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Does your organization need a marketing automation platform?

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Does your organization need a marketing automation platform?

Marketing automation platforms are a critical part of the martech ecosystem for many businesses, offering many benefits by streamlining manual B2B marketing tasks, including lead management, email campaign development and landing page creation.

But deciding whether or not your company needs a marketing automation platform calls for the same steps involved in any software adoption, including a comprehensive self-assessment of your organization’s business needs, staff capabilities, management support and financial resources.

Have we outgrown our current marketing system?

Marketing automation is often a solution for companies that are growing rapidly and need to scale their efforts. If you have data in multiple databases that cannot be consolidated or are using an email system that can’t deliver the level of behavioral targeting you need, it may be time for marketing automation.

What marketing automation capabilities are most critical to our business?

Identify and prioritize your software requirements and the key capabilities you’ll need from the new system. Do your sales reps need real-time access to marketing data? Then native CRM integration is a must-have. Do you have a sophisticated social media presence? Then social marketing management and integration will be important. By knowing what you need, you’ll be in a better position to control the selection process and choose the platform that will most benefit the organization.

What kind of marketing automation platform do we need?

Marketing automation is not a one-size-fits-all solution; it’s important to find the right fit. Nearly all companies offer the same basic capabilities for email, website tracking and a marketing database. Additional capabilities vary, however, so it’s important to identify what you need. Is inbound marketing (social media, blogging, SEO) more important than outbound (email)? Are reporting and analytics the key features you need? Is lead scoring a crucial part of your marketing process? Do you need greater capabilities in audience segmentation and personalization?

What are our goals?

It is critical to know up front what your goals for the marketing automation system will be. Do you want to improve the quality of leads handed off by marketing to sales? Or increase revenue by increasing conversion at key stages in the buying cycle? Do you want to improve visibility into the buying and sales cycles to optimize marketing engagement? Or do you want to reach the growing portion of your leads that are mobile users? Bring key stakeholders together to establish the organization’s goals.

How will this platform integrate with our existing tech stack?

The odds are that you already have a tech stack in place, (e.g., several standalone tools for social media management, SEO, webinar hosting, etc.). You’ll need to identify them all so you can ask the marketing automation vendor about integration. Many vendors offer app marketplaces, which provide faster access to the participating systems. Virtually all marketing automation vendors offer APIs, but they may be an add-on to the price of the platform.

Does management support this purchase?

Every marketer should have an executive sponsor to secure support at the C-level. If you are not the ultimate decision-maker for this purchase, you will need management to buy into the idea before you go any further. Present a compelling case that the benefits of new software vastly outweigh the costs. This could include converting more leads, making sales more efficient and improving campaign ROI.

Do we have the internal skillset and staff necessary?

To maximize your ROI, staff will need training and a willingness to develop and execute new business processes. You may also need to consider several new hires. If your marketing and sales organizations have been operating in silos, they will need to work more cooperatively on lead scoring and routing systems, lead qualification definitions and more effective marketing collateral and communications. Identify someone in the organization who will take the lead on the selection process, as well as who will be using the system once it has been adopted.

How will we measure success?

This is one of the toughest questions, and ties in directly to understanding why you are adopting a marketing automation platform. If your goal is to increase conversions, you’ll need to know what your conversion rate is before automation in order to measure its impact. If it’s to improve email efficiency, be prepared with metrics on open rates, clicks, etc. In addition to measuring against your marketing goals, it’s wise to measure the depth and breadth of platform usage. Many marketers only use basic email capabilities, which ends up being a costly investment.

Have we realistically assessed the cost?

Some marketing automation platforms are all-inclusive, while others feature add-on tools and services that can significantly increase costs. In addition to the cost of the software license itself, consider the costs of ongoing services and training, as well as the indirect costs associated with getting staff up and running on the new system (i.e., more cooperation and data sharing between marketing and sales). If you don’t have your own IT or design staff, be sure to ask questions about what these services cost on an hourly basis. For example, if the platform offers templates, find out how many, and how much it costs to customize template design.

Snapshot: Marketing automation

For today’s marketers, automation platforms are often the center of the marketing stack. They aren’t shiny new technologies, but rather dependable stalwarts that marketers can rely upon to help them stand out in a crowded inbox and on the web amidst a deluge of content.

HubSpot noted late last year that marketing email volume had increased by as much as 52% compared to pre-COVID levels. And, thankfully, response rates have also risen to between 10% and 20% over their benchmark.

To help marketers win the attention battle, marketing automation vendors have expanded from dependence on static email campaigns to offering dynamic content deployment for email, landing pages, mobile and social. They’ve also incorporated features that rely on machine learning and artificial intelligence for functions such as lead scoring, in addition to investing in the user interface and scalability.

The growing popularity of account-based marketing has also been a force influencing vendors’ roadmaps, as marketers seek to serve the buying group in a holistic manner — speaking to all of its members and their different priorities. And, ideally, these tools let marketers send buyer information through their tight integrations with CRMs, giving the sales team a leg up when it comes to closing the deal. Learn more here.


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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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