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7 areas where it shines and struggles

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7 areas where it shines and struggles

AI is changing our world even if we can’t see it. It’s helping us navigate to places faster, get products into our hands and even diagnose diseases. In this article, though, I want to explore the role AI can have in marketing. It may not be as grandiose as helping cure cancer but marketing needs to reckon with the role of AI in its world.

This is a timely article, especially since ChatGPT went viral. If you haven’t been following the news, ChatGPT is a project by OpenAI, a company working on driving making AI tangible in the business world. It functions like any kind of chatbot where you can ask all kinds of questions and get answers back in seconds.

The “cool” factor is that you can ask highly specific questions and get back answers that could have been written by a human. For example, I asked ChatGPT to tell me the three most important elements in marketing but to give me the answer in the form of a haiku.

Here’s what I got back.

The trouble with AI is sorting through the hype. Parlor tricks like my haiku question are cool, especially on Linkedin. But we need to get to the essence of the value AI can provide while being clear on what it cannot do. Here are a few guidelines for thinking about AI in 2023 and beyond. 

Dig deeper: Why we care about AI in marketing

Where AI shines right now

AI is still in its early stages. Despite what you may see and hear in conferences and Linkedin posts, AI still has a long way to go. It can do several things quite well but it still struggles with others.

If you read or follow certain people, you would think we are just a few months away from living in a Black Mirror episode where AI rules everything.

Keep in mind that some use cases of AI — such as self-driving cars — have been “10 years away” for more than 50 years. I don’t doubt that we will accomplish certain feats but it will take longer than expected. 

In the meantime, here are the areas where AI can legitimately help marketing teams. 

1. Cleaning data

Marketers have a love-hate relationship with Google Sheets. It’s common to encounter dirty data that needs to be cleaned before it can be used.

I recently helped a team clean an Excel file with hundreds of contact requests structured in the worst way possible. AI — and even ChatGPT — can help you here.

There are now Google Sheets extensions that sort through your data and apply transformations. You even see the beginning of this kind of shortcut built into Google Sheets directly by suggesting formulas you can use.

2. Transcribing videos

Video captions are huge in today’s world — just look at any TikTok video. Luckily transcribing is becoming easier with AI, and it’s surprisingly accurate. 

You can do it after the video is recorded or even in real time. The addition of subtitles provides all kinds of benefits and you no longer need a human to give you great captions. 

3. Creating assets

The days of Getty images might be over. AI can create images or assets of all kinds. I saw a project that creates human avatars to be used in marketing. The assets look realistic and don’t carry complex usage licenses.

There will still be demand for pictures of real places and events but other artistic work will be slowly replaced by AI-generated images.

4. Surfacing insights

Tools like Google Analytics are using AI to surface insights from your data. Some insights are pointless, while others are worth exploring. Expect to see more of this kind of data analysis as a way to sort through the increasing amount of data that marketing teams collect.

Marketers do not lack data, but insights. AI might finally be the breakthrough that allows us to dig through a never-ending pile of data points. 

Dig deeper: ChatGPT to support digital experience analytics

Where AI struggles

We are not being replaced by AI — yet. Maybe poem writers might struggle to find work but AI can’t match certain human skills. The debate on whether this will always be true is a topic for another article.

AI should be viewed as support for marketing. You will still need real humans for several tasks, but thanks to AI, you can free up your time to tackle the three areas below. 

5. Creativity

AI can surface insights but creativity is still the realm of humans. Deciding what campaigns to run, how to appeal to human desires and how to bring it all together is something only humans can do.

Kayak recently ran ads — the Kayak Deniers — that were brainstormed by AI. They looked at the language and topics that were popular in social media and then created ads around them. 

They are clever but will be less impressive once everyone starts doing them. If everyone is using the same algorithms, you will end up with the same answers. Hence, the value of human creativity.

6. Uniqueness

While AI text may be factual, it is missing the unique voice of humans. We all know authors we could recognize by simply reading a few sentences of their writing. You can still infuse the concept of a voice into all your content.

AI will kill boring content that simply states facts. That’s probably for the best. If someone wants the facts about B2B marketing, they should go to Wikipedia. If they want to solve their problems, they need humans to help them.

7. Strategy

Humans still need to figure out the strategy. Making these decisions isn’t just about looking at the data but taking into account a variety of factors. Sometimes marketing teams have to make choices that don’t match the data because their experience (a.k.a., gut) says so.

We can see this play out in the chess world. World-class players like Magnus Carlsen rely heavily on AI to prepare for matches and run through different positions. However, during games, Carlsen is known to make the opposite move a computer would recommend. He knows that his opponents are looking at the same data creating an opportunity to make unexpected decisions.

Expect to see more companies rely on AI and then be surprised when competitors make seemingly “wrong” moves that work. Strategy will simply evolve to take into account what kinds of algorithms other companies might be using and how they can be defeated. 

Dig deeper: 17 AI-powered writing tools and how to make best use of them

AI is here to stay

The rise of AI will continue. You would be surprised at how much this innovation touches today, but most of it happens behind the scenes. AI is freeing us from mundane tasks so we can focus on those things that truly matter.

We must embrace AI and use it to drive revenue and growth within our teams. In an era of decreasing budgets and higher expectations, marketing needs to pour more resources into creativity with fewer people. AI will help bridge that by becoming one of your most effective unpaid assistants.


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Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About the author

Ruben Ugarte

Ruben Ugarte is the global expert in Decisions, Strategy, and Data and author of the Data Mirage and Bulletproof Decisions. He helps executives at the most innovative medium and large enterprises find their hidden treasures and use them to dramatically boost performance, increase profitability, and make their teams world-class. He has done this across five continents and in three languages. His ideas have helped hundreds of thousands of people make better decisions.

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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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