MARKETING
The state of intent data in 2023 and beyond
In B2B sales and marketing, intent has become an essential ingredient as salt and pepper are in cooking. You wholeheartedly believe it is required in every recipe, but you’re not always sure of the right amount or when to apply it.
With our increasing reliance on intent data and its broadening definition, now is a good time to assess the state of intent and plan on what might be ahead.
I tapped into a group of trusted B2B marketers to gain perspective on all things intent. In this article, we will:
- Sprinkle in knowledge gained from a recent roundtable with B2B marketing leaders on the data, tools and processes used in sales and marketing account-based go-to-market (GTM) motions.
- Get a broad view from three savvy data and intent executives who have seen a few things in building Michelin-rated worthy GTM strategies.
Together, we can capture a snapshot of intent’s current state, understand the challenges and opportunities and preview what should be on the menu going forward.
What is the number one value proposition of intent in today’s GTM efforts?
Marketing is playing a larger, more proactive role in the buying-selling process. With B2B buyers and buying teams spending more time doing their research online and through peer networks, sales has less access to buyers.
This big shift has thrust intent into the spotlight to identify and prioritize the right accounts to reach out to based on account and buyer behavior and, in turn, catapulting outbound sales and outreach as today’s number one intent use case.
Mike Burton, co-founder and head of commercial sales at intent industry pioneer Bombora, puts it this way:
“Because sales sit so close to revenue, intent data can galvanize action and increase sales productivity. This sales use case has a compound effect making other GTM functions more impactful including demand gen, SDRs and field marketers.”
Orchestrated timing between sales and marketing still remains a significant challenge, largely because of the data, tech and process silos that exist across departments.
Intent data is being relied on to integrate GTM motions and define roles across functions helping sales and marketing stay in sync and to identify the best opportunity accounts at the right time.
Kerry Cunningham, director of research at revenue technology leader 6Sense, shares:
“Most buyers are researching your solution and don’t know your company or solution exists. Here’s the reality — you lose 100% of the deals you don’t compete for. The goal is to never miss an opportunity when your solution can solve a customer problem or fill a need.
Intent plays an essential role in exposing account timing and need to prioritize account and buyer engagement.”
Dig deeper: How to leverage intent and engagement in the buying cycle
What can GTM leaders do now to get more value from intent signals?
Sales and marketing teams are not leveraging intent to its full value or potential yet.
Beyond account identification and prioritization (timing), more GTM teams are starting to apply intent to identify and align buyer and account needs with contextual content and messaging.
David Crane, VP of portfolio marketing and marketing chief of staff at intent aggregator Intentsify, says:
“If we boil down all the use cases across all the GTM functions that leverage intent data, the common denominator is efficiency.
“Rather than marketers, BDRs, sales pros and customer success reps having to spend valuable time and effort to understand buyers’ specific needs and pains, they can gain insights directly from intent signals.
“Done right, GTM teams can quickly supply buyers with the information they want (e.g., content, creative assets, talk tracks) when they need it.”
As more GTM teams adopt account-based tools and more effectively use their websites to implement and manage ABM programs, intent’s value is increasing.
More than a quarter of an ABM platform’s value is the intent data it generates to use in sales and marketing activities, according to Gartner.
When intent powers ABM tools and an organization’s webpages and these components are used together, marketers highlight the increased intelligence they can put to work resulting in higher conversions to sales opportunity and revenue.
Cunningham emphatically states:
“The most valuable signals we don’t pay attention to are on your website. Only 3% of visitors fill out forms, so relying on this tactic is futile. Rather, deanonymizing traffic and using intent is the key to unlocking immediate opportunity. GTM teams need to harvest this info otherwise, you will waste all that marketing and sales time and effort.”
Dig deeper: Using intent as a unit of B2B campaign measurement
With the changing B2B buying-selling landscape, experts highlight that to get more value out of intent data investment, we must:
- Focus on where and how to apply intent during the GTM process.
- Collapse data and functional silos that leave big gaps.
Bombora’s Burton cites two areas in his work across more than 650 customers:
“The first is using intent for strategic planning. This means understanding what is happening across different cohorts of your total available market (TAM) and where your target accounts are in their buying stages.
The second is augmentation of first-party anonymous data, especially as third-party data becomes scarcer. We see leading organizations creating a first-party data mart and augmenting it with intent data. Having this info appended allows for precision targeting at scale.”
Crane weighs in on what he is seeing across a rapidly growing Intentsify customer base:
“First, GTM teams and the data science and ops teams that support them, need to get better about baking intent data into their GTM strategies from the start. Today, intent data is treated more like an after-market component that individual roles use but don’t always share across functions.
Secondly, GTM teams need to improve how they convert intent signals into actionable insights as well as their processes for quickly acting on those insights while the data is still relevant. These challenges are likely a consequence of difficulty in effectively leveraging multiple intent data sources, which we see more and more B2B teams focused on solving.”
Intent as marketing’s essential ingredient in GTM strategy
Intent data is seeing an unprecedented rate of adoption as B2B GTM teams focus on:
- Efficiency and productivity internally.
- Customer experience and engagement with buyers and accounts externally.
While outbound sales are the top use case today for intent as noted by our experts, we’re seeing marketing teams be the driver of activation. As Cunningham succinctly summarizes:
“Marketing’s job is to ensure organizations never miss out on an opportunity to compete for a deal; this is how marketing becomes indispensable!”
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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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