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How To Use Amazon Hidden Keywords To Increase Product Discoverability

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How To Use Amazon Hidden Keywords To Increase Product Discoverability

Amazon is the biggest name in the game for selling products online. But with 1.9 million selling partners, the competition is fierce.

To claim your market share, you need to show up in the searches people are performing.

And that starts with keywords.

Just as if you were optimizing a webpage for Google, you need to include the right words and phrases on your product page to ensure you’re showing up in relevant searches.

Your titles, features, and descriptions must be optimized, but that’s not enough.

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There’s another factor Amazon takes into account when delivering results to queries, something many third-party sellers aren’t aware of: hidden keywords.

If you’re completely unaware of what these are and how they work, or you want to discover the secret to using them to your advantage, you’re in the right place.

In this piece, we’ll take an in-depth look at Amazon’s hidden keywords and show you everything you need to know to put them to work for your Amazon store.

What Are Amazon’s Hidden Keywords?

Hidden keywords, sometimes called backend keywords, are any words related to your product that aren’t included in the title or description.

For example, they’re the terms Amazon returns after a sponsored product ad shows for an item, the ad is clicked on, and the product is purchased, or the queries a customer entered into an Amazon Search.

They’re any words related to your product that aren’t in the product title or description. These could be generic terms or synonyms for your product.

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And they should be included in the 250 characters per field (up to five fields) that you supply to Amazon to help boost discoverability in their search results pages.

So, search terms, right? Not exactly. I know this isn’t very clear, so we’ll try clarifying things.

(And yes, the fields in which you enter these hidden keywords in the Amazon UI are also called “Search Terms” to make things a bit more confusing.)

Plus, the report you download from Amazon for reporting on these search terms for advertising efforts is called a “Search Term Report.”

In Google paid search, we’d call it a “Search Query Report,” which seems to make more sense, but apparently, Amazon disagrees.

Calling hidden keywords just “keywords” also gets confusing, especially when choosing keywords for sponsored product campaigns.

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And while I hate the name with every search bone in my body, Amazon calls them hidden keywords, which does help to differentiate.

How To Think About Hidden Keywords

Here’s the best way I can think of to help you determine how to think about these terms, how you might best use them, and where you might source future terms from:

Remember the party game Taboo? You broke into teams and pulled a card with a word or object.

Your goal was to get your partner or team to guess the word without saying it or several other restricted-related terms before time ran out.

If you said a forbidden word, the other team would “buzz” you, and your turn was over.

For example, the main word is “football,” but you can’t say football, touchdown, end zone, pigskin, or NFL – what words would you say to get your team to say “football”? Those would be your hidden keywords.

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Let’s use a product example.

If the item were a Michael Kors shoe, you’d include the brand name, type of shoe, size, and attributes like a color or pattern all in the title.

And if you couldn’t get all that in the title, it should be in the product description, alongside additional details like material type or comfort.

Those details in the title and description are not what you’d want to use for hidden keywords. Instead, you want to use terms that would help someone find your product if they hadn’t searched for what you visibly provided on the page.

You might, in this case, try to use: slip-on evening closed toe under $100.

Amazon Help gives these examples:

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Screenshot from sellercentral.amazon.com, July 2022

But even those examples wouldn’t begin to fill the first search term box of 250 characters. It can be quite difficult to fill each search term slot without resorting to extreme stuffing, especially if you’re manually inputting.

Choosing Hidden Keywords

Choosing hidden keywords is where I see the most cross-over between search on search engines and search on Amazon. What tools can you use on one for the other?

Many blogs recommend the Google Keyword Planner, Keywordtool.io, Ubersuggest, or search query reports from Shopping Campaigns.

I don’t disagree with those suggestions at all – but only for generating ideas or starting points.

The way people search on Amazon and how Amazon surfaces results differ from Google, so the best way to populate and perpetuate this field is using data from Amazon or your own listings whenever possible.

That means a Search Terms Report, a client-provided list, product details, attributes, or features will work best in compliance and upkeep.

Like search keyword lists or text ads, you can’t include inaccurate or misleading information, promotions (like buy one get one), subjective claims, or profanity.

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You use a single space to separate terms and nothing else, which makes the search person in me cringe (I want to add that comma or semicolon so much).

This also means that when you review a bunch of hidden keywords for a product, it looks like a nonsensical line of gobbledygook, even if you follow best practices and use a logical order with your best keywords first.

Also, thanks to the good old “+variants” exercise that Google has put us search folks through, you no longer have that reflex to put in common misspelling, title cases, and pluralization.

The same goes for hidden keywords, making them even more difficult to add, especially by the time you reach search term box four and run out of ideas.

However, one big difference I tend to forget as a search person is that these hidden keywords don’t hold relevancy or scores or rank the same way they do on Google.

That’s why you should change them regularly to keep up with incoming queries and impressions on Amazon.

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This keeps your product pages more likely to be listed on a search results page.

This is particularly true if Amazon is finding some of the terms you submitted as not relevant or not using them. If this is the case, replace them and re-submit.

Adding Hidden Keywords

Now that your hidden keywords are selected, it’s time to add them to your product. Here’s how to do that on a per product basis in the Amazon Seller Central UI.

  1. Log in to Seller Center and click the Inventory tab.
  2. On the right, look for the “edit” button and click it.
  3. You will see the “offer” tab; click on “keywords” to open the hidden keywords section.

This can be time-consuming, but if you have an army of content writers or interns to do it for you, have at it. If not, you may want to brew a new pot of coffee because this could take a while.

You may not like the re-assess and adjustment time, though, especially if you have a catalog size of more than a few hundred products.

You might find it worthwhile to investigate your feed capabilities, whether you’re using a feed tool provider or generating your product feeds in-house and sending them to Amazon.

Dynamic generation possibilities can scale this process for sellers with large catalogs depending on the sophistication level.

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The output would more closely resemble my earlier gobbledygook comment than if a human were to enter them manually, but again, scale.

How To Check If Your Hidden Keywords Got Added

Unfortunately, the only way to check whether your hidden keywords have been added is through random spot checks. And unfortunately, this is a manual process.

Copy the entire string from a search terms box (wait at least 24 hours after submittal before doing this), and search for it on Amazon.

If the product listing that is supposed to be associated with those search terms appears, it’s working. If not, try another group of terms from another search term box and repeat.

But what if the product listing still doesn’t appear? It may be that not all the terms you provided were used (there may have been an editorial or duplicate error), or you need to continue through all five boxes.

I’ve seen cases where only one of the five boxes is picked up, indexed, and used. As you can see, it’s not a great system in terms of being able to track and adjust.

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Fun tidbit: If you remember Yahoo SSP feeds (also known as paid inclusion), this process and indexation may ring a bell. In 2008, you sent content via a feed to supplement Yahoo organic search results meant possibly faster and more frequent information than a crawl.

Final Thoughts On Hidden Keywords

Hopefully, by this point, you’ve developed a working understanding of Amazon’s Hidden Keywords and how to add them on the backend to generate more traffic to your product pages.

Finding the perfect mix for your needs is a bit labor-intensive but is well worth the effort.

Just remember to keep up with it. Keep testing and identifying which keywords are working and which ones aren’t.

Replace the underperformers with new keywords until you find the perfect mix. And then do it all again.

Amazon is an amazing tool for online retailers. And using backend keywords is a great way to ensure you’re receiving the traffic – and making the sales you need.

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How To Use ChatGPT For Keyword Research

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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.

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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.

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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}?

Screenshot from ChatGPT 4, April 2024

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.

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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.

ChatGPT keyword prompt subtopicScreenshot from ChatGPT 4, April 2024

Again, 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}chatgpt keyword research prompt for most popular keywords

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}”

chatgpt keyword research prompt longtail keywordsScreenshot ChatGPT 4,April 2024

List 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!

chatgpt keyword research semantic intentScreenshot ChatGPT 4, April 2024

Tip: 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:

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“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.”

chatgpt for question keyword researchScreenshot ChatGPT 4, April 2024

Generating 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.

Generating Keyword Ideas using ChatGPT Based on the Alphabet Soup MethodScreenshot 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”

ChatGPT Alphabet keyword research methodScreenshot from ChatGPT 4, April 2024

Tip: 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”

ChatGPT and user personasScreenshot from ChatGPT 4, April 2024

You could even go a step further and ask for questions based on those topics that those specific user personas may be searching for:

ChatGPT and keyword research based on personaScreenshot ChatGPT 4, April 2024

As 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”

question and longtail and user persona using a table for ChatGPT keyword researchScreenshot from ChatGPT 4, April 2024

Generating 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.”

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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.

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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].”

Using Chat GPT as a Keyword Categorization ToolScreenshot 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.

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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.

Using Chat GPT For Keyword ClusteringScreenshot 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”

question based keywords keyword research ChatGPTScreenshot ChatGPT 4, April 2024

2. Comparison Patterns

Example:

“Generate 50 keywords for the topic “{Topic}” that contain any or all of the following “for, vs, alternative, best, top, review”

chatgpt comparison patterns for keyword researchScreenshot ChatGPT 4, April 2024

3. 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.

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Example prompt:

“For the top {Topic} brands what are the top “vs” keywords”

ChatGPT brand patterns promptScreenshot ChatGPT 4, April 2024

4. 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”

ChatGPT best based keyword researchScreenshot ChatGPT 4, April 2024

Again, 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.

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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:

ahrefs screenshot for best seoScreenshot 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;

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translating keywords with ChatGPTScreenshot 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.
verifying the data with ahrefsScreenshot from Ahrefs Keyword Explorer, April 2024

But 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.

top keyword from ahrefs keyword explorerScreenshot 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

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.

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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.

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OpenAI Expected to Integrate Real-Time Data In ChatGPT

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OpenAI ChatGPT announcement

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:

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“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.

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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.”

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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.

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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

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Google’s Strategies For Dealing With Content Decay

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Disappointed stressed businessman staring at the stacked paperwork on his desk

In the latest episode of the Search Off The Record podcast, Google Search Relations team members John Mueller and Lizzi Sassman did a deep dive into dealing with “content decay” on websites.

Outdated content is a natural issue all sites face over time, and Google has outlined strategies beyond just deleting old pages.

While removing stale content is sometimes necessary, Google recommends taking an intentional, format-specific approach to tackling content decay.

Archiving vs. Transitional Guides

Google advises against immediately removing content that becomes obsolete, like materials referencing discontinued products or services.

Removing content too soon could confuse readers and lead to a poor experience, Sassman explains:

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“So, if I’m trying to find out like what happened, I almost need that first thing to know. Like, “What happened to you?” And, otherwise, it feels almost like an error. Like, “Did I click a wrong link or they redirect to the wrong thing?””

Sassman says you can avoid confusion by providing transitional “explainer” pages during deprecation periods.

A temporary transition guide informs readers of the outdated content while steering them toward updated resources.

Sassman continues:

“That could be like an intermediary step where maybe you don’t do that forever, but you do it during the transition period where, for like six months, you have them go funnel them to the explanation, and then after that, all right, call it a day. Like enough people know about it. Enough time has passed. We can just redirect right to the thing and people aren’t as confused anymore.”

When To Update Vs. When To Write New Content

For reference guides and content that provide authoritative overviews, Google suggests updating information to maintain accuracy and relevance.

However, for archival purposes, major updates may warrant creating a new piece instead of editing the original.

Sassman explains:

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“I still want to retain the original piece of content as it was, in case we need to look back or refer to it, and to change it or rehabilitate it into a new thing would almost be worth republishing as a new blog post if we had that much additional things to say about it.”

Remove Potentially Harmful Content

Google recommends removing pages in cases where the outdated information is potentially harmful.

Sassman says she arrived at this conclusion when deciding what to do with a guide involving obsolete structured data:

“I think something that we deleted recently was the “How to Structure Data” documentation page, which I thought we should just get rid of it… it almost felt like that’s going to be more confusing to leave it up for a period of time.

And actually it would be negative if people are still adding markup, thinking they’re going to get something. So what we ended up doing was just delete the page and redirect to the changelog entry so that, if people clicked “How To Structure Data” still, if there was a link somewhere, they could still find out what happened to that feature.”

Internal Auditing Processes

To keep your content current, Google advises implementing a system for auditing aging content and flagging it for review.

Sassman says she sets automated alerts for pages that haven’t been checked in set periods:

“Oh, so we have a little robot to come and remind us, “Hey, you should come investigate this documentation page. It’s been x amount of time. Please come and look at it again to make sure that all of your links are still up to date, that it’s still fresh.””

Context Is Key

Google’s tips for dealing with content decay center around understanding the context of outdated materials.

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You want to prevent visitors from stumbling across obsolete pages without clarity.

Additional Google-recommended tactics include:

  • Prominent banners or notices clarifying a page’s dated nature
  • Listing original publish dates
  • Providing inline annotations explaining how older references or screenshots may be obsolete

How This Can Help You

Following Google’s recommendations for tackling content decay can benefit you in several ways:

  • Improved user experience: By providing clear explanations, transition guides, and redirects, you can ensure that visitors don’t encounter confusing or broken pages.
  • Maintained trust and credibility: Removing potentially harmful or inaccurate content and keeping your information up-to-date demonstrates your commitment to providing reliable and trustworthy resources.
  • Better SEO: Regularly auditing and updating your pages can benefit your website’s search rankings and visibility.
  • Archival purposes: By creating new content instead of editing older pieces, you can maintain a historical record of your website’s evolution.
  • Streamlined content management: Implementing internal auditing processes makes it easier to identify and address outdated or problematic pages.

By proactively tackling content decay, you can keep your website a valuable resource, improve SEO, and maintain an organized content library.

Listen to the full episode of Google’s podcast below:


Featured Image: Stokkete/Shutterstock

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