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Let consumers tell you how they want to be contacted

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Let consumers tell you how they want to be contacted

Ping. “Don’t bother me.”

Consumers don’t like being reminded to buy something. But they will tolerate it if they have some say in how they are notified.

Preference centers are emerging as a way for digital marketers to stay in touch with their customers without displeasing them. Brands can set-up a front-end where consumers can choose how often they want to be notified, through which channel, as well as what kind of information they are interested in hearing about.

The technique yields zero-party data and can be used to build a long-term customer relationships. But trust is required, so don’t be evil. Customers will enter this bargain so long as you promise to respect their wishes and keep their data private.

Back in the Stone Age…

…marketers tried hard to figure out how often they could contact their customers, usually via e-mail. Even time of day and the substance of the message were taken into account as “judgment factors”. But that approach was not foolproof.

“Email marketing can cause inbox fatigue.” noted Alex Cash, director of strategy at OneTrust PreferenceChoice, which offers a consent and preference management platform. “As people have become flooded with marketing emails over the past few years, they become irritated and sometimes ignore inboxes altogether. Unfortunately for marketers, this means fewer opens and more unsubscribes.”

“Our pockets have been buzzing and beeping more [in] the years since the introduction of the iPhone.” said Nirish Parsad, practice lead for privacy, identity and marketing tech at Tinuiti. “We’ve got text messages, push notifications, and various forms of in-app notifications, all fighting for some attention. So, the shortcomings? If your comms strategy in 2022 is just email, that’s a lot of effort for a 20% open rate, if you’re lucky.”

“In the past, B2B and B2C both had very detailed and granular preference centers, with the hopes of limiting the number of unsubscribes, but that over-complicated the operation.” said Lauren Harrison, senior marketing consultant at CloudKettle, a consulting firm. Sometimes firms asked for too much information. “Preferences were ignored, and recipients stopped wanting to fill the whole form out.” she said.

Ready, ask, aim, fire

So why not ask the customer how they want to be informed, and let them set the controls? That sounds easy. But marketers must give a lot of thought to how they want to set up a preference center. What information can you ask for without frustrating the customer? You don’t need to find out their entire life story when you ask them to fill out a form.

 “Think about your onboarding experiences, quizzes and surveys, and areas where preferences can be remembered to make the experience better.” Parsad said. “Customers want personalization, so it’s important to use this information to transform the web experience. You’re learning a lot more about them than just their name, email and address.”

Cash put the preference center in a strategic context, as part of a data management strategy. “Marketers should look for solutions that can integrate with existing customer journeys and UIs like webforms, whilst also providing flexible UIs out of the box for additional data and consent capture.” he said.

“A preference center is not an ideal place for data collection for B2B and B2C, as it really should empower the user to manage how they would like to be communicated.” Harrison said. “In collecting information about [the customer] and their preferences, you are allowing them to control the content.”

Build it right and they will come

Marketers can make strategic choices when constructing the preference center. But those choices should be supported by data. Here A/B testing comes into play. “Develop a few different versions of the form, asking different questions and measure which has the most form fill-outs, and which has the most people drop off part way through.” Harrison said.

“Another method is doing focus groups with customers to obtain feedback directly from them on what works and doesn’t.” Harrison added. “It is a good practice to have someone outside of marketing/sales review the form to ensure it makes sense and is not too complicated.”

“Marketers can gauge success from several metrics: Opt-in and opt-down rates, unsubscribes, or the development of first-party and zero-party data sets.” Cash said. Analysis can determine “which initiatives are most effective, and shine light on how trust and transparency are leading to ROI.”

“Net promoter score (NPS) is a great indicator, and I wish marketers used customer delight metrics to guide various strategies.” Parsad said. “Customer loyalty and retention are other great metrics to start looking at.”

Read next: How to extract value from zero-party data

Don’t miss these steps

Pay attention to the details, since mistakes will compromise the preference center and undermine your marketing strategy.

Harrison pointed out the need to work with a graphic designer to make sure the e-forms look good and render well across all browsers and devices. Avoid asking for information you don’t need. Be sure you can deliver on your promise, whether it is a communication limited to certain topics or frequency. “If you give an option to set communication limits, make sure you actually have the technical ability to comply with that request.” Harrison said. “Finally, ask yourself if you are compliant with anti-spam laws. Remember that this is based on the location of the recipient, not your business.”

“Consider a preference center as a growing component of the user experience.” Cash said. “Do winning marketers develop a marketing plan one year and then rinse-and-repeat the same plan every year after? Of course not, and preference management is the same.”

Parsad put down this checklist:

  • A preference center pulls in any part of your organization that communicates or interacts with the customer. Marketing, sales, customer service, operations, billing, etc. 
  • Map out all the interactions, and identify all the areas where you are capturing data – both zero party and first party. 
  • Be transparent, and prepare to give your customers control over their data. 
  • Choice, control and transparency are what are necessary. 
  • Deliver immediate value.

About The Author

Let consumers tell you how they want to be contacted
William Terdoslavich is a freelance writer with a long background covering information technology. Prior to writing for Martech, he also covered digital marketing for DMN. A seasoned generalist, William covered employment in the IT industry for Insights.Dice.com, big data for Information Week, and software-as-a-service for SaaSintheEnterprise.com. He also worked as a features editor for Mobile Computing and Communication, as well as feature section editor for CRN, where he had to deal with 20 to 30 different tech topics over the course of an editorial year. Ironically, it is the human factor that draws William into writing about technology. No matter how much people try to organize and control information, it never quite works out the way they want to.


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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

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!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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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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