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Gather ‘Round the Campfire for the MozCon 2022 Day Three Recap!

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The MozCon 2022 Final Agenda Is Here!

If Camp MozCon has to come to an end, we wanted to send it off with a bang. After all, we have to get through the next 364 days before we get to do this again!

So, in true MozCon style, we brought in the good coffee, handed out more Roger figurines, and cheered on our best pals as they took the stage.

Now, we aren’t going to say we saved the best for last, but we have to admit that our camp counselors for day three were absolute powerhouses.

Why Real Expertise is the Most Important Ranctor Factor of Them All — Lily Ray

When it comes to E-A-T, there is no better person to look to than Lily. She kicked off the morning by reminding us that showing expertise to Google is paramount. But just because the word “expert” is in there, that doesn’t mean the tactics are overly complicated.

Lily shared multiple examples of businesses that are ranking for very competitive/authoritative keywords, and her analysis of how these sites rose to the top. Throughout this analysis, she reminded us that adding “E-A-T features” isn’t enough, and that our content actually has to be quality as well.

Some of the top websites noted in this session sported features like:

As she often does, Lily mentioned (and showed examples) how E-A-T may work across the Google universe such as YouTube, Google Maps, Google News, and so on. With this in mind, it’s imperative that we continue to build our authority on and off of our sites.

You Need Audience Personas, Not Buyer Personas — Amanda Natividad

Buyer personas can be helpful, but only some of the time, for some of the people on your team. That’s why today Amanda schooled us on the audience personas, why they’re important, and how to create them.

First and foremost, your audience doesn’t end at “people who will buy from you.” Your audience also includes people who may amplify you and people who may pay attention to you. And as it turns out, each of these audiences are looking to you for different types of content.

Each of these audiences has different motivations. They are also different in what they talk about and where they hang out. By understanding the way each of these audiences works, you’ll be able to create more effective marketing strategies.

Rabbit Holes: How Google Pushes Us Down The Funnel — Dr. Pete Meyers

As SEOs, we like to focus on the keywords that land toward the bottom of the funnel. This is because we know these keywords lead to more conversions and revenue. But as Dr. Pete would argue, there is far more to search than what happens between awareness and conversion. Apparently, Google would too, hence their article: “Decisions Decoded.”

In this talk, Dr. Pete focused on the Refine Search portion of the SERP. As he clicked on the refinements and interacted with the SERPs, he found himself further down the funnel. And if Google can make him do it, he figured they could make anyone do it — including our customers!

Dr. Pete argues that the majority of searches happen in the exploration and evaluation phase of decision-making. If we want to play in that game, we must allow users to go through this journey through our sites. This can be done by introducing the idea of the next step, creating more middle-of-the-funnel content, and by optimizing for Google’s search features.

Our site needs to be present at all stages of the funnel, not just at the bottom. If we rely on users to know what they want right away, we are alienating ourselves from potential profit.

Beyond the Button: Tests that Actually Move the Needle — Karen Hopper

We’ve all run a CRO test on button colors. But Karen urged us to go a step further and play with fire.

She taught us to be curious about what works for others, use the first-party data we have available, and monitor how certain users interact with our content. Then, using this data, she showed us how to create a meaningful hypothesis that included what we want to test, how we would test it, and what we expect to happen.

With all of these hypotheses, we then learned how to prioritize tests using expected impact, learning priority, and technical effort.

Now, we are ready to run the test! But in doing so, we need to understand the size of the audience necessary to prove the statistical significance and remember NOT to make any assumptions based on early data.

This talk was a bit of a math-heavy one, but definitely one we needed to remind us how to properly execute SEO testing strategies.

Understanding Key Performance Factors: Using Data to Make Smart Decisions for Organic Search — Joe Hall

SEO is a marathon, not a sprint, right? Right, but here’s the thing — “even marathons have finish lines.”

Clients want to see results and we have to deliver them. In order to do this, we have to shift our focus from what is important to what is impactful.

Every domain has unique characteristics that search engines understand. These unique characteristics are measured by what Joe calls “key ranking factors.” Each site also has its own goals, which can be measured by KPIs.

Key performance factors and key performance indicators, when used together, can help you prioritize impactful changes. Joe showed us how to collect the data for these metrics and find their correlation using the CORREL function. Once we have this data, we’ll be able to identify the recommendations that are most correlated to the KPIs set out by the client.

And yes, correlation doesn’t equal causation, but as Joe aptly puts – it doesn’t rule out causation, either.

Finding Your Way To SEO & Content Success: A Framework — Ross Simmonds

The king of content distribution is back and better than ever. Ross Simmonds taught us how to think like a media company so that we can stop halting at the word “content” and follow through with the “marketing” in content marketing. Doing so can show you up to 10x the pageviews.

The growth content framework Ross shared included four steps:

  1. Research

  2. Create

  3. Distribute

  4. Optimize

When we “think like a media company”, we need to think about distribution, development, finance, partnerships, and outreach.

A smart brand will distribute content in a way that keeps content relevant and hyped up for almost six months. We were reminded to tap into our owned channels, different niche opportunities, reframe the original content into a new format, and then to optimize for future success.

And here is the thing: Ross didn’t just tell us to do these things, he shared some of his secrets on how to make them scaleable too!

Things I Learned from Sales Teams that Every SEO Should Know — Petra Kis-Herczegh

Getting buy-in isn’t usually a linear process, and it’s hardly ever an easy one. Petra shared with us her theory of the “buy-in-ish” cycle, which goes: fake buy-in, half results, lack of proof, repeat.

This makes sense when we think of how most people go about getting buy-in. In most situations, people start by asking for questions that have no answer other than “yes”.

Our new goal is to focus on getting to the next step, not necessarily focusing on a sweeping “yes”. When you seek buy-in, you should engage in healthy conflict and spend time understanding the concerns and objections from stakeholders. By understanding your audience, you will be able to speak their language when proposing solutions.

In the actual proposal, Petra reminds us, it’s massively important to use the language spoken by decision-makers. After all, we aren’t logical decision-makers, we are biased and emotional decision-makers. With that in mind, we must play to the feelings of your stakeholders to make them comfortable with our ideas.

The Untapped Power of Content Syndication — Amanda Milligan

We care about what’s happening nearby. Yet local media remains untapped as a distribution resource, despite the fact that they also have respectable DAs. This is a missed opportunity.

The easiest way to create local content at scale is to tap into local data sets like the Census, Zillow, or Tripadvisor. Using this data, you can create content — or even better — tools!

Amanda shared an example of using AAA’s data to create a gas price calculator that they shared with local publishers. Spoiler alert: the publishers were stoked.

Because Amanda works for Stacker Studios, she has the pleasure of working with tons of publishers, and was nice enough to share with us the five things publishers are looking for:

  1. Employment & jobs trends

  2. Rent & real estate trends

  3. Trends in crime stats and rates

  4. Ways to avoid scams

  5. “News you can use” stories

Advanced On-Page Optimization — Chris Long

Chris turned a bunch of heads when he came out by claiming that we were in an on-page optimization rut. That’s because, eventually, most SEOs start to review old content and simply add a few keywords or internal links.

Chris covered the importance of making the shift from keyword-focused to entity-focused. To do this, you need to identify the most commonly used entities in top ranking content and ensure you’re mentioning them.

Another way to stay creative is to stay fresh. At Go Fish, they found that top sites were updating content as quickly as every eight minutes! To test the effect of this factor, they updated some of their pages’ titles, timestamps, and content (less than 5% of text) and immediately saw positive results.

If the data is outdated, why would Google trust that the content is trustworthy?

Chris covered five full strategies to become more creative with your on-page optimization, including a competitive research method that blew our minds. This session will definitely be one we rewatch.

Keyword Research for Thanks Instead of Ranks — Wil Reynolds

As he admitted in his presentation, the roots of what Wil presents will almost always be the same. He said it back in 2015, and he started off by saying the same thing again this year: “we have the power to influence what people find.”

It all comes down to customers, business, big data, and silos. If you want to be great, you have to overcome the things your competitors stop at. Your customers care about dollars, but when you report dollars, don’t just report on potential dollars. Dollars can be connected to opportunity costs, acquisition costs, and the like.

Keyword research builds empathy and can be used to speak to multiple people in the room, but be careful with your automated analyses and outputs. Wil shared how the Google Pixel 6 solved a very real problem for his family: a camera that can capture multiple skin tones in one image without under/overexposure. However, he then went on to show us how he could use keyword research for photography to address the real issues of potential Pixel 6 users. As it turns out, these issues should actually be taken to most of the decision-makers in a business (think UX, design, and DE&I).

The biggest takeaways from this year’s talk were to dig a little deeper, think about where you can add value, take the extra step and take every finding as a clue, and remember that “the limit to your greatness at work is how quickly you fold at your first no/can’t”.

This talk was filled to the brim with amazing insights, and we’ve barely begun to scratch the surface, so make sure you pick up the video bundle to see the full thing.

So long for now!

Well, campers, we hope you had as much fun as we did this year. It’s hard to put into words how much we missed hanging out with all of you, and we are so happy to have had the chance to do so the last few days.

This isn’t the end, though! We want to see what insights you grab during the replays and what things you put into action, and hopefully gather again next year for even more amazing learnings.

Happy camping!


Read all the MozCon 2022 daily recaps:



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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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