MARKETING
Your 2023 Planning Shouldn’t Be All About That Tech
Do marketers dream of magical tools? (I couldn’t resist that Blade Runner reference).
As we enter the fourth quarter (for many), it’s time for planning. Budgets are due. Plans are being formed. Leftover money must be spent before the year’s end.
Is it any wonder that marketers’ thoughts turn to technology? You may be mulling over questions such as:
- What technology should we budget for?
- Which new tools will help us achieve our plan?
- What cool new capability might we buy with that leftover money?
This year’s tech questions seem particularly complex. I hear content marketers asking if blockchain will become the next new thing. Or if they should invest in artificial intelligence software? Or if they should finally acquire a content calendaring tool. How about a new analytics solution? Or is it time to invest in a DAM? What is a DAM?
Many marketers dream of investing in tools to automate processes, create insightful dashboards, or spread content evenly across myriad channels in the right way to reach the right people at the right time on the right device.
Wait. Did we forget about intent data? Add that to our tech dream board, too!
But all those dreams could quickly become nightmare scenarios, requiring skill levels your company can’t accommodate.
Do you dream of finding a #ContentMarketing tool to make everything easier? Take a beat before you buy – or risk a nightmare scenario, says @Robert_Rose via @CMIContent. Click To Tweet
Caveat emptor: Think before you buy
Have you heard the aphorism “a boat is a hole in the water that you throw money into”? It means that when you decide to invest in a boat, you’re not just buying the boat – you’re also committing to all the things that go along with owning a boat. That includes renting a dock, acquiring a trailer, keeping up with the significant maintenance required, and paying for the fuel and other costs of operating it.
It’s not a stretch to adapt that saying to our industry: “Marketing tech is a hole in the business that you throw money and time into.”
That doesn’t mean you shouldn’t invest in it (or buy that boat if you need it or love it). Marketing technology can return extraordinary value.
But be conscious of what you’re buying. Any marketing technology worth purchasing involves implementation, training, user learning curve time, and ongoing administration.
I’ve recently seen some real challenges on this front. One B2B company I worked with has been stuck in some form of software selection or technology implementation cycle since the beginning of the year. They’re limited in the amount of content marketing they can create because they’ve been so busy trying to figure out the technology to create more content marketing.
Ironic.
Tech purchases won’t necessarily make your 2023 content dreams come true. What should you focus on to set your program up for success?
I have a few ideas.
Tech purchases alone won’t make your 2023 #Content dreams come true, says @Robert_Rose via @CMIContent. Click To Tweet
Focus on change first, not technology
I’ve been advising clients and colleagues to worry less about which new technology will be a must-have for 2023. Instead, work on developing the muscle to evolve content activities into repeatable processes.
In other words: How do you change?
I find that it’s critical to hold frequent discussions with stakeholders about the audience/customer journey. Content marketers aren’t the only ones creating bold new plans for content in the coming year.
You’ll probably participate in many meetings to understand what the sales team wants, what the brand team thinks, what the public relations crew has on their mind, and what senior leadership thinks.
But success isn’t built from a mutual understanding of those separate agendas. The teams must come together to develop one collaborative content strategy for customer and audience engagement.
Coordinated communication is one of the hallmarks of a successful content strategy. To achieve it, focus on these three fundamentals:
1. Orchestrate connected experiences, not siloed hand-offs
Think about next year’s plan in a way that lets you decouple customer and audience data management from the content experience. Explore how you can create a unified view of your subscribers and customers so that things like “audience,” “lead,” “opportunity,” and “customer” are attributes in a single database instead of siloed buckets.
That probably means technology will eventually play a role. But first, create awareness of what content is planned, by whom, and where it will be distributed.
Almost every business would benefit from communicating about the portfolio of content that will be created rather than meeting about what was created.
2. Shift to meaning-driven (not data-driven) content operations
What meaning do the email address, first name, and last name of someone who registered for a white paper contain? Little to none. You can, perhaps, draw some inferences about buying intent based on the topic of the digital asset. But the intent with which that data was provided may completely circumvent that inference. (If the email shared is [email protected] – you’ll have a pretty good idea.)
That kind of marketing data has no inherent meaning. It is a collection of facts, figures, and attributes about people or their behavior. You need more interactions with that person to develop a relationship.
For next year’s planning, businesses must develop new strategies to find the emotional value in data that’s given rather than gathered. For example, let’s look at an email address gathered from gating a white paper versus one given to subscribe to a newsletter after reading that white paper. How much more valuable is that email address if you know it’s given willingly, trustingly, and with the expectation of receiving valuable communication from your brand?
3. Organize for agility, not speed
You’ve probably read many essays about how content marketing teams need to become more agile in their operations. But agility isn’t about moving faster. It’s about focusing on high-value, high-priority activities.
The constant pressure of more and more content arises from a fear of moving too slowly. Replace that fear with joy by planning to spend more time developing powerful thought leadership stories and less time creating endless assets.
Think about how to shift your processes to spend more time planning big, meaningful, powerful, differentiated content. Once you create those stories, you can then decide whether and how best to transform them into digital assets.
Can you separate the process of content creation and digital asset production – and become more agile in the process? I think you’ll find you can.
Can you separate the process of #Content creation from digital asset production, asks Robert Rose via @CMIContent. Click To Tweet
Content marketing field of dreams
An “if we buy it, they will come” approach (to paraphrase another famous movie line) rarely leads to success.
And you can’t measure success by how much technology you deploy. That’s like thinking you can get to work faster by purchasing more cars. You’ll just accrue more debt and spend all your time managing and maintaining those cars.
What will 2023 bring? The metaverse? The return of NFTs? A B2B version of TikTok? The collapse of third-party data? We. Don’t. Know.
But, as you’re looking at your budget, plan, or year-end spending, take a beat. Before you dive into a tool, think about what you hope you and your team will be spending time and money on this time next year.
Write it out. What does your day look like?
That’ll help you set up a better dream for how you might accomplish it.
It’s your story. Tell it well.
HANDPICKED RELATED CONTENT:
Get Robert’s take on content marketing industry news in just five minutes:
Watch previous episodes or read the lightly edited transcripts.
Cover image by Joseph Kalinowski/Content Marketing Institute
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.”
-
WORDPRESS6 days ago
How to Connect Your WordPress Site to the Fediverse – WordPress.com News
-
SEARCHENGINES7 days ago
Daily Search Forum Recap: September 12, 2024
-
SEARCHENGINES6 days ago
Daily Search Forum Recap: September 13, 2024
-
SEO5 days ago
The Expert SEO Guide To URL Parameter Handling
-
SEO6 days ago
SEO Experts Gather for a Candid Chat About Search [Podcast]
-
SEO7 days ago
OpenAI Claims New “o1” Model Can Reason Like A Human
-
SEO3 days ago
9 HTML Tags (& 11 Attributes) You Must Know for SEO
-
WORDPRESS5 days ago
7 Best WordPress Event Ticketing Plugins for 2024 (Tested)
You must be logged in to post a comment Login