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If you use WordPress, if you use Yoast plugin, you can actually have your title tags update automatically year-to-year or even month-to-month leveraging that. It's not right for all circumstances, but for certain keyword queries it works pretty well.

80% of the answers delivered by Google’s voice assistant came from the three top results in search engine results pages.Even more, 60% of the results came from featured snippets and 70% overall came from SERP features.

If you think of optimizing the paragraph for the intent of voice, make sure it’s around 42 words,

SEMrush found schema was indeed in use in the vast majority of results, but 36% of the answers given by the Google Home devices contained no Schema at all.

Target question-based keywords. Check if there is a featured snippet on the SERP and what type it is (paragraph, list, table etc) using a tool like Ahrefs. Keep your paragraph and sentences fairly short. Answer the query as directly as possible. Structure your content with logical subheadings (H2, H3, H4 etc). Use tables to display any data. Include the question within the answer if possible. Include a summary at the start or end of the content.

consider including just your site name at the beginning or end of each page title, separated from the rest of the title with a delimiter such as a hyphen, colon, or pipe

Differentiate the descriptions for different pages. Identical or similar descriptions on every page of a site aren't helpful when individual pages appear in the web results. In these cases we're less likely to display the boilerplate text. Wherever possible, create descriptions that accurately describe the specific page. Use site-level descriptions on the main home page or other aggregation pages, and use page-level descriptions everywhere else. If you don't have time to create a description for every single page, try to prioritize your content: At the very least, create a description for the critical URLs like your home page and popular pages.

Programmatically generate descriptions. For some sites, like news media sources, generating an accurate and unique description for each page is easy: since each article is hand-written, it takes minimal effort to also add a one-sentence description. For larger database-driven sites, like product aggregators, hand-written descriptions can be impossible. In the latter case, however, programmatic generation of the descriptions can be appropriate and are encouraged. Good descriptions are human-readable and diverse. Page-specific data is a good candidate for programmatic generation. Keep in mind that meta descriptions comprised of long strings of keywords don't give users a clear idea of the page's content, and are less likely to be displayed in place of a regular snippet.

Small ranking changes consistently happen when your re-run ranking reports in competitive industries.

like many of the Google My Business features, we found that the services menu has no impact on ranking.  Wondering which fields do have an impact?  See our articles on categories, the business name, reviews, & the website field.

While Google is more likely to rewrite meta descriptions for long-tail keywords, it’s only by a small margin.

Surprisingly, it seems that keeping your meta descriptions within limits doesn’t change the probability of Google rewriting them much.

Relevant and compelling meta descriptions entice clicks, so they’re still worth writing—even though they’re only shown only 37% of the time, on average.That said, if your site is huge, it pays to prioritize pages that:Already get organic trafficWere created to rank in GoogleAre likely to get shared on social media (where the meta description will be used for the social snippet description in the absence of OG tags)

if brand interest goes up organic will probably get credit for more conversions, and we will look good. If it goes down we will look bad. If we’re not paying attention, if we’re not involved in brand activity, these changes will be out of our control and we’ll be blind to the causes.

There are also some stories filtering through the SEO industry, by way of pub chats, DMs and private groups, of people influencing rankings by driving up specific branded searches. The theory could be summed up with this example;Google already knows lego.com is a good result for the search “Lego toys”Google’s algorithms start to relate the concept “Lego” closely to the concept “toys”Because the concepts are closely related Google starts to believe that lego.com is also a good result for the broader “toys” search.

We have a couple of ways to track overall brand performance, you can use these to help benchmark efforts over time.Direct traffic to the homepage

To improve the topical Authority, a source should cover all the related details to a topic with a certain context, query, and intent template by satisfying the related and possible search intents. To improve the topical authority, the “keyword gap” is not as important as the “information gap”.

Because MEB understands content better, publishers and webmasters get more traffic to their properties, and they can focus on satisfying their customers instead of spending time finding the right keyword that will help them rank higher.

These entries are all optimized around a single keyword (usually a long tail). And they’re NOT written like normal blog posts. Instead, each entry is more like a Wikipedia article.

a recent SEO experiment discovered that “duplicate images” (like stock photos) can hurt your page’s rankings.

Content Features are things like: Calculators Comparison charts Feature breakdowns Pros and cons lists Summaries Quote boxes

John Mueller, Search Advocate at Google, basically calls negative SEO a meme these days

Gary Illyes, another Google’s representative, has made similar statements: [I’ve] looked at hundreds of supposed cases of negative SEO, but none have actually been the real reason a website was hurt

here’s what we think:Negative SEO can still work, but it’s much less of a problem than it used to be.

Technical tasks such as marking up with structured data will become more and more obsolete since Google needs less and less structured information for understanding via natural language processing.

The content and links remain the most important influencing factors. Links are joined by other important factors that underpin authority. Co-occurrences in search queries and content (text, video, audio and images) are important trust and authority signals

content marketing along the customer journey

t’s possible to estimate how much traffic you’ll lose or gain from Google SGE. We propose an open SGE Impact Model, which anyone can implement using an Excel spreadsheet.

In a study of 23 websites, the aggregate organic traffic drop as a result of SGE was 18-64%. Our study focused on websites in the technology industry, with traffic mainly from informational keywords. There is large variance inside our sample, with some websites gaining as much as 219% in traffic while others are losing as much as 95%. See the results of the study.

t’s possible to optimize pages to appear in SGE snapshot carousels

One of the most significant impacts of AI on SEO is personalized search results.

AI algorithms can understand natural language queries and provide accurate results. Therefore, SEO strategies should include conversational keywords and phrases matching people's speech.

AI-powered predictive analytics can help businesses identify trends and predict future outcomes

5) Search will change more in 2023 than it has since Google went mainstream in the early 2000s.

You.com, Character.AI, Metaphor and Perplexity are among the wave of promising young startups looking to take on Google and reinvent consumer search with LLMs and conversational interfaces.

Enterprise search—the way that organizations search and retrieve private internal data—is likewise on the cusp of a new golden age. Thanks to large-scale vectorization, LLMs enable true semantic search for the first time: the ability to index and access information based on underlying concepts and context rather than simple keywords. This will make enterprise search vastly more powerful and productive.

Rankings totally different [high impact]​ - SGE's method of selecting and ranking pages it shows is completely different from traditional ranking factors. This could have high impact on sites currently ranking high for keywords.  Local results sub par [low impact]​ - SGE's presentation of local results is clearly not as good as the traditional results, so if it remains as it currently is, users will probably prefer not using it.  Shopping results limit traffic opportunities [high impact]​ - Shopping results could have a high impact if you are not showing up in Google's product results. No web results are shown, so some brand sites will lose traffic. Top of funnel research useful (but you may be left out!) [high impact]​ - Informational searches could have a high impact if your brand isn't included. The key to getting included seems to be getting mentioned in third party lists that SGE depends on heavily.  Intent sometimes “off” [low impact] -  SGE is very bad at understanding the intent of queries. If users see this mismatch often, it may sour them to using SGE.

LLM prompting involves designing text inputs to generate a response from an LLM. The goal of prompting is to steer the behaviour of the LLM in a way that elicits a desired outcome. Recent research has focused on developing effective prompting techniques that can expand LLMs' capabilities when carrying out a variety of tasks. Examples include prompt patterns [21], in-context instruction learning [22], evolutionary prompt engineering [23] and domain-specific keywords with a trainable gated prompt to guide toward a target domain for general-domain LLMs [24]. Zhong et al. [25] experiment with prompting LLMs to do scientific tasks across fields like business, science, and health by providing the LLM with a research goal and two large corpora, asking the LLM for corpus-level difference. Reppert et al. [26] develop iterated decomposition, a human-in-the-loop workflow for developing and refining compositional LLM programs that improves performance on real-world science question and answer tasks.