MARKETING
5 Ways You Can Leverage Data to Upgrade Your Email Marketing Game
As a marketer, I’m sure you are aware of the fact that creating the ’ideal’ email campaign is not an easy feat. There is a lot of competition in any given market, so setting yourself apart from the pack is essential. Again, leveraging data is the key here.
What data are we talking about here?
Anything from email addresses to email clicks, purchase history to customer preferences, types of users to website visits and traffic, etc. All these customer touchpoints can act as catalysts in making your email marketing campaigns better.
But why do we need to leverage data?
When it comes to promoting your business and getting in touch with customers, email marketing is one of the most powerful tools. However, making your message stand out among the hundreds, if not thousands, of emails people receive daily can be challenging. Using data in email marketing helps you better understand target demographic, tailor messages to each recipient, and boost open and click-through rates.
In this article, we will discuss 5 ways to use data to improve your email marketing strategy and see your campaigns through to a successful conclusion. We’ll show you how to use data to generate results and establish genuine connections with your target audience by segmenting your email list and conducting A/B tests on your campaigns. Let’s dive in.
One: Segmenting Your Email List
To segment your email list, you divide your subscribers into subsets with similar characteristics like, age, gender, occupation, location, income, etc. If you divide your email list into subsets, you can send messages tailored to each group’s interests and needs.
How to Use a Segmented Email List of Subscribers
Create a win-back campaign for inactive subscribers, send a welcome series to new subscribers, or organize your email list based on a customer’s purchase history to make relevant product recommendations.
Benefits of email list segmentation
Because of segmentation, not only will your email marketing campaigns be more successful, but the engagement of your subscribers will increase, leading to a more significant number of successful conversions. If you do this, you can improve the quality of your email campaigns and forge deeper connections with your readers.
Two: Personalizing Your Email Campaigns
Email personalization refers to adapting the message and its delivery to each recipient based on their interests, preferences, and habits gleaned from their inbox.
How to personalize your email campaigns with data
Customers’ names, locations, purchasing histories, and online activities can all be used to tailor their experience based on their preferences and interests. It may also include content that adapts in real-time to factors like the day of the week, the temperature outside, or any number of other variables.
Benefits of email personalization
As a marketer, you can better connect with subscribers by tailoring your email campaigns to their tastes and interests using data. This method can increase engagement metrics like opens, clicks, and conversions.
Three: Optimizing Your Email Sending Time
Determining when the optimal time is to send emails helps to maximize engagement and open rates.
How to optimize your email sending time with data
To collect data so that you can optimize your email send time – best time of day and week to send emails – you should first examine your subscribers’ activity patterns, such as open and click rates. An email marketing software can collect this information for you and use it to plan the best times to send out emails based on how engaged recipients have been in the past.
Benefits of email sending time optimization
Sending emails at optimal times can improve open and click-through rates, boost conversions, and improve return on investment (ROI).
Four: A/B Testing Your Email Campaigns
A/B testing is a method for determining which version of a promotional effort, in this case, an email campaign performs better by comparing and contrasting the two.
How to A/B test your email campaigns with data
Data-driven A/B testing of email campaigns requires deciding what to test, creating two email versions with the same content except for one variable, and sending them to separate audiences. Then, you’ll need to keep tabs on the feedback, sort through the data, and pick a victorious iteration.
Benefits of A/B testing
A/B testing in email marketing has many positive effects. You can use it to zero in on the optimal format, headline, body copy, and CTA for your target demographic.
Some aspects of an email you can A/B test
- Subject line
- Pre-header text
- Call-to-action
- Layout or color scheme
Five: Monitoring Your Email Campaign Performance
Constantly checking in on your email marketing campaign’s stats is necessary to improve your performance.
How to monitor your email campaign performance
Metrics from your email service provider, Google Analytics, heat mapping, polls, and surveys are all fair game. However, identifying trends and making strategy adjustments require setting up regular reports and tracking metrics over time.
Benefits of email campaign performance monitoring
Keeping tabs on how well your email campaign is doing can help you improve it, get more people to interact with it, and get the most out of it financially. Your email marketing conversion rate, customer retention rate, and revenue will all increase thanks to the data-driven decisions you make after analyzing your campaign’s performance.
How to effectively monitor email campaign performance
Email open rate analysis is an excellent example of tracking the success of your email marketing campaign:
- See which emails are most open by conducting A/B tests of different subject lines, sending times, and content.
- You can improve your emails’ open rates, click-through rates, and overall engagement by using heat mapping tools to examine how recipients interact with them.
- By conducting a survey, you can learn much about your audience and what they want to see in future emails.
Key Takeaways
Data-driven strategies like these can help you maximize the value of every email you send for your email marketing campaigns. So, don’t wait any longer; immediately implement data into your email marketing initiatives and watch your business flourish.
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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