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LinkedIn & AI: How They Team Up & Why It’s Important

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LinkedIn & AI: How They Team Up & Why It's Important

Another day, another article, you might think, from some “random” on the internet preaching about
marketing and artificial intelligence. But I’m not here to give you fluff and generic knowledge about what
you could easily Google online. 

Hi, I’m Joshua B. Lee, and you might know me as the “Dopamine Dealer on LinkedIn”. In the past 2 decades, I’ve built 16 businesses, authored a book called Balance is Bullsh*t, and I’ve had clients like MySpace and Google managing nearly a billion dollars in advertising spends.

While working with companies that are larger than life, I realized one thing: The digital landscape became
quite “noisy”. AKA, there were too many automated things, robotic language, and SELL SELL SELL energies online, and the human touch got lost in the mix.

TL;DR: Human connection was obliterated, and too many people focused a lot on monetization for profit’s sake. I’m a consumer myself, so I saw a gap that could be fixed and asked, “How can I bring back the heart in this digital universe? How can I help people see beyond the screen and build genuine
connections?” 

Enter → Standout Authority, my baby since 2014. We’re all about helping folks (like you, who’s reading
this) bring the human back to your brand.

And we’ve chosen to zero in on LinkedIn—the Avengers’ HQ of business platforms—to build authentic
relationships and clients.

Why LinkedIn?

Perhaps this number will sum it up for you: as of April 2023, LinkedIn has 922.3 million active members
on the platform.

So if you’re looking for the perfect place for marketing, networking, and reaching your audience as a thought leader in your field, this would be THE platform for you.

And as LinkedIn turns 20 this year, it’s making a huge push towards AI—quite the HOT topic everywhere,
regardless of the niche/industry.

Here’s what’s coming to a LinkedIn profile you want to get going:

LinkedIn’s Drive to Embrace AI and Transform Content Creation 

LinkedIn continues to push the boundaries of AI-powered transformation, making your content creation
more engaging, entertaining, and downright amazing.

Here are some of the bold moves LinkedIn has been making towards AI: 

  • Ever since LinkedIn joined forces with the latest AI technology, ChatGPT, the platform has been on a roll (If you didn’t know yet, Microsoft invested $10 billion into OpenAI).
  • Since then, they’ve released a series of helpful tools such as “Smart Replies” and “Resume Assistant”— just a couple of examples of how LinkedIn has harnessed the power of AI to streamline your messaging and job-hunting experience.  
  • LinkedIn has created Collaborative Articles, a feature that allows multiple creators to work together on a single AI-generated article, offering diverse viewpoints on a given topic. 
  • AI isn’t just great for writing; it’s also an amazing helper when it comes to insights and analytics. LinkedIn is launching Content Insights, an AI-driven tool that provides data on article performance. You can’t know if your marketing is going in the right direction if you don’t know your numbers. 

LinkedIn’s AI revolution aims to foster collaboration, amplify top voices, and help creators get their high-
quality content in front of the right audience.

LinkedIn’s Supercharged Move to AI

Within 3 months, LinkedIn’s AI team managed to roll out new ChatGPT-based tools. These AI-gasmic
features are designed to make your LinkedIn experience more seamless and efficient than ever.

Let’s dive deeper:

LinkedIn + ChatGPT: A Dynamic Duo

1684874428 679 LinkedIn AI How They Team Up Why Its

LinkedIn is looking to encourage us to use ChatGPT to write posts. Enter up to 30 words, click Draft
Post,” and instantly have a draft to review, edit, or post as is. In beta testing, this will be a premium
feature.

And being the Dopamine Dealer and Top Voice of LinkedIn has its perks… I’ve gained access to the beta
for the Generative AI tool (ChatGPT-4 based), and I’m one of the first to test it out. While it’s initially
available as a premium feature, the benefits it offers are bound to be worth every penny.  Think of Draft
using AI as your virtual writing assistant—the Jarvis to your Tony Stark, or the Alfred to your Batman.

It can help you:  
→ Save time. 
→ Enhance your productivity.  
→ Ensure your posts are polished to perfection.

Turbocharged Content Moderation: The AI Shield

1684874428 950 LinkedIn AI How They Team Up Why Its

Let’s face it, we’re constantly scrolling through an abundance of user-generated content, so it’s no
surprise that effectively managing and curating content on your brand’s online platforms can be an
overwhelming task.

Fortunately, there’s a solution: AI-powered content moderation is poised to revolutionize this process. By
leveraging artificial intelligence, content moderation can be automated, allowing for efficient classification, flagging, and removal of harmful content.

Here are three ways you can harness the power of AI for content moderation: 

  • AI Content Moderation for Texts: Utilize AI to analyze the tone, categorize content, and
    monitor brand and competitor mentions through natural language processing and entity
    recognition techniques. 
  • AI Content Moderation for Images & Videos: Tap into the potential of Computer Vision
    (Visual-AI) to identify undesirable or harmful content. With the integration of natural language
    processing, AI can even detect suggestive content within images. 
  • AI Content Moderation for Voice Recordings: Explore the realm of voice analysis
    technology. AI-powered tools can transcribe voice recordings into text and analyze tone and
    intent using natural language processing algorithms. 

Thanks to the extraordinary capabilities of ChatGPT, LinkedIn’s AI-driven content moderation has been
turbocharged, making it more powerful and effective than ever before.

Job & Career Support Right at your Fingertips

We’ve all been there: that squeamish ordeal of job-hunting:

Scrolling through hundreds of companies, writing different cover letters, and tailoring your CVs to help
yourself stand out. With LinkedIn’s integration with ChatGPT’s natural language understanding, job-
hunting transforms into something you no longer have to hate.

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Here’s what’s in store for you:

Hyper-personalized job recommendations that match your unique profile, skills, and passions. It’s like
your personal matchmaker who finds you the perfect career fit every time. Single. time.

Curated selection of job recommendations that are tailor-made for you. You’ll find yourself thinking,
“How’d they know this is exactly what I’m looking for?”

Networking not your favorite way to market yourself? You might change your mind. The platform will now
have the ability to suggest conversation starters (introverts would probably love this the most),
recommend events, and identify shared interests. Way to break the ice—easily.

Going beyond helping you with job searches, LinkedIn’s got your back for your career as well, so you can
ace those interviews and land the job of your dreams.

It can now give feedback on your resume, as well as offer coaching and guidance for your interviews. It’s like your very own pocket career coach that you
can take anywhere.

As LinkedIn’s AI revolution continues to excite us and evolve in ways we can’t imagine, I can fully understand if you’re curious about the future of professional networking and its potential impact on
marketing and tech.

If you’d like to stay on top of the latest LinkedIn news and all-things-AI, follow me on LinkedIn where my
network gets first dibs on some of the newest AI updates and features out there.


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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

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!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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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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