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Is Elon laughing?

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By Vishesh Raisinghani

Is Elon laughing? Reports say Mark Zuckerberg’s ‘Twitter-killer’ just suffered a stunning 50% collapse in daily active users after white-hot start — but here’s why Musk should still worry

Threads seems to be unravelling — for now.

After a record-breaking launch, Mark Zuckerberg’s new app Threads has seen the numbers wane — significantly. Threads attracted over 100 million users within five days of its launch, demolishing ChatGPT’s record of fastest-growing consumer app and earning it the nickname “Twitter killer.”

However, recent data from industry sources suggest many of these users haven’t stayed active on the platform since the white-hot launch.

Engagement settles lower

Active users on the new app declined by 50% from 49 million on July 7th to 23.6 million on July 14th, according to a new report by SimilarWeb. That means only a quarter of the platform comes back to check and interact on the app every day. Even Mark Zuckerberg admitted that the number of people returning to the app is in the “tens of millions.”

This means that the so-called “Twitter killer” still has plenty of work ahead of itself. Twitter is a private company that doesn’t release these numbers publicly, but the latest figures from the company’s last earnings report suggest the daily active user base stood at roughly 238 million. According to Elon Musk, that number has surged to 259.4 million recently.

Effectively, Threads has only 10% of the daily active users of its biggest rival. However, that doesn’t necessarily mean Musk will get the last laugh.

Why Twitter should be worried

There is evidence to suggest that rivals like Threads are seeping users and engagement from the legacy social app. Web traffic to Twitter was down 5% within the first two days of Threads being launched, according to data from SimilarWeb. Although this has recovered a little since then, traffic is still 11% lower year-over-year.

The fact that a rival app captured 10% of the user base within weeks should also be a concern. Zuckerberg has a track record of successfully scaling social media platforms — Facebook, Instagram, and Whatsapp each boasts billions of daily active users.

Elon Musk recently admitted that Twitter’s revenue had dropped 50% while the company was cash flow negative due to a “heavy debt load.” Musk’s decision to scale back content moderation may have scared off advertisers, according to a Bloomberg report. Researchers have seen a significant uptick in hate speech and violent content on the site in recent months.

Billionaire entrepreneur Mark Cuban mocked Musk on Twitter by saying “Go red, no bread,” while retweeting Musk’s announcement about revenue declines.

Cuban has been a vocal critic of Musk’s policies ever since he took over the social media brand last year.

“Who he supports or denigrates is the Twitter equivalent of State intervention. He owns the platform, he can do what he chooses,” he said in a tweet earlier this year. “But it’s disingenuous to say Twitter is the home of free speech when he chooses to often put his thumb on the scale of reach.”

Cuban is an active user of both Threads and Twitter

Feature Image Credit: Frederic Legrand – COMEO/Shutterstock

By Vishesh Raisinghani

Vishesh Raisinghani is a freelance contributor at MoneyWise. He has been writing about financial markets and economics since 2014 – having covered family offices, private equity, real estate, cryptocurrencies, and tech stocks over that period. His work has appeared in Seeking Alpha, Motley Fool Canada, Motley Fool UK, Mergers & Acquisitions, National Post, Financial Post, and Yahoo Canada.

Sourced from moneywise

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Is Your Brand Trusted Significantly More Than ChatGPT?

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By Chad S. White

Brands have two major levers they can pull to protect themselves from the negative effects of growing use of generative AI.

The Gist

  • AI disruption. Generative AI is set to disrupt SEO significantly.
  • Content shielding. Brands need strategies to protect their content from AI.
  • Direct relationships. Building strong direct relationships is key.

Do your customers trust your brand more than ChatGPT?

The answer to that question will determine which brands truly have credibility and authority in the years ahead and which do not.

Those who are more trustworthy than generative AI engines will:

  1. Be destinations for answer-seekers, generating strong direct traffic to their websites and robust app usage.
  2. Be able to build large first-party audiences via email, SMS, push and other channels.

Both of those will be critical for any brand wanting to insulate themselves from the search engine optimization (SEO) traffic loss that will be caused by generative AI.

The Threat to SEO

Despite racking up 100 million users just two months after launching — an all-time record — ChatGPT doesn’t appear to be having a noticeable impact on the many billions of searches that happen every day yet. However, it’s not hard to imagine it and other large language models (LLMs) taking a sizable bite out of search market share as they improve and become more reliable.

And improve they will. After all, Microsoft, Google and others are investing tens of billions of dollars into generative AI engines. Long dominating the search engine market, Google in particular is keenly aware of the enormous risk to its business, which is why it declared a Code Red and marshalled all available resources into AI development.

If you accept that generative AI will improve significantly over the next few years — and probably dramatically by the end of the decade — and therefore consumers will inevitability get more answers to their questions through zero-click engagements, which are already sizable, then it begs the question:

What should brands consider doing to maintain brand visibility and authority, as well as avoid losing value on the investments they’ve made in content?

Protective Measures From Negative Generative AI Effects

Brands have two major levers they can pull to protect themselves from the negative effects of growing use of generative AI.

1. Shielding Content From Generative AI Training

Major legal battles will be fought in the years ahead to clarify what rights copyright holders have in this new age and what still constitutes Fair Use. Content and social media platforms are likely to try to redefine the copyright landscape in their favor, amending their user agreements to give themselves more rights over the content that’s shared on their platforms.

A white robot hand holds a gavel above a sound block sitting on a wooden table.
Andrey Popov on Adobe Stock Photo

You can already see the split in how companies are deciding to proceed. For example, while Getty Images’ is suing Stable Diffusion over copyright violations in training its AI, Shutterstock is instead partnering with OpenAI, having decided that it has the right to sell its contributors’ content as training material to AI engines. Although Shutterstock says it doesn’t need to compensate its contributors, it has created a contributors fund to pay those whose works are used most by AI engines. It is also giving contributors the ability to opt out of having their content used as AI training material.

Since Google was permitted to scan and share copyrighted books without compensating authors, it’s entirely reasonable to assume that generative AI will also be allowed to use copyrighted works without agreements or compensation of copyright holders. So, content providers shouldn’t expect the law to protect them.

Given all of that, brands can protect themselves by:

  • Gating more of their web content, whether that’s behind paywalls, account logins or lead generation forms. Although there are disputes, both search and AI engines shouldn’t be crawling behind paywalls.
  • Releasing some content in password-protected PDFs. While web-hosted PDFs are crawlable, password-protected ones are not. Because consumers aren’t used to frequently encountering password-protected PDFs, some education would be necessary. Moreover, this approach would be most appropriate for your highest-value content.
  • Distributing more content via subscriber-exclusive channels, including email, push and print. Inboxes are considered privacy spaces, so crawling this content is already a no-no. While print publications like books have been scanned in the past by Google and others, smaller publications would likely be safe from scanning efforts.

In addition to those, hopefully brands will gain a noindex equivalent to tell companies not to train their large language models (LLMs) and other AI tools on the content of their webpages.

Of course, while shielding their content from external generative AI engines, brands could also deploy generative AI within their own sites as a way to help visitors and customers find the information they’re looking for. For most brands, this would be a welcome augmentation to their site search functionality.

2. Building Stronger Direct Relationships

While shielding your content is the defensive play, building your first-party audiences is the offensive play. Put another way, now that you’ve kept your valuable content out of the hands of generative AI engines, you need to get it into the hands of your target audience.

You do that by building out your subscription-based channels like email and push. On your email signup forms, highlight the exclusive nature of the content you’ll be sharing. If you’re going to be personalizing the content that you send, highlight that, too.

Brands have the opportunity to both turn their emails into personalized homepages for their subscribers, as well as to turn their subscribers’ inboxes into personalized search engines.

Email Marketing Reinvents Itself Again

Brands already have urgent reasons to build out their first-party audiences. One is the sunsetting of third-party cookies and the need for more customer data. Email marketing and loyalty programs, in particular, along with SMS, are great at collecting both zero-party data through preference centers and progressive profiling, as well as first-party data through channel engagement data.

Another is the increasingly evident dangers of building on the “rented land” of social media. For example, Facebook is slowly declining, Twitter has cut 80% of its staff to avoid bankruptcy as its value plunges, and TikTok faces growing bans around the world. Some are even claiming we’re witnessing the beginning of the end of the age of social media. I wouldn’t go that far, but brands certainly have lots of reasons to focus more on those channels they have much more control over, including the web, loyalty, SMS, and, of course, email.

So, the disruption of search engine optimization by generative AI is just providing another compelling reason to invest more into email programs, or to acquire them. It’s hard not to see this as just another case of email marketing reinventing itself and making itself more relevant to brands yet again.

Feature Image Credit: Andrey Popov on Adobe Stock Photo

By Chad S. White

Chad S. White is the author of four editions of Email Marketing Rules and Head of Research for Oracle Marketing Consulting, a global full-service digital marketing agency inside of Oracle. Connect with Chad S. White:  

Sourced from CMSWIRE

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Diller confirms plans for legal action over AI publishing

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By Miranda Nazzaro

Media titan Barry Diller confirmed Sunday he and a group of “leading publishers” plan to take legal action regarding the use of published works in training artificial intelligence (AI) systems.

Diller, the chairman and senior executive of internet and media conglomerate IAC, said he thinks generative AI is “overhyped, as all revolutions that are in the very beginning,” in an interview Sunday morning with CBS’s Margaret Brennan on “Face the Nation.”

AI systems are trained and improved using large language models, which ingest compilations of written works like books, news stories and social media posts.

Diller said he and others in the publishing industry don’t agree with how AI systems take in publishers’ content.

“It’s not that either Google or Microsoft, who are the two real leaders of this in terms of, certainly Google with having a monopoly on advertising. They, too, want to find a solution for publishers,” Diller told Brennan. “The problem is they also say that the fair use doctrine of copyright law allows them to suck up all this stuff.”

“It is, it will be, long-term catastrophic if there is not a business model that allows people professionally to produce content,” Diller continued. “That would be, I think everybody agrees is catastrophic.”

Diller claimed legislation or litigation is needed to protect the copyright of publishers.

“Of course, say we’re open to commercial agreements. But on the side of those people who are depending upon advertising, Google, for instance, they say, ‘Yes, we’ll give you a revenue share,’” Diller said. “Right now, the revenue share is zero. So, what percent of zero would you like today? I mean that’s rational, but it’s not the point. The only way you get to the point is protect fair use. In other words, protect the copyright.”

Diller would not disclose or confirm who is he planning to launch litigation with, only calling them “leading publishers.”

“It took 15 years to get back paywalls that protected publishers, I don’t think that same thing is going to happen,” Diller said.

When asked if generative AI poses a threat to Hollywood studio workers’ jobs, Diller said, “In this case, I think the one-to-three-year period, not much is going to happen. But post that, there are, of course, all these issues.”

Diller is not the first to consider legal action over AI publishing. Comedian Sarah Silverman and two other authors are currently suing Meta and OpenAI for alleged copyright infringement, claiming the platforms’ AI systems were “knowingly and secretly trained” with unauthorized copies of their books.

The Associated Press announced last week it would license its archive of news stories to ChatGPT maker OpenAI to help train the AI company’s system.

Feature Image Credit: (AP Photo/Kathy Willens)

By Miranda Nazzaro

Sourced from The Hill

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ChatGPT isn’t proving to be the death knell for Alphabet or for search advertising

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By Jon Swartz

Google appears to be in a good position to compete for digital advertising against OpenAI

OpenAI’s ChatGPT loomed over Alphabet Inc.’s Google earlier this year, threatening the search giant’s core business of advertising.

But the menace, which seemed so dire in April, hasn’t materialized. Analysts increasingly believe Google GOOGL, +0.55% GOOG, +0.59% is well-positioned to compete for digital advertising against the initial outsize influence of startup OpenAI and its major investor, Microsoft Corp. MSFT, +0.18%, this year.

“As Google incorporates more [artificial-intelligence and machine-learning] tools … we have not seen any evidence of share shifts to [Microsoft’s] Bing, and in fact see ad budgets shifting back to [Google] Search as indications are that ad spend tailed off after the initial bump at Bing,” Deutsche Bank analyst Benjamin Black said in a note this month.

Black maintains a buy rating on Google shares, with a price target of $125.

Google’s brightened advertising outlook extends to rivals Meta Platforms Inc. META, -0.79%, Pinterest Inc. PINS, -2.00% and Yelp Inc. YELP, +3.02% as ad agencies loosen spending after a cautious start to 2023 because of economic uncertainties, Black said.

Analysts also anticipate Google search resilience despite the Bing threat, and they expect faster YouTube growth following several down quarters, with hopes high around the launch of NFL Sunday Ticket on YouTube TV this year.

Here’s what to expect when Alphabet’s numbers hit after Tuesday’s closing bell.

What to expect

Earnings: Analysts tracked by FactSet expect Alphabet to report $1.34 a share in earnings, up from $1.21 a year before. On Estimize, which crowdsources projections from hedge funds, academics and others, the average projection calls for $1.34 a share in earnings.

Revenue: The FactSet consensus calls for $72.8 billion in total revenue, up from $69.9 billion the previous year. Those contributing to Estimize expect $72.8 billion in revenue. Excluding traffic-acquisition costs, analysts from both FactSet and Estimize forecast $60.25 billion in revenue.

Stock movement: Alphabet shares have gained 36% so far this year. The broader S&P 500 SPX, -0.28% is up 18% in 2023.

Of the 50 analysts tracked by FactSet who cover Alphabet shares, 38 have buy ratings and four have hold ratings, with an average share-price target of $135.94.

What to watch for

Investors are keeping a close eye on Google Cloud, which accounts for a sliver of the company’s overall revenue.

Why? As most enterprises hash out their generative-AI strategies, it’s unclear how much benefit Google Cloud may reap in the second quarter and going forward. A second-half tailwind could offset ongoing cost-optimization headwinds, Jefferies analyst Brent Thill said in a note last week.

Goldman Sachs analyst Eric Sheridan maintained a buy rating on Alphabet shares with a price target of $140. “Broader industry conversations have continued to increase our conviction that [Alphabet] will be a long-term AI winner,” he said in a note last week.

“We think [Alphabet’s] potential for margin outperformance (especially into 2024), YouTube revenue reacceleration [and] sustained cloud computing growth (with improved margins) remain underappreciated,” Sheridan said.

Feature Image Credit: Getty Images

By Jon Swartz

Jon Swartz is a senior reporter for MarketWatch in San Francisco, covering many of the biggest players in tech, including Netflix, Facebook and Google. Jon has covered technology for more than 20 years, and previously worked for Barron’s and USA Today. Follow him on Twitter @jswartz.

Sourced from MarketWatch

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How to Train ChatGPT to Write Like You

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ChatGPT is useful for some tasks, but what if it sounded more like you?

ChatGPT generates remarkably human-like write-ups but lacks something important: a unique personal voice. While ChatGPT can compose thoughtful prose on any topic, the phrasing often rings hollow. To make ChatGPT truly your writing companion, you need to train it to write with your style, pacing, word choices, and tone.

Fortunately, with a few prompting techniques, you can train ChatGPT to adopt a unique writing style that matches yours.

2 Ways to Teach ChatGPT to Write Like You

To get started, we’ll assume the persona of a detail-oriented author who uses a lively, engaging tone, provides detailed, accessible explanations, make liberal use of analogies, and address the reader directly throughout their text. The author also has a knack for using analogies to explain key concepts. Here’s a sample of the author’s work.

The task is to get ChatGPT to adopt the author’s writing style. Here we have three options. We can ask ChatGPT to write in a “detail-oriented, conversational manner using a lively, engaging tone, providing detailed, accessible explanations, making liberal use of analogies, and addressing the reader directly throughout their text”—much like the author. ChatGPT will oblige, but this approach will produce unpredictable results for several reasons. For example, how frequently does the author use analogies in each write-up? How informal does the author get? Does the author use light-hearted humor?

Trying to describe your writing style to ChatGPT will make the instruction way too broad. There are ways too many details that this approach wouldn’t be able to capture, resulting in a style that might not be in tune with that of the author; creating a ChatGPT prompt to deliver this information would be a challenge.

To teach ChatGPT to write like you, you can:

  1. Train ChatGPT with several samples of text you’ve written
  2. Use a Personal Preference Map (PPM)

Both options require a different approach, which you can check out below.

1. Training ChatGPT With Samples of Your Work

To train ChatGPT with samples of your work, head over to ChatGPT and use the prompt below, immediately followed by a sample of your written work that best captures your writing style.

Extract the writing style in the text provided below. Please study the tone, word choice, mannerism, sentence structure, pacing, explanation style, and other stylistic elements in order to mimic this author's unique voice: [Paste the sample here]

After using the prompt above, you should get a result similar to this:

Of course, one sample might not be enough to thoroughly capture every aspect of your writing style. So, you can repeat the prompt above with three to five more samples within the same ChatGPT conversation. After iterating through the number of samples you wish to use, you can then use the prompt below to unify the extracted styles.

Unify all the extracted writing styles and present them in a clear detailed form. 
Use the tone, word choice, sentence structure, pacing, explanations, and other 
stylistic elements you have extracted from the different samples provided to 
mimic this author's unique voice. Your instruction is to write an article 
on the topic: "Topic to write goes here." Maintain the author's perspective 
and attitudes while covering new subject. Write smoothly and convincingly 
in the author's distinctive voice.

The prompt above should immediately apply a combination of all the writing styles extracted from all the samples to write whichever topic you provided in the prompt. It doesn’t have to be an article, it can be an email, a speech, an essay, jokes, or even a song.

When working with normal write-ups like blogs or articles, if you want ChatGPT to stick to the structure and style of a writing sample as much as possible, using one sample (and, to a lesser extent, two samples) seems to be much more effective. To do this, use the prompt below:

Pay attention to the tone, word choice, mannerisms, sentence structure, pacing, explanation style, and other stylistic elements in order to mimic the unique style of the author of the text below. Use the same stylistic elements to write an article on the topic: "Some article topic goes here." [Paste the sample here]

Also, for the best results, we recommend using GPT-4 and, specifically, the GPT-4 Code Interpreter plugin for the task. You’ll be able to work with more text or even, ideally, stack several articles in a text or word file and ask ChatGPT to analyze the content for its writing style.

2. Training ChatGPT Using a Personal Preference Map (PPM)

A Personal Preference Map (PPM) is a key-value list of preferences ChatGPT can use to produce responses that better align with your preference. In this case, ChatGPT can extract a PPM from written samples to learn about your writing preferences and use it to replicate your writing style on demand. If you are unfamiliar with PPM, we’ve discussed it extensively in MakeUseOf’s eBook on Unlocking the Potential of ChatGPT. It is lightweight and easy to read, so do check it out.

To use a PPM, you’ll need to first extract it before using it as a prompt whenever you have something to write. To extract a PPM from samples of your work, use the prompt below:

I want you to extract a Personal Preference Map (PPM) from the data I provide in the next prompt. Now, a PPM is a key => value pair of conditions mapped to preferences. Below are examples of key => value pairs:

Tone => sarcastic, sassy, and loving

Word choice => formal, complex

Sentence structure => mixed of short and long, mostly short

Explanation style => imagery, vivid, relatable

Only reply affirmatively if you understand the task and do nothing else. When I provide the next prompt, extract the PPM using the same logic and formatting used above. The key => value pairs should be separated using “=>” Apart from the tone, word choice, and explanation style, I want you to include 10 other stylistic elements that better capture a writing style.

Using the prompt above on this article about how Auto-GPT is different from ChatGPT, we captured several stylistic elements the author uses in the article.

Extracted PPM using ChatGPT

Although the PPM approach is slightly more complex, it offers enormous attention to detail. While our previous method takes a more generalist approach to describing and applying an author’s style, PPM can get as detailed as possible, far more than anyone can easily discern at first glance.

Another advantage of using a PPM is the flexibility and portability it offers. You can easily tweak the writing style with precision by hanging a few words. You can also use the PPM in a different AI chatbot like Claude AI or Google Bard. We used the PPM above on the Claude AI chatbot and asked it to give it a topic to write. It was able to replicate as many of the stylistic elements used by the target author as possible.

Using ChatGPT PPM on Claude AI chatbot

Make ChatGPT Work for You

The beauty of ChatGPT is its versatility—with the right guidance, the AI chatbot can be taught to write in practically any style you want. If you’re tired of ChatGPT’s soulless writing style, you don’t have to settle for it. ChatGPT can do better than bland, generic outputs. With the right mix of training data, prompts, and feedback, you can transform this AI chatbot into your own writing doppelganger. Go for it.

By Maxwell Timothy

Sourced from MUO

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Is Your Brand Trusted Significantly More Than ChatGPT?

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By Chad S. White

Brands have two major levers they can pull to protect themselves from the negative effects of growing use of generative AI.

The Gist

  • AI disruption. Generative AI is set to disrupt SEO significantly.
  • Content shielding. Brands need strategies to protect their content from AI.
  • Direct relationships. Building strong direct relationships is key.

Do your customers trust your brand more than ChatGPT?

The answer to that question will determine which brands truly have credibility and authority in the years ahead and which do not.

Those who are more trustworthy than generative AI engines will:

  1. Be destinations for answer-seekers, generating strong direct traffic to their websites and robust app usage.
  2. Be able to build large first-party audiences via email, SMS, push and other channels.

Both of those will be critical for any brand wanting to insulate themselves from the search engine optimization (SEO) traffic loss that will be caused by generative AI.

The Threat to SEO

Despite racking up 100 million users just two months after launching — an all-time record — ChatGPT doesn’t appear to be having a noticeable impact on the many billions of searches that happen every day yet. However, it’s not hard to imagine it and other large language models (LLMs) taking a sizable bite out of search market share as they improve and become more reliable.

And improve they will. After all, Microsoft, Google and others are investing tens of billions of dollars into generative AI engines. Long dominating the search engine market, Google in particular is keenly aware of the enormous risk to its business, which is why it declared a Code Red and marshalled all available resources into AI development.

If you accept that generative AI will improve significantly over the next few years — and probably dramatically by the end of the decade — and therefore consumers will inevitability get more answers to their questions through zero-click engagements, which are already sizable, then it begs the question:

What should brands consider doing to maintain brand visibility and authority, as well as avoid losing value on the investments they’ve made in content?

Protective Measures From Negative Generative AI Effects

Brands have two major levers they can pull to protect themselves from the negative effects of growing use of generative AI.

1. Shielding Content From Generative AI Training

Major legal battles will be fought in the years ahead to clarify what rights copyright holders have in this new age and what still constitutes Fair Use. Content and social media platforms are likely to try to redefine the copyright landscape in their favour, amending their user agreements to give themselves more rights over the content that’s shared on their platforms.

A white robot hand holds a gavel above a sound block sitting on a wooden table.
Andrey Popov on Adobe Stock Photo

You can already see the split in how companies are deciding to proceed. For example, while Getty Images’ is suing Stable Diffusion over copyright violations in training its AI, Shutterstock is instead partnering with OpenAI, having decided that it has the right to sell its contributors’ content as training material to AI engines. Although Shutterstock says it doesn’t need to compensate its contributors, it has created a contributors fund to pay those whose works are used most by AI engines. It is also giving contributors the ability to opt out of having their content used as AI training material.

Since Google was permitted to scan and share copyrighted books without compensating authors, it’s entirely reasonable to assume that generative AI will also be allowed to use copyrighted works without agreements or compensation of copyright holders. So, content providers shouldn’t expect the law to protect them.

Given all of that, brands can protect themselves by:

  • Gating more of their web content, whether that’s behind paywalls, account logins or lead generation forms. Although there are disputes, both search and AI engines shouldn’t be crawling behind paywalls.
  • Releasing some content in password-protected PDFs. While web-hosted PDFs are crawlable, password-protected ones are not. Because consumers aren’t used to frequently encountering password-protected PDFs, some education would be necessary. Moreover, this approach would be most appropriate for your highest-value content.
  • Distributing more content via subscriber-exclusive channels, including email, push and print. Inboxes are considered privacy spaces, so crawling this content is already a no-no. While print publications like books have been scanned in the past by Google and others, smaller publications would likely be safe from scanning efforts.

In addition to those, hopefully brands will gain a noindex equivalent to tell companies not to train their large language models (LLMs) and other AI tools on the content of their webpages.

Of course, while shielding their content from external generative AI engines, brands could also deploy generative AI within their own sites as a way to help visitors and customers find the information they’re looking for. For most brands, this would be a welcome augmentation to their site search functionality.

2. Building Stronger Direct Relationships

While shielding your content is the defensive play, building your first-party audiences is the offensive play. Put another way, now that you’ve kept your valuable content out of the hands of generative AI engines, you need to get it into the hands of your target audience.

You do that by building out your subscription-based channels like email and push. On your email signup forms, highlight the exclusive nature of the content you’ll be sharing. If you’re going to be personalizing the content that you send, highlight that, too.

Brands have the opportunity to both turn their emails into personalized homepages for their subscribers, as well as to turn their subscribers’ inboxes into personalized search engines.

Email Marketing Reinvents Itself Again

Brands already have urgent reasons to build out their first-party audiences. One is the sunsetting of third-party cookies and the need for more customer data. Email marketing and loyalty programs, in particular, along with SMS, are great at collecting both zero-party data through preference centers and progressive profiling, as well as first-party data through channel engagement data.

Another is the increasingly evident dangers of building on the “rented land” of social media. For example, Facebook is slowly declining, Twitter has cut 80% of its staff to avoid bankruptcy as its value plunges, and TikTok faces growing bans around the world. Some are even claiming we’re witnessing the beginning of the end of the age of social media. I wouldn’t go that far, but brands certainly have lots of reasons to focus more on those channels they have much more control over, including the web, loyalty, SMS, and, of course, email.

So, the disruption of search engine optimization by generative AI is just providing another compelling reason to invest more into email programs, or to acquire them. It’s hard not to see this as just another case of email marketing reinventing itself and making itself more relevant to brands yet again.

By Chad S. White

Chad S. White is the author of four editions of Email Marketing Rules and Head of Research for Oracle Marketing Consulting, a global full-service digital marketing agency inside of Oracle.

Sourced from CMSWIRE

chatgpt,  digital experience, search, email marketing, artificial intelligence, generative ai, artificial intelligence in marketing

 

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Can ChatGPT Actually Make You Rich?

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By Shyam Nandan Upadhyay

ChatGPT can enhance your abilities 10 times, but not if you’re a 0, because 10×0 amounts to 0

‘Get richer with ChatGPT’, ‘Making money online got easier’, ‘How you can make money with ChatGPT’, ‘Access my database of 125+ ChatGPT prompts to help you make money online for $5’.

Wait, stop, calm down!

So, if you’re fed up with all these paid advertisements trying to push different courses down your throats, luring you to make ‘easy’ money using ChatGPT, welcome to the club! Search engines and social media platforms like Instagram, Twitter, Facebook and even LinkedIn are brimming with such posts. These ‘influencers’ make ChatGPT seem like an easy money-minting machine.

But have people actually been able to monetise ChatGPT and its free version? Well, a lot of individuals claim to have been leveraging its capabilities to generate income. From branding to app-creation to providing writing services, they claim it opens avenues to earn ‘free money’ whether you’re an aspiring entrepreneur, content creator, or a freelancer.

You must’ve also come across tons of articles listing numerous ways to rake in the greens. These articles usually either bank on the chatbot’s capabilities to code and hint at it being used to build apps or websites ‘without any prior knowledge’ or for affiliate marketing, content marketing, optimising video production, or becoming a prompting expert amongst many other things.

However, there are some who claim to have made money this way. Ukrainian entrepreneur Ihor Stefurak built a Chrome extension using ChatGPT despite having zero coding knowledge. He claims to have generated $1000 in revenue within just 24 hours of launching the extension.

Many such claims and tutorials are flying fast and thick on YouTube, claiming to help make $100 a day but seem to know nothing about the tool, the model it is based on or even its name. Some coolly call it ChatGTP!

Meanwhile, there has also been a notable surge in AI-written ebooks on Amazon. These are ranked as high as 50,377 on the Kindle book store and also have five-star ratings in the hundreds. According to reports, as of mid-February there were over 200 e-books in Amazon’s Kindle store, listing ChatGPT as the author or co-author. The number may not seem like a lot but the actual number may be much higher since many authors do not disclose in the Kindle store that their book was written entirely, or in part, by a computer because Amazon’s policies do not require it.

In fact, the market is so saturated that making decent money out of this is improbable. According to Reuters, Brett Schickler, who wrote a children’s book titled, ‘The Wise Little Squirrel: A Tale of Saving and Investing’, (sold at the Amazon Kindle store for $2.99 and $9.99 for a printed version) netted less than $100.

Can Only Enhance 

The reality is that ChatGPT alone cannot guarantee financial success. While ChatGPT can be an invaluable tool in reducing your workload, it is crucial to understand that it is not a magical solution that will automatically generate top-tier content for you. If you lack familiarity with a particular subject, you will struggle to differentiate between good and poor quality content.

For example, let’s consider a scenario where you follow someone’s advice on starting a successful blogging business with the assistance of ChatGPT despite having no prior experience in content creation. Even if ChatGPT generates a basic piece of content, you might perceive it as exceptional because you lack the knowledge of what constitutes top-tier content.

What you can actually do is create videos on how to make money with AI. As they say, ‘When there’s a gold rush, sell shovels and pickaxes’.

On a serious note, what you can actually do is automate parts of your workflow with ChatGPT APIs, which are free to use. One can take up email affiliate marketing, content marketing, or learn and preach better avenues like prompt engineering.

It is crucial not to be deceived by influencers who disseminate misleading content. Do not believe them when they claim that ChatGPT holds the secret to success or that it can effortlessly make you money. Instead, focus on learning and honing your skills, utilising ChatGPT as a tool to support you in accomplishing your goals.

By Shyam Nandan Upadhyay

Shyam is a tech journalist with expertise in policy and politics, and exhibits a fervent interest in scrutinising the convergence of AI and analytics in society. In his leisure time, he indulges in anime binges and mountain hikes.

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ChatGPT and the Art of Affiliate Marketing: Expert Tips for Maximizing Conversions

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Let’s dive in and discover how ChatGPT can empower your affiliate marketing journey and help you achieve remarkable results

In the world of affiliate marketing, conversions are the lifeblood of success. As an affiliate marketer, your ultimate goal is to drive users to take action, whether it’s making a purchase, signing up for a service, or clicking on an affiliate link. To achieve this, you need effective strategies that engage your audience and maximize conversions.

One powerful tool that has revolutionized the way affiliate marketers engage with their audience is ChatGPT, an AI-powered language model. ChatGPT allows marketers to create dynamic and interactive chat experiences that address user queries, provide personalized recommendations, and guide potential customers along their buyer’s journey. By integrating ChatGPT into affiliate marketing strategies, marketers can optimize conversions and unlock new possibilities. So, let’s dive in and discover how ChatGPT can empower your affiliate marketing journey and help you achieve remarkable results.

Personalized Recommendations

Personalized product recommendations are one way in which incorporating ChatGPT into your affiliate marketing approach may benefit you and your audience. Using ChatGPT’s AI features, you may examine a user’s data, preferences, interests, and browsing history to produce recommendations that meet their unique requirements.

According to Jitendra Vaswani, you may leverage information from user registration forms, surveys, and other channels to provide personalized recommendations using ChatGPT. This can include your age, gender, location, interests, income, and online shopping behaviours. ChatGPT can then generate customized product recommendations based on the information provided.

Create Conversational Experiences

Conventional advertising methods typically include broadcasting information to consumers without soliciting their feedback. But with ChatGPT’s help, you can have lively chats that feel genuine to your users. By integrating ChatGPT into your affiliate marketing plan, you can give your customers a more personal and engaging experience.

There are many benefits to affiliate marketing conversations that can help increase conversions. Users are encouraged to join the conversation rather than receive information, making for a more exciting and involved experience. When users are actively involved in the process, retention rates, user satisfaction, and conversion rates all rise. When designing conversational experiences with ChatGPT, consider the following techniques:

  • Prompt Engagement: Use open-ended questions, quizzes, or prompts to encourage users to participate in the conversation actively. You create a sense of involvement and investment by asking for their opinions, preferences, or experiences.
  • Address User Queries: Incorporate ChatGPT to address user queries in real-time. According to Rand Fishkin, Co-founder of Moz: “ChatGPT empowers you to provide immediate answers to user questions, overcome objections, and guide potential customers towards making a purchase. You establish trust and demonstrate your commitment to excellent customer service by providing immediate responses to their questions or concerns. This level of responsiveness and support can significantly improve conversion rates in affiliate marketing.”
  • Guide Through Decision-Making: Use conversational experiences to guide users through decision-making. Ask probing questions, offer comparisons, and provide helpful insights that help them make informed choices.
  • Personalize Interactions: Tailor the conversational experiences to the individual user by using their name or referencing their past interactions. Personalization creates a sense of connection and familiarity, leading to higher engagement and conversions.
  • Use Multimedia Elements: Enhance conversational experiences by incorporating multimedia elements such as images, videos, or GIFs. Visual and auditory stimuli can capture attention, convey information more effectively, and evoke emotional responses.
  • Storytelling Approach: Frame the conversation as a narrative or story that unfolds gradually. This approach captivates users’ attention, keeps them engaged, and creates a compelling journey toward conversion.
  • Call-to-Action Prompts: Strategically place call-to-action prompts within the conversation to guide users toward the desired action. Well-timed prompts can nudge users to purchase, subscribe to a service, or explore further.

Creating conversational experiences with ChatGPT transforms the traditional marketing approach into an interactive dialogue. Users feel more connected to your brand as they actively participate and engage with your content. This heightened engagement increases their likelihood of taking the desired action and ultimately boosts conversion rates. Experiment with different conversational styles, analyse user responses, and iterate to optimize conversational experiences over time.

Guide Users Through the Buyer’s Journey

To maximize conversions in affiliate marketing, it’s crucial to guide users effectively throughout their buyer’s journey. By implementing ChatGPT at various touch points along this journey, you can provide valuable assistance, address concerns, and ultimately nurture users toward making a purchasing decision.

  • Initial Research: At the beginning of the buyer’s journey, users are typically in the research phase, seeking information and exploring their options. Implement ChatGPT-powered chatbots on your website or landing pages to engage with users, answer their queries, and provide relevant information about the products or services you’re promoting. By assisting users during this crucial stage, you establish credibility, build trust, and position yourself as a helpful resource.
  • Comparison and Consideration:  As users progress along the buyer’s journey, they begin comparing and considering different options. According to Jitendra Vaswani, a renowned affiliate and SEO expert,” ChatGPT can assist by offering side-by-side comparisons, highlighting the products’ or services’ unique selling points, and addressing specific concerns or questions. This personalized guidance helps users make informed decisions and increases the likelihood of conversion.”
  • Decision-Making:  When users are on the verge of making a purchase, they often have final questions or may need reassurance. ChatGPT-powered chatbots can provide that extra level of support and encouragement. They can highlight customer testimonials, offer limited-time promotions, or address last-minute hesitations. By providing this personalized support, you instil confidence in users and help them finalize their decision.
  • Post-Purchase Support: ChatGPT can continue to play a role even after the purchase is made. Use chatbots to offer post-purchase support, such as order tracking, product usage tips, or troubleshooting assistance. Providing a seamless post-purchase experience enhances customer satisfaction, encourages repeat purchases, and potentially generates positive word-of-mouth referrals.

Remember, the goal is to make the buyer’s journey as smooth and seamless as possible, providing users with the necessary information and support at each stage. By guiding users effectively with the help of ChatGPT, you can create a positive user experience that leads to higher conversion rates and long-term success in affiliate marketing.

Measure and Analyse Performance
To maximize conversions in affiliate marketing, measuring and analysing the performance of your ChatGPT-powered strategies is essential. Set clear objectives, track engagement metrics, monitor conversion and click-through rates, and utilize A/B testing to identify practical elements. Analyse user feedback, integrate with analytics tools, and continuously refine and optimize your approach based on the insights gained. You can optimize your affiliate marketing efforts by leveraging data-driven decision-making and driving better results.

Wrapping Up

To sum up, maximizing conversions with ChatGPT and affiliate marketing can be a game-changer for your business. To achieve this, you should choose the right platform, create an engaging chatbot, use targeted messaging, optimize your affiliate marketing strategy, and leverage customer feedback. Remember to test and tweak your approach for maximum results continually. Overall, it’s important to remember that maximizing conversions takes time and effort, but the results are well worth it. Using these tips and taking action will make you one step closer to achieving your business goals. Best of luck!

Disclaimer: This article is a paid publication and does not have journalistic/editorial involvement of Hindustan Times. Hindustan Times does not endorse/subscribe to the content(s) of the article/advertisement and/or view(s) expressed herein. Hindustan Times shall not in any manner, be responsible and/or liable in any manner whatsoever for all that is stated in the article and/or also with regard to the view(s), opinion(s), announcement(s), declaration(s), affirmation(s) etc., stated/featured in the same.

Feature Image Credit: Jitendra Vaswani, Founder, Bloggers Ideas

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20 of the best free AI and ChatGPT courses available this week

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By Joseph Green

Find free courses from the likes of MIT, Google, and IBM.

TL;DR: A wide range of AI and ChatGPT(opens in a new tab) courses are available for free on edX. Enroll in the best courses from the likes of Google, IBM, and Harvard, without spending anything.

Artificial intelligence and chatbots like ChatGPT are not going anywhere, so maybe it’s time to learn something about this technology? The time is now.

edX offers online courses from the likes of MIT, Google, IBM, and Harvard. And better yet, some of the best online courses are even available for free. We’ve checked out everything on offer from edX, and lined up a selection of standout AI and ChatGPT courses that you can take for free.

These are the best free AI and ChatGPT courses as of July 18:

These courses are completely free, but you can receive a verified certificate of completion for a small fee. There’s no pressure to upgrade, but it might be nice to stick something on your CV.

All products featured here are independently selected by our editors and writers. If you buy something through links on our site, Mashable may earn an affiliate commission.

Feature Image Credit: Pexels

By Joseph Green

Joseph joined Mashable as the UK Shopping Editor in 2018. He worked for a number of print publications before making the switch to the glittery world of digital media, and now writes about everything from coffee machines to VPNs.

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Is Your Brand Trusted Significantly More Than ChatGPT?

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By Chad S. White
Brands have two major levers they can pull to protect themselves from the negative effects of growing use of generative AI.

The Gist

  • AI disruption. Generative AI is set to disrupt SEO significantly.
  • Content shielding. Brands need strategies to protect their content from AI.
  • Direct relationships. Building strong direct relationships is key.

Do your customers trust your brand more than ChatGPT?

The answer to that question will determine which brands truly have credibility and authority in the years ahead and which do not.

Those who are more trustworthy than generative AI engines will:

  1. Be destinations for answer-seekers, generating strong direct traffic to their websites and robust app usage.
  2. Be able to build large first-party audiences via email, SMS, push and other channels.

Both of those will be critical for any brand wanting to insulate themselves from the search engine optimization (SEO) traffic loss that will be caused by generative AI.

The Threat to SEO

Despite racking up 100 million users just two months after launching — an all-time record — ChatGPT doesn’t appear to be having a noticeable impact on the many billions of searches that happen every day yet. However, it’s not hard to imagine it and other large language models (LLMs) taking a sizable bite out of search market share as they improve and become more reliable.

And improve they will. After all, Microsoft, Google and others are investing tens of billions of dollars into generative AI engines. Long dominating the search engine market, Google in particular is keenly aware of the enormous risk to its business, which is why it declared a Code Red and marshalled all available resources into AI development.

If you accept that generative AI will improve significantly over the next few years — and probably dramatically by the end of the decade — and therefore consumers will inevitability get more answers to their questions through zero-click engagements, which are already sizable, then it begs the question:

What should brands consider doing to maintain brand visibility and authority, as well as avoid losing value on the investments they’ve made in content?

Protective Measures From Negative Generative AI Effects

Brands have two major levers they can pull to protect themselves from the negative effects of growing use of generative AI.

1. Shielding Content From Generative AI Training

Major legal battles will be fought in the years ahead to clarify what rights copyright holders have in this new age and what still constitutes Fair Use. Content and social media platforms are likely to try to redefine the copyright landscape in their favour, amending their user agreements to give themselves more rights over the content that’s shared on their platforms.

A white robot hand holds a gavel above a sound block sitting on a wooden table.
Andrey Popov on Adobe Stock Photo

You can already see the split in how companies are deciding to proceed. For example, while Getty Images’ is suing Stable Diffusion over copyright violations in training its AI, Shutterstock is instead partnering with OpenAI, having decided that it has the right to sell its contributors’ content as training material to AI engines. Although Shutterstock says it doesn’t need to compensate its contributors, it has created a contributors fund to pay those whose works are used most by AI engines. It is also giving contributors the ability to opt out of having their content used as AI training material.

Since Google was permitted to scan and share copyrighted books without compensating authors, it’s entirely reasonable to assume that generative AI will also be allowed to use copyrighted works without agreements or compensation of copyright holders. So, content providers shouldn’t expect the law to protect them.

Given all of that, brands can protect themselves by:

  • Gating more of their web content, whether that’s behind paywalls, account logins or lead generation forms. Although there are disputes, both search and AI engines shouldn’t be crawling behind paywalls.
  • Releasing some content in password-protected PDFs. While web-hosted PDFs are crawlable, password-protected ones are not. Because consumers aren’t used to frequently encountering password-protected PDFs, some education would be necessary. Moreover, this approach would be most appropriate for your highest-value content.
  • Distributing more content via subscriber-exclusive channels, including email, push and print. Inboxes are considered privacy spaces, so crawling this content is already a no-no. While print publications like books have been scanned in the past by Google and others, smaller publications would likely be safe from scanning efforts.

In addition to those, hopefully brands will gain a noindex equivalent to tell companies not to train their large language models (LLMs) and other AI tools on the content of their webpages.

Of course, while shielding their content from external generative AI engines, brands could also deploy generative AI within their own sites as a way to help visitors and customers find the information they’re looking for. For most brands, this would be a welcome augmentation to their site search functionality.

2. Building Stronger Direct Relationships

While shielding your content is the defensive play, building your first-party audiences is the offensive play. Put another way, now that you’ve kept your valuable content out of the hands of generative AI engines, you need to get it into the hands of your target audience.

You do that by building out your subscription-based channels like email and push. On your email signup forms, highlight the exclusive nature of the content you’ll be sharing. If you’re going to be personalizing the content that you send, highlight that, too.

Brands have the opportunity to both turn their emails into personalized homepages for their subscribers, as well as to turn their subscribers’ inboxes into personalized search engines.

Email Marketing Reinvents Itself Again

Brands already have urgent reasons to build out their first-party audiences. One is the sunsetting of third-party cookies and the need for more customer data. Email marketing and loyalty programs, in particular, along with SMS, are great at collecting both zero-party data through preference centers and progressive profiling, as well as first-party data through channel engagement data.

Another is the increasingly evident dangers of building on the “rented land” of social media. For example, Facebook is slowly declining, Twitter has cut 80% of its staff to avoid bankruptcy as its value plunges, and TikTok faces growing bans around the world. Some are even claiming we’re witnessing the beginning of the end of the age of social media. I wouldn’t go that far, but brands certainly have lots of reasons to focus more on those channels they have much more control over, including the web, loyalty, SMS, and, of course, email.

So, the disruption of search engine optimization by generative AI is just providing another compelling reason to invest more into email programs, or to acquire them. It’s hard not to see this as just another case of email marketing reinventing itself and making itself more relevant to brands yet again.

Feature Image Credit: Andrey Popov on Adobe Stock Photo

By Chad S. White

Chad S. White is the author of four editions of Email Marketing Rules and Head of Research for Oracle Marketing Consulting, a global full-service digital marketing agency inside of Oracle. Connect with Chad S. White:  

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