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5 tips to increase user adoption of new martech tools

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5 tips to increase user adoption of new martech tools

One of the most common challenges organizations face concerning their martech stack is user adoption. Gartner’s 2020 Marketing Technology Survey showed that only 58% of marketing organizations utilize the full breadth of their martech stack’s capabilities.

If your end-users are not embracing a tool, it will be impossible to take full advantage of its capabilities. Under-utilization of tools can hurt your martech team’s reputation and the ability to get budget for future technology implementations. Therefore, it is critical to get your end-users engaged and using new technologies early and often.

Here are five tips to help drive user adoption of new martech tools.

Tip #1: Build a super user group and make them your advocates

It is natural for end users to resist the inevitable changes when asked to adopt new technology. Even if you upgrade or replace a tool users have complained about for years, you should expect some resistance. A new technology, even a better one, requires additional work for your users to learn the tool and adjust their day-to-day routines. This is where building a super user group can be a huge asset.

  • Invite a small subset of your end users to be your super users. Try and pick people that have a lot of influence over their peers.
  • Include your super users as early as possible in the process to feel some ownership over the tool. If it is possible to invite them to join and weigh in on the “bake-off” between the final two tools during the buying process, all the better.
  • When onboarding the tool, utilize the super user group as your main user testing group. Take as much of their feedback as possible, and take the time to explain why some customizations they ask for may not be possible. The better they understand what the tool can and cannot do, the more likely they will share those explanations with their peers once the tool is live.

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Tip #2: At launch, don’t be afraid of training tactics that won’t scale

The first impression that many users have of the new technology is often the one they will stick with, regardless of how many changes or improvements you make to the tool. If your tool gets a negative reputation amongst your initial users, that negativity will spread to future groups of users in other divisions or to new employees joining the team.

That is why it is so important that you go above and beyond to make sure your users have a good first impression when launching a new tool. Do not be afraid of implementing training tactics that may not scale over the long term, like doing 1:1 sit-downs or video calls with your users and walking them through the tool personally.

These tactics may not be viable as you roll the tool out to larger and larger groups. But if the tool has a solid reputation from the initial user group, these tactics may not be needed as you grow. Future users will be looking forward to getting their chance to use it and, therefore, are more likely to take advantage of your more scalable training resources.

Tip #3: Offer a variety of ongoing training resources

A critical misstep that often befalls marketing technology implementations is taking a one and done approach to user training. Even if your initial training plan is successful, it is important to continue to offer a variety of training resources on an ongoing basis. This ensures that users will have the opportunity to upskill in the tool and take advantage of new features and offers additional opportunities for those late adopters not to be left behind.

  • Short webinars and “tips and tricks” videos. Video training can be especially effective for software. Create videos that enable users to follow along and see the software interface. Break these down into five to 10 minutes snippets for specific use cases or tasks and provide a link to a library of these videos.
  • Office hours. Establish regular office hours where users can drop in, ask their personal questions, and get 1:1 help from an administrator. Keep a log of what types of questions come up during office hours, and use those frequent questions as topics to create a short video training about. Offering these sessions can also encourage users to occasionally hold off on sending their questions via an email, IM, or support ticket if they know they can get them answered during office hours.
  • Newsletter or Slack channel. Provide links to new training videos, offer a “tip of the week” and communicate minor updates or bug fixes via a regular newsletter or slack channel.

Tip #4: Provide rewards or recognition for top users

Show off your top users and the wins they generate from taking advantage of the tool. If your general population of users can see tangible success stories from their peers, they will be more motivated to try and create a success story of their own.

  • Highlight “key win” case studies and remember to share these with your vendor. The vendor may choose to share it within their network, giving even more positive exposure to your top users.
  • Write or record a fun 1:1 interview with the “user of the month.” If it aligns with your company culture, you could even create a funny, over-the-top type of trophy (perhaps take some inspiration from college football teams’ turnover gimmicks) for the user to proudly display on their desk while they hold the title.
  • Offer gift cards or company swag to the top users monthly or quarterly.

Tip #5: Take advantage of vendor or outside resources to execute quick wins

One of the best ways to drive the adoption of a new tool is to generate some quick wins. If you are having trouble delivering on a particular project or idea within the tool, whether due to inexperience or lack of internal resources, do not just push that project “down the road.” Users will get frustrated hearing repeatedly that the changes they desire are coming in a future phase or at a later date. You need wins!

  • Use your customer success manager. Many SaaS vendors will provide you with a dedicated customer success manager (CSM) to support your account. SaaS companies have recognized the importance of retaining clients. As a result, customer success roles grew at the sixth fastest rate in the U.S., according to LinkedIn’s 2020 Emerging Jobs Report. Take advantage of your CSM. Don’t fall into the trap of only talking with your CSM once a quarter to get a high-level update of what’s on their product roadmap. Their role is to make you successful and turn you into an advocate who will drive referrals for their product. Use them. Meet with them frequently to talk about ideas or projects you’re working on, and ask them to pull in resources on their side to help execute. Often they will be able to call in favors with technical resources, or they can connect you with other clients who can help talk you through how they solved a similar challenge.
  • Plan and budget for outside help (if possible). When making your pitch for the new technology, include some budget for your implementation partner, third-party agency or outside contractors to help administer the tool for a limited “warranty period” after launch; ideally, for 60 to 90 days. No matter how much user testing you do before the official launch of the technology, there will inevitably be bugs to fix or new ideas that you will want to be able to execute quickly. Having a plan and a budget for expert resources to help you deliver those wins will generate goodwill for the tool, ultimately increasing user adoption.

Maintaining or growing your martech budget year over year often depends upon your ability to demonstrate tool utilization and report on a strong ROI for your martech stack. Your users have to actively engage with your tools to have a chance to deliver on that positive ROI. To give your team and your tech stack the best chance at success, invest in user adoption strategies when implementing new tools.


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


About The Author

5 tips to increase user adoption of new martech tools
Megan Michuda is currently the SVP, director of marketing operations and innovation at BOK Financial. Prior to joining BOK Financial, she served as global head of marketing technology at Janus Henderson Investors. Janus Henderson was a Stackie Award winner in 2018. Megan is currently responsible for BOK Financial’s marketing technology stack, marketing automation, digital analytics, and marketing operations. In 2020, Megan’s startup Stacktus was acquired by CabinetM, a leader in martech management. Megan is now both a user of CabinetM as well as an advisor. Megan received her bachelor’s degree from Brown University and her master’s of science in technology management from University of Denver.


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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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