SEO
How Zapier Built a Content Marketing Machine
How do you help people discover software they need but don’t yet know exists?
That was the challenge I faced when I became the second member of Zapier’s editorial team in 2014.
Zapier’s team had built a tool to automate your tedious business tasks. Anything you could do by copying and pasting—tweeting new blog posts, emailing new customers, adding orders to a spreadsheet, alerting your team of outages—Zapier could do faster, better, and while you slept. Therein lay a content strategy.
Most people didn’t know they needed Zapier three years after it was first released, but they did know they needed a way to speed up their work and solve software issues. We could tell them how to build better software workflows—and recommend Zapier along the way.
That strategy helped us build a library of content that today brings in over 2 million readers to Zapier each month. Here’s how we built it.
People weren’t searching for Zapier, not in 2014 when the product was new to the market. But they were searching for Zapier’s complements, the tools that worked with Zapier that they were already using. That’s why Zapier created its App Directory, originally called the Zapbook, as a directory of every app that integrated with Zapier.
Every new app that integrated with Zapier got a landing page listing what it automated. Gmail’s page, for example, showed you could save attachments to Google Drive, send an email when your form got filled out, or create an Asana task via email.
Zapier’s App Directory also listed permutations for every integration: Gmail + Salesforce, Gmail + Slack, Gmail + Google Sheets, and on and on. That’s where the real magic happened. People would search for two app names (hoping to get them to work together) and then stumble upon Zapier along the way.
Today, there are 4,403 individual integration pages, plus an incredible 38,612 pair pages that together bring in over 299,000 monthly organic search visits.
It was difficult to rank for the more popular software, but there was always a very good chance that Zapier could rank for a lesser-known app pair—say, ShipStation and PayPal—when there was little, if any, content online about using those two tools together.
The challenge was making the App Directory pages unique. Zapier started the directory with a couple dozen preset sentences; when a new two-app page was created, it’d generate a phrase like “Connect App X and Y to automate your work and be more productive.” The danger was in having so many pages with similar, thin content.
So one of my first projects was writing software reviews for the App Directory. I’d test an app and write a 500-word walkthrough of what it was like to use that tool, add a few screenshots, and more to flesh out each app’s page.
Another similar content initiative revolved around automation templates. Zapier knew which apps people connected the most, and we knew from users how those automations were used. We’d turn those into Zapier workflows that anyone could enable in a few clicks—and I’d write a roughly 100-word description to help those workflows rank in search.
And it worked. First with Zapier’s team building templates, then with partners building templates for their users and, more recently, with Zap templates users can build and share on their own.
One of the top search results today for “email daily,” for example, is for a Zap that will let you set up an automatic daily email—a simple template that brings in ~2,400 organic visitors per month for search terms like “everyday email” and “send automatic email.”
Between those workflows and cross-linked content on the blog, today Zapier doesn’t rely on app walkthroughs to flesh out its App Directory pages. But the strategy helped boost the directory in its earliest days.
Write great stuff, and people will come. That was our basic strategy on Zapier’s blog.
It was something our managing editor, Melanie Pinola, brought from Lifehacker. “Their answer for what success looks like is ‘creating content that’s helpful,’” she told us.
My writing was focused on software tutorials and roundups. Zapier supported, at that time, hundreds of apps. I couldn’t write about everything, so it made sense to prioritize by popularity.
I’d start at the high level, checking Zapier’s software categories on Ahrefs to see which were most popular. To-do list apps and CRM software got 46,000 and 36,000 searches a month. I’d figured it was better to cover those first, then focus on smaller categories like HR or invoicing software later.
Then I’d drill down from there to find what people were searching for around these categories.
For example, I’d click the term “crm software” in Ahrefs and find that the top question was “what is CRM software” and that “CRM meaning” was a related popular term. So I’d make a note to write a guide for beginner CRM users. I’d also see the top CRMs people were searching for, such as HubSpot, when I was first writing the roundup (and Keap if you check for top CRM keywords today).
The research would also uncover topics to cover in the future. The most popular questions were about what a CRM is, so that’d be the next article I’d write as a companion to the CRM roundup. So “best CRM for small business” was another popular, easier-to-rank term—and Zapier later followed up on the original CRM roundup with a more focused roundup of those specifically for small businesses.
With keyword research out of the way, I’d switch to researching software to build an in-depth roundup article focused on the best CRM software—the keyword that most people were searching for when looking for a new CRM.
I’d test every CRM that Zapier supported, along with dozens of others. I’d take screenshots and write an App Directory roundup of each CRM tool, then pull the findings into a roundup article that showed how each app was differentiated from its peers.
It took days of research, but the final pieces were incredibly in-depth (my original CRM roundup covered 25 tools, and my Zapier project management app roundup was over 8,000 words and covered 50 tools).
We wrote hundreds of software roundup articles on Zapier—with 171 “best of” posts live on Zapier’s blog today. Together, they bring in an estimated 1.1 million organic visits each month, years after many of them were originally researched and published.
Maybe I didn’t have to write so much. Shorter pieces can rank well too. And Zapier’s more recently updated takes on those pieces pick eight or 10 best options for a more Wirecutter-style selected take.
But the ultra-long-form pieces had their advantages. The longer content included more keywords—niche keywords, again, that we were more likely to rank for. They also let us surprise and delight more teams at other companies. I’d email each app I featured, letting them know about the article. Slowly but surely, as more partners linked to our roundups, Zapier gained backlinks and climbed Google’s search rankings.
The research took forever, but it always inspired follow-up posts. Once I’d finished the roundup, I switched gears and wrote the “What is a CRM?” article. That today still brings in hundreds of monthly organic visitors, along with the over 13,000 monthly organic visitors from the roundup. Over time, using this strategy, we ended with an incredibly wide range of roundups and tutorials that have dominated Zapier’s search traffic for years.
Sidenote.
One caveat: I never wrote roundups about automation tools. My rules of what not to write included not making a roundup or comparison table that had my employer’s product. It’d be impossible to portray Zapier’s content as truly independent if Zapier itself was featured on the list. But I could be unbiased—as much as anyone could be—about our partners and the tools in their categories. And that let Zapier build an audience of readers who trusted our writing.
Roundups weren’t for everyone. To borrow terms from the project development lifecycle, they were written for readers in the discovery phase who were searching for a new tool.
Then they’d need to do stuff in the app. That’s where Zapier’s tutorials (and the App Directory’s premade Zapier workflows) came in. Those brought in readers during their development phase—when they were developing a workflow and were most likely to start using Zapier.
Google Sheets-focused tutorials worked especially well here. I wrote a tutorial on how to use the LOOKUP function in Google Sheets—plus how to automatically look up data in spreadsheets and more with Zapier. A companion tutorial showed how to split text—say, split a first and a last name into separate columns—in spreadsheets, followed by how to automate that in forms and more with Zapier.
These tutorials bring in a couple thousand search visits per month—fewer visitors than roundups, but these are visitors more likely to need and use Zapier.
But you only need so many app roundups and tutorials. The next time we wrote about to-do list apps, you wouldn’t be interested; the app you picked was humming along. You might be interested in learning how other teams manage projects, how remote work works, or about hitting inbox zero.
That’s why Zapier also wrote productivity articles: to maintain our relationship with readers by sending them something interesting each week. Those were the pieces easiest to syndicate—to get others to republish as guest posts that built backlinks and brought in new sources of readers and a bit more brand equity. They were less of my focus in Zapier’s earlier years but more of a core part of Zapier’s brand building and audience retention work today.
Roundups brought in far more pageviews. Tutorials brought in far more customers per pageview. Productivity posts brought back more repeat readers. Together, they built a search-powered growth engine.
What is published can always be published again too.
That was the third pillar of Zapier’s content: our Learning Center and its ebooks.
Once I’d written everything core about a software category like CRMs or a popular tool like Google Sheets, I’d pull those posts together, build them into an ebook with Leanpub, then publish on the Kindle and iBooks stores. The new ebook landing page drove email signups from book downloads and earned a higher time on site as people read one post after another instead of browsing just a single roundup.
Best of all, Zapier got a new audience from the ebook stores as a bit of off-Google SEO. People searched for Google Sheets in the Amazon store, downloaded Zapier’s book, then clicked through as they read the book. It wasn’t as easy to measure or value as Google search clicks, but it was search-driven traffic all the same.
Search data was a core part of prioritizing which of my ideas were best to write first. But experimentation also played a large part in my writing.
One day, for instance, I was trying to connect to the Wi-Fi at a mechanic while getting my car’s battery changed. It hit me that I should write a quick tutorial on how to get the Wi-Fi password pop-up to open when it wouldn’t at airports, coffee shops, and the like. A few hundred words later, the hastily written post was live.
And it blew up, getting over 100,000 visits a month at its peak—more traffic than most of our well-researched, search-focused content did. It’s still, today, bringing in thousands of readers every month, ranking organically in the top three for terms like “force wifi login page” and “hilton wifi login,” of all things.
Turns out, experimenting and scratching your own itches can work out every so often too.
Final thoughts
Search data is historical data, records of what people searched at some time in the past.
If you hit a problem today and are on the bleeding edge, that problem may be something few people face today but one that more and more people will start facing later. If you write about some new thing, it’s not going to show promise in Ahrefs data today.
Just be patient. When that thing you wrote about suddenly is in the news or becomes an emerging trend, you’ll be ahead of the game before it starts.
So do your research. Publish stuff where you have a chance to rank well on search. Write long-form, especially at first, if it gives you a chance to build more keywords and connections into a piece.
But also, never stop experimenting. If you really want to write something, go for it even if the stats aren’t there yet. It can’t hurt, and it just may be your breakout piece.
SEO
56 Google Search Statistics to Bookmark for 2024
If you’re curious about the state of Google search in 2024, look no further.
Each year we pick, vet, and categorize a list of up-to-date statistics to give you insights from trusted sources on Google search trends.
Check out more resources on how Google works:
Learn more
SEO
How To Use ChatGPT For Keyword Research
Anyone not using ChatGPT for keyword research is missing a trick.
You can save time and understand an entire topic in seconds instead of hours.
In this article, I outline my most effective ChatGPT prompts for keyword research and teach you how I put them together so that you, too, can take, edit, and enhance them even further.
But before we jump into the prompts, I want to emphasize that you shouldn’t replace keyword research tools or disregard traditional keyword research methods.
ChatGPT can make mistakes. It can even create new keywords if you give it the right prompt. For example, I asked it to provide me with a unique keyword for the topic “SEO” that had never been searched before.
“Interstellar Internet SEO: Optimizing content for the theoretical concept of an interstellar internet, considering the challenges of space-time and interplanetary communication delays.”
Although I want to jump into my LinkedIn profile and update my title to “Interstellar Internet SEO Consultant,” unfortunately, no one has searched that (and they probably never will)!
You must not blindly rely on the data you get back from ChatGPT.
What you can rely on ChatGPT for is the topic ideation stage of keyword research and inspiration.
ChatGPT is a large language model trained with massive amounts of data to accurately predict what word will come next in a sentence. However, it does not know how to do keyword research yet.
Instead, think of ChatGPT as having an expert on any topic armed with the information if you ask it the right question.
In this guide, that is exactly what I aim to teach you how to do – the most essential prompts you need to know when performing topical keyword research.
Best ChatGPT Keyword Research Prompts
The following ChatGPT keyword research prompts can be used on any niche, even a topic to which you are brand new.
For this demonstration, let’s use the topic of “SEO” to demonstrate these prompts.
Generating Keyword Ideas Based On A Topic
What Are The {X} Most Popular Sub-topics Related To {Topic}?
The first prompt is to give you an idea of the niche.
As shown above, ChatGPT did a great job understanding and breaking down SEO into three pillars: on-page, off-page & technical.
The key to the following prompt is to take one of the topics ChatGPT has given and query the sub-topics.
What Are The {X} Most Popular Sub-topics Related To {Sub-topic}?
For this example, let’s query, “What are the most popular sub-topics related to keyword research?”
Having done keyword research for over 10 years, I would expect it to output information related to keyword research metrics, the types of keywords, and intent.
Let’s see.
Screenshot from ChatGPT 4, April 2024Again, right on the money.
To get the keywords you want without having ChatGPT describe each answer, use the prompt “list without description.”
Here is an example of that.
List Without Description The Top {X} Most Popular Keywords For The Topic Of {X}
You can even branch these keywords out further into their long-tail.
Example prompt:
List Without Description The Top {X} Most Popular Long-tail Keywords For The Topic “{X}”
Screenshot ChatGPT 4,April 2024List Without Description The Top Semantically Related Keywords And Entities For The Topic {X}
You can even ask ChatGPT what any topic’s semantically related keywords and entities are!
Screenshot ChatGPT 4, April 2024Tip: The Onion Method Of Prompting ChatGPT
When you are happy with a series of prompts, add them all to one prompt. For example, so far in this article, we have asked ChatGPT the following:
- What are the four most popular sub-topics related to SEO?
- What are the four most popular sub-topics related to keyword research
- List without description the top five most popular keywords for “keyword intent”?
- List without description the top five most popular long-tail keywords for the topic “keyword intent types”?
- List without description the top semantically related keywords and entities for the topic “types of keyword intent in SEO.”
Combine all five into one prompt by telling ChatGPT to perform a series of steps. Example:
“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, Step 4, and Step 5”
Example:
“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, Step 4 and Step 5. Step 1 – Generate an answer for the 3 most popular sub-topics related to {Topic}?. Step 2 – Generate 3 of the most popular sub-topics related to each answer. Step 3 – Take those answers and list without description their top 3 most popular keywords. Step 4 – For the answers given of their most popular keywords, provide 3 long-tail keywords. Step 5 – for each long-tail keyword offered in the response, a list without descriptions 3 of their top semantically related keywords and entities.”
Generating Keyword Ideas Based On A Question
Taking the steps approach from above, we can get ChatGPT to help streamline getting keyword ideas based on a question. For example, let’s ask, “What is SEO?”
“Perform the following steps in a consecutive order Step 1, Step 2, Step 3, and Step 4. Step 1 Generate 10 questions about “{Question}”?. Step 2 – Generate 5 more questions about “{Question}” that do not repeat the above. Step 3 – Generate 5 more questions about “{Question}” that do not repeat the above. Step 4 – Based on the above Steps 1,2,3 suggest a final list of questions avoiding duplicates or semantically similar questions.”
Screenshot ChatGPT 4, April 2024Generating Keyword Ideas Using ChatGPT Based On The Alphabet Soup Method
One of my favorite methods, manually, without even using a keyword research tool, is to generate keyword research ideas from Google autocomplete, going from A to Z.
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Screenshot from Google autocomplete, April 2024
You can also do this using ChatGPT.
Example prompt:
“give me popular keywords that includes the keyword “SEO”, and the next letter of the word starts with a”
Screenshot from ChatGPT 4, April 2024Tip: Using the onion prompting method above, we can combine all this in one prompt.
“Give me five popular keywords that include “SEO” in the word, and the following letter starts with a. Once the answer has been done, move on to giving five more popular keywords that include “SEO” for each letter of the alphabet b to z.”
Generating Keyword Ideas Based On User Personas
When it comes to keyword research, understanding user personas is essential for understanding your target audience and keeping your keyword research focused and targeted. ChatGPT may help you get an initial understanding of customer personas.
Example prompt:
“For the topic of “{Topic}” list 10 keywords each for the different types of user personas”
Screenshot from ChatGPT 4, April 2024You could even go a step further and ask for questions based on those topics that those specific user personas may be searching for:
Screenshot ChatGPT 4, April 2024As well as get the keywords to target based on those questions:
“For each question listed above for each persona, list the keywords, as well as the long-tail keywords to target, and put them in a table”
Screenshot from ChatGPT 4, April 2024Generating Keyword Ideas Using ChatGPT Based On Searcher Intent And User Personas
Understanding the keywords your target persona may be searching is the first step to effective keyword research. The next step is to understand the search intent behind those keywords and which content format may work best.
For example, a business owner who is new to SEO or has just heard about it may be searching for “what is SEO.”
However, if they are further down the funnel and in the navigational stage, they may search for “top SEO firms.”
You can query ChatGPT to inspire you here based on any topic and your target user persona.
SEO Example:
“For the topic of “{Topic}” list 10 keywords each for the different types of searcher intent that a {Target Persona} would be searching for”
ChatGPT For Keyword Research Admin
Here is how you can best use ChatGPT for keyword research admin tasks.
Using ChatGPT As A Keyword Categorization Tool
One of the use cases for using ChatGPT is for keyword categorization.
In the past, I would have had to devise spreadsheet formulas to categorize keywords or even spend hours filtering and manually categorizing keywords.
ChatGPT can be a great companion for running a short version of this for you.
Let’s say you have done keyword research in a keyword research tool, have a list of keywords, and want to categorize them.
You could use the following prompt:
“Filter the below list of keywords into categories, target persona, searcher intent, search volume and add information to a six-column table: List of keywords – [LIST OF KEYWORDS], Keyword Search Volume [SEARCH VOLUMES] and Keyword Difficulties [KEYWORD DIFFICUTIES].”
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Screenshot from ChatGPT, April 2024
Tip: Add keyword metrics from the keyword research tools, as using the search volumes that a ChatGPT prompt may give you will be wildly inaccurate at best.
Using ChatGPT For Keyword Clustering
Another of ChatGPT’s use cases for keyword research is to help you cluster. Many keywords have the same intent, and by grouping related keywords, you may find that one piece of content can often target multiple keywords at once.
However, be careful not to rely only on LLM data for clustering. What ChatGPT may cluster as a similar keyword, the SERP or the user may not agree with. But it is a good starting point.
The big downside of using ChatGPT for keyword clustering is actually the amount of keyword data you can cluster based on the memory limits.
So, you may find a keyword clustering tool or script that is better for large keyword clustering tasks. But for small amounts of keywords, ChatGPT is actually quite good.
A great use small keyword clustering use case using ChatGPT is for grouping People Also Ask (PAA) questions.
Use the following prompt to group keywords based on their semantic relationships. For example:
“Organize the following keywords into groups based on their semantic relationships, and give a short name to each group: [LIST OF PAA], create a two-column table where each keyword sits on its own row.
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Screenshot from ChatGPT, April 2024
Using Chat GPT For Keyword Expansion By Patterns
One of my favorite methods of doing keyword research is pattern spotting.
Most seed keywords have a variable that can expand your target keywords.
Here are a few examples of patterns:
1. Question Patterns
(who, what, where, why, how, are, can, do, does, will)
“Generate [X] keywords for the topic “[Topic]” that contain any or all of the following “who, what, where, why, how, are, can, do, does, will”
Screenshot ChatGPT 4, April 20242. Comparison Patterns
Example:
“Generate 50 keywords for the topic “{Topic}” that contain any or all of the following “for, vs, alternative, best, top, review”
Screenshot ChatGPT 4, April 20243. Brand Patterns
Another one of my favorite modifiers is a keyword by brand.
We are probably all familiar with the most popular SEO brands; however, if you aren’t, you could ask your AI friend to do the heavy lifting.
Example prompt:
“For the top {Topic} brands what are the top “vs” keywords”
Screenshot ChatGPT 4, April 20244. Search Intent Patterns
One of the most common search intent patterns is “best.”
When someone is searching for a “best {topic}” keyword, they are generally searching for a comprehensive list or guide that highlights the top options, products, or services within that specific topic, along with their features, benefits, and potential drawbacks, to make an informed decision.
Example:
“For the topic of “[Topic]” what are the 20 top keywords that include “best”
Screenshot ChatGPT 4, April 2024Again, this guide to keyword research using ChatGPT has emphasized the ease of generating keyword research ideas by utilizing ChatGPT throughout the process.
Keyword Research Using ChatGPT Vs. Keyword Research Tools
Free Vs. Paid Keyword Research Tools
Like keyword research tools, ChatGPT has free and paid options.
However, one of the most significant drawbacks of using ChatGPT for keyword research alone is the absence of SEO metrics to help you make smarter decisions.
To improve accuracy, you could take the results it gives you and verify them with your classic keyword research tool – or vice versa, as shown above, uploading accurate data into the tool and then prompting.
However, you must consider how long it takes to type and fine-tune your prompt to get your desired data versus using the filters within popular keyword research tools.
For example, if we use a popular keyword research tool using filters, you could have all of the “best” queries with all of their SEO metrics:
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Screenshot from Ahrefs Keyword Explorer, March 2024
And unlike ChatGPT, generally, there is no token limit; you can extract several hundred, if not thousands, of keywords at a time.
As I have mentioned multiple times throughout this piece, you cannot blindly trust the data or SEO metrics it may attempt to provide you with.
The key is to validate the keyword research with a keyword research tool.
ChatGPT For International SEO Keyword Research
ChatGPT can be a terrific multilingual keyword research assistant.
For example, if you wanted to research keywords in a foreign language such as French. You could ask ChatGPT to translate your English keywords;
Screenshot ChatGPT 4, Apil 2024- The key is to take the data above and paste it into a popular keyword research tool to verify.
- As you can see below, many of the keyword translations for the English keywords do not have any search volume for direct translations in French.
Screenshot from Ahrefs Keyword Explorer, April 2024But don’t worry, there is a workaround: If you have access to a competitor keyword research tool, you can see what webpage is ranking for that query – and then identify the top keyword for that page based on the ChatGPT translated keywords that do have search volume.
-
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Screenshot from Ahrefs Keyword Explorer, April 2024
Or, if you don’t have access to a paid keyword research tool, you could always take the top-performing result, extract the page copy, and then ask ChatGPT what the primary keyword for the page is.
Key Takeaway
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ChatGPT can be an expert on any topic and an invaluable keyword research tool. However, it is another tool to add to your toolbox when doing keyword research; it does not replace traditional keyword research tools.
As shown throughout this tutorial, from making up keywords at the beginning to inaccuracies around data and translations, ChatGPT can make mistakes when used for keyword research.
You cannot blindly trust the data you get back from ChatGPT.
However, it can offer a shortcut to understanding any topic for which you need to do keyword research and, as a result, save you countless hours.
But the key is how you prompt.
The prompts I shared with you above will help you understand a topic in minutes instead of hours and allow you to better seed keywords using keyword research tools.
It can even replace mundane keyword clustering tasks that you used to do with formulas in spreadsheets or generate ideas based on keywords you give it.
Paired with traditional keyword research tools, ChatGPT for keyword research can be a powerful tool in your arsenal.
More resources:
Featured Image: Tatiana Shepeleva/Shutterstock
SEO
OpenAI Expected to Integrate Real-Time Data In ChatGPT
Sam Altman, CEO of OpenAI, dispelled rumors that a new search engine would be announced on Monday, May 13. Recent deals have raised the expectation that OpenAI will announce the integration of real-time content from English, Spanish, and French publications into ChatGPT, complete with links to the original sources.
OpenAI Search Is Not Happening
Many competing search engines have tried and failed to challenge Google as the leading search engine. A new wave of hybrid generative AI search engines is currently trying to knock Google from the top spot with arguably very little success.
Sam Altman is on record saying that creating a search engine to compete against Google is not a viable approach. He suggested that technological disruption was the way to replace Google by changing the search paradigm altogether. The speculation that Altman is going to announce a me-too search engine on Monday never made sense given his recent history of dismissing the concept as a non-starter.
So perhaps it’s not a surprise that he recently ended the speculation by explicitly saying that he will not be announcing a search engine on Monday.
He tweeted:
“not gpt-5, not a search engine, but we’ve been hard at work on some new stuff we think people will love! feels like magic to me.”
“New Stuff” May Be Iterative Improvement
It’s quite likely that what’s going to be announced is iterative which means it improves ChatGPT but not replaces it. This fits into how Altman recently expressed his approach with ChatGPT.
He remarked:
“And it does kind of suck to ship a product that you’re embarrassed about, but it’s much better than the alternative. And in this case in particular, where I think we really owe it to society to deploy iteratively.
There could totally be things in the future that would change where we think iterative deployment isn’t such a good strategy, but it does feel like the current best approach that we have and I think we’ve gained a lot from from doing this and… hopefully the larger world has gained something too.”
Improving ChatGPT iteratively is Sam Altman’s preference and recent clues point to what those changes may be.
Recent Deals Contain Clues
OpenAI has been making deals with news media and User Generated Content publishers since December 2023. Mainstream media has reported these deals as being about licensing content for training large language models. But they overlooked a a key detail that we reported on last month which is that these deals give OpenAI access to real-time information that they stated will be used to give attribution to that real-time data in the form of links.
That means that ChatGPT users will gain the ability to access real-time news and to use that information creatively within ChatGPT.
Dotdash Meredith Deal
Dotdash Meredith (DDM) is the publisher of big brand publications such as Better Homes & Gardens, FOOD & WINE, InStyle, Investopedia, and People magazine. The deal that was announced goes way beyond using the content as training data. The deal is explicitly about surfacing the Dotdash Meredith content itself in ChatGPT.
The announcement stated:
“As part of the agreement, OpenAI will display content and links attributed to DDM in relevant ChatGPT responses. …This deal is a testament to the great work OpenAI is doing on both fronts to partner with creators and publishers and ensure a healthy Internet for the future.
Over 200 million Americans each month trust our content to help them make decisions, solve problems, find inspiration, and live fuller lives. This partnership delivers the best, most relevant content right to the heart of ChatGPT.”
A statement from OpenAI gives credibility to the speculation that OpenAI intends to directly show licensed third-party content as part of ChatGPT answers.
OpenAI explained:
“We’re thrilled to partner with Dotdash Meredith to bring its trusted brands to ChatGPT and to explore new approaches in advancing the publishing and marketing industries.”
Something that DDM also gets out of this deal is that OpenAI will enhance DDM’s in-house ad targeting in order show more tightly focused contextual advertising.
Le Monde And Prisa Media Deals
In March 2024 OpenAI announced a deal with two global media companies, Le Monde and Prisa Media. Le Monde is a French news publication and Prisa Media is a Spanish language multimedia company. The interesting aspects of these two deals is that it gives OpenAI access to real-time data in French and Spanish.
Prisa Media is a global Spanish language media company based in Madrid, Spain that is comprised of magazines, newspapers, podcasts, radio stations, and television networks. It’s reach extends from Spain to America. American media companies include publications in the United States, Argentina, Bolivia, Chile, Colombia, Costa Rica, Ecuador, Mexico, and Panama. That is a massive amount of real-time information in addition to a massive audience of millions.
OpenAI explicitly announced that the purpose of this deal was to bring this content directly to ChatGPT users.
The announcement explained:
“We are continually making improvements to ChatGPT and are supporting the essential role of the news industry in delivering real-time, authoritative information to users. …Our partnerships will enable ChatGPT users to engage with Le Monde and Prisa Media’s high-quality content on recent events in ChatGPT, and their content will also contribute to the training of our models.”
That deal is not just about training data. It’s about bringing current events data to ChatGPT users.
The announcement elaborated in more detail:
“…our goal is to enable ChatGPT users around the world to connect with the news in new ways that are interactive and insightful.”
As noted in our April 30th article that revealed that OpenAI will show links in ChatGPT, OpenAI intends to show third party content with links to that content.
OpenAI commented on the purpose of the Le Monde and Prisa Media partnership:
“Over the coming months, ChatGPT users will be able to interact with relevant news content from these publishers through select summaries with attribution and enhanced links to the original articles, giving users the ability to access additional information or related articles from their news sites.”
There are additional deals with other groups like The Financial Times which also stress that this deal will result in a new ChatGPT feature that will allow users to interact with real-time news and current events .
OpenAI’s Monday May 13 Announcement
There are many clues that the announcement on Monday will be that ChatGPT users will gain the ability to interact with content about current events. This fits into the terms of recent deals with news media organizations. There may be other features announced as well but this part is something that there are many clues pointing to.
Watch Altman’s interview at Stanford University
Featured Image by Shutterstock/photosince
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