SEO
The Future of AI Chatbots and Search
Here it is, Google finally announced their own AI chatbot— Google Bard. Like its presumed rivals, ChatGPT and Bing Bot, Bard can understand queries and generate human-like answers in response.
But is this the start of a new way of how we search the web in the future?
This unveiling is just the next stage in the AI arms race between Google and OpenAI and Microsoft. And, with a recent update–and many more features to come–Google is already promising to transform the online search landscape as we know it.
Now that it’s widely available, here’s all you need to know about Google Bard.
What is Google Bard?
Google Bard is an experimental conversational AI chat service from Google that serves like a ChatGPT. It is Google’s own AI chatbot that can generate human-like responses to any prompt you wish to tell the AI.
But unlike ChatGPT, Google Bard was initially based on LaMDA (Language Model for Dialogue Applications)–a family of conversational large language models (LLM). LaMDA is trained on massive data sets and parameters, which has allowed the AI to “learn” useful information, as well as our language.
Recently at Google’s I/O 2023, it was revealed that Bard was now powered by their other, most advanced LLM: PaLM 2. This, as they stated, will allow Bard to be a highly efficient bot, and even fix previous issues (likely linked to their misinformation blunder when they first announced Bard a few months ago).
Powered by their LLMs, the result is that Bard can perform tasks such as answering questions and following instructions, and can carry a conversation with users in a surprisingly natural way.
Aside from that, it can do what most AI chatbots nowadays can do: write and debug code, and answer math problems. A more popular use is helping with one’s writer’s block by creating outlines, collaborating on essays, or even providing more details for articles. The sky’s the limit, it seems, with a powerful AI chatbot like Bard.
What is Google Bard used for?
This experimental, conversational AI is trained to communicate with users and provide the answers or results they’re looking for. As I said, the sky’s the limit for this kind of tech, but here are a few examples of how you can use Google Bard:
- Get information–Bard generally can provide easy-to-understand and factual answers to the questions you have. As long as your prompt does not violate any content guidelines from Google, Bard will respond with the information you would like to know. You can even ask strange questions such as “What is the meaning of life?” and it will give you an answer.
- Generate different kinds of writing–from poems to emails to blog articles, Google Bard can help you with your writing. Bard’s answers can range from formal, creative, and even casual, depending on your prompt. The pieces or ideas you can get from Bard’s content responses can help you build ideas for your craft or job.
- Translate–It can function pretty similarly to Google Translate. It even knows informal words or phrases in foreign languages, such as slang, which can be pretty useful. But, Google can only answer in English, with support for Japanese and Korean languages. The expansion of language support beyond English is planned and part of a 40-year expansion plan for Bard.
- Code–A more recent feature, Bard is now able to help users with simple programming and software development tasks. This includes code generation, code debugging, and explanation.
- Summarize data–Bard can quickly digest and summarize the most important points from articles, blog posts, and web pages for you. You can also ask it to help you compare data or research.
This, of course, is not an exhaustive list of what this AI chatbot can do. You can ask it to find a recipe, write your CV, and even help you prepare for a presentation.
It would be impossible for me to list all of Bard’s use cases here, and what you’ll use it for will depend on what you’re looking for.
Is Google’s Bard available?
Yes, Google Bard is now available. Google announced Bard and its functions and features back in February 2023 and they announced that it is now available for everyone to use in May 2023 at Google I/O. It is currently accessible in 180 countries and territories.
How can I access Google Bard?
Bard can be accessed by searching bard.google.com, using the Google Bard Chrome Extension, or just by searching it up in any browser you use.
When accessed, you will see this page and you can now start using and providing whatever prompts you want.
How to use Google Bard
The user interface (UI) of Bard is pretty easy to navigate. Simply type in your prompt in the text box, press enter, and a conversation with the AI chatbot starts.
Longer answers are broken down and can also use rich text formatting, often in bullet points or lists, which makes it easy to scan.
If you want more information, If you’re not happy with Bard’s first response, or if you want more information, it provides the option of viewing its other drafted answers. This can provide a more detailed response or more context. You can also like or dislike the draft to let Bard know if you preferred its other answers or not.
If you want to see other topics or look at more information online, you have the option to Google it. This shows related search topics that, when clicked, lead to organic search results.
Is Google Bard Safe to Use?
Google Bard, while pretty powerful, isn’t infallible.
When generating answers, Bard typically follows prompts from the user and can remember past instructions and questions (similar to Bing Bot). However, it doesn’t follow every prompt, as it has built-in safety controls and strictly adheres to Google’s content policies and AI principles.
This reduces the chances of it producing “bad” results, such as offensive dialogue.
That said, there’s still a chance that it can provide misleading information or potentially malicious answers.
It’s important to understand that Google Bard is a still-developing AI tool that may at times produce bad results. Understanding this will lessen the risks for us users.
Bard is also trained to learn from its users, as it provides a way to rate its responses. On the UI, there is also the option to report legal issues with its response, which includes the following:
Are Google Bard’s Answers Accurate?
No. Bard is still considered an experimental AI, meaning that its accuracy is still flawed—Google Bard itself disclosed that it might produce false or misleading information from time to time, and encourages users to fact-check.
This statement above is important because, unlike ChatGPT, Google Bard has access to all of the internet. That means it can see information about current events and modern context, and therefore reference them in its answers. However, this doesn’t mean that the AI is fully updated with real-time information.
So while it can provide relevant answers to topical questions, it doesn’t mean that the answers it provides are 100% correct–hence the need for a disclaimer.
Does Google Bard Cite its Sources?
As of May 2023, Bard now cites its sources. Announced by Google’s representative, Jack Krawczyk, he says this update is part of their goal to make Bard more useful, while also increasing the reach of the original publishers it gets its information from.
This is a very welcome update for web publishers and SEOs like me and me. If Bard decides to cite your article, users can easily navigate to it, if they’re interested in learning more. But we have yet to see if this update does lead to more traffic, or if users will ignore these citations.
That said, Bard’s citations don’t seem to be successfully implemented, as of the time of writing. Bing Bot, in comparison, has been providing citations for a while now, and does so more reliably. But still, it’s a step in the right direction.
What Does Google Bard Mean for SEO?
As I hinted earlier, the release of Google Bard effectively ushers in the new age of search, which many are calling the new Search Generative Experience or SGE.
An experimental version of search as we know, it deprioritized the 10 blue links that have defined Google’s first page for years.
How? Well, Bard does the heavy lifting for you. Instead of sifting through several articles or pages to get the answer you want, Bard can potentially present it to you in a more concise manner. It even allows you to ask follow-up questions.
It might be incredibly useful and time-saving for many, but it now means that users have the option to not visit multiple sites to get their answers or make their decision. These clicks are what our websites rely on–and are very important for SEO.
What does this entail? We might see less traffic for the next few months, especially if more and more users adopt and prefer Bard over organic search.
But, ultimately, Google will be pushed to find ways for traffic (and revenue) to continue reaching creators and their sites, so there’s still an incentive for us to create content.
Key Takeaway
The race towards AI and the new age of search shows no signs of stopping with the official release of Google Bard.
While appealing to many, and offering several use cases, Bard is still in its early stages and has a few limitations that we need to be aware of.
I will continue to test Bard’s features as they are rolled out, but for now, all we know about this AI is covered in this article–and with several implications to SEO that we have to consider as the chatbot may become more mainstream in the coming months.
SEO
How to Revive an Old Blog Article for SEO
Quick question: What do you typically do with your old blog posts? Most likely, the answer is: Not much.
If that’s the case, you’re not alone. Many of us in SEO and content marketing tend to focus on continuously creating new content, rather than leveraging our existing blog posts.
However, here’s the reality—Google is becoming increasingly sophisticated in evaluating content quality, and we need to adapt accordingly. Just as it’s easier to encourage existing customers to make repeat purchases, updating old content on your website is a more efficient and sustainable strategy in the long run.
Ways to Optimize Older Content
Some of your old content might not be optimized for SEO very well, rank for irrelevant keywords, or drive no traffic at all. If the quality is still decent, however, you should be able to optimize it properly with little effort.
Refresh Content
If your blog post contains a specific year or mentions current events, it may become outdated over time. If the rest of the content is still relevant (like if it’s targeting an evergreen topic), simply updating the date might be all you need to do.
Rewrite Old Blog Posts
When the content quality is low (you might have greatly improved your writing skills since you’ve written the post) but the potential is still there, there’s not much you can do apart from rewriting an old blog post completely.
This is not a waste—you’re saving time on brainstorming since the basic structure is already in place. Now, focus on improving the quality.
Delete Old Blog Posts
You might find a blog post that just seems unusable. Should you delete your old content? It depends. If it’s completely outdated, of low quality, and irrelevant to any valuable keywords for your website, it’s better to remove it.
Once you decide to delete the post, don’t forget to set up a 301 redirect to a related post or page, or to your homepage.
Promote Old Blog Posts
Sometimes all your content needs is a bit of promotion to start ranking and getting traffic again. Share it on your social media, link to it from a new post – do something to get it discoverable again to your audience. This can give it the boost it needs to attract organic links too.
Which Blog Posts Should You Update?
Deciding when to update or rewrite blog posts is a decision that relies on one important thing: a content audit.
Use your Google Analytics to find out which blog posts used to drive tons of traffic, but no longer have the same reach. You can also use Google Search Console to find out which of your blog posts have lost visibility in comparison to previous months. I have a guide on website analysis using Google Analytics and Google Search Console you can follow.
If you use keyword tracking tools like SE Ranking, you can also use the data it provides to come up with a list of blog posts that have dropped in the rankings.
Make data-driven decisions to identify which blog posts would benefit from these updates – i.e., which ones still have the chance to recover their keyword rankings and organic traffic.
With Google’s helpful content update, which emphasizes better user experiences, it’s crucial to ensure your content remains relevant, valuable, and up-to-date.
How To Update Old Blog Posts for SEO
Updating articles can be an involved process. Here are some tips and tactics to help you get it right.
Author’s Note: I have a Comprehensive On-Page SEO Checklist you might also be interested in following while you’re doing your content audit.
Conduct New Keyword Research
Updating your post without any guide won’t get you far. Always do your keyword research to understand how users are searching for your given topic.
Proper research can also show you relevant questions and sections that can be added to the blog post you’re updating or rewriting. Make sure to take a look at the People Also Ask (PAA) section that shows up when you search for your target keyword. Check out other websites like Answer The Public, Reddit, and Quora to see what users are looking for too.
Look for New Ranking Opportunities
When trying to revive an old blog post for SEO, keep an eye out for new SEO opportunities (e.g., AI Overview, featured snippets, and related search terms) that didn’t exist when you first wrote your blog post. Some of these features can be targeted by the new content you will add to your post, if you write with the aim to be eligible for it.
Rewrite Headlines and Meta Tags
If you want to attract new readers, consider updating your headlines and meta tags.
Your headlines and meta tags should fulfill these three things:
- Reflect the rewritten and new content you’ve added to the blog post.
- Be optimized for the new keywords it’s targeting (if any).
- Appeal to your target audience – who may have changed tastes from when the blog post was originally made.
Remember that your meta tags in particular act like a brief advertisement for your blog post, since this is what the user first sees when your blog post is shown in the search results page.
Take a look at your blog post’s click-through rate on Google Search Console – if it falls below 2%, it’s definitely time for new meta tags.
Replace Outdated Information and Statistics
Updating blog content with current studies and statistics enhances the relevance and credibility of your post. By providing up-to-date information, you help your audience make better, well-informed decisions, while also showing that your content is trustworthy.
Tighten or Expand Ideas
Your old content might be too short to provide real value to users – or you might have rambled on and on in your post. It’s important to evaluate whether you need to make your content more concise, or if you need to elaborate more.
Keep the following tips in mind as you refine your blog post’s ideas:
- Evaluate Helpfulness: Measure how well your content addresses your readers’ pain points. Aim to follow the E-E-A-T model (Experience, Expertise, Authoritativeness, Trustworthiness).
- Identify Missing Context: Consider whether your content needs more detail or clarification. View it from your audience’s perspective and ask if the information is complete, or if more information is needed.
- Interview Experts: Speak with industry experts or thought leaders to get fresh insights. This will help support your writing, and provide unique points that enhance the value of your content.
- Use Better Examples: Examples help simplify complex concepts. Add new examples or improve existing ones to strengthen your points.
- Add New Sections if Needed: If your content lacks depth or misses a key point, add new sections to cover these areas more thoroughly.
- Remove Fluff: Every sentence should contribute to the overall narrative. Eliminate unnecessary content to make your post more concise.
- Revise Listicles: Update listicle items based on SEO recommendations and content quality. Add or remove headings to stay competitive with higher-ranking posts.
Improve Visuals and Other Media
No doubt that there are tons of old graphics and photos in your blog posts that can be improved with the tools we have today. Make sure all of the visuals used in your content are appealing and high quality.
Update Internal and External Links
Are your internal and external links up to date? They need to be for your SEO and user experience. Outdated links can lead to broken pages or irrelevant content, frustrating readers and hurting your site’s performance.
You need to check for any broken links on your old blog posts, and update them ASAP. Updating your old blog posts can also lead to new opportunities to link internally to other blog posts and pages, which may not have been available when the post was originally published.
Optimize for Conversions
When updating content, the ultimate goal is often to increase conversions. However, your conversion goals may have changed over the years.
So here’s what you need to check in your updated blog post. First, does the call-to-action (CTA) still link to the products or services you want to promote? If not, update it to direct readers to the current solution or offer.
Second, consider where you can use different conversion strategies. Don’t just add a CTA at the end of the post.
Last, make sure that the blog post leverages product-led content. It’s going to help you mention your products and services in a way that feels natural, without being too pushy. Being subtle can be a high ROI tactic for updated posts.
Key Takeaway
Reviving old blog articles for SEO is a powerful strategy that can breathe new life into your content and boost your website’s visibility. Instead of solely focusing on creating new posts, taking the time to refresh existing content can yield impressive results, both in terms of traffic and conversions.
By implementing these strategies, you can transform old blog posts into valuable resources that attract new readers and retain existing ones. So, roll up your sleeves, dive into your archives, and start updating your content today—your audience and search rankings will thank you!
SEO
How Compression Can Be Used To Detect Low Quality Pages
The concept of Compressibility as a quality signal is not widely known, but SEOs should be aware of it. Search engines can use web page compressibility to identify duplicate pages, doorway pages with similar content, and pages with repetitive keywords, making it useful knowledge for SEO.
Although the following research paper demonstrates a successful use of on-page features for detecting spam, the deliberate lack of transparency by search engines makes it difficult to say with certainty if search engines are applying this or similar techniques.
What Is Compressibility?
In computing, compressibility refers to how much a file (data) can be reduced in size while retaining essential information, typically to maximize storage space or to allow more data to be transmitted over the Internet.
TL/DR Of Compression
Compression replaces repeated words and phrases with shorter references, reducing the file size by significant margins. Search engines typically compress indexed web pages to maximize storage space, reduce bandwidth, and improve retrieval speed, among other reasons.
This is a simplified explanation of how compression works:
- Identify Patterns:
A compression algorithm scans the text to find repeated words, patterns and phrases - Shorter Codes Take Up Less Space:
The codes and symbols use less storage space then the original words and phrases, which results in a smaller file size. - Shorter References Use Less Bits:
The “code” that essentially symbolizes the replaced words and phrases uses less data than the originals.
A bonus effect of using compression is that it can also be used to identify duplicate pages, doorway pages with similar content, and pages with repetitive keywords.
Research Paper About Detecting Spam
This research paper is significant because it was authored by distinguished computer scientists known for breakthroughs in AI, distributed computing, information retrieval, and other fields.
Marc Najork
One of the co-authors of the research paper is Marc Najork, a prominent research scientist who currently holds the title of Distinguished Research Scientist at Google DeepMind. He’s a co-author of the papers for TW-BERT, has contributed research for increasing the accuracy of using implicit user feedback like clicks, and worked on creating improved AI-based information retrieval (DSI++: Updating Transformer Memory with New Documents), among many other major breakthroughs in information retrieval.
Dennis Fetterly
Another of the co-authors is Dennis Fetterly, currently a software engineer at Google. He is listed as a co-inventor in a patent for a ranking algorithm that uses links, and is known for his research in distributed computing and information retrieval.
Those are just two of the distinguished researchers listed as co-authors of the 2006 Microsoft research paper about identifying spam through on-page content features. Among the several on-page content features the research paper analyzes is compressibility, which they discovered can be used as a classifier for indicating that a web page is spammy.
Detecting Spam Web Pages Through Content Analysis
Although the research paper was authored in 2006, its findings remain relevant to today.
Then, as now, people attempted to rank hundreds or thousands of location-based web pages that were essentially duplicate content aside from city, region, or state names. Then, as now, SEOs often created web pages for search engines by excessively repeating keywords within titles, meta descriptions, headings, internal anchor text, and within the content to improve rankings.
Section 4.6 of the research paper explains:
“Some search engines give higher weight to pages containing the query keywords several times. For example, for a given query term, a page that contains it ten times may be higher ranked than a page that contains it only once. To take advantage of such engines, some spam pages replicate their content several times in an attempt to rank higher.”
The research paper explains that search engines compress web pages and use the compressed version to reference the original web page. They note that excessive amounts of redundant words results in a higher level of compressibility. So they set about testing if there’s a correlation between a high level of compressibility and spam.
They write:
“Our approach in this section to locating redundant content within a page is to compress the page; to save space and disk time, search engines often compress web pages after indexing them, but before adding them to a page cache.
…We measure the redundancy of web pages by the compression ratio, the size of the uncompressed page divided by the size of the compressed page. We used GZIP …to compress pages, a fast and effective compression algorithm.”
High Compressibility Correlates To Spam
The results of the research showed that web pages with at least a compression ratio of 4.0 tended to be low quality web pages, spam. However, the highest rates of compressibility became less consistent because there were fewer data points, making it harder to interpret.
Figure 9: Prevalence of spam relative to compressibility of page.
The researchers concluded:
“70% of all sampled pages with a compression ratio of at least 4.0 were judged to be spam.”
But they also discovered that using the compression ratio by itself still resulted in false positives, where non-spam pages were incorrectly identified as spam:
“The compression ratio heuristic described in Section 4.6 fared best, correctly identifying 660 (27.9%) of the spam pages in our collection, while misidentifying 2, 068 (12.0%) of all judged pages.
Using all of the aforementioned features, the classification accuracy after the ten-fold cross validation process is encouraging:
95.4% of our judged pages were classified correctly, while 4.6% were classified incorrectly.
More specifically, for the spam class 1, 940 out of the 2, 364 pages, were classified correctly. For the non-spam class, 14, 440 out of the 14,804 pages were classified correctly. Consequently, 788 pages were classified incorrectly.”
The next section describes an interesting discovery about how to increase the accuracy of using on-page signals for identifying spam.
Insight Into Quality Rankings
The research paper examined multiple on-page signals, including compressibility. They discovered that each individual signal (classifier) was able to find some spam but that relying on any one signal on its own resulted in flagging non-spam pages for spam, which are commonly referred to as false positive.
The researchers made an important discovery that everyone interested in SEO should know, which is that using multiple classifiers increased the accuracy of detecting spam and decreased the likelihood of false positives. Just as important, the compressibility signal only identifies one kind of spam but not the full range of spam.
The takeaway is that compressibility is a good way to identify one kind of spam but there are other kinds of spam that aren’t caught with this one signal. Other kinds of spam were not caught with the compressibility signal.
This is the part that every SEO and publisher should be aware of:
“In the previous section, we presented a number of heuristics for assaying spam web pages. That is, we measured several characteristics of web pages, and found ranges of those characteristics which correlated with a page being spam. Nevertheless, when used individually, no technique uncovers most of the spam in our data set without flagging many non-spam pages as spam.
For example, considering the compression ratio heuristic described in Section 4.6, one of our most promising methods, the average probability of spam for ratios of 4.2 and higher is 72%. But only about 1.5% of all pages fall in this range. This number is far below the 13.8% of spam pages that we identified in our data set.”
So, even though compressibility was one of the better signals for identifying spam, it still was unable to uncover the full range of spam within the dataset the researchers used to test the signals.
Combining Multiple Signals
The above results indicated that individual signals of low quality are less accurate. So they tested using multiple signals. What they discovered was that combining multiple on-page signals for detecting spam resulted in a better accuracy rate with less pages misclassified as spam.
The researchers explained that they tested the use of multiple signals:
“One way of combining our heuristic methods is to view the spam detection problem as a classification problem. In this case, we want to create a classification model (or classifier) which, given a web page, will use the page’s features jointly in order to (correctly, we hope) classify it in one of two classes: spam and non-spam.”
These are their conclusions about using multiple signals:
“We have studied various aspects of content-based spam on the web using a real-world data set from the MSNSearch crawler. We have presented a number of heuristic methods for detecting content based spam. Some of our spam detection methods are more effective than others, however when used in isolation our methods may not identify all of the spam pages. For this reason, we combined our spam-detection methods to create a highly accurate C4.5 classifier. Our classifier can correctly identify 86.2% of all spam pages, while flagging very few legitimate pages as spam.”
Key Insight:
Misidentifying “very few legitimate pages as spam” was a significant breakthrough. The important insight that everyone involved with SEO should take away from this is that one signal by itself can result in false positives. Using multiple signals increases the accuracy.
What this means is that SEO tests of isolated ranking or quality signals will not yield reliable results that can be trusted for making strategy or business decisions.
Takeaways
We don’t know for certain if compressibility is used at the search engines but it’s an easy to use signal that combined with others could be used to catch simple kinds of spam like thousands of city name doorway pages with similar content. Yet even if the search engines don’t use this signal, it does show how easy it is to catch that kind of search engine manipulation and that it’s something search engines are well able to handle today.
Here are the key points of this article to keep in mind:
- Doorway pages with duplicate content is easy to catch because they compress at a higher ratio than normal web pages.
- Groups of web pages with a compression ratio above 4.0 were predominantly spam.
- Negative quality signals used by themselves to catch spam can lead to false positives.
- In this particular test, they discovered that on-page negative quality signals only catch specific types of spam.
- When used alone, the compressibility signal only catches redundancy-type spam, fails to detect other forms of spam, and leads to false positives.
- Combing quality signals improves spam detection accuracy and reduces false positives.
- Search engines today have a higher accuracy of spam detection with the use of AI like Spam Brain.
Read the research paper, which is linked from the Google Scholar page of Marc Najork:
Detecting spam web pages through content analysis
Featured Image by Shutterstock/pathdoc
SEO
New Google Trends SEO Documentation
Google Search Central published new documentation on Google Trends, explaining how to use it for search marketing. This guide serves as an easy to understand introduction for newcomers and a helpful refresher for experienced search marketers and publishers.
The new guide has six sections:
- About Google Trends
- Tutorial on monitoring trends
- How to do keyword research with the tool
- How to prioritize content with Trends data
- How to use Google Trends for competitor research
- How to use Google Trends for analyzing brand awareness and sentiment
The section about monitoring trends advises there are two kinds of rising trends, general and specific trends, which can be useful for developing content to publish on a site.
Using the Explore tool, you can leave the search box empty and view the current rising trends worldwide or use a drop down menu to focus on trends in a specific country. Users can further filter rising trends by time periods, categories and the type of search. The results show rising trends by topic and by keywords.
To search for specific trends users just need to enter the specific queries and then filter them by country, time, categories and type of search.
The section called Content Calendar describes how to use Google Trends to understand which content topics to prioritize.
Google explains:
“Google Trends can be helpful not only to get ideas on what to write, but also to prioritize when to publish it. To help you better prioritize which topics to focus on, try to find seasonal trends in the data. With that information, you can plan ahead to have high quality content available on your site a little before people are searching for it, so that when they do, your content is ready for them.”
Read the new Google Trends documentation:
Get started with Google Trends
Featured Image by Shutterstock/Luis Molinero