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Living the agile marketing values: A do’s and don’ts guide

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Living the agile marketing values: A do’s and don’ts guide

If you’re looking for some actionable ways to live out the agile marketing values in your everyday work life, we’ve put together this handy guide for you to share and discuss with your team.

Value #1: Focusing on customer value and business outcomes over activity and outputs

Do’s:

  • Discuss desired outcomes before beginning any work.
  • Measure success at early intervals. Did the tactic perform as expected?
  • Be willing to pivot and change work that under-performs.
  • Double down on high-performing marketing.
  • Have team members focus on collaborating to finish all pieces of work (writing, design, etc)  and have it customer-ready.

Don’ts:

  • Reward people for output or hours worked.
  • Work on things just because they are in the plan.
  • Measure teams on the number of stories they did – often less is more!
  • Focus on tasks of individual roles.

Many marketers struggle to apply agile marketing in a way that adds value to team members. Learn how to break that pattern in this free e-book, “MarTech’s Guide to agile marketing for teams”.

Click here to download!


Value #2: Delivering value early and often over waiting for perfection

Do’s:

  • Think in terms of minimally viable; what’s the simplest version we can get out there that still meets our desired outcome?
  • Reduce the number of hand-offs and sign-offs needed to go live.
  • See where you can repurpose existing content and images.
  • Consider delivering what you have now, but adding the bells and whistles later (maybe your website just needs to be usable, but it can have more functionality later).
  • Can a non-expert pitch in and help? Perhaps you don’t need your best designer for some simpler pieces.

Don’ts:

  • Get caught up in analysis paralysis.
  • Spend too much time with upfront planning.
  • Wait until you have the ‘expert’ available if that person is in high demand.
  • Have an all or nothing approach to getting work in front of customers.

Value #3: Learning through experiments and data over opinions and conventions

Do’s:

  • Allow teams to experiment, even if they may get it wrong the first time.
  • Use A/B testing or other methods to learn how customers react.
  • Give people time for brainstorming and creative thinking of new ideas.
  • Show leaders the data behind a campaign’s performance, and use that to make decisions around future work.

Don’ts:

  • Keep doing what you’ve always done without questioning why.
  • Overload teams with deliverables or they won’t have time to experiment.
  • Be afraid to take risks and be wrong.
  • Take on work because a very important person thinks it’s a good idea if it’s not what customers are looking for.

Value #4: Cross-functional collaboration over silos and hierarchies

Do’s:

  • Form agile marketing teams with cross-functional skill sets in order to create fully customer-ready marketing initiatives.
  • Allow team members to work outside of their job title, rather than only within their specialization.
  • Encourage the entire team to be responsible for all aspects of work.

Don’ts:

  • Form teams with a lot of external dependencies.
  • Wait for the ‘expert’ to do work if it bottlenecks your team.
  • Create sub-teams within your team, handing off work from person to person rather than everyone collaborating.

Value #5: Responding to change over following a static plan

Do’s:

  • Keep changing your marketing backlog (prioritized list of future work) as you learn more from past campaign performance, customer feedback or market/environmental conditions.
  • Create quarterly roadmaps that show your campaign plans, but continually discuss them with stakeholders in real-time and swap things out as change happens.
  • Discontinue work that isn’t performing as expected or creating a high degree of customer value, even if it was part of a plan.

Don’ts:

  • Use ‘we’re agile’ as an excuse to continually insert new work at the last minute – that will actually hinder your teams’ productivity.
  • Spend too much upfront time planning work in great detail, or you may be wasting time.
  • Create plans that can never change.

Read my recent article, Living the 5 values of agile marketing and visit the Agile Marketing Manifesto for more in-depth information.

Marketing work management: A snapshot

What it is: Marketing work management platforms help marketing leaders and their teams structure their day-to-day work to meet their goals on deadline and within budget constraints, all while managing resources and facilitating communication and collaboration. Functions may include task assignments, time tracking, budgeting, team communication and file sharing, among others.

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Why it’s important today. Work environments have changed drastically due to the COVID-19 pandemic. This has heightened the need for work management tools that help marketers navigate these new workflows.

Marketers have been at work developing processes that allow them to work with those outside their own offices since marketing projects—campaigns, websites, white papers, or webinars—frequently involve working with outside sources.

Also, with marketers required to design interfaces, write content, and create engaging visual assets today, more marketers are adopting agile workflow practices, which often have features to support agile practices.

What the tools do. All of these changes have heightened the need for marketing work management software, which optimizes and documents the projects undertaken by digital marketers. They often integrate with other systems like digital asset management platforms and creative suites. But most importantly, these systems improve process clarity, transparency, and accountability, helping marketers keep work on track.

Read next: What is marketing work management and how do these platforms support agile marketing

The post Living the agile marketing values: A do’s and don’ts guide appeared first on MarTech.

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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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