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(Re)Introducing your favorite Optimizely products!

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(Re)Introducing your favorite Optimizely products!



It’s important to us that you, our valued customers and partners, can identify with the tools you use daily.  

In that pursuit, Optimizely set out to simplify the way we talk about our product suite. That starts, first and foremost, with the words we use to refer to the technology.  

So, we’ve taken a hard look at everything in our portfolio, and are thrilled to introduce new names we believe are more practical, more consistent, and better representative of the technology we all know and love.  

You may have seen some of these names initially at Opticon 2022 as well as on our website. In the spirit of transparency, the team here at Optimizely wanted to make sure you had full visibility into the complete list of new names, as well as understand the context (and rationale) behind the changes. 

So, without further ado… 

Which names changed?  

Some, but not all. For your ongoing reference, below is a complete list of Optimizely products, with previous terminology you may be familiar with in the first column, and (if applicable) the new name in the second column.  

Used to be… 

Is now (or is still)… 

Meaning… 

DXP 

Optimizely Digital Experience Platform 

A fully-composable solution designed to support the orchestration, monetization, and experimentation of any type of digital experience — all from a single, open and extensible platform. 

Content Cloud 

Optimizely Content Management System 

A best-in-class system for building dynamic websites and helping digital teams deliver rich, secure and personalized experiences. 

Welcome 

Optimizely Content Marketing Platform 

An industry-leading and user-friendly platform helping marketing teams plan campaigns, collaborate on tasks, and author content. 

DAM 

Optimizely Digital Asset Management 

A modern storage tool helping teams of any size manage, track, and repurpose marketing and brand assets (with support for all file types). 

Content Recs 

Optimizely Content Recommendations 

AI-powered and real-time recommendations to serve the unique interests of each visitor and personalize every experience. 

B2B Commerce 

Optimizely Configured Commerce 

A templatized and easy-to-deploy platform designed to help manufacturers and distributors drive efficiency, increase revenue and create easy buying experiences that retain customers. 

Commerce Cloud 

Optimizely Customized Commerce 

A complete platform for digital commerce and content management to build dynamic experiences that accelerate revenue and keep customers coming back for more. 

PIM 

Optimizely Product Information Management 

A dedicated tool to help you set up your product inventory and manage catalogs of any size or scale. 

Product Recs 

Optimizely Product Recommendations 

Machine-learning algorithms optimized for commerce to deliver personalized product recommendations in real-time. 

Web 

Optimizely Web Experimentation 

An industry-leading experimentation tool allowing you to run A/B and multi-variant tests on any channel or device with an internet connection. 

Full Stack 

Optimizely Feature Experimentation 

A comprehensive experimentation platform allowing you to manage features, deploy safer tests, and roll out new releases – all in one place. 

Personalization 

Optimizely Personalization 

An add-on to core experimentation products, allowing teams to create/segment audiences based on past behavior and deliver more relevant experiences. 

Program Management 

Optimizely Program Management 

An add-on to core experimentation products, allowing teams to manage the end-to-end lifecycle of an experiment. 

ODP 

Optimizely Data Platform 

A centralized hub to harmonize data across your digital experience tools, providing one-click integrations, AI-assisted guidance for campaigns, and unified customer profiles. 

 

So, why the change?  

 It boils down to three guiding principles:  

  1. Uniformity: Create a naming convention that can be applied across the board, for all products, to drive consistency 
  2. Simplicity: Use terms that are both practical and concise, ensuring the names are something that everyone can understand and identify with  
  3. Completeness: Develop a framework that showcases the full and complimentary nature of all the products and solutions within the Optimizely suite 

 As the Optimizely portfolio comes together as a complete, unified platform, it’s important that our names reflect this, as well as support our 3 key solutions (i.e. orchestrate amazing content experiences, monetize every digital experience, and experiment across all touchpoints).  

Other questions? We’ve got you covered. 

Q: Why have you made these product name changes? 

    • We wanted to simplify how we talk about our portfolio. The renaming applies a naming convention that is both practical and concise.  

 

Q: Do the new product name changes affect the products I own? 

    • No, there is no impact to product functionality or capabilities.  

 

Q: Do the new product name changes affect who is my Customer Success Manager or Account Manager?  

    • No, there are no changes to your Customer Success Manager or Account Manager. 

 

Q: Do the new product name changes affect the ownership of the company?  

    • No, ownership of the company has not changed. We have only made changes to the Product Names. 

 

Q: Have any contact details changed that I need to be aware of?  

    • Only contact details for former Welcome customers has changed. These are the new contact details you should be aware of: Optimizely, Inc.| 119 5th Ave | 7th Floor | New York, NY 10003 USA. Phone: +1 603 594 0249 | www.optimizely.com 

 

Q: Where can I send any follow up questions I might have?  

    • If you have any questions about the Product Names, please contact your Customer Success Manager or Account Manager.  


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MARKETING

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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