MARKETING
How to manage email addresses in a customer data platform
The main purpose of a customer data platform is to merge all your customer data into one place, where you can orchestrate online and offline campaigns based on customer attributes, transactions, or behavior. As a very simple example, you can find the people who frequent your pages about skiing and send them an email when you get a new ski-related product in stock.
Such a campaign is only possible if you’ve been able to enrich the customer’s online profile with their email address.
In other words, your prospect may have purchased something from you, so you have his information in your store, and he may also visit your website. Still, until you can merge those records, you can’t use his on-site behavior to send him appropriate messages. Knowing how to enrich an online profile with an email address is a study in itself and beyond the scope of this article, although I discuss it in some depth in this short video.
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It’s nice to think that once you’ve attached an email address to an online profile, you can merge customer data on that email address, and voila, you have your single customer view.
Nothing is that easy. Some of your customer data won’t have an email address, and people usually have several email addresses that change over time — due to changing jobs, mergers and acquisitions or simply from creating personal addresses on several different systems.
This is where you need to make an important decision. The idealistic goal of a CDP is to merge all your customer data, but the reality is that might not be worth the trouble. It all depends on what you expect your CDP to do and think through that. You need to compare customer data scenarios with your use cases.
The simple path is to make the email addresses unique. You have a separate record in your CDP for each email address. That means you might have multiple records per customer, which seems to contradict the whole point of a CDP — which is to have a single view of the customer — but that solution is perfectly okay for some use cases.
To get into this a little deeper, it’s helpful to discuss the distinction between online and offline profiles.
Let’s say I worked for CompanyX in 2020, and my email address at that time was [email protected] While at CompanyX, I attended one of your webinars, so you have a record for me in your customer database that includes that CompanyX email address.
In 2021 I left CompanyX and started with CompanyA, where my email address changed to [email protected]
In 2022, you invested in a CDP and imported all your webinar information, which created a profile for [email protected] (the out-of-date and now useless email address). That same year, I visited your site. Your CDP created a profile based on that visit — that is, it put a cookie on my web browser and started recording the interactions I had with your website – but it didn’t know who I was. When I downloaded your white paper using my current email address — [email protected] — I changed from unknown to known (hurray!), but you still don’t know that I attended one of your webinars because that account has me as [email protected]
How are you going to get a single customer view?
Even though the CDP has a profile for [email protected], who attended your webinar, that profile is essentially useless. The email address is defunct, and it doesn’t correspond to any active online profile, so you can’t target me as a webinar attendee on your website. If you create a segment of “people who attended webinars,” that profile will be included, but it won’t do you any good. It won’t be actionable.
The example points out the limitations of merging profiles based on email addresses. You simply won’t get all the information you have on your customers into one record.
As an alternative, let’s say the form to download the white paper included name and address. Now — assuming I used my home address, which stayed the same from 2020 to 2022 — you have the possibility of merging my CompanyX record with my CompanyA record. Now you can target me on the web as a webinar attendee.
The overall point is that you have to think through the many to one problem with email addresses. One person — Greg Krehbiel — has many different email addresses and potentially many different touch points with your company that are associated with those different email addresses. If you can’t merge those profiles into one record, you won’t have a complete view of your company’s connection with me.
Does that matter? Maybe, maybe not. My actionable profile — the one where you have what I do on your website and my current email address — will not include the fact that I attended your webinar.
Is that a big problem? It depends on how often you think it will happen and the consequences of getting something wrong. For example, it’s one thing to fail to include me in a list of “past webinar attendees,” but it’s another to include me in a list of “people who have never attended a webinar.”
The challenge here is that you can go down quite a rabbit hole trying to solve every edge case and exception. The more you think about it, the easier it is to come up with ordinary events that will mess up your data.
- What if there’s a typo in an online form to collect an email address?
- What happens when a company changes the structure of its email address (e.g., from first initial, last name @ company dot com to first name dot last name @ company dot com)?
- When someone calls customer service and changes their email address, how will you deal with that when you re-import the data?
You can drive yourself crazy thinking of how things can get messed up.
So what do you do?
As mentioned above, the simplest thing is to have one email address per customer profile. But that means you’re giving up on the idea of a “single customer view.” If that’s okay — if you think through all your use cases, and it doesn’t matter too much — then go with that.
Another option is to allow the email field to have multiple email addresses. The only downside to that approach is that email is no longer a unique identifier for your customer profiles. But you can always use something else.
Here’s an exercise for you to figure this out. Come up with a list of scenarios where someone’s email might change or why they might have multiple emails:
- Changed job.
- New personal email.
- Serious email and junk email.
- IT guy at the company decided to change the format of the emails.
- The company changed its name, etc.
With that list in one hand and your merge rules in the other, review all your use cases. In what situations will you fail to get a “single customer view”? How big of a problem does that pose to your overall strategy, and what do you hope to get out of your CDP?
If you don’t think long and hard about how you intend to manage your customers’ email addresses, your CDP implementation is likely to disappoint you. The guidelines in this article should have put you on a path to uncovering the right solution for your unique requirements.
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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