With AI overviews and LLMs summarizing everything, it became clear that anything that is easily summarized by AI is not worth pursuing. We're now only targeting BOFU keywords tied to real customer problems and jobs to be done. The closer the keyword is to someone's purchasing decision, the more valuable it is. Outdated metrics such as keyword volume and search difficulty belong in the past.
SEO professionals who are experienced focus on too much strictly on 'intent' and 'business-impact', as opposed to just which keywords are being searched the most. If the content on a website does not have potential to create revenue or engagement then that content is not worth continued effort to build a larger content footprint. When SEOs make their best business decisions, they make them based on an evaluation of a page. The focus of making optimizations is on pages that already have proven success (traction) rather than publishing more and more new content. The best SEO teams use the Google search engine results page (SERP) to find out what to scale before they start scaling content. For example if Google is rewarding 'tools' and 'comparisons', producing yet another blog post on the same topic will be unsuccessful. Now authority is used to filter out low-quality content when it is on a topic that we do not have real-world experience or data or workflow to support. From my own experience, the best way I have had success in SEO is to consider the updates, merges and pruning of content on the website prior to developing new content. Following this path provides the opportunity to be aligned with both the search engines' algorithms and the users.
No longer do seasoned SEO teams make educated guesses. They use impact-first decision frameworks. Instead of chasing volume, they evaluate pages based on business value, intent precision, and update potential. We focus on content that provides substantial gains from relatively minor incremental changes. And in our experience, refreshing high-intent pages results in 20-30% gains more rapidly than new content. The search behavior layering system is another effective method. Teams analyze how users arrive, what actions they take, and where they encounter obstacles. We prioritize and scale pages that are conversion-adjacent or that users have timely questions about. Probably the most significant change is likely the most difficult: restraint. Successful teams streamline and scale what is already effective, eliminate what isn't, and continuously adjust to the new winners. With the changes in search algorithms, more consistent outcomes are favored over novel ideas.
What set us apart at EVhype was a breakthrough in simply not trying to scale everything. When we had an overflow of keyword ideas, we had to set a limit. In our case, the limit was to ask ourselves, "Will improving this page change a real decision for a real user?" This significantly decreased our content backlog. Some of the best SEO teams use a three-layer framework: demand, defensibility, and payoff. Real queries and SERP behavior give the demand, not keyword volume. Can you contribute an experience, data, or a unique perspective - something others can't? The payoff is about the downstream impact: conversions, return visits, assisted revenue, etc. In the SERPs, potential looks a lot more like revenue than ranking. In this new era, keywords don't matter as much as the format of the content. We focus on content that we can refine, add to, or change the format of, including guides, comparisons, and calculators.
The framework that a lot of SEO teams are following right now is one that aligns with EEAT content. Each of these components of content may show up slightly differently depending on the page or intent of the page (informational to actionable), so it is important to download any site data showcasing: 1) What website pages are being visited the most, 2) What is the heat map of their experiences on each page, and 3) What is the drop point at which they bounce (or do they convert instead)? An additional opposite question can also be, 4) What pages do we want people to visit, but they are not finding, and why is that the case? From here, you can help decide the intent of these pages, how to reorganize and revamp the content and SEO components, such as H2s, paragraph styles, and even an overview at the top of the page, which can support both SEO and AI optimization on the page. You can then do a keyword audit to know not only what keywords fit the intent of this page, which may differ from another page, but also where they should be, whether it be in the subheaders, meta description, and title tags, or within the paragraphs in bullet points or another scannable layout.
We keep track of how quickly pages move up in Google after we post them or update them. If a page quickly goes from nowhere to page one, that means Google likes the way we've written about that subject. More of our work is written in the same way. Even if a lot of people look for a keyword, we stop pushing a page if it doesn't move much after we optimize it. We don't need to try to get ranks if we don't have a chance. I spent months trying to rank for big searches that big sites already had. Those pages didn't move. But small narrow topics that we didn't even try would rank in days. To begin, we try our ideas in areas that are easier. We watch what works well and then do it again. Google tells us where to get ahead. Moving slowly wastes time and money.
From my experience, advanced SEO teams rely on combinations of data analytical research, competitive analysis, and industry trends when making these types of decisions. For example, I was able to help an independent film production client determine the best content format based on their brand identity; as such, I believe the key to determining this is through an understanding of the dynamics of how users interact with search engines, search engine algorithms, and what are the specific needs of your targeted audience.
I saw a shift for our clients starting in 2025. We are no longer prioritizing by keywords volume or ranking potential, our decision system changed pretty early during mid 2025. We changed our strategy to not only stick to keywords but added 8-10 word phrases and questions. One of our clients, a veterinary hospital client in Oakdale, saw no drop in keyword ranking but visits to the site slowed by 30%. This sudden drop on site visits along with drop in footfall, forced us to change our decision system. We had to focus more on geo-local marketing, GMB optimization, and AI SEO to help the brand get retrieved on LLMs. We moved beyond traditional keywords that usually is a big part of parasiteSEO, and moved to phrase-based, 7-8 intent based questions-led hierarchies. Our content marketing strategy also shifted to more towards answer first, size was not considered while writing articles or blogs. Then focused on updated schema across the site to make it easy for LLMs to crawl, understand and retrieve our content. It took us around 13-14 weeks, when we started to notice GPT referrals, AI Overviews visibility, GMB clicks, and direct calls. By the end of 5 month, our client was ranking in the top 3 AI Overviews. Now our decision system/framework is simple. We ask these three questions (note this framework is for local business marketing only): - Can this location landing page answer the long-questions that people would ask on google and in LLMs? - The content we write for the business, can it be cited or summarized accurately by AI systems? - Does it support brand recall and local action, not just clicks? We tested this framework across 30+ clients over the last year (Roofing industry, dental clinics, lawyers, homecare, and landscaping businesses), the pattern has been consistent. We have seen consistent performance with LLM assisted conversions, GMB actions, and direct calls increase. My final advice would be that now SEO teams that still optimize only for rankings will feel confused by the data. Only the teams that optimize for visibility across SERPs, AI systems, and local surfaces will see momentum.
The best SEO teams have stopped looking at keyword numbers; their focus is now on what people actually do on their websites, or the ones they are contracted to. This includes if they actually read the thing, if they finish reading the thing, or if they just scroll and click away. The reason for this is that Google has become a lot smarter and has realized when people actually like things or not. If a user stays on your website and scrolls around and possibly shares it with someone else, then Google gets a signal that that thing was actually useful to somebody. Meaning SEO teams are no longer on the hunt for the next big keyword; no, they are looking at their websites and finding the pages that people actually like to spend time on. Now, these pages get all the attention; they get upgraded and even possibly expanded on into bigger and better things. What it all comes down to for SEO teams is to no longer try to trick Google's algorithm. But instead, try to create things that people actually want to read or spend time with. These teams know that creating content that ranks is not as impressive as building content that people want to read.
After 20 years of operating an across-the-nation transportation business, I have observed that top search-engine-optimisation (SEO) teams implement decision-making processes similar to operation teams. They evaluate each web page based on its intent strength, business impact, and authority; instead of focusing solely on the potential for traffic to come to the page. Pricing, planning and risk decisions are the areas of greatest focus for AI engines and potential customers, therefore, pages related to these are prioritized over others. Additionally, we evaluate behavioral signals (e.g., how long someone stays on a web page or how many sales lead to an order) and whether or not sales teams use the content. Formats that clearly articulate one job will scale over time. All other formats will eventually be removed as they become non-relevant. Over time, as algorithms change, companies will need to continue to develop prioritised lists of content based on their intent to use or search for a given keyword, rather than jumping on every new keyword trend that arises.
There are teams of SEOs using scoring systems to select the best projects. (and, alternatively, RICE or PIE) as inputs. They use these tools to figure out which pages will help the greatest number of people. Teams concentrate on already what a user is searching for. They value the new information that nobody else has. This makes them stick out from generic content. They group like with like to show that they are experts. It helps people and AI find their work. That way, they only spend time on the most crucial pages.
To determine the building blocks to scale up, a well-established SEO department uses consistent, seamless processes based upon what has the highest search volume. In addition to search volume, an experienced SEO team will reach beyond the monthly outstanding traffic and look at the business objectives of the pages and keywords. Therefore, understanding the intent behind each keyword search and its conversion opportunities will determine how a page ranks in the long term. The team's analytical skills will review data over time to see which pages have the best opportunity to rank higher and which will require improvement. Additionally, user behavior will provide insight into how users interact with a webpage and how long they will remain on the site. Finally, an SEO team will determine which content formats to use based upon the best approach to answering the user's question. This structured approach helps keep SEO teams on track as they continue to adapt to changing search behaviors and search engine algorithms.
My SEO team doesn't just chase high-volume keywords. We have a system for finding where competitors are weak, and we run scripts to spot ranking opportunities others miss. Focusing on pages that can rank quickly has worked much better for us when algorithms change. If you're building your own process, try grouping your keywords, using a simple scoring sheet, and make sure you check it again every month.
In our business, we just care about what gets us local phone calls. We're always checking our website stats to see which pages get clicks. One trick we learned is to go back and update our solar and roofing pages every few months, especially when people's search habits change. Our simplest metric is how many people actually call us. That tells us what content to double down on. Don't just worry about your Google rankings, figure out what pages make the phone ring.
Here's what actually works for SEO. We combine the numbers with a simple scoring system to pick our targets. At our company, we rate keywords by search volume and ranking difficulty. All of a sudden, we knew exactly what to write next. Just make sure you adjust that scorecard every few months, because Google and search habits never stay the same.
Figuring out where to scale used to be a mess. Now I use a simple system that weighs traffic, seasonality, and conversions against our current rankings. It wasn't easy at first, but it keeps my team from chasing every shiny keyword and instead focuses on what actually drives results. Just make sure whatever system you use is simple and flexible. You have to be able to adapt quickly when search engines or customer behavior changes.
The biggest trap in local SEO is lack of focus. We stopped guessing and started copying what worked. We'd find the landing pages that brought us the most actual client inquiries, then build similar pages for other areas. We use a simple impact versus effort grid each week to decide what's next. When you can tie a blog post directly to a new customer, you know exactly where to spend your time.
With my healthcare clients, I don't just look at search volume. I want to see what people are actually asking. A keyword might have high numbers, but does it answer a real patient question and is it medically compliant? We recently rewrote our FAQ section based on new patient questions. Our rankings jumped, and more importantly, so did appointments. Start with the information pages that answer what people are asking, then see what works and adjust from there.
At Design Cloud, we figured out what worked by tracking traffic and conversions for each page. We'd look at our use case articles before and after SEO updates, and the difference was night and day. It really comes down to matching what people search for with the pages that actually make you money. My advice is to regularly check your search data and user flows to find easy ways to scale.
SEO teams use topical authority mapping to figure out which clusters are providing the best return on investment. Instead of going after high-volume keywords, they target "high-intent entities" which indicate deep expertise to search engines and AI models alike. It's often in the form of a value-vs-viability matrix, where content is considered based on how likely it will be to show up in AI-powered overviews. Brands stay visible as the platforms evolve by building structured data and "answer-first" content at scale. This systematic methodology starts very low-key generating traffic and evolves towards becoming a reference to large language models in the long term, gaining authority through time commitment.