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How to Use AI to Improve Your Email Marketing Performance

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How to Use AI to Improve Your Email Marketing Performance

Artificial intelligence makes a ton of things in different parts of our lives easier – from a surge in voice command bots (Siri, Google Home, And Alexa are just a few that come to mind) to AI-powered systems being added to electric and hybrid vehicles, AI is making our daily lives more efficient. But it’s not just our personal lives that AI touches; it also improves different aspects of our professional lives – one of those being the email marketing performance of B2B and B2C organizations.

Email marketing has, for some time now, benefited from automation, especially considering that small businesses and agencies are always on the lookout for ways to better manage and automate the customer life cycle. And while AI can be a little daunting to more conventional marketers who haven’t used it before, artificial intelligence offers a direct and cost-effective means to conduct and carry out email marketing-based campaigns. AI-powered tools stand to drive long-lasting results for organizations that aren’t afraid to dip their toes into this burgeoning and innovative technology.

To that end, let’s explore how AI can be used to improve your business’s email marketing performance and how it can truly thrive when marketers combine added human emotion and empathy into their marketing content.

What’s AI doing in email marketing, anyway?

Before we cover the benefits of introducing AI to your email marketing strategies, let’s quickly consider why AI found its way into email marketing in the first place.

In case you don’t already know, AI broadly refers to the different technologies and related algorithms that help machines tackle tasks that would otherwise require an actual human being to accomplish. It’s what makes those handy virtual assistants that we mentioned earlier work so well, it’s behind the recommendations you get when shopping online, and when it comes to email marketing, it’s what makes the algorithms under a software application’s hood so good at giving marketers data-driven insights into their campaigns.

Using AI in email marketing

Alright, so you’ve gotten a quick definition of what AI is and how it found its way into email marketing – now it’s time to show off some ways you can use artificial intelligence in your email marketing campaigns.

1. Retarget visitors who didn’t complete their purchases

Retargeting tactics leverage advertisements to engage potential clients with whom your brand may have previously interacted but never committed to a transaction. It helps marketers connect with the audience they’re after with the right content at the right time. And while marketing teams come and go as often as the years pass, email retargeting is a tactic that’s here to stay — nearly half of all marketing pros think retargeting is a useful and heavily underused email marketing tactic.

Email retargeting, coupled with AI, lets organizations connect with prospective clients with whom they’d otherwise never speak again. It gives marketers a chance to get people up to speed with their brand. How? By using algorithmic functions.

AI uses many algorithms to distinguish between prospective clients and the kinds of conversions they’ll likely reward marketers with. AI is so smart about this that it can even curate the specific types of content that a prospect wants to see (something that’s relevant to them, like a loyalty program or attractive discount) and subsequently make it likelier for marketers to generate juicy conversions.

2. Write better subject lines

Let’s face it: any marketer knows that a surefire way to get more eyes on an email is with a compelling subject line. Your subject line indicates what the rest of the email will talk about. Do you want to lure bloggers and privacy-minded folks into checking out your anonymous web hosting service? You’d want to grab their attention fast with something like “thwart unwanted attention” in your subject line. Got an AI-driven email marketing product you want marketers to know about? Things like “data-driven” and “automation” should be in the subject line.

But putting together great subject lines that stand out isn’t that easy (it’s actually pretty tedious if you’ve ever tried it yourself). Thankfully, AI is good at automating tedious and laborious processes. AI-driven algorithms can do the jobs of dozens of copywriters and generate subject lines that drive big increases in ROI. Plus, AI can monitor how successful an email marketing campaign is to optimize subject lines that marketers can use during subsequent campaign loops.

3. Customize your promotions

Everyone likes a good promotion because promotions are one of the best ways to improve how well your content reaches its target audience. Personalized promotions make impressions on attractive prospects and make it much easier for you to establish lasting and more meaningful connections and collaborations.

It’s important that you do everything in your power to make sure that you’re holding on to prospects and, whenever possible, converting them into clients who last. You can do this by feeding them a steady source of personalized deals, samples, and promotions related to their interests. AI makes creating this drip feed easier for marketers by ingesting data related to client purchasing habits and highlighting which promotions marketers should consider using when reaching out to different prospects.

Marketers can achieve greater levels of promotional personalization with AI. Buyers will become keener on interacting with the content you send them, especially if you’re using AI to help automate the process of building promotions that speak to the unique needs that different prospects have.

Conclusion

AI is here to make email marketing a breeze for senders. It’s no surprise that it can be intimidating for traditional marketers to embrace artificial intelligence, but once they do, they’re bound to realize that AI makes for a deliberate and cost-effective email marketing approach. It’s recommended that marketers work together with AI to drive greater ROI and more effectively and efficiently scale their marketing campaigns and subsequent campaign loops.

We hope this article has helped you realize not only how to use AI when it comes to your email marketing campaigns but how much AI can improve your email marketing performance, too.

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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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