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9 Marketing Automation Mistakes You Can’t Afford to Make

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According to a 2021 HubSpot Blog Marketing Trends Report, 69% of marketers surveyed say they use automation in their marketing role.

Whether automation is a new or standard practice in your company, we want to help you avoid common traps marketers often fall into.

In this post, we’ll discuss them and alternatives that solve these challenges.

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1. You have dirty data.

In a 2021 state of marketing automation report, 58% of B2B professionals say the number one tactic that most amplifies the success of their marketing automation tool is quality data.

Dirty data can cost brands not only money but also time, as they take actions based on inaccurate information.

This can be anything from duplicate records and naming inconsistencies to outdated contact information and incorrect attribution.

A simple example of dirty data is an email list that’s never been cleaned. Your list likely has disengaged users, spam addresses, and duplicate emails that threaten the integrity of your data.

This will lead to low engagement numbers, damage to your IP reputation, high email marketing costs, and a loss of leads.

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For your automation to function properly, it’s essential that you work with clean data to ensure your work will be worth the effort you’re putting in.

2. You picked the wrong automation tool.

A HubSpot Blog research report on media and content planning revealed that finding the right tool is a roadblock for many marketers.

In fact, 45.9% of those surveyed who don’t rely on marketing automation say the biggest obstacle they face is that they can’t find platforms with the capabilities they need.

In addition, 59% of B2B professionals say they don’t feel they’re utilizing their marketing automation tools to their fullest potential, according to the state of marketing automation report.

So, not only are marketers struggling with picking tools, they also struggle to use them.

Picking the right marketing automation tool is essential, as it will determine how successful your strategy is. Here are the top features to look for in marketing automation software:

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  • User-friendly, intuitive interface
  • Advanced analytics and reporting
  • Knowledge base and customer support tools
  • Integrations
  • Scalable options

Check out this article on the top marketing automation tools available on the market.

3. Your marketing and sales teams aren’t aligned.

The worst thing you can do with marketing automation is operating in a silo. At the end of the day, marketing is a function designed to support sales, products, and other business sectors.

As such, it’s imperative that your marketing team bring in all necessary stakeholders to build workflows that align with teams beyond your own.

This is particularly important with marketing and sales teams who work hand-in-hand to turn leads into marketing-qualified leads (MQLs) then sales-qualified leads (SQLs) and finally customers.

Have you thought about what processes would benefit your sales team? This could look like an automated email from a sales rep once a lead has completed a high-intent behavior.

Of course, to define what that behavior is, you have to define that with the sales team.

Marketing automation software can enable sales reps to focus on converting leads instead of tedious tasks.

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4. You don’t train your team.

According to the state of marketing automation report, 31% of B2B professionals say the most significant barrier to using marketing automation tools is lack of training, the most popular answer after lack of resources.

Automation tools are powerful but worthless if your team doesn’t know how to use them.

Holding training sessions will ensure that key stakeholders know your tool’s capabilities, are aware of current workflows and understand the processes to create new ones.

Here are a few tips for training your team:

  • Curate your training to the team – Information overload is a very real thing. To prevent this from happening and keep your sessions productive, only teach what’s relevant to that team.
  • Invite service provider reps to participate – No one will know the software better than its reps. Reach out to your provider and see if they provide training sessions.
  • Hold a multi-step training process – One session likely won’t be enough to efficiently train your team. Make sure you hold multiple sessions, using a combination of various learning strategies to promote learning.

5. You set and forget.

Although automation does suggest a set-and-forget approach, the reality is it’s very hands-on.

The difference is that your attention is going to something else. Instead of focusing on output, you can direct your attention to assessing performance and optimizing.

6. You only leverage only one type of automation strategy.

Too often, marketers start using marketing automation, get familiar with one set of tasks, then focus on that. Never expanding beyond what they already use.

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This is how you miss out on opportunities to improve your brand. Take advantage of all of the features your software offers to maximize efficiency.

There are probably a lot of little tasks over the course of your work day that don’t seem time-consuming individually. However, if you add up all of the time you spend posting on social media, updating contact information, and other tasks, you end up with a large chunk of your day spent on things that can probably be automated.

Poke around your marketing automation to see which processes you can make more efficient. For example, in the HubSpot software, users can bulk update lead contact information instead of clicking into each record and changing details there.

The more processes you automate, the more time you’ll have each day to strategize with your team about content, lead generation, and lead nurturing tactics to keep attracting quality leads to your site.

Here are automation strategies you can leverage:

  • Chatbots
  • Task management
  • Lead scoring
  • Lead nurturing
  • Contract/quote automation
  • Lead rotation
  • Drip campaigns

7. Your automation software doesn’t integrate with your CRM.

A marketing automation system is supposed to make marketing easier. A CRM system is supposed to make managing leads and customers easier.

If your automation software and CRM don’t talk to each other, then you are making a lot more work for yourself.

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Before deciding on marketing automation and CRM platforms, make sure they can integrate with one another, and make sure you have the budget to make it happen.

8. You don’t have a goal.

Take advantage of the ease of use marketing automation software provides and invest time and efforts into determining your goals first. Once you have them, you’ll want to assign these goals to each automated effort – social media, email workflows, and so on – to ensure it’s easy to track progress.

After all, marketers need a way to measure success when it comes to marketing automation, and one means of doing so is by evaluating goal attainment. For example, here at HubSpot, the Visual Workflows tool lets you set a specific goal for each automated workflow.

A goal might be a new lead transitioning into a marketing-qualified lead based on certain behaviors, such as downloading a specific number of content offers.

HubSpot Visual Workflows also allows you to track the percentage of contacts in each workflow that achieve the goal, which is another great way to measure the success and ROI of your marketing automation.

9. You don’t segment your email list.

You have a database full of qualified leads, but you’re using marketing automation software to blast out tons of emails that aren’t customized at all. As a result, your leads are churning because your emails aren’t useful to them.

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The solution? Develop a lead nurturing strategy that includes email list segmentation so you’re sending specific emails to specific people that they’re more likely to open.

With the right marketing automation software, it’s easy to execute an email list segmentation strategy that delivers strong results. For example, HubSpot customers can use the Visual Workflows App to target their emails based on dozens of criteria, both demographic and behavioral.

Marketing automation is a powerful tool for any company – the trick is knowing how to optimize it and which pitfalls to avoid. By keeping these in mind, you’ll ensure your automation is working at its maximum potential.

Editor’s Note: This post was originally published in Nov. 2016 and has been updated for comprehensiveness

Free Resource: How to Reach & Engage Your Audience on Facebook

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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.”

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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.”

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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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