MARKETING
Can You Keep the Human Touch When Using Marketing Automation?
Marketers, we find ourselves in a quandary: We want to automate as much of our marketing as possible, yet we don’t want any of it to feel automated.
We’d love to be able to just set it and forget it. But great content marketing is designed to build relationships (that drive revenue). And unfortunately, automating our communication can make that goal harder – not easier – to achieve.
#ContentMarketing is designed to build relationships. Automating communication can make that goal harder, says @DrewDavisHere via @CMIContent. Click To Tweet
Sure, there are tools designed to automate posts on social media profiles and even the direct messages sent through LinkedIn. We can also choose to automate our most valuable interactions, such as our welcome emails and thank-you notes.
But when we do, the resulting messages don’t feel authentic. They lack personalization – a critical factor in relationship-building and revenue generation. In fact, research from McKinsey found companies with the fastest rate of revenue growth were more likely to prioritize personalization in their communication.
So, as much as we may want to put tasks on autopilot to increase productivity, we wonder how much our relationship-building efforts might suffer if we do.
What should marketers automate?
I’ve spent the last three months wrestling with that question, and it turns out I’m not the only one.
Even in 2017, 43% of marketers stated the most important objective of a marketing automation strategy is optimizing productivity. It’s not hard to understand why. The average marketer spends 1.25 days each week on non-core tasks, according to new research from Airtable. That’s 25% of our workweek spent managing, organizing, approving, reporting, gathering, and shuffling our marketing campaigns and content through the marketing mill.
Marketers spend 1.25 days each week on non-core tasks, such as organizing, approving, reporting, etc., according to Airtable research, says @DrewDavisHere via @CMIContent. Click To Tweet
That’s 1.25 days we could reclaim by automating the right stuff.
Where do we start?
What is the “right stuff”?
Here’s what a few experts had to say on the subject:
“Automate the admin, the mundane, the data collection. Animate the rest with personality,” suggests Patrick Lyver, founder and president of the web design agency Kleurvision Inc. “It works for me, and there are a lot of tools that can help.”
Automate the mundane and animate the rest with personality, says @patricklyver via @DrewDavisHere @CMIContent. Click To Tweet
Gloria Lafont, president of Action Marketing Co., agrees: “Automation does not mean set it and forget it, nor eliminate the human. It means eliminating as many repetitive tasks as possible in the marketing implementation, so you have more time to focus on making the relationship-building more effective.”
Automation does not mean set it and forget it, nor eliminate the human, says @GloriaLafont via @DrewDavisHere @CMIContent. Click To Tweet
Our team set aside 30 days to experiment with ways to follow Patrick and Gloria’s advice. By embracing three simple, strategic ideas, we found an approach that automates mundane, repetitive tasks without eliminating the human touch.
HANDPICKED RELATED CONTENT:
1. Start with recently acquired customers
My core belief is all good marketing starts with the customers you’ve got. Instead of starting our automation activities with prospecting, social media, and lead generation, we focused on the processes implemented immediately after acquiring a new client.
From the instant we sign a new deal until the final invoice is paid, our team identified 49 separate multi-step automations that could save us time. More importantly, those automations allowed us to craft a unique, consistent, and high-quality client experience.
Designing these automations was surprisingly easy: List every little interaction, task, and deliverable in the client relationship. We just had never tried to formalize or automate them. It’s stuff we’ve done manually for a decade. It’s second nature. Then, we used our CRM’s built-in automation workflows and Zapier to turn each task into a tiny automation.
How much time did we claw back? It’s hard to say precisely, but I’d guess four to six hours per week. That’s six hours we can now spend on marketing instead of managing.
Yet, we have also recognized that to achieve marketing success with these automated efforts, we need to maintain a high-touch, highly personalized experience for our customers.
That brings us to our second strategy:
2. Ready-to-personalize communication
Any CRM can “personalize” an email or text message: Simply insert {first name} here, add {company name} there, and schedule it to be sent.
However, I am unaware of a CRM or even an AI tool that’s genuinely aware of the communication nuances across different client relationships. For example, some of our clients are “business-casual” communicators. Their emails feel like they’re wearing shorts to the office:
- They use extra exclamation points and emojis.
- They send short, punchy text messages.
Other clients communicate with all the formality of a black-tie affair:
- Their messages are crammed with corporate lingo.
- Every imaginable stakeholder gets cc’ed.
- Even their email signatures include legal disclaimers – just in case.
Then, there are clients that fall somewhere in the middle. I call this style “the mullet of marketing” – all business up front and party in the back.
These nuances matter in communication. They’re what supplies that human touch we’re so afraid of losing when we automate.
So, instead of sending pre-written, generically personalized emails directly from our CRM, our team generates ready-to-personalize messages.
Ready-to-personalize or RTP messages don’t get sent directly from the CRM to the client. They require a manual step added into the account management process: For each campaign, the account manager receives a notice that a draft needs their attention.
The CRM has already filled in all the critical customer data – such as first name, company name, and amount due. All the account manager needs to do from there is add some brand personality to the message. It could be as simple as popping in a few emojis, removing the exclamation points, or asking how the customer enjoyed their long weekend or a recent vacation.
Then, they hit send, and off it goes.
RTP has transformed our perspective on how powerful marketing automation can be.
Yet, that still leaves one last element of our approach that still needs work.
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3. Create a single source
Zero percent – yes 0% – of marketers have a single source of truth for up-to-date information on marketing activities, according to the Airtable report.
On average, Airtable’s 300 survey respondents report they must reconcile between nine and 11 data sources to build a holistic view of their marketing activities and audience insights.
That’s a ton of work.
Any marketer who’s attempted to marry their Google Analytics with their customer database, email marketing platform, social media insights, and a pipeline of opportunities has faced this nightmare head-on.
Fortunately, there’s a solution: customer data platforms. CDPs used to be for massive enterprises blessed with a vast IT staff capable of building custom connectors for proprietary platforms.
But that was the old days.
Today, any company (even yours) can use free (or low-cost) web-based tools to build your own CDP.
We’re planning to use those tools to reduce the number of platforms needed to run reports and find new insights. We’re confident those insights will help us find the perfect balance between automated efficiency and authentic communication that builds client relationships. So, that’s next on our list.
With our initial 90-day automation experiment closing, we’re excited to see if we can achieve similar results when communicating with our prospects, leads, and open opportunities.
All tools mentioned in the article are identified by the author. If you have a tool to suggest, please feel free to add it in the comments.
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.”
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