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Fractional-CMOs Don’t Need to Be Scared of AI

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Fractional-CMOs Don't Need to Be Scared of AI

AI will not fundamentally change your role as a Fractional CMO, despite what the masterminds and gurus are selling.

Are You Scared of AI?

This feels like January of 2020, when the pandemic was just starting to get some attention. I remember going to my gym in Fishtown, Philadelphia and talking with the owner about this “weird virus thing.” He didn’t think it was going to be a big deal. I thought there might be a lock-down until July 4. Obviously neither of us were right.

That’s where we are with AI.

There are some people freaking out about how everything is going to change.

And others who are utterly clueless.

I think academia is getting pretty worried about the implications of students writing theses and essays with a few prompts. Similar to the revolution Wikipedia brought about, but this time, much much more dramatic.

In marketing, there are the tacticians who are directly affected:

  • Content writers: If you’ve ever used a resource like WriterAccess to get blogs or articles created, you might have paid $0.1 to $0.12 a word for the best-of-the-best writer (I’m talking about ex-Jeopardy contestants!). I have to imagine that those writers are at least having AI write the first draft of their articles, then just making some minor edits and collecting their fee.
  • Copywriters: I’m seeing these folks really focus on harnessing AI. The take that I like is that copywriters will leverage AI to pull together creative ideas, cutting down the time to find The Big Idea. Tools like Jasper can help craft headlines, ad copy, email copy, and can absolutely support a copywriter. That said, I think the art of copywriting is safe from the robots, for now. There’s just so much consideration that is required in a good piece of copy that a simple Jasper prompt can’t repeatedly churn out.
  • Marketing agencies: Writing boilerplate content for websites? Crafting a more readable About Us page? For the reduction of suffering across all humankind, let’s hope agencies are leveraging AI to help with this necessary evil.

Things are going to change.

But then again, the only constant in life is that everything changes.

If you’ve been in the business game for more than a couple years, you’ve seen other revolutionary advances.

Take, for example, crypto.

We saw all-time highs for bitcoin and ethereum prices in November 2021. If you were plugged into that world, you probably heard of the Decentralized Autonomous Organizations (DAOs) that were doing incredible, innovative work with smart contracts and their tokens.

Then the market saw a significant correction, wiping out over $700B in market capitalization over 6 months.

Some say that crypto is dead, but it’s clear the fundamental technology is here to stay. Development of the ethereum smart contract software Solidity began 7 years ago, and saw dramatic development over the bull run of crypto.

The high-times of token prices attracted some of the best developers in the world to work together on open source projects that moved the technology forward by leaps and bounds. That technology is slowly (and in some cases, rapidly) seeping into our day-to-day lives in the field of banking, regulatory compliance, insurance, supply chain management and more.

What I want you to get out of this comparison is that AI is right now at the “all time high” in the mainstream … and has a lot of room to grow in popularity. ChatGPT is being talked about on small-town country radio stations, in PTA meetings at high schools, at global summits of business leaders (just like bitcoin was). There’s worldwide attention on the technology… and that attention will wane at some point.

The implications of AI will seep into our day-to-day lives. We might notice it in tools like Notion with their release of Notion AI, and we may also not notice when a tool has AI baked into its core. Will anyone say “My car has AI!” in ten years? Or will they just appreciate that their car understands their requests better, and provides a more seamless experience?

The Great Search Engine AI Race is an example of noise related to AI. Yes, the way Google shows rankings may change… I’ve heard SEO folks talk about how Google might no longer show rich snippets and instead answer the query themselves with their AI engine. Maybe Bing with their partnership with OpenAI will somehow climb out of their sub-10% market share position to own, what? 15%? 20% of the market?

Does that matter? I guess. But it’s really not revolutionary for the consumer. We’ll experience a better experience, but then will quickly adapt to it.

AI is about to become ubiquitous; part of our day-to-day lives in a way that (should) make us feel as though it’s not even there. Saying something is “powered by AI” will start to feel like a high school entrepreneurial pitch event where all the students claim their project uses an “algorithm.”

So what’s a Fractional CMO to do about it?

The same thing we did when TikTok came out. Which is the same thing we did when Clubhouse was all the rage on Twitter. We do the same thing we did when Leadpages and then Clickfunnels made building funnels and sales pages easier…

We roll these new tools into our strategy for our clients and execute them at the right time.

That’s it. That’s your job.

Fractional CMOs Solve Bigger Problems. That should be your mantra as you build your Fractional CMO practice. The bigger the problem, the bigger the reward – for your client, for their customers, and for you and your bank account.

What Companies Need from Their CMO in the New Era of AI

Nervous or scattered CEOs might ask you to put all your attention on AI, and for most businesses, that is simply not a good use of your time.

Instead, there’s one word that accurately describes what companies need… and that word is leadership.

The fractional CMO, the interim CMO, and the full-time CMO all have the same basic requirement: To be the leader for their marketing department and to push the team to make the dreams of the CEO and/or the board of directors come true.

AI becomes a tool in your toolbelt. It is also a tool in your client’s competitor’s toolbelt.

A few years ago, I was working as a Fractional CMO for a private equity company and I remember sharing my concerns about the increased CPM on Facebook over a few week stretch. HIs reply was timeless:

“It affects us and our competition the same. Don’t lose sleep over it. Keep fighting.”

What simple, golden advice.

The same is true with AI.

AI content writers mixed with lifelike voice generators, overlaid on a slideshow of images produced by DALL-E seems like a scary and innovative tactic… and it might be. But it’s just a tactic.

And it’s your job to decide if it’s the right tactic or not.

It’s your job to chart the best path, no matter the tools and tactics that emerge.

Oftentimes, the number one thing a business needs is end-to-end tracking of lead source to purchase. Or simply just having a rock-solid offer. Or focusing on one advertising channel to 10x sales of their hero product. Or a salesperson who will call all the webinar attendees who stayed for the whole 60-minute webinar but didn’t purchase.

For most companies, AI is simply another tactic that seems exciting and revolutionary, but in reality, it’s a level-5 tool and the company is stuck at level 1.

Business basics like tracking, generating advertising controls, creating product ascension to maximize customer lifetime value, collecting and sharing testimonials, and delivering a world-class customer experience will last until the end of time. AI is here to stay and yes, it changes everything, but it’s not the panacea to profitability that some marketers want it to be.

Stay focused. Stay in your lane. Bring in more sales. Look for low-hanging fruit that you can use AI on. Test your favorite copywriter’s work against a rewrite by AI and see who wins.

Be open to swinging the AI hammer, but treat it like a tool.

Keep fighting.

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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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