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Marketo’s October releases: A manager’s guide

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Marketo’s October releases: A manager’s guide

Marketo’s Dynamic Chat updates were aimed at improving user experience — from minor updates like automating meeting links within calendar invites to more major updates like allowing new data types to use more fields. 

The October release continues a series of Dynamic Chat chatbot enhancements. Previous chatbot enhancements are here. The release of Dynamic Chat is discussed here

Dynamic Chat now supports Boolean logic, integers and floating point data 

Dynamic Chat audience targeting was enhanced by adding support for data types that will enable the Marketo chatbot to target based on scores and answers to yes/no questions. Support was added for booleans, integers and floating point data. 

Didn’t get that far in math class? Here’s a quick rundown:

Booleans enable the chatbot to determine whether a field is “True” or “False” and store that value on the record.  

  • Why it helps: An organization may use the Boolean logic to ask questions that more accurately route customer calls. For example, if a prospect answers that she is in Canada and wants to speak to a salesperson — both are “true” in this case — her call could be routed automatically to the proper field office. This is known as “truth values” or “truth variables.”

Integer: Integers, commonly referred to as “int,” are whole numbers that can be either positive, negative, or zero. Integers cannot be a fractional number. Examples of integers are -2, 0, 2, 10 and 15.

  • Why it helps: Integers could be used to identify highly engaged leads. By leveraging the Lead Score attribute, an integer data type, Dynamic Chat users could define the audience criteria based on their score. In this case, the chat would only appear for leads with scores that meet the Lead Score defined in the audience criteria. 

Float: Short for “floating point,” this is a number with a decimal point. Floats are typically used when more precision is needed.

  • Why it helps: This feature will allow users to leverage more existing Marketo fields by syncing native and custom attributes across all three data types for better audience targeting. The data type can also be used to better target key accounts, something that all demand generation teams can appreciate. This increased level of precision will help create more meaningful experiences for both the visitor and the website.

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Automated updates to meeting invites 

Scheduling meetings in Dynamic Chat will be enhanced for both web visitors and sales representatives. 

  • For visitors: There will be an option to automatically include a Teams or Meet link in Google and Outlook calendar invites. This will be included in every calendar invite sent to visitors.
  • For sales representatives: Reps will now receive an automated email notification whenever a meeting is scheduled with them. They will also receive any relevant information about the visitor’s chatbot communications. 

Why we care: Nobody likes back-and-forths, and this update ensures meeting links are posted to both the visitor’s and the sales rep’s calendars. 

It’s also a time saver for Marketo admins and sales reps. Admins no longer have the task of sending conversations generated by Dynamic Chat sessions to sales representatives, and reps won’t have to go into Dynamic Chat to view conversations. 

New roles and permissions announced 

Any Marketo admin knows the frustration of users having too much access to the platform. This can lead to things breaking and ultimately, more work for the Marketo admin. We were excited to hear Dynamic Chat is offering more granular permissions. These custom user roles will aid in governing the visibility and usage of the application. 

The custom user roles are:

  • Full access: Designed for more advanced users, this role can take full advantage of Dynamic Chat, like publishing dialogues and editing the color scheme.
  • Read-only access: Suitable for sales representatives, this role allows users to view information, but not make changes. This role is still helpful, as the user can view the audience criteria or stream designer.
  • Restricted access: This user cannot view or access the Configuration or Integration sections.

Why we care: This update will make sales reps’ lives easier. They’ll be empowered to learn more about their prospects, without the assistance of admins. 

And since only admin-level access users can make revisions to the chat dialogue, unintentional changes will be minimized. 

Backend enhancements to Dynamic Chat 

Marketo will be improving the Dialogue canvas in Dynamic Chat (where the user builds out the chat stream) with the addition of a new feature that organizes the canvas into a clean and coherent format. All this is made possible with the click of a button through Auto Arrange. 

Prior to this update, the canvas was difficult to visually navigate. Now, the canvas can be organized in an organized, easy-to-read format. 

Why we care: We appreciate any update that saves us time. This update will be helpful from a usability standpoint, especially for those with more complex dialogues. Although this update is fairly minor, it will make it easier and more efficient for users to visually navigate their Dialogue Canvas. 

The Auto Arrange button can be found in the top right corner of the canvas (included as the last icon in the screenshot below).

What does it look like in action? Here’s a preview.

Dialogue canvas before utilizing the Auto Arrange feature.
Dialogue canvas before utilizing the Auto Arrange feature.
Dialogue canvas after utilizing the Auto Arrange feature.
Dialogue canvas after utilizing the Auto Arrange feature.

View the complete set of October 2022 Marketo Release Notes.

This article is presented through a partnership between MarTech and Perkuto + MERGE , a marketing operations consultancy.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.



About The Author

Lindsay DiLemmo

Digital Content Specialist at Perkuto. Detail-oriented wordsmith with a passion for creating memorable content that tells a story. Over 4 years of experience in the digital marketing space, focused on SEO-driven content, social media strategy, and boosting brand awareness. Loves hot yoga, traveling, and spending time with my partner and two French bulldogs.

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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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