MARKETING
5 ways MOps can elevate the annual planning process
Many enterprises are now doing annual planning for 2024. For marketing departments, it can be a challenging time. How can we make a plan that’s firm enough to serve as the foundation for an annual budget and flexible enough to adapt to unexpected market changes?
Amid the demands, marketing operations (MOps) teams emerge as potential game-changers — serving as strategic partners among marketing leaders and innovators in the planning process.
In a world where many marketing departments merely reuse last year’s plan, MOps teams can bring a fresh perspective. They are well-equipped to challenge the status quo and offer innovative solutions to the planning process.
Here are five ways your MOps team can help transform your annual marketing plan.
1. Build a consistent planning template
MOps professionals are experts in structure and process. They play a crucial role by creating a consistent template for annual planning.
This template outlines the necessary steps — from setting business objectives to shaping marketing tactics. Having a consistent template will enable marketing to communicate with team members both inside and outside of the department.
Key actions
- Collaborate with different departments to create a comprehensive, adaptable and standardized template that can be the bedrock of all future marketing plans.
- Ensure that the template incorporates business objectives, key actions, how things will be measured and critical dependencies.
2. Streamline information flow
Reflecting on the past year’s initiatives, a marketing leader could easily find themselves submerged in a sea of data and activities generated by their department. This is where the MOps team can step in with their data management and analysis skills.
Serving as curators, MOps can determine what information is crucial for the planning process, where to source it and how to interpret it. They can ensure that each marketing leader has clear and actionable insights at their fingertips.
Key action
- Establish an internal data repository or dashboard where all relevant information is updated, analyzed and readily available for marketing planning.
3. Learn from the past: Translate data into strategy
Using the data repository or dashboard described above as a tool, the MOps teams can lead review sessions with cross-functional teams to analyze the performance of last year’s campaigns and tactics.
What performed well? What didn’t? Why? Processing this information is only the first step. The real magic lies in converting these analyses into actionable marketing strategies for the upcoming year.
MOps teams, given their dual skill set of understanding both technology and marketing metrics, are perfectly positioned to facilitate this process.
Key actions
- Organize cross-functional review sessions of last year’s campaigns. Include team members across the department, from product marketing to creative designers to media agency partners.
- Brainstorm new ideas that could have made a difference to improve last year’s efforts and discuss ways to integrate those into the upcoming marketing plan.
Dig deeper: 3 ways MOps can bridge the gap in marketing analytics
4. Prioritize the annual plan
Every marketing department has more goals and objectives on its wish list than it can actually accomplish. The MOps team can provide significant value by helping marketers prioritize their activities for the upcoming year.
By assessing the potential ROI of various strategies, weighing them against the company’s core objectives and factoring in the available resources, they can provide a clear hierarchy of what marketing initiatives should take precedence.
Key actions
- Develop a scoring or ranking system for potential marketing activities. This system could be based on anticipated ROI, alignment with company goals, feasibility and available resources.
- Regularly review this system as part of the planning process to ensure it reflects the ever-evolving marketing landscape. As the MOps team, your role is to balance data-driven decisions and fostering marketing creativity. Always leave room for innovative ideas and experiments.
5. Establish the process for ongoing adjustments throughout the year
An annual plan, while crucial, isn’t set in stone. Having the process in place to pivot as things change throughout the year is paramount. Here, the MOps team can introduce the concept of agile marketing to the broader marketing division.
Agile marketing, borrowing principles from agile software development, involves breaking down large projects into smaller tasks, regular check-ins and continuous feedback loops.
Key actions
- Set up regular intervals (i.e., monthly) for marketing teams to review their progress against the plan, discuss potential challenges and recalibrate if needed.
- Encourage a culture of open communication. The quicker the MOps team is informed about potential shifts or disruptions in the market, the more effectively they can guide the necessary pivots, ensuring the annual plan remains a guiding star and not an anchor.
Elevating the annual planning process
A successful marketing plan goes beyond the boundaries of the marketing department, reaching out and integrating with every tier of the organization. Using insights from MOps teams, marketing can make a flexible plan that adapts quickly to market changes while staying focused on its goals.
Connecting data with creative ideas turns the annual plan into a dynamic strategy. MOps teams that innovate and challenge norms have the ability to improve the planning process and uplift the entire organization.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.
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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