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MARKETING

5 Years a Leader : Taking a Look Into What Sets Us Apart

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11 B2B Content Ideas to Fuel your Marketing (with Examples)

Editor’s Note: In the 2022 Magic Quadrant for CMP (Content Marketing Platforms), Gartner has once again named Welcome a Leader, positioning us furthest to the right for ‘Completeness of Vision’ and highest for ‘Ability to Execute’ for the 5th consecutive year.

Five years in a row!

We’re thrilled to share that once again we’re positioned furthest for ‘Completeness of Vision’ and highest for ‘Ability to Execute’ — as well as ranked the #1 vendor across all three use cases (B2B Demand Gen, B2C Narrative Design, & Complex, Distributed Marketing).

You might wonder if, after all these years, we’d get tired of this honor. Nothing could be further from the truth.

In fact, we could not be more excited about this latest result.

We believe this repeated recognition is a testament to our commitment to innovation and customer success and validates the investments we’ve made to help customers transform how marketers experience the world of work every day.

Read on for more details about the Welcome platform and what we believe sets us apart in this year’s Gartner Magic Quadrant for Content Marketing Platforms.

Why Gartner Named Welcome a 5x Leader

Welcome’s platform helps marketers create and deliver content through faster, repeatable processes that solve for enterprise-level use cases.

Here’s what we believe distinguished Welcome from the pack:

1. Seamless Integration with Tools You Use Daily

Welcome’s codeless app marketplace offers a low-effort way to provide interoperability between our content marketing platform and more than 100 downstream systems/channels (e.g. CMS, Social, Sales Asset Management, enterprise DAMs, and more). This enables marketing teams to integrate with a large range of MarTech capabilities in just a few clicks. The marketplace is part of Welcome’s goal to create an operating system for marketers where all marketing activities can be managed within the platform. In fact, Welcome received the highest possible score for content distribution.

2. Content Goes Atomic, Up Goes Personalization at Scale

Welcome is one of only a few CMP vendors supporting atomic content strategies and production, an emerging content distribution capability. Others in this market use AI to make content recommendations based on engagement data. Welcome automatically generates a variety of modular content assets to support personalization for specific audiences and channels. When a new content asset is created, the platform will automatically suggest variants for different channels (e.g., social media-friendly and blog-friendly versions). The speed and ease of creating and tagging atomic content help content marketers achieve more scale and have greater impact.

3. Generative AI for Real-Time Content Creation

Welcome is the only content marketing platform featured in this Magic Quadrant using generative AI to help content marketers write new content based on a small number of provided inputs. These units of atomic content can be automatically assembled into variants for distribution across different channels. This not only increases the efficiency of content creation but results in the ability to develop content targeted to the needs of key personas. Additionally, AI helps automate the work assignment process and optimize how work is completed over time. 

4. The Analytics Edge

Welcome is also one of a few vendors offering advanced content performance analytics, going beyond SEO-analytics to measure content engagement across the entire customer journey and to demonstrate the impact of content on pipeline generation. Welcome’s AI/ML capabilities use past content performance to recommend future content and improve content production processes. Its highest scoring use case is for complex, distributed content marketing teams due to its strength in content performance analytics, for which it was rated ‘excellent’ (highest possible score).

B2B and B2C marketers at complex, enterprise organizations seeking advanced content creation and distribution features powered by AI/ML capabilities that support scalable processes should consider Welcome’s offering.

What Now?

Welcome’s product roadmap will continue to focus on expanding AI-generated content capabilities, enhancing atomic content creation capabilities for greater personalization, and enabling marketing teams to manage all their marketing activity — using Welcome’s full complimentary suite of content marketing, work management and data asset management capabilities.

Meanwhile, Welcome’s acquisition by Optimizely, the world’s leading digital experience platform, will only accelerate the two companies combined vision to allow marketers to manage the full digital experience lifecycle — from content ideation & planning through distribution & experimentation — all from a single, unified platform.

Editor’s note: for more details about the combined Welcome x Optimizely product offering & roadmap, check out this post by Shafqat Islam, CEO of Welcome.

Thank You for an Incredible Year—More Awaits in 2022

Helping customers be successful will always be at the center of everything we do. Welcome is not in the business of simply selling solutions to customers. We are in the business of enabling digital transformation and growth by being a strategic partner to our customers.  We believe our placement in this latest Gartner Magic Quadrant is a reflection of our customer centricity. It’s part of our DNA, and it’s what feeds our innovation as we continuously develop a future-ready CMP solution for our customers. 

Get a complimentary copy of the full report here.

Gartner, Magic Quadrant for Content Marketing Platforms, Nicole Greene, David Millstein, Jeffrey L. Cohen, 16 March 2022​.

Gartner Peer Insights reviews constitute the subjective opinions of individual end users based on their own experiences and do not represent the views of Gartner or its affiliates. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Welcome.​

5 Years a Leader Taking a Look Into What


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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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