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Indeed Advertising: How to Get Started

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indeed advertising how to get started

Indeed: Likely a place you think about looking for jobs if you’re in the market. But have you considered advertising on the platform? If you’re looking to start advertising on Indeed for the first time or the first time in a while, here is a bit of an overview to give you a path forward.

I started advertising on the platform for the first time a few months ago and was astonished by the limited “how to advertise on Indeed” resources out there. While definitely not all-encompassing, my hope is this blog gives you some confidence to take the first plunge.

Indeed Sponsored Jobs

Sponsored jobs are a way to make your listings stand out. Think of them like boosting job posts on a more macro scale. We’re looking to give job postings extra visibility and nudge more and highly-qualified people toward applying.

Indeed provides this synopsis of their platform here.

You decide how much to spend and we deliver relevant, quality candidate traffic. In this way, you can craft recruitment campaigns, track your return on investment and reach the widest audience of quality job seekers. While setting up your Indeed campaign, our team is available to answer any questions and help you make adjustments so you can reach your target audience.

If you’ve searched for jobs on the platform, you’re likely very familiar with these sponsored postings that populate above and below the organic results.

indeed sponsored post exampleJob Feed

If you already are advertising jobs organically on Indeed, then you have already taken the first necessary step towards advertising on Indeed. If you still need to link your job feed to Indeed, I recommend going straight to the source for submitting your XML Feed.

Here are a number of recommendations Indeed provides for ensuring your job listings perform to their best potential. Most of these are pretty obvious like don’t discriminate & don’t offend people but there are some solid reminders about being concise and specific.

While not something I plan on covering in-depth today, this is an area that can really impact performance. Your feed is essentially your Indeed landing page. Ensure your job descriptions are captivating and the names are consistent, then begin testing.

Campaign Structure

This is one major lever you can pull to significantly impact your ads’ overall performance. Similar to any search or social campaign, think critically about what your priorities are, how you’re budgeting, and how you’re reporting.

Segmenting the campaign by job type or location (if you have multiple) is likely going to be the best starting point. Think critically about how you’re graded on budgets or goals because that will likely be the main driving force for your structure. From there, you can refine by state, eliminate specific jobs, or do radius targeting. The filters are very limited here, but you can use phrase matching and negatives to refine postings to your liking.

I will say, you don’t really get a whole lot of options when building out a campaign. You’re basically just slicing and dicing the feed to reach the most specific set of jobs for your goal. Looping back to feed creation, it’s important to ensure job names are uniform enough to filter down in this instance.

indeed interface add jobsSimilar to paid search and paid social, there is no right way to structure your advertising account. There are simply different ways. I highly suggest approaching this with a testing mindset and continuing to refine and test as you go.

Automatic vs. Manual

One thing you’ll notice really early on is how little transparency there is on Indeed compared to other ad platforms. As a result, you’ll likely do what I did and lean towards manually pulling all of the levers you can (there aren’t many).

If you want to go the manual route, you get to choose your max CPC and pick between a couple of budgeting options. If you go the automatic route, you’re picking your monthly budget. As you can tell, there is not a whole lot of difference between those options. Your maximum CPC is going to become one of the few metrics you’ll use to manually control and test.

Max CPC vs. Automated

You have to option of setting a maximum cost-per-click or letting the Indeed system optimize. When I got started, I used another brand’s account to compare against and it gave me a baseline benchmark, but that’s all I had to reference. Indeed gives you very little information on averages for potential searches you’d be showing for so it’s a bit of a shot in the dark. I can tell you, CPCs are much lower than most ad platforms. The campaign I ran had average CPC’s in the $0.30 range.

I started with manual bidding and eventually switched over to automated. The before and after isn’t drastically different, but I have seen CPC’s creep down, especially when there are a lot of impressions to offer. During busy times, my average CPCs were half as expensive. I also had my max CPCs set at almost double that of the actual avg. CPC, which shows just how poorly informed my initial starting CPC was.

indeed interface campaign budgetsClick Balancing

This is one of the few other metrics you can tweak (opting in or out). Essentially, this setting allows you to either spread clicks across all jobs or let search-demand drive the clicks. I’d suggest testing this setting because you’re likely going to have very different results depending on the structure.

Indeed…Take the Wheel?

As you probably gathered by this point, control over your Indeed ads is minimal. Indeed doesn’t even provide search queries your ads are showing for, so good luck working within the advertising platform to do things like improving CTR.

It takes a change in mindset to adjust to this lack of control, even with all of the automation features we’re already using in other popular ad platforms. You are not really able to tinker or test in an organized fashion like we’re accustomed to in other ad platforms.

All that being said, Indeed is a channel with much lower CPCs and high-intent for job searches. If you work in an industry that has a lot of jobs that need to get filled (recruiting, staffing, you’re a large company), you should at least be testing Indeed ads.

If you’re looking for more PPC resources, including some forward-looking trends and projections, make sure to check out Hanapin’s Best PPC Resources of 2019, which is a compilation of our 10 best resources from the last year.

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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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