MARKETING
10 Tips to Revolutionize Email Marketing Campaigns with Artificial Intelligence
Wouldn’t it be awesome to have a digital space where you never receive an irrelevant or vague email in your inbox? A digital space where every email you receive is tailored to your needs and interests?
Well, here’s the good news! That dreamy digital space is not a far-fetched dream anymore and we need to thank the power of artificial intelligence in email marketing for it!
Artificial intelligence is changing the game in email marketing. While it allows you to send perfectly curated emails to your subscribers, it also helps your emails resonate with potential customers and drive better results!
In this post, we will shed light on a few ways in which artificial intelligence is transforming email marketing and how it can help you too to take your campaigns to a whole new level.
We are as excited as you are, so without any further ado, let’s get started!
10 Ways To Leverage Artificial Intelligence for Email Marketing
1. Send personalized and well-tailored emails
Personalization has undoubtedly been a buzzword in the email marketing landscape for years and with artificial intelligence in the picture, things go on to a whole new level.
AI helps you analyze customer data like purchase history, social media activities, browsing behavior, and much more. This information can then be included and leveraged to create personalized emails that are tailored to the individual subscriber and their likes and preferences. Doing so will result in higher open and click-through rates and gradually fetch more sales!
Have a look at how Netflix is sending recommendations to its user as per their preferences.
2. Leverage predictive analytics
Simply put, predictive analysis is the utilization of data, statistics, algorithms, and machine learning to identify future outcomes as per historical data.
In the field of email marketing, predictive analytics can help in identifying how likely a recipient is to open the email sent by you. The details obtained from the analysis can also be used to determine the products and services that your subscribers are most likely to be interested in.
3. Better your customer retention rate
Artificial intelligence can be used to identify consumers who are likely to churn and unsubscribe. You can then look for means and ways to engage your customers to avoid this situation. One great way will be to run personalized retention campaigns.
4. Conduct A/B testing easily
A/B testing is the process of sending two different versions of a certain element in an email to a group of subscribers to identify the version which performs better and is capable of generating more leads.
With AI, you will be able to automate the process by leveraging machine learning algorithms to analyze the results. This helps you optimize your campaigns and enhance your overall return on investment (ROI).
5. Automate segmentation
Segmenting your email list is crucial as it allows you to divide your audience based on their preferences and behavior and target them with personalized content.
With the help of artificial intelligence, you can easily automate the segmentation process by analyzing customer data and creating lists based on several factors like geographic location, purchase history, and engagement levels. This not only saves your time but also ensures that the subscriber receives emails that are relevant and suit their preferences and needs.
6. Check the Email spam score
Artificial intelligence can be used to check the email spam score before scheduling the email. Evaluating the spam score can help you determine if the email will be redirected to the spam section.
Various other techniques can be used for this process but one common method is to include machine learning algorithms to analyze the content of the email including the subject line, email body, and other files that may be attached to the email.
7. Curate impactful subject lines
You read that right! Artificial intelligence can be used to create compelling subject lines that can lead to better open rates for your emails.
One way is to use natural language processing to analyze the content of the email. It generates a subject line that can lure your subscribers and is informative at the same time.
Take inspiration from how the eyewear brand Clear has curated a click-worthy subject line that is super compelling.
8. Optimize email-sending times
Sending the email at the correct time is of utmost importance. Hence, you must be aware of when to schedule the emails as per the subscriber’s location and preferred time. The time optimization feature in the AI tool helps analyze and predict the perfect time to send the email for better results.
9. Up your reputation
Your reputation can leave a huge impact on your subscriber base as well as your email marketing campaign. Artificial intelligence will help you detect any issues that are likely to come up and help you work to rectify those issues on time to ensure a good reputation.
Additionally, AI can provide insights and recommendations based on data analysis, which can help you make informed decisions about your email marketing strategies. By using data-driven insights, you can successfully optimize your campaigns, improve your performance and build your reputation as a data-driven email marketer.
10. Improve email deliverability
Email deliverability plays an essential role in determining the success of email marketing campaigns. AI assists in improving email deliverability by analyzing various factors and suggesting improvements.
For instance – If a subscriber’s emails start getting marked as spam all of a sudden at a tremendous rate, artificial intelligence can investigate and look into the matter and suggest corrective actions.
Calling It A Wrap!
Email marketing can help you grow your business by leaps and bounds. In fact, according to statistics, 81% of SMBs rely on emails as their primary customer acquisition channel!
Artificial intelligence and email marketing are indeed a match made in heaven! The power of AI in email marketing lies in its ability to collect data, analyze it, and provide relevant insights that can help in upscaling your email marketing campaigns.
Excited to include AI in your upcoming email campaigns? Go for it!
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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