the average last-updated date across the top 20 results.
If the average is 3 months, refresh every 3 months or earlier. If it’s 18 months, you have more runway. Know the number before you invest in creating the piece because it will influence ongoing resources required to compete.
For example, if you’re targeting a topic like “best credit cards”, you’ll need to update it at least once or twice a month just to keep up with competitors.
If you don’t have the resources to dedicate to ongoing updates for such a topic, don’t include it in your content plan.
Step 4: Identify and match search intent
Search intent is the why behind a search query. Google wants to rank only relevant content, so if you want your content to rank, you need to match what searchers are actually looking for.
To find your topic’s search intent, try the AI Identify Intents feature in Keywords Explorer:
It gives you a percentage breakdown of searchers’ goals and the type of content that best serves each one.
For evergreen topics, search intent is usually stable. But it can shift over time as Google better understands what searchers want. You can verify it before writing and again when refreshing.
The SERP comparison report in Keywords Explorer lets you see exactly what changed between two points in time.
For instance, search results for “compound interest” have shifted over the last three years, demoting calculation-heavy content in favor of more explanatory, informational pieces.
You can see if similar changes have occurred for your topics and adjust your evergreen content strategy accordingly.
Step 5: Cover important subtopics and close topical gaps
Once you understand intent, use Ahrefs’ Content Gap report to find the subtopics searchers expect to see covered. This step is about pulling everything together into an evergreen content structure.
You’ll want to include subheadings that age well and cover subtopics with long-term interest, too.
Select the top-ranking pages from the SERP overview and open them in Content Gap:
You’ll get all the common keywords they rank for, revealing the subtopics your content should also address.
For example, if we’re writing about pistol squats, these seem like potential subtopics:
- Pistol squat progression
- How to do a pistol squat
- What is a pistol squat
- Pistol box squat
- How hard is a pistol squat
For evergreen topics, required subtopics tend to be consistent across the top results, which is itself a useful stability signal. If subtopics vary wildly or skew toward current tools and products, the topic may be less stable than it first appeared or not suitable for an evergreen strategy.
Step 6: Avoid content angles with a short lifespan
Sometimes a topic might be stable, but the angle you take on it can introduce an (avoidable) expiry date.
Pop culture references, trend-dependent framings, mentions of a specific year, and tool-specific walkthroughs all reduce the shelf life of otherwise evergreen content.
For example, here’s an article about what content marketers can learn from the Marvel Cinematic Universe.
In this case, the topic (content marketing) is evergreen. But the content isn’t. The article is forgettable once the MCU hype dies, which it did:
If your goal is to create evergreen content, avoid trendy angles or references.
Also, aim to write to the underlying concept, not the current example of it. And avoid language that embeds a timestamp (such as “earlier this year,” “last month,” “in 2025”).
If the piece is genuinely evergreen, it should feel accurate and relevant two years from now.
Note that this isn’t a hard rule. If freshness is part of your angle (a “best of” list, a data-driven roundup, an annual update), date signals are appropriate. Apply this guidance to content where timelessness is the goal.
Step 7: Maintain your content on a regular cadence
Even when a topic’s core answer doesn’t change, three things decay around it:
- Stats and data age
- Examples become outdated
- Competitive landscape shifts
A page that was the best answer two years ago may no longer be, not because it got worse, but because competitor pages were refreshed in that time.
A meaningful refresh isn’t changing “2024” to “2025” in the title. It means replacing outdated stats with current sourced figures, swapping aged examples for current ones, adding subtopics that have emerged, and updating screenshots where UIs have changed.
We’ve seen this pay off directly on the Ahrefs blog.
Our free SEO tools post is a good example. The topic is relatively stable, but when large language models changed the landscape faster than anyone expected, we updated the post to include ChatGPT. The result was an immediate spike in search traffic:
Use your content refresh rate from Step 3 to determine your maintenance schedule.
Set a reminder at that cadence for each key evergreen page. Additional triggers for a content update might be:
- Organic traffic drops 20% from peak
- You’ve dropped from an AI Overview
- Key stats you cite have been superseded
- New products or features have been launched
- A referenced tool has changed significantly
- A new subtopic has emerged
- Competitors have substantially refreshed
- Your post ranks, but doesn’t convert
Use Ahrefs’ Web Analytics to monitor content performance at a page level. As a free, privacy-friendly alternative to Google Analytics, it’ll show you which pages are declining in performance and may benefit from an update.
Final thoughts
Compound interest has been explained on clay tablets, in manuscripts, in printed tables, and in blog posts. The format keeps changing, the core concept never does.
That’s evergreen. And it’s still the highest-leverage content strategy available to most publishers. Topics with stable, lasting demand give you compounding returns on a single piece of work over years rather than days.
What’s changed is how you sustain it.
Evergreen is a topic strategy, not a publishing strategy. The work of staying competitive involves refreshing content, maintaining freshness signals, and building authority over time. These tasks are now a permanent part of any evergreen strategy.
But the topics that reward that work are the same ones they’ve always been: semantically stable, consistently searched, and worth building on.
Any questions? Feel free to ping us on X.
