MARKETING
Unleashing the Power of AI
Artificial Intelligence seems to be everywhere we look – from streaming services to self-driving cars and virtual assistants — it’s the talk of the town!
But what exactly is AI? And how can it benefit businesses and their customers?
Let’s take a closer look at artificial intelligence meaning, its rise in popularity, and the advantages and disadvantages of artificial intelligence to determine if incorporating this innovative tool is right for you.
What Is Artificial Intelligence?
Simply put, Artificial intelligence, or AI, is a form of computer programming which enables machines to “think” like humans. This intelligence can be used to process data, solve problems, and make decisions automatically.
AI uses algorithms that analyze and interpret large amounts of data from various sources, allowing it to learn from past experiences to make future decisions.
Although still in its early stages, the potential benefits of AI are vast, from streamlining businesses to improving healthcare outcomes. It’s exciting to see how this technology is changing the world and how we can harness its power for the greater good.
Popular AI Use Cases
Artificial intelligence use cases are vast, ranging from healthcare and finance to transportation and security.
You must have seen AI-powered chatbots being used for customer service inquiries. These are very popular on ecommerce websites and offer a personalized shopping & browsing experience.
Artificial intelligence is also being used to improve facial recognition software in security applications, as well as for automating predictive analytics in finance and banking.
Not to forget, the healthcare industry is rapidly adopting AI technology to reduce costs, improve diagnosis and treatment accuracy, and provide better health services to patients.
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And, we are sure, you must be familiar with Apple’s Siri, Amazon’s Alexa, and Google assistant – they’re all powered by AI!
Now that you understand the term artificial intelligence and its applications let’s look at the pros and cons of AI.
What Are The Advantages & Disadvantages Of AI?
Any technological advancement has its pros and cons, and AI is no exception. While it has a huge positive potential to revolutionize the world, some serious drawbacks must be considered before investing in AI technology.
Let’s study some advantages of artificial intelligence and its possible downsides as well.
Artificial Intelligence Advantages
- Minimum-to-No Errors
One of the key benefits of AI-driven systems is their extreme accuracy and reliability.
Unlike us humans, machines do not make mistakes simply due to fatigue, distractions, or emotional biases. Thus, they can perform tasks with unmatched precision and consistency.
This is the differentiator in industries where human error can be costly, such as healthcare, finance, space exploration, etc.
- Increased Productivity
People are amazing; human intelligence, grit, and work ethic can do magic when used to their full potential.
But human resources have limitations. Our attention and focus span often decrease with time, resulting in lower productivity levels.
Sitting too long in front of a screen can make us tired and sloppy. Even if we start the day fresh, we might have something else on our minds, like a breakup or a sports team losing. It’s “natural” but that’s the thing.
Unlike humans, computers and programs don’t get tired – AI can work round the clock with the same levels of energy and enthusiasm, boosting business productivity.
- Improved Decision-Making
AI-driven decision-making is fast, unbiased, and driven purely by data. No personal opinions or judgments are considered when making decisions, thus eliminating any potential bias.
This is particularly advantageous when decisions are difficult and can be adversely affected by emotions or personal opinions – legal, political, and financial matters, for example.
- Enhanced Automation
AI-driven systems can take over mundane, repetitive tasks to free up human resources for more creative, innovative tasks.
This helps streamline the process and makes it easier to manage large volumes of data with minimum human intervention.
In email campaigns, for example, AI can take over the task of sending out 2-3 emails a week. This frees up time and resources for more creative content and allows marketers to tailor their emails to different target audiences better.
- Increased Accessibility And Availability
A human being will always need time off. Whether it’s for vacation, health reasons, or fulfilling a family commitment, we humans need to take a break.
AI-driven technologies, on the other hand, are available 24/7. They don’t get sick, don’t need breaks, and can be accessed from anywhere in the world.
This better accessibility and 24/7 uptime make artificial intelligence a great tool for businesses, especially to perform repetitive jobs. Why? They keep doing the same task with the same precision, accuracy, and quality without getting fatigued, over and over again.
- Cost Efficient
AI-driven systems are cost-efficient in the long run.
While an initial investment is required for setting up such a system, the ROI is higher in the long run since AI-driven systems require no additional labor costs or salaries.
They also do not need to be trained or upgraded regularly, meaning the cost of maintenance is quite low.
Therefore, when used correctly and efficiently, AI-driven systems can help businesses reduce costs while also improving productivity.
- Countless Applications
While human beings can wear multiple hats to do different jobs, AI robots can do infinitely more.
From facial recognition and natural language processing to motion tracking and computer vision, the possibilities are endless with AI.
Similarly, machine learning algorithms can be used for predictive analytics, allowing businesses to identify potential opportunities and risks before they happen. AI-driven systems can also help in identifying customer preferences and predicting customer behavior.
- Improved Security
AI-driven systems offer enhanced security and better protection of sensitive customer data.
AI-driven authentication mechanisms can identify malicious users who are trying to gain unauthorized access to data and systems.
AI-driven systems can also monitor user activity in real time, detect anomalies, and alert administrators to potential threats.
These technologies are essential in today’s digital world, where cyber security is paramount.
AI-driven systems are also much more efficient at detecting and blocking fraud, thus keeping businesses safe from potential financial losses.
Artificial Intelligence Disadvantages
Despite all the advantages of artificial intelligence, it comes with some drawbacks. Let’s look at a few artificial intelligence disadvantages.
- Lack Of Emotion & Critical Thinking
AI-driven systems lack the ability to understand human emotions and empathize with people.
This means that AI-driven systems are not equipped to respond to emotional cues and cannot provide the same level of customer service as a human being.
Also, AI-driven systems cannot think critically and make decisions based on emotions. This can be a major limitation when providing customer service or making complex decisions.
- Unpredictable Behavior
AI-driven systems can perform complex tasks and make decisions quickly, but they are not infallible.
AI-driven systems can face unforeseen errors and exhibit unpredictable behavior in certain situations.
This means there is a lack of control over the system, which can lead to undesirable outcomes.
- Job Losses
The increased use of AI-driven technologies could lead to job losses as machines take over human labor.
This could significantly impact the economy, leading to a reduction in purchasing power and an increase in unemployment.
Therefore, AI-driven technologies must be used responsibly, and their impact on the job market should be considered carefully.
- Ethical Issues
The increased use of AI-driven technologies has also raised ethical concerns, as they can be used to manipulate data, influence public opinion, and even control people’s behavior.
The potential for misuse of AI-driven technologies is real, meaning governments and businesses need to be aware of the ethical implications of using these technologies.
- High Cost
The cost of developing and deploying AI-driven technologies can be quite high, making them inaccessible to large businesses and highly advanced organizations.
Therefore, it is important for businesses to consider the cost implications before investing in advanced AI-based technologies.
Overall, artificial intelligence offers numerous benefits like digital assistance, high productivity & efficiency, improved security, and more.
However, artificial intelligence disadvantages like lack of empathy and unpredictable behavior mean it can’t imitate the human brain.
The ethical issues and high implementation costs also signify that AI can’t entirely replace human resources.
Should You Adopt Artificial Intelligence?
Being diplomatic, we’d say: “only you can decide if AI is the right choice for your business” or “you have to weigh the pros and cons of AI” — that’s nonsense!
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The truth is that AI offers excellent potential for businesses of all sizes, and it’s becoming a requirement to stay relevant in today’s tech-driven world.
Businesses and individuals that know how to leverage AI-driven technologies can see improved efficiency, cost savings, and a competitive edge over their peers.
So, yes, you should definitely consider adopting AI-driven technologies for your business. The long-term benefits could far outweigh the risks that come with it.
Strategically Integrate Artificial Intelligence For Maximum Benefits
While AI has many advantages, it should be approached with caution.
Incorporating artificial intelligence without a proper plan or human oversight can lead to vulnerabilities. For instance, uploading content without fact-checking could risk a decline in your reputation or visibility on platforms like Google.
Moreover, while isolated AI projects may bring success, you need to ensure scalability and plan for the long term to maintain your success.
Comprehensive planning, fact-checking, and human oversight are essential to ensure that the AI-driven technologies you adopt actually deliver tangible benefits.
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MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
Introduction
With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.
Types of YouTube Ads
Video Ads
- Description: These play before, during, or after a YouTube video on computers or mobile devices.
- Types:
- In-stream ads: Can be skippable or non-skippable.
- Bumper ads: Non-skippable, short ads that play before, during, or after a video.
Display Ads
- Description: These appear in different spots on YouTube and usually use text or static images.
- Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).
Companion Banners
- Description: Appears to the right of the YouTube player on desktop.
- Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.
In-feed Ads
- Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.
Outstream Ads
- Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.
Masthead Ads
- Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.
YouTube Ad Specs by Type
Skippable In-stream Video Ads
- Placement: Before, during, or after a YouTube video.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Action: 15-20 seconds
Non-skippable In-stream Video Ads
- Description: Must be watched completely before the main video.
- Length: 15 seconds (or 20 seconds in certain markets).
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Vertical: 9:16
- Square: 1:1
Bumper Ads
- Length: Maximum 6 seconds.
- File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
- Resolution:
- Horizontal: 640 x 360px
- Vertical: 480 x 360px
In-feed Ads
- Description: Show alongside YouTube content, like search results or the Home feed.
- Resolution:
- Horizontal: 1920 x 1080px
- Vertical: 1080 x 1920px
- Square: 1080 x 1080px
- Aspect Ratio:
- Horizontal: 16:9
- Square: 1:1
- Length:
- Awareness: 15-20 seconds
- Consideration: 2-3 minutes
- Headline/Description:
- Headline: Up to 2 lines, 40 characters per line
- Description: Up to 2 lines, 35 characters per line
Display Ads
- Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
- Image Size: 300×60 pixels.
- File Type: GIF, JPG, PNG.
- File Size: Max 150KB.
- Max Animation Length: 30 seconds.
Outstream Ads
- Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
- Logo Specs:
- Square: 1:1 (200 x 200px).
- File Type: JPG, GIF, PNG.
- Max Size: 200KB.
Masthead Ads
- Description: High-visibility ads at the top of the YouTube homepage.
- Resolution: 1920 x 1080 or higher.
- File Type: JPG or PNG (without transparency).
Conclusion
YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
A deeper dive into data, personalization and Copilots
Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.
To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.
Dig deeper: Salesforce piles on the Einstein Copilots
Salesforce’s evolving architecture
It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?
“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”
Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”
That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.
“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.
Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”
Let’s learn more about Einstein Copilot
“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.
For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”
Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”
It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”
What’s new about Einstein Personalization
Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?
“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”
Finally, trust
One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.
“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”
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