Do animals have names? According to the poet T.S. Eliot, cats have three: the name their owner calls them (like George); a second, more noble one (like Quaxo or Cricopat); and, finally, a “deep and inscrutable” name known only to themselves “that no human research can discover.”
But now, researchers armed with audio recorders and pattern-recognition software are making unexpected discoveries about the secrets of animal names—at least with small monkeys called marmosets.
That’s according to a team at Hebrew University in Israel, who claim in the journal Science this week they’ve discovered that marmosets “vocally label” their monkey friends with specific sounds.
Until now, only humans, dolphins, elephants, and probably parrots had been known to use specific sounds to call out to other individuals.
Marmosets are highly social creatures that maintain contact through high-pitched chirps and twitters called “phee-calls.” By recording different pairs of monkeys placed near each other, the team in Israel says they found the animals will adjust their sounds toward a vocal label that’s specific to their conversation partner.
“It’s similar to names in humans,” says David Omer, the neuroscientist who led the project. “There’s a typical time structure to their calls, and what we report is that the monkey fine-tunes it to encode an individual.”
These names aren’t really recognizable to the human ear; instead, they were identified via a “random forest,” the statistical machine learning technique Omer’s team used to cluster, classify, and analyze the sounds.
To prove they’d cracked the monkey code—and learned the secret names—the team played recordings at the marmosets through a speaker and found they responded more often when their label, or name, was in the recording.
This sort of research could provide clues to the origins of human language, which is arguably the most powerful innovation in our species’ evolution, right up there with opposable thumbs. In years past, it’s been argued that human language is unique and that animals lack both the brains and vocal apparatus to converse.
But there’s growing evidence that isn’t the case, especially now that the use of names has been found in at least four distantly related species. “This is very strong evidence that the evolution of language was not a singular event,” says Omer.
Some similar research tactics were reported earlier this year by Mickey Pardo, a postdoctoral researcher, now at Cornell University, who spent 14 months in Kenya recording elephant calls. Elephants sound alarms by trumpeting, but in reality most of their vocalizations are deep rumbles that are only partly audible to humans.
Pardo also found evidence that elephants use vocal labels, and he says he can definitely get an elephant’s attention by playing the sound of another elephant addressing it. But does this mean researchers are now “speaking animal”?
Not quite, says Pardo. Real language, he thinks, would mean the ability to discuss things that happened in the past or string together more complex ideas. Pardo says he’s hoping to determine next if elephants have specific sounds for deciding which watering hole to visit—that is, whether they employ place names.
Several efforts are underway to discover if there’s still more meaning in animal sounds than we thought. This year, a group called Project CETI that’s studying the songs of sperm whales found they are far more complex than previously recognized. It means the animals, in theory, could be using a kind of grammar—although whether they actually are saying anything specific isn’t known.
Another effort, the Earth Species Project, aims to use “artificial intelligence to decode nonhuman communication” and has started helping researchers collect more data on animal sounds to feed into those models.
The team in Israel say they will also be giving the latest types of artificial intelligence a try. Their marmosets live in a laboratory facility, and Omer says he’s already put microphones in monkeys’ living space in order to record everything they say, 24 hours a day.
Their chatter, Omer says, will be used to train a large language model that could, in theory, be used to finish a series of calls that a monkey started, or produce what it predicts is an appropriate reply. But will a primate language model actually make sense, or will it just gibber away without meaning?
Only the monkeys will be able to say for sure.
“I don’t have any delusional expectations that they will talk about Nietzsche,” says Omer. “I don’t expect it to be extremely complex like a human, but I would expect it to help us understand something about how our language developed.”
We occasionally hear from ecommerce pros seeking employment. Many this year report extended searches with little to no acknowledgment from would-be employers after submitting a resume.
To inquire, we once again turn to Harry Joiner. He’s a 20-year ecommerce recruiter with a seasoned perspective for job seekers and the companies that hire them.
The entire audio of my recent conversation with Joiner is embedded below. The transcript is edited for length and clarity.
Kerry Murdock: In January, you called the state of ecommerce employment fragmented. What is it now?
Harry Joiner: It’s still that way. It’s the Baskin-Robbins 31 flavors of candidates: part-time, full-time, remote, interim, project, et cetera. It’s crazy.
Remote roles are more brittle than on-site. It’s easier for a company to phase out remote roles because those folks will presumably land on their feet more quickly. That’s an anecdotal observation on my part.
Overall, it seems companies are hiring for incremental improvements in, say, sales and operations but not high-impact strategic roles. For my money, nothing beats a full-time on-site role where the executive controls the entire ecommerce profit-and-loss statement.
Murdock: What’s a brittle role?
Joiner: It’s one with a higher risk of going away, such as a project-based position. Folks in brittle roles must figure out how to extend their worth to the company. They should study how the company makes money and how it creates value for the customer to find out what drives their utility.
Murdock: We hear from experienced ecommerce pros looking for work who send 50, 100 resumes with no response from the employer. What’s your advice to them?
Joiner: A lot of it has to do with candidates not being targeted about who they’re sending their resume to. I addressed it in a recent LinkedIn post, “10 Ways to Speed Up Your Job Search.“
At a high level, candidates need to do many things: optimize their resume, optimize their LinkedIn profile, network, use job alerts — all of that — and consult with job coaches and mentors. There’s a right way and a wrong way to manage an ecommerce candidacy. We’re seeing highly qualified people make it to the top of a search funnel with an opportunity to phone screen. And they are not converting that phone call into a second-round interview.
It’s not because their LinkedIn profile or resume didn’t serve them well. The purpose of those things is to get a phone screen. But once on a phone screen, the candidate’s job is to unpack how they will make money for the company. A lot of people can’t do that. That’s where coaching and mentoring comes in.
I offer that type of coaching, as do others. It’s all learnable. It starts with knowing what the company is looking for and connecting the dots of what the position will cost the company versus the candidate’s return.
Murdock: Do you ever work on an engagement that doesn’t involve LinkedIn?
Joiner: I’ve been doing this for 20 years. I’ve had only three searches that didn’t involve LinkedIn. Two of those were my first. There was a search about five years ago where the winning candidate didn’t come from LinkedIn. He refused to be on the platform. But everybody else, yes, you need to be on LinkedIn.
Murdock: Changing direction, we’ve all read the headlines that the ecommerce growth is slowing. What do you hear from employers?
Joiner: The ecommerce industry is maturing. It’s not declining. My business partner, Allan Seibert, told me recently that we are not seeing that many searches this year for new positions. We’re seeing searches for backfills to replace folks who have left. We’re also not seeing new positions stemming from artificial intelligence technologies, by the way.
Murdock: What does that mean for candidates, no new positions?
Joiner: It’s a competitive market for job seekers. It’s critical that job seekers remain in the right head space. Stay fit. Don’t drink too much. Watch what you eat, et cetera. Candidates should look very closely at what they have done right in their careers, their successes. What outcomes or organizational transformations have they driven? Candidates need to do a better job of taking an inventory of everything they’ve done right so that those things will show up in how they market themselves and engage with hiring committees.
I addressed other tips in my LinkedIn post. Start with practicing and preparing for interviews. Conduct mock interviews and record yourself. There’s no shortcut to researching the company’s culture and business model and understanding how it makes money. Look at the company’s products online and its sales tactics. Who is buying those products? Put yourself in customers’ shoes. It will help you prepare better questions for interviews. It will also demonstrate interest and your fit with the company.
Next is the mental state, which I touched on. I’m seeing candidates this year get ground down with the job search. To them, I say stay organized and proactive. Establish regular follow-ups, review and adjust the strategy, take online courses, join professional communities, stay connected with people, and figure out alternative ways to get in the door. Be as proactive and positive as possible.
Murdock: Tell us again how folks can follow you, get in touch.
Eli Schwartz, Author of Product-Led SEO, started a discussion on LinkedIn about there being too many CMOs (Chief Marketing Officers) who believe that AI written content is an SEO strategy. He predicted that there will be reckoning on the way after their strategies end in failure.
This is what Eli had to say:
“Too many CMOs think that AI-written content is an SEO strategy that will replace actual SEO.
This mistake is going to lead to an explosion in demand for SEO strategists to help them fix their traffic when they find out they might have been wrong.”
Everyone in the discussion, which received 54 comments, strongly agreed with Eli, except for one guy.
What Is Google’s Policy On AI Generated Content?
Google’s policy hasn’t changed although they did update their guidance and spam policies on March 5, 2024 at the same time as the rollout of the March 2024 Core Algorithm Update. Many publishers who used AI to create content subsequently reported losing rankings.
Yet it’s not said that using AI is enough to merit poor rankings, it’s content that is created for ranking purposes.
“Our long-standing spam policy has been that use of automation, including generative AI, is spam if the primary purpose is manipulating ranking in Search results. The updated policy is in the same spirit of our previous policy and based on the same principle. It’s been expanded to account for more sophisticated scaled content creation methods where it isn’t always clear whether low quality content was created purely through automation.
Our new policy is meant to help people focus more clearly on the idea that producing content at scale is abusive if done for the purpose of manipulating search rankings and that this applies whether automation or humans are involved.”
Many in Eli’s discussion were in agreement that reliance on AI by some organizations may come to haunt them, except for that one guy in the discussion
Google’s John Mueller debunked the common recommendation that it’s good to link out to other websites for SEO and ranking benefits.
Canonical SEO
The word canonical (in the context of facts and rules) means ideas and beliefs that are commonly accepted as true and correct. SEO has a number of canonical beliefs that data back decades. Some of the canonical SEO practices used to be true but lost their relevance after Google evolved. Other canonical practices are purely speculative beliefs based on “common sense reasoning” but not on anything real like a research paper, patent or a statement by a Googler.
Origins Of Outbound Link SEO
One such speculative canonical belief is the SEO practice of adding three outgoing links to every article. The reason for that belief probably comes from things Google said in a different context and also from how SEOs responded to Google’s link spam algorithms.
Speaking from memory, it was announced in 2005 at Pubcon New Orleans that Google was using statistical analysis to identify spammy linking patterns. SEOs responded by creating links that “looked normal” which meant to link out to a paid link but surround it with links to “authority sites” like .edu and .gov pages. At this point SEOs were linking out in order to make their paid outbound links “look normal.”
Again speaking from memory, there was a trend where SEOs didn’t want to link to other sites because they wanted to “hoard” PageRank and circulate it only to their own pages. The idea was that linking to other sites would “waste” that PageRank and make their sites weaker because there was less PageRank circulating to through their internal links. Googlers responded by saying that it’s good to link out. SEOs responded by saying that it’s good for SEO to link out. Which entirely misses the context in which Googlers said it was good to link out.
Decades later SEOs are telling each other that linking out is good for SEO but none of them knows why it’s good for SEO. They just tell each other that because the practice of linking out has become a canonical belief, something that everyone agrees is true and accurate.
I lived through all these changes and know where those beliefs came from. They came from a combination of statements that Googlers have made and were repeated over the years but the context was forgotten so that all that’s left is “it’s good to link out” and that’s what people believe.
John Mueller Debunks Outbound Link Myth
Someone on LinkedIn asked for what the specific amount of links were best for SEO. They wanted clarification on what the exact amount of outbound links were for SEO.
This is the question that was asked:
“I have a question. It’s a common practice among SEOs to believe that adding a total of 2-5 internal links and around 1-3 external links in a 1000-word blog post is beneficial. They also think that adding more links could be harmful to their site, while adding fewer links might not provide much value.
Could you please clarify whether the quantity of links really matters?”
Google’s John Mueller answered:
“Nobody at Google counts the links or the words on your blog posts, and even if they did, I’d still recommend writing for your audience. I don’t know your audience, but I have yet to run across *anyone* who counts the words before reading a piece of content.”
What Is The Right Answer?
Mueller recommends writing for the audience. The underlying idea there is that if you know what the audience wants then you know what to give them.
What the audience wants has nothing to do with the number of “entities” you add to your content or how many outbound links you have on the page. If that’s your approach to SEO then you may want to evaluate how much of what’s published is for search engines and how much of it is for users because creating content for search engines have always been the likeliest way to produce content that doesn’t catch on and ranks.
I’m not being a Google apologist either, this is the pragmatic approach for beating competitors by understanding what works. For example, years before the Reviews algorithm came out I consulted for clients who had review websites and I told them that they needed to add more original images, more hands-on reviews, more metrics and comparisons. So a couple years later when the Reviews update guidelines came out it all made sense because I knew from my own personal experience ranking my own review websites that this was the best approach.
So the right answer for most SEO questions is most often found by reframing the question around the people the content is created for. When it comes to outbound links the question shouldn’t be “how many outbound links is best for SEO?” the question should be “do these outbound links fit the context of what the web page and what a reader would want?”
A good context for adding an outbound link is when something is quoted or cited. For example, if the content mentions scientific research or what someone else said, then that research or the page page documenting what was said should be linked to. That’s what users would want, right?
AI-powered search tools like SearchGPT have sparked both excitement and concern among SEOs. Recently, industry prognosticators have expressed fears about AI-driven tools undermining traditional traffic sources. They worry that widespread adoption of these tools will divert so much traffic away from previously profitable websites that the decline in visibility will “unalive” those sites completely.
Table of contents
It’s normal to feel nervous about new technologies, especially when they seem to change not only the core of how you understand search works, but also change searcher behavior in general. Thankfully, anxiety fades when facts are clear. Let’s break down why AI-powered search is not built on theft and how it fits into the broader SEO ecosystem.
Understanding how AI-powered search works
Before addressing the claims of content theft, we must first understand how tools like SearchGPT function. At its core, these AI tools are large language models (LLM) trained on vast amounts of publicly available text data. This training process involves learning patterns in language to generate human-like text responses. Unlike traditional data analysis or fact-learning, the “training” focuses on understanding and predicting language rather than memorizing specific facts. This, then, begs the question: “Does it really, truly answer questions, or does it just create accurate-sounding guesses?”
Data gathering and synthesis
When a user submits a query, SearchGPT (specifically, but this is probably true of similar tools) processes the input by analyzing and interpreting the request using its trained language patterns. This means the way the search for facts is constructed is more accurate than relying solely on the terms inputted by the user. Then, instead of merely searching for and retrieving existing content, it looks at all the content from multiple top sources. It synthesizes that information (meaning it reads and evaluates all the retrieved content) to construct a coherent and comprehensive response.
The “synthesizing” process involves:
identifying relevant data points
understanding the context of the query
evaluating the expertise and likelihood of accuracy
and integrating information in a way that aligns with the user’s intent
Generating original content
SearchGPT doesn’t copy and paste text from websites. Instead, it generates new content based on the patterns it has learned during training. This process is similar to how human writers use their knowledge and experience to create original articles. By leveraging sophisticated algorithms, SearchGPT (and other tools) ensures that the generated text is both unique and informative, providing valuable answers without replicating existing content verbatim.
Ensuring accuracy and relevance
To maintain high standards of accuracy and relevance, AI-powered search has processes in the background to evaluate the reliability of the information it synthesizes. It prioritizes data from authoritative sources, cross-references information to minimize errors, and continually adapts to new information to provide up-to-date answers. This dynamic capability ensures that users receive responses that are not only accurate but also reflect the latest knowledge and trends.
The dynamic nature of AI responses
This is where the general understanding of how AI creates search responses and content goes astray. When tools like ChatGPT or AI-powered search tools write new content or provide answers, they are not relying solely on data points and facts that they have been *previously* trained on; the data set is not “old.” The AI’s ability to search for and adopt new information allows it to refine its responses over time, ensuring that the answers remain relevant, valuable, and accurate. This continuous learning process means that AI-powered tools can adjust responses to better meet users’ needs as user behavior and information evolve, providing a more personalized and effective search experience.
To sum up, tools like SearchGPT function by gathering and synthesizing information from a wide array of sources (that they find on the web) to generate original, accurate, and relevant responses to user queries. This process ensures that while the AI provides quick and concise answers, it does so by leveraging a deep understanding of language and context rather than stealing or copying content.
The role of attribution and source linking
The biggest concern among SEOs is the traffic loss if AI-powered search provides direct answers without driving clicks to the source website. This fear is completely understandable but overlooks an important aspect: the role of attribution.
Many AI-powered search engines, including those integrating models like SearchGPT, prioritize providing users with accurate, high-quality information. In doing so, they include links back to the original sources. This attribution ensures that websites receive credit and traffic for their content. Rather than stealing clicks, AI serves as a conduit, directing engaged users to the source of the information for more in-depth exploration.
However, this also means that the core concern, that some sites might lose traffic because they are not chosen as the cited source for the information, is a reasonable concern. The way to combat this loss isn’t to fight against adopting new technology (because that is probably futile at this point). The best way to fight is to ensure the cited source is YOUR source. This will become the new focus of SEO.
AI as a complement, not a competitor
The notion that AI-powered search will “kill” websites is rooted in a misunderstanding of how these tools are intended to function. AI doesn’t replace the need for high-quality, authoritative content; it amplifies it. Search engines and AI tools rely on the experience, expertise, authoritativeness, and trustworthiness (EEAT) of websites to deliver relevant and credible information to users.
Websites that invest in EEAT will continue to thrive, as AI tools will naturally prioritize their content in response to user queries. In this sense, AI becomes a partner in the SEO journey, helping to surface the best content and ensure it reaches the right audience.
Websites that are “killed” by AI-powered search won’t be innocent victims of a new technology run amok; rather, they’re more likely to have been removed from the knowledge pool by digital Darwinism — “survival of the fittest“ and all that.
The future of SEO in an AI-driven world
As with any technological advancement, AI-powered search tools will require SEOs to adapt and evolve their strategies. However, this evolution doesn’t mean the end of traditional SEO practices. Instead, it highlights the importance of optimizing for both AI and human users — which is not all that different from the old guidance to “optimize for both robots and human users.” See? What’s old is new again!
By creating valuable, authoritative (read: unique!) content that meets users’ needs, websites can continue to grow their visibility and influence in an AI-driven world. SEO professionals who embrace these changes and integrate AI into their strategies will be better positioned to succeed.
Dispelling the myth of theft
The idea that AI-powered search is built on theft is misleading and overlooks the potential benefits these tools bring. Rather than fearing AI, SEOs should leverage it to enhance their strategies, drive more meaningful engagement, and ensure their content remains at the forefront of search results.
AI isn’t here to steal; it’s here to drive evolution. It’s not the biggest or loudest that thrive on the web, but those who adapt. Just as in nature, survival belongs to the fittest—those who innovate, evolve, and embrace the future.
Carolyn Shelby is an expert in SEO and AI, specializing in enterprise and technical SEO and optimizing web architectures. She views SEO and AI as powerful tools to narrate a brand’s journey, aligning content with core values to engage and convert audiences. Her approach is both data-driven and distinctly human, using straightforward, innovative methods to achieve real results.
Yelp has filed an antitrust lawsuit against Google in federal court in San Francisco.
The suit alleges that Google has illegally leveraged its monopoly in general search to dominate the local search and local search advertising markets, harming competition and consumer choice.
Key Allegations
Yelp’s complaint accuses Google of engaging in anticompetitive conduct, including:
Self-preferencing its own “inferior” local search product over competitors
Driving traffic and revenue away from rivals like Yelp
Making it harder for competitors to achieve scale
Increasing costs for rivals
Limiting consumer choice to grow its market power
The company claims Google’s local listings are “on average, shorter, more prone to error, less subject to quality control, and less likely to be useful to consumers” compared to Yelp and other specialized providers.
The lawsuit seeks injunctive relief, monetary damages, and a declaratory judgment that Google’s conduct violates antitrust laws.
Background & Context
This legal action escalates Yelp’s fight against Google’s practices in local search, which extends over a decade.
It follows a recent ruling by Judge Amit Mehta, which found that Google illegally maintained its monopoly in general search. Yelp believes the decision provides a foundation for its case.
Key points from Judge Mehta’s ruling include:
Google was found to be a monopolist that abused its dominant position.
The company’s paid default agreements with device makers and browsers foreclosed about 50% of the search market from rivals.
Google’s conduct had anticompetitive effects, including reducing incentives for competitors to innovate.
Aaron Schur, Yelp’s General Counsel, says in a statement provided to Search Engine Journal:
“Judge Amit Mehta’s recent ruling in the government’s antitrust case against Google, finding Google illegally maintained its monopoly in general search, is a watershed moment in antitrust law, and provides a strong foundation for Yelp’s case against Google.”
Potential Remedies
While specific remedies will be shaped by the discovery process, Yelp has pointed to the “Focus on the User” plan as one potential solution.
This proposal suggests modifying Google’s search algorithm to surface the best content from across the internet, rather than favoring Google’s own properties.
Looking Ahead
This lawsuit represents the latest chapter in the debate over Google’s search market dominance.
Google hasn’t responded to the lawsuit. The company has previously defended its practices as beneficial to users and argued that it faces genuine competition in local search.
Early SEO milestones might be easy, but scaling the results needs an upgraded approach.
What could that look like?
Like startups that come up with a solid niche idea and compete significantly with larger companies, we SEO pros and content strategists need to work harder to develop unique, fresh, niche strategies.
However, whenever we think of creating strategies, we start looking at what competitors are doing. We start feeling that we can win this game by outperforming our competitors.
Remember: we win when our focus is on winning the game and not on how to make our competitors lose.
So, here comes an upgraded approach to our SEO strategy – going beyond competitor analysis.
However, since our SEO strategies heavily rely on content, we’ll discuss content research beyond competitor analysis in this blog.
Now, What Is Content Research Beyond Competitor Analysis?
Most of us analyze our competitors to develop content ideas. It’s easy and quick.
But…
What if your competitors are ranking in the top positions but are not serving users’ intent?
What if your competitors might not be yielding enough traffic despite better rankings?
What if your competitors are driving massive organic traffic but not enough conversions?
Also, there may be some competitors that are doing extremely well regarding content KPIs serving SEO growth.
You may feel that if the competitors can achieve such results in one year, you can achieve them in six months by copying their strategies.
But that’s where you limit yourself in growth. Your competitors’ SEO and content teams might also be struggling; who knows?
This is why your content research must go beyond competitor analysis.
In this approach, we don’t look at what content competitors have written.
We don’t want to copy them or repeat their mistakes. We want to work in ways that truly resonate with our target audiences, geographies, business models, and industries.
So, the “content research beyond competitor analysis” approach helps us bring unique and fresh perspectives to our content research, creating incredible value for our audience and clients and scaling our SEO results extensively.
11 Ways Of Content Research Beyond Competitor Analysis To Scale SEO ROI
We have 11 ways to use this approach. Let’s uncover them one by one with step-by-step processes and examples.
1. Use Semrush
This is our basic step of content research since most of our initial goal is driving organic traffic.
And because Semrush is handy for most of our team members at Missive Digital, we log in immediately to start our content research instead of looking at competitors.
We put seed, actual, long-tail, and more keywords to do our content research, depending on the search volume, keyword difficulty, and search intent.
For example, we have put “diamond jewelry” into Semrush and will add the filters according to our SEO strategy.
Screenshot from Semrush, August 2024
Another content research feature of Semrush that we use extensively is Topic Research. We choose the content topics based on which ones relate directly or indirectly to our website.
Screenshot from Semrush, August 2024
2. Use Ahrefs
To do the content research on Ahrefs, we follow the same steps as Semrush, but here, we also use Content Explorer.
We filter based on the Page Traffic and reference domains to identify queries that can bring us traffic and conversions.
Screenshot from Ahrefs, August 2024
Then, we also examine the frequency of republishing, which gives our team an idea of when to schedule it next for content optimization, considering the performance.
Screenshot from Ahrefs, August 2024
3. Use Google News
While auditing the content, if we realize that the client is already writing a lot of content, we try researching content ideas through Google News.
Also, for some D2C industries like jewelry, the trend also comes from celebrities wearing them – so we keep a close eye on Google News.
Screenshot from search for [diamond necklace], Google, August 2024
Sometimes, we prefer covering the news depending on the topics, while other times, we’ll check if these topics have any search volume and can be evergreen to continue driving us some value throughout.
For example, the screenshot below shows a ‘B’ necklace worn by Selena Gomez in reference to her boyfriend.
Screenshot from search for [diamond necklace], Google, August 2024
We immediately check if there’s any search volume for “b necklace” on an SEO tool and see the screenshot below:
Screenshot by author, August 2024
Bingo! Now, we have to discuss with the client’s team for our next content piece.
4. Use People Also Ask, AlsoAsked
Since most B2B IT and SaaS clients are highly technical, we sometimes struggle to understand the topic and create a content strategy.
Screenshot from search for [kubernetes architecture], Google, August 2024
The only limitation we have with People Also Ask is that it provides a few Q&As for a topic until you click on one, while AlsoAsked provides an entire list in one go, which saves you time.
Screenshot from search for [kubernetes architecture], Google, August 2024
We now have too much to learn about a topic and create content on, right?
5. Check Google Trends
No matter what industry you are in, you’ve got something or the other trending.
In our SEO industry, SearchGPT is trending.
Screenshot from Google Trends, August 2024
So it’s worth writing about it to take the early advantage and grab the traffic share.
See, a lot of people are writing about it:
Screenshot from search for [searchgpt], Google, August 2024
So, it’s worth constantly watching what’s trending via Google Trends.
6. Hop On ChatGPT Or Gemini
Remember, we are here to do content research on ChatGPT or Gemini, not to choose the titles they suggest.
Here is a sample content research prompt that we have put for a contact center software company on ChatGPT:
Screenshot from ChatGPT, August 2024
And here are the responses below:
Screenshot from ChatGPT, August 2024
Since the topics are not up to the mark considering the audience (“BPO” in this case), based on the above content ideas, we’ll pick up the seed keywords or topics such as:
Lessons from a Legacy Contact Center Software Company.
The Contact Center Software Market In The BPO Segment.
Optimizing Your Contact Center Operations.
How to Drive Innovation in Your Customer Support Department?
And more.
7. Monitor Social Media
Yes, we are all active on social media, so we can use it for our content research. Still, we are not considering competitors on social media at the moment.
These are examples of self-created social media content that can be turned into blogs.
However, you can keep monitoring the types of content that get the most visibility and engagement on social media – be it LinkedIn, Instagram, X, or any other platform.
Turn them into your blogs or webinars, but don’t forget to mention them since it’s their original content idea.
8. Dive Into Industry-specific Research Studies
The most unique way to research content ideas is to read your industry-specific research studies extensively. And there’s no one way to do it.
For example, for one of the ecommerce consulting companies, we can get various content ideas from HBR’s eCommerce pricing test:
Why Should Ecommerce Brands Stop Offering Free Shipping?
X Benefits of No Free Shipping or Conditional Shipping.
Free Shipping vs. Conditional Shipping.
Image from HBR, August 2024
In the below study by Broadridge on Digital Transformation, the below can become the topic clusters, and each can have its own spoke-like content topics.
Image from study by Broadridge on Digital Transformation, August 2024
For example, if we take Unleashing Artificial Intelligence, we can pick up so many topics out of just one graphic:
Image from study by Broadridge on Digital Transformation, August 2024
9. Check Industry-Specific Forums/Communities
Most of our clientele includes IT companies, and we have used IT forums and communities like StackOverflow for content research.
For example, we can come up with the below topic clusters when covering Flutter for the non-technical and technical target audiences:
Flutter animation widgets.
Flutter dependency management.
Why add Firebase to your Flutter app?
And more.
Screenshot from Stack Overflow, August 2024
Similarly, there will be many such forums or communities of your client or employers available to peek into for such content ideas, except for competitive analysis.
10. Google site:reddit.com “my topic”
One such unique idea by Kunjal Chawhan is to Google site:reddit.com “my topic,” and let’s see what content ideas look like for a couple of topics:
Looking at the above screenshot, below are the topics that we can definitely create:
X Most Popular Social Media Platforms for Ecommerce.
How to Use Video Podcasts to Drive Ecommerce Sales?
How to Boost Ecommerce Sales When Digital Marketing Seems Expensive?
And more.
So yes, Kunjal’s way of content research is amazing, and from that, you can similarly Google:
site:“your industry’s leading site” “topic”
For example:
site:searchenginejournal.com “ai content”
site:quora.com “ai content”
site:practicalecommerce.com “sales”
Let’s move on to the last but not the least method of content research, except for looking at competitors.
11. See What Competing Sites Have NOT Covered
Now you might wonder, “Weren’t the above content research ways except for competitors analysis?”
Yes, they are the ways to research content ideas except for what competitors have written.
But here, I’m trying to make a point where you have to see exactly what indirect competing sites are NOT writing about despite targeting the same industry, keyword clusters, and audience.
What is an indirect competing site?
An indirect competing site is a website that ranks for the industry and search queries of your target audience but is not exactly your product/service competitor. This can be a marketplace, publishing site, or product review site.
Let’s take a website, “leadsquared.com,” for indirect competitive analysis and pick the queries that rank after 50th positions and have a keyword difficulty of less than 29.
Screenshot by author, August 2024
Pick those queries and search on Google: site:leadsquared.com “sales funnel vs sales pipeline”.
Screenshot from search for [site:leadsquared.com “sales funnel vs”, August 2024
Now, you’ll see that the website has no content on that topic; you can create that if that falls under your product/service offering and can target your audience and industry.
In short, you can cover the below topics:
Sales funnel vs. sales pipeline.
Sales funnel vs. marketing funnel.
Sales funnel vs. flywheel.
And more.
Just ensure these content topics align with your offerings to bring maximum ROI.
How Will Content Research Beyond Competitor Analysis Contribute To SEO Efforts?
When you go beyond competitor analysis for content research, you discover a few benefits:
You innovate – With innovative content ideas, you can experiment and build better strategies that can bring unbelievable results. Also, with AI taking the space predominantly, businesses are looking for innovation in their business and marketing. So when you innovate, you may get better attention and even resources.
You get niche opportunities – Instead of just focusing on what competitors are doing, you go deeper into understanding your target audience and explore new content ideas that your competitors might have missed. In such scenarios, you get better results since competition is reduced.
You create unique, audience-specific content – My LinkedIn post saw great engagement because it resonated with its audience. This opened us to something unique and specific to the pain point of SEOs and content strategists: content ideation to scale SEO results with a not-so-usual approach. Such content helps us build authority in the market, which is essential today to becoming market leaders.
You capitalize on emerging trends – Being an early adopter of something has huge potential for success. When you create your content strategy focused on what’s new or trending in your industry before it becomes mainstream, you get the most eyes right from the beginning and even repeat eyes going forward.
You build better engagement and loyalty – You can extend beyond blogs, a traditional way of driving SEO results. Videos, whitepapers, case studies, user-generated content, and many more content formats can take the lead in building user engagement and brand loyalty through SEO.
You earn backlinks – Yes, such unique content may require less effort to build backlinks since it can earn them.
Stop looking at competitors for content research; try using these fresh and unique ways to drive better content ROI.
Just remember two things: Competitors are not always right, and you are not necessarily required to look upon them when developing your SEO content strategies.
You can copy and paste your competitors’ strategies to achieve certain SEO milestones, but creating history requires an upgraded approach. What say?
This week’s Ask An SEO question comes from Carrazana in Cuba, who asks:
“How do you find the right, long-tail keywords for articles? I can not find the right keywords and long tail keywords for my post and articles. I use keywords everywhere.”
Great question, Carrazana! Lots of content professionals struggle with finding long tail keywords, and many worry about cross-over between posts, also known as keyword and topic cannibalization.
The way to find long tail keywords and prevent cannibalization is to change your mindset on needing keywords by article and incorporate non-traditional research tools. So, let’s solve this so it is no longer an obstacle for you.
I’m going to start by addressing cannibalization, then jump into using non-traditional keyword research methods like LinkedIn hashtags and strategies our agency uses to generate ideas for our clients.
One thing I’d like to emphasize is to not focus on keywords; focus on the topic, and providing the best possible user experience for the intent of the topic.
Cannibalization
Instead of thinking about the keywords that are needed, think about the topic that you’re writing for.
The same words and phrases could mean different things and have different intent based on the topic, even if they’re used in the same way. Not in the sense of a homonym or double entendre, but as in search intent.
The same phrase for the service should exist in multiple pages of content, including product or service pages for conversions, and in guides to help consumers learn more, decide where to purchase, or how to prepare. The difference here is the topic changes based on the intent.
On the conversion page, the phrase needs to reinforce that this is a page that the consumer can take action on. For a how-to guide, it is more informative and should help the consumer know how to do it themselves, prepare for the professional to come and visit, or learn how to hire the right person for the job.
Search engines are smart enough to know the intent of content and can show it as needed. This is why you want to have a clear intent when creating content.
If you sell apples, do not define what an apple is on your product or service page.
The person already knows; instead, define it on a blog post about “what an apple is.” The product or service page should be about the benefits of using the specific apple, like baking, eating it directly, or feeding it to specific animals as a treat.
Your blog posts can include definitions, guides, and comparisons of which apples are better for specific purposes and why, as well as other non-conversion-oriented content.
Both the product page and at least one guide will have “apples for horses,” but the intent is different.
One page clearly shows where you can buy an apple to feed a horse, while the other explains why that particular apple is better for horses, which may be its nutritional value or the way a horse’s tastebuds and body respond to the sugar or fiber content.
I’m making this up for the example; don’t take it as factual advice. You can deploy schema to let the search engines know when to show each page based on search intent.
Product and service schema goes on the pages where you want conversions, and article or blog posting schema can go on the guides and informative ones. The machine learning portions of the search engine will look at the associations around the text while other aspects read the schema to determine what the purpose of the page is.
Proper implementation and clear wording make the search engine’s job easy and reduce the chance of cannibalization. Now that you know how to prevent cannibalization, let’s go into finding long tail keyword topics.
Finding Long-Tail Keyword Phrases
Finding long-tail keyword phrases is simple when you step outside of the normal tool sets. You have data points your competitors and third parties don’t have access to using customer data, and there are non-traditional places you can search.
Customer Support
Start by reading customer service and live chat transcripts. See if you can extract questions that mention specific products or services or by a category like blue t-shirts or red apples. With this information, you can see the words and language your customers are using, and how frequently.
These become long tail phrases for content on all forms of pages. You can also see the questions they have, reasons they return product, and recommendations customer support offers to guide them to the correct option to purchase.
These data points lead to sizing guides and comparison shopping content, articles about one fabric being better than another for a purpose like cocktail parties or running a marathon, and answer questions for the shopping and checkout process.
You may also find that these are questions being asked about your competitors like which of their models is similar to a specific product on your website.
You can create solutions on your site to bring in this type of traffic by answering their customers’ questions and optimizing your site for them via search.
LinkedIn, Pinterest, Instagram, And Other Hashtag Sites
Social media sites that power part of their search and algorithm with hashtags are a goldmine of topics.
Go to LinkedIn and click on a hashtag like #SEO or #business. You’ll see how many people subscribe to it, how often it is used, and engagement on new content published within the hashtag’s feed.
If the hashtag is being used regularly and has engagement, look at the posts that exist within it. By knowing which gets the most comments, activity, and other signals, you can use them as a basis for new content on your own website.
As a bonus, they can be shared on these social platforms and hopefully get social media engagement too.
Bonus tip: The most engaged may only be engaged because the person or company that shared has an active following. Look for three that are similar in topic and see if two of the three have engagement to determine if it has the potential for a bit of virality on social media.
Forums And Q&A Sites
Next, use forums and question-and-answer sites. Take a Reddit forum and plug it into an SEO tool like Semrush, Ahrefs, or Moz to see the keywords and phrases they’re ranking for.
You may find a lot of long tail that could be relevant to your own product or service offerings.
Then look at the specific threads showing up for these phrases and see if there are new long-tail keyword phrases being used by the community. This gives you insight into their mindset – compare it with your own live chat and customer service data.
Q&A Keyword Tools
There are some great tools out there to find long-tail phrases, like AlsoAsked.com and AnswerThePublic.com. When you type a keyword phrase in you can see the ideas these tools come up with for topics to write about and the keywords the tools feel are related to the main topic.
Use Autocomplete On YouTube And Search Engines
The last tip is to use auto-complete on search engines, including YouTube. Once on YouTube, type in a portion of a phrase or a keyword and you’ll see it begin to autofill potential matches.
When there’s one that is relevant for your audience, click it and then look at the titles and descriptions from each video.
Many creators use chapters, and these chapters are what the content creator found to be helpful and relevant to the phrase. Each can become topics and phrases for you as well. Next, watch each video, listen to the wording and phrases the YouTuber uses, and read the comments section below.
You’ll learn the questions that weren’t answered in the video, the jargon users use, and find more content ideas as well as gaps you can fill in to bring new information into the mix. This same strategy applies to TikTok, Instagram Reels, and other video content platforms.
There’s no shortage of ways to find long-tail keyword phrases; the only limit is your own creativity.
As a content writer and SEO professional, you have tons of it! I hope this post helps you find more to write about.
More resources:
Featured Image: Paulo Bobita/Search Engine Journal
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