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Knowledge management for content marketers: My tech stack

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Knowledge management for content marketers: My tech stack

Knowledge management for content marketers My tech stack

While I’m not technically a content marketer, the workflows I’ve developed as a journalist and researcher can benefit anyone creating content in our diverse, information-rich environment. In this article, I’ll explain my philosophy and share the elements that are working for me, with the aim of sparking ideas that benefit your content marketing program and, by extension, the audience you’re trying to reach.

First, let me take a step back and explain a term I used in the headline: Knowledge management. I remember back in high school learning about how the U.S. economy was becoming driven by information. As a budding writer, it instantly made sense to me — I was going to be a “knowledge worker.” What wasn’t so clear back then was how complex this task of knowledge management was going to be. Instead of going to a library and furiously documenting book-borne facts on notecards, today, the information is everywhere.

The knowledge juggling act

1651242238 958 Knowledge management for content marketers My tech stack

I have ADHD, so this issue may be more intense for me than for others, but do you ever find yourself lying in bed at night going through a mental list of things you’re afraid of forgetting? It’s like you’re juggling dozens of bits of information in the foreground of your mind, which is preventing you from doing the important job of recharging your brain with a good night’s sleep.

Taming the beast

The goal of knowledge management, in my view, is taming all of the important information coming at you — emails, newsletters, trade publications, webinars, events and even conversations — so it’s available when you need it, and only when you need it. For content marketers, some of the things you might want to manage include:

  • Article ideas.
  • Points you want to make in upcoming articles.
  • People you want to interview or otherwise tap for their wisdom (such as asking a colleague to do a blog post for your company’s site).
  • Research material, including writing by others as well as data.
  • Your editorial calendar and the status of content in production.

A few factors make this challenging. First is the fact that different types of information are optimally stored in different ways. An editorial calendar might be best captured on, say, a calendar application, or something organized in a temporal order. Information about people and companies lends itself to a CRM-type organizational scheme, with multiple contacts per company. Content status might call for a checklist or other task-management application. Data might be best stored and analyzed in a spreadsheet.

1651242238 824 Knowledge management for content marketers My tech stack

And then there’s everything else — web content you read that sparks ideas, a white paper you download that makes an important point you want to cite, a great infographic or data visualization whose structure would apply perfectly to something you want to express, a Twitter thread that captures the zeitgeist better than you ever could by yourself. I’m sure you get the idea. And I haven’t even mentioned email.

I’ve struggled with this for years and tried just about every productivity tool you can imagine, but, recently, perhaps because of advances in machine learning and artificial intelligence, things in my world are starting to take shape. The principles guiding my knowledge management these days include:

  • Use as few tools as you can. Switching contexts and cutting and pasting are time sucks, plus they increase the risks of introducing errors. Given that guideline…
  • Get as close as you can to a “best-of-breed” solution for your use case. It just doesn’t make sense to store contacts in a Google Document or use a spreadsheet for things that can’t be sorted and filtered. You’ve got to be able to use the information you’re collecting. The key to making best-of-breed work is that…
  • Everything must connect as seamlessly as possible.

Here’s how I do it

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Over many free trials and proofs of concept, I’m settling into a few tools that I’ll describe to you below. I’ll start with connectivity here because it’s the most important element. With the ubiquity of APIs, connectivity should be a given. But not all integrations are created equal — the way an API is set up can make a difference between seamless synchronization and endless frustration.

  • For connecting things: Zapier. I’m not a coder, though I’m teaching myself how to use Webhooks and APIs with the much-needed help of Zapier. Typically, though, the built-in triggers and actions work just fine for most purposes. Honestly, I don’t know what I’d do without a tool like this. Zapier integrates with all the other tools and allows you to achieve the “flow” part of workflow.
  • For task management and timelines: ClickUp. While primarily a task management app, the company seems to aspire to be everything to everyone (with uneven results, thus far). The task management elements are fantastic and I love the flexibility and design of the interface — the usefulness of color coding cannot be overestimated.
  • For people and companies: Airtable and Noloco. Because my primary responsibility is to create our company’s MarTech Intelligence Reports, I gather a lot of data about marketing technology vendors, and, of course, the contacts at those companies are key. I’ve used ClickUp for tracking people and companies, but it’s clunky — it’s just not made to do that. The best combination I’ve hit on thus far is using Airtable to store and establish connections between different tables of data and Noloco to set up displays customized to individual users. I could share my whole Airtable with our sales team, but then their eyes would glaze over and they’d never find the information they need. Two observations: Airtable is trying to develop better views through its Interfaces beta functionality, but it isn’t quite there yet, in my opinion. And Noloco also works (in beta) with Google Sheets, though it’s very awkward at the moment. All this to say that I’d love to make this one tool rather than two, but nothing I’ve found seems to do everything I need in this area.
  • For gathering structured data: JotForm. Yes, there are better-looking form applications, but JotForm is incredibly flexible (offering conditional logic, direct integrations with lots of things, pre-filling, etc.) as well as CSS control of look-and-feel. I even use it internally when I’m gathering structured data like information that eventually goes into Airtable or ClickUp.
  • For unstructured data: Mem. This one could be an article in itself (and it probably will be, in the future), but, for me, Mem is where I dump “everything else” — emails, bookmarks, scrapes of web content, notes and transcripts from meetings and virtual events, etc. Eschewing the folder structure that made Evernote a non-starter for me, Mem connects your entries via hashtags and, now, the recently-debuted Memex artificial intelligence capability. The idea is that you are writing or looking at something in the main window of the tool, and Mem automatically surfaces everything that’s related in the right sidebar, making it easy to find “that thing I saw last month” that relates to the project I’m working on now.

There’s so much more to say, and in the coming weeks and months, I’ll continue to explore these personal-level technologies that can boost your productivity as a marketer. Stay tuned for deeper dives into the subjects I’ve touched on here, including specific examples of workflows that make a difference.


About The Author

20 questions to ask digital asset management platform vendors during

Pamela Parker is Research Director at Third Door Media’s Content Studio, where she produces MarTech Intelligence Reports and other in-depth content for digital marketers in conjunction with Search Engine Land and MarTech. Prior to taking on this role at TDM, she served as Content Manager, Senior Editor and Executive Features Editor. Parker is a well-respected authority on digital marketing, having reported and written on the subject since its beginning. She’s a former managing editor of ClickZ and has also worked on the business side helping independent publishers monetize their sites at Federated Media Publishing. Parker earned a master’s degree in journalism from Columbia University.

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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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