MARKETING
How to find your next, best customers with ABM
You’re likely familiar with the Pareto Principle, the old 80/20 rule and how it applies to marketing — 80% of your profit comes from 20% of your customers. You also know who those “best” customers are. The metric that illuminates your best customers is customer lifetime value.
But do you know who your next best customers are? Those who will replace your current set of best customers as they “age out” or perhaps join and augment your profitability? I propose that you deploy very specific strategies to identify them and nurture them to their potential, even before they’ve signed their first contract.
The most effective and efficient way is account-based marketing or ABM. It requires resources and it delivers payback. Let’s peel back the layers of what makes an effective ABM strategy, from developing your ICP to deeply personalizing prospect journeys through qualitative research and two-way dialogue.
Understanding ABM
ABM is a targeted, personalized and measurable process focusing on a specific set of high-value customers-to-be by creating and immersing them in a personalized customer experience. It’s a strategy that’s all about acquiring revenue and profit.
Plenty of three-letter acronyms are related to this marketing approach. The ones you need to know right now are:
- ICP, or ideal customer profile: It’s a data picture of your best customers.
- TAM, or total addressable market: Your ICP is likely a small circle inside this ballpark.
- CLV, or customer lifetime value: The metric that means money. How long does the customer relationship last and how profitable has it been? The objective: happier customers that stay longer and buy more.
The uncomfortable truth is that close coordination of marketing and sales (and soon customer success) is required to create and maintain the increasingly personalized customer experience.
Your ICP is ABM’s GPS
Your ICP is a broad-stroke profile of your best customers. This is where separating the wheat from the chaff in your TAM begins. It is the model that ABM prospecting will begin pursuing.
Not every interested prospect is going to turn into a long-term customer. Your TAM has a subset of your ICP. The ICP is the prompt you put in your ABM satellite navigation. There are three levels to a successful ICP:
- The first is in broad strokes: firmographics (vertical, revenue, number of employees, location, etc.). Interestingly, a customer of ours found that by digging a bit here, the percentage of budget allocated to HR was a clear indicator that a company was really in the ICP.
- The second level lays out the preconditions or the reasons they may benefit from becoming a customer (e.g., targeted companies with larger legal departments will benefit from our software).
- The third level takes an educated guess at what titles to target and why (e.g., SME or subject matter expert, a key advisor to the decision-making process).
Personalization, or the ability to personalize, is a key concept within ABM. This ability to personalize depends on the information we gather through analysis and increasingly from two-way communications based on trust.
We may intuit that the SME in a targeted company needs detailed information. We need to learn the specific concerns and use cases to become a differentiator for personalization. We want to focus deeply on these companies and executives.
Levels of personalization within ABM
With only our ICP to keep us warm, the ability to personalize is generally “Dear Santa,” because we really don’t know much more. We can begin to offer more specific content based on assumptions and trying to earn engagement.
We construct a preliminary consideration or buying journey and use content marketing to populate that consideration journey with what folks need to move on to the next step and eventually engage with sales.
The next step is qualitative research to generate specific and in-depth personas. Who are the people making the decisions and what are their personal and professional concerns and information needs?
Then, we engage and have real conversations. We probe and learn and create the customer experience personalized to the company, the customer and the buying team. Let’s not forget that B2B has always been, and always will be, personal.
Now, here’s where marketing and sales have to collaborate and coordinate. to deliver this increasingly personalized experience. They need to share intelligence and collaborate on strategies, tactics and implementation to understand and satisfy the prospects’ drivers and articulate solutions in how they describe their challenges.
As if it wasn’t bad enough that you have to talk to those annoying customers, now marketing has to hold hands, share and collaborate with sales.
The successful integration of marketing and sales is the topic for another day. But I’ll give you three hints:
- Management must walk the talk.
- There must be shared measurements.
- There must be shared compensation.
As we move closer to conversion to customer, you should begin an even deeper immersion in the personalized customer experience by introducing the customer success team.
The end game
I was part of a team doing NPS (Net Promoter Score) research but with a strong qualitative component. Not only do we ask if you would recommend Company A, but we spend most of our time probing why.
I was interviewing the C-suite decision maker of one of the sponsoring company’s best customers. I asked him, what is the most important benefit you receive as a customer?
His answer was short and direct, “Our salesman. He’s part of our team and helps us to solve problems. He knows what we need and goes out and gets it.”
That is where you want to be. That is where ABM can bring you. ABM is a more efficient and productive use of resources and generates the highest ROI of all marketing strategies. Find, invest and create your next, best customers.
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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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