MARKETING
A Privacy First-World Won’t Hurt Your Customer Relationships, It Will Transform Them: Insights from HubSpot’s CMO
As marketers, we thrive on data.
Data can help us identify when content is underperforming, and pivot to provide the highest value to our prospects and customers. It can also enable us to explore new, underutilized channels, and discover the best platforms to connect with our audiences.
All of this is to say: Any changes to the existing data collection ecosystem will create uncertainty around the future of marketing, and make some marketers fearful about how their current strategies will perform in a privacy-first world.
But a privacy-first world doesn’t inhibit a company’s ability to know and better serve their customers — it improves it. A privacy-first world is a world in which creating and maintaining relationships directly with your customers is the only way to truly understand them.
Here, we’ll explore how the future of privacy will impact your business. Plus, how you can prepare for it.
What is a privacy-first world?
A privacy-first world means that a company’s strategies, technologies, and solutions will need to adhere to a consumer’s right to data privacy and security, first and foremost.
This shift has been a long time coming. Consumers no longer trust corporations with their data — in fact, only about one-third of customers believe companies are currently using their data responsibly.
Additionally, in the past year alone, 76% of consumers feel they don’t know what companies are doing with their data.
To combat consumers’ concerns, regulations such as the EU ePrivacy Directive CCPA, and LGPD are increasingly requiring transparency around data collection, making a privacy-first marketing strategy necessary to reach global audiences.
Certain industries have always taken a first-party data approach when it comes to building relationships with their audiences . Nonprofit and advocacy organizations, for instance, have always leveraged data collected directly from their supporters and donors for marketing materials. So while a privacy-first world might be new for some businesses, it’s not new for all.
Why Privacy-First Matters
As consumers raise their standards in regards to data privacy and security, it’s vital that the advertising industry adapt to meet these needs.
A privacy-first approach ultimately encourages marketers worldwide to develop stronger and more transparent relationships with prospects and customers.
First-party data allows you to better understand your customer based on information they have consented to share with you, which in turn allows ads to be more relevant.
Plus, caring about your customers’ data is simply good business practice. A privacy-first strategy will become a competitive advantage in the years to come.
So the real question here should be: how can you prepare for a privacy-first world? Let’s dive into that, now.
How can you prepare for a privacy-first world?
We need to reimagine our marketing and advertising strategies to ensure company growth doesn’t come at the expense of consumers’ trust.
As Google’s Director of Product Management, Ads Privacy and Trust, David Temkin, puts it, “Developing strong relationships with customers has always been critical for brands to build a successful business, and this becomes even more vital in a privacy-first world.”
To invest in and prepare for privacy-safe growth, companies need to shift to a first-party data model. Marketers that effectively use their first-party data can generate 2X the incremental revenue from a single ad placement or outreach.
To adjust to a privacy-first world, marketers will need to ensure they have systems in place to collect and measure first-party data effectively. A CRM, for instance, allows you to collect, track, and analyze your first-party data while providing your visitors with the transparency and knowledge that their data is being used for more personalized messaging and a better user experience — not for following their every move across the web.
First-Party Data Use in Action
There are tremendous advantages to first-party data when it comes to marketing. Let’s say, for instance, that you recently eyed a Casper pillow, filled out a form with your email, but got distracted and abandoned the site. Later, you spot this email in your inbox:
Here, Casper marketers are using first-party data to analyze your behavior on their site. Once they’ve identified that you might be interested in a pillow, they can send a targeted, personalized abandoned cart email to encourage you to complete the transaction.
HubSpot and Google’s New Integration for Better First-Party Data Collection
For HubSpot customers, we have good news: HubSpot will be offering an integration with Google’s Enhanced conversions (EC) for web in the coming months. Among other benefits, Enhanced Conversions allows companies to increase the amount of observable conversions they can measure, and ultimately improve their return on ad spend. Visit this page to learn more and stay up to date on HubSpot’s Enhanced Conversions launch.
Zoe Financial, a wealth planning platform, has seen a 200% increase in revenue by leveraging the current integration between Google Ads and HubSpot. With the addition of Enhanced conversions in the coming months, Zoe plans to continue to take full advantage of the suite of products Google and HubSpot have, thereby optimizing their marketing and client acquisition strategies.
The Founder and CEO of Zoe Financial, Andres Garcia-Amaya, said, “Our north star is the client, and clients value their privacy. Partnering with Google and HubSpot helps ensure the two-way communication of our client’s data in a safe way.”
To excel in a privacy-first world, marketers need to leverage clean, first-party data to measure and optimize their advertising and audience strategies. And they need to realize the full value of investments in first-party data solutions.
Change is always difficult. For marketing teams that have relied for years on third-party data for their advertising strategies, it will take time to adjust to this ‘new normal’ when it comes to data privacy. However, this privacy-first shift should empower marketers to use their privileges to gain trust, rather than to lose it.
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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