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Tips to incorporate knowledge collection into your daily workflows

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Tips to incorporate knowledge collection into your daily workflows

This week at Forrester’s B2B Summit in Austin (my first in-person event in years), Jackie Palmer, VP of product marketing at Demandbase, and I chatted about the inconveniences inherent to our current working culture and environment. She told me she’d heard from one of my colleagues the day before, but because she’d been out enjoying dinner and drinks, she’d snoozed the message so she could get back to it later.

We agreed on these points: thank goodness for snoozing and what a relief it is that we can also now schedule messages (emails, Slack DMs, texts, etc.) to be sent at a later time. Both of these technological breakthroughs let us get things done when time permits, allowing busy professionals to squeeze in a quick few minutes of work here and there (while out to dinner, for example) without getting completely bogged down when the task turns out to be less bite-sized than we originally expected.

Checked an email but don’t have the time or resources to reply immediately? Put it back in the queue or schedule it to reappear when you’re likely to have everything you need. Had an idea you want to share with a colleague? Jot down your message but schedule it to arrive in their inbox when they’re sure to be focused on work.

Last week, I laid out a framework for personal knowledge management and shared some of the apps in my toolbox. This time, I’ll share some techniques for knowledge capture that take advantage of technology to ensure the right bit of info is in the right place at the right time. (It strikes me that this is the same language we use when we discuss getting customers and prospects to engage with our content.)

2022 MarTech replacement survey2022 MarTech replacement survey

The main idea behind all of these workflows is that for each type of information you’re gathering — a person’s contact info, a task that needs doing, an insightful article you want to find later, etc. — you have a single endpoint with multiple inputs. So, no matter the context (squeezing in a check of the mobile phone, completely on-task at your desk, multitasking in a virtual meeting, etc.), you have an easy way of getting that information to the right place so it can be surfaced at the right time.

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You can collect and put information of any type in the right place for later use, no matter your current context.

The ubiquitous form

I’m a huge fan of forms for information collection because they give you so many options on the other end. You can slice and dice data, or just treat it like freeform text.

Zapier browser extension + ??

Zapier offers an extension for Chrome that lets you set up a form to appear as a right-hand sidebar next to whatever you’re doing. One great use for this is when I need to add new contacts to my database, or when I’m collecting information about vendors when I’m researching for our MarTech Intelligence Reports (MIR). Sometimes, this information will arise when someone introduces me to someone else via email. Other times, I start this process from online research on a webpage.

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Here’s what the Zapier Chrome Extension looks like in your browser window

In any case, to ensure the information goes to the right place, I tap on the Zapier extension for Chrome which gives me a sidebar where I can grab info from my main screen without leaving that context. At the moment, I want contact information to be stored and accessible from a whole bunch of different places, so I use a Zapier zap to send that kind of info to Google Contacts, ClickUp, Airtable and (because I’m testing it right now) Folk. I input it once and click on the send button and voila — no more duplicate data entry or cutting and pasting. It’s not perfect, but it helps a lot.

Bonus: Here’s a link to my Zapier zap that does this, which you can customize to your own application

JotForm

We ask vendors in the categories we cover in our MarTech Intelligence Reports to complete forms that quiz them about their companies and their product offerings in the tech sector we are examining. This helps ensure we ask the same questions of every vendor and, with some types of questions, we can turn answers directly into charts or graphs. The final section of the questionnaire asks for their views on the trends driving the category as a whole. This qualitative information is super valuable info for me, so I use Zapier to ensure their answers end up in Mem, where I can surface it when I’m outlining and writing.

I use these forms internally, too. They have a lot of capabilities that make them more powerful than the Zapier browser extension, and one of the most important is the ability to use drop-downs, checkboxes and radio buttons. These types of inputs ensure that you get consistent, structured data, without pesky alternative- or misspellings, typos, etc.

With this consistent data, it’s much easier to slice, dice and analyze the resulting data without doing a big cleanup. When I’m collecting information on vendors in various categories in the early stages of MIR research, I use a form that feeds data into Google Tables or Airtable, where I can analyze it all later. I’ll set my desktop up where I’ve got the form on one side of the display and the information destined to be input on the other. Because I use dropdown fields like “Software Category,” where I can choose from various options, I can later look at all of the companies in that category side by side, though I can jump from category to category when I’m collecting information.

Email forwarding or BCCing

As a marketer, you probably do a lot of work in email. However, email interfaces — however well-designed — aren’t the ideal places to surface the information that you share and receive via email. So, when you’re considering what elements to include in your personal knowledge base, make sure that email forwarding is supported as a means for importing information.

With some tools, like ClickUp, I can BCC a certain email address when I’m sending a message that’s related to a particular task, and that email (as well as many replies) will be included in the “comments” field of a task.

Recording + AI transcription

This is something I’ve used for virtual meetings (be sure to get permission), webinars or events, Twitter chats, podcasts and the like. Once you’ve recorded speech, drop it into Otter or Speak for automated transcription, then dump the transcription into your unstructured repository (be sure to keep the original audio in case the auto-translation is less-than-accurate).

Read it later

I use Pinboard (the evolution of what was delicious) to capture two kinds of information: articles that look promising but I don’t currently have time to read, and articles I’ve read that I want to refer to later — such as when I’m assembling something I’m writing. If you pay for the “archive” account ($39/year), Pinboard keeps a local copy of the content on the URLs you’ve bookmarked. Later, you can find relevant info via tags or full-text search even if the original content source is no longer online.

Conclusion

These are just a few of the ways I try to ensure important bits of information don’t pass me by in the course of the day. I hope they spark a few ideas for you that can help you smooth your workflow. I’ll explore organizing and surfacing that information in the weeks to come.


About The Author

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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.”

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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