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Optmyzr Launches Rule Engine for Microsoft Ads Management

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New advanced tool helps pay-per-click (PPC) professionals implement their strategies for Microsoft Ads accounts with the same efficiency as Google Ads

pay-per-click (PPC) pros to expand their use of the platform as a mainstream way to reach audiences via paid search marketing.

LOS ALTOS, Calif., April 15, 2020 (GLOBE NEWSWIRE) — Dynamics of Internet search are shifting dramatically in the face of pressures from the COVID-19 pandemic and economic turmoil. More people are turning to Bing and Google to gather information and engage in commerce. Bing now accounts for approximately 34 percent of all web searches, requiring pay-per-click (PPC) pros to expand their use of the platform as a mainstream way to reach audiences via paid search marketing.

Optmyzr is a leading provider of PPC management software, doing business since 2013. Rooted in Google Ads management, the company has consistently added functionality specific to Microsoft Ads and other platforms, including Amazon and Facebook. ” data-reactid=”14″ type=”text”>Los Altos-based Optmyzr is a leading provider of PPC management software, doing business since 2013. Rooted in Google Ads management, the company has consistently added functionality specific to Microsoft Ads and other platforms, including Amazon and Facebook.

Today, Optmyzr unveiled the general availability of new Bing-specific functionality with the release of Rule Engine for Microsoft Advertising. Much like its Google Rule Engine counterpart, the new Optmyzr tool allows PPC pros to be more nimble working across major search platforms. PPC pros can now easily create custom PPC optimizations, automate bulk changes to Microsoft Ads, and create advanced strategies that combine their business data with Microsoft Ads data.

At its core, Rule Engine for Microsoft Advertising allows easy creation of custom PPC strategies. The new tool provides an intuitive step-by-step campaign setup wizard that includes pre-built strategies addressing a wide range of common business challenges. PPC pros can incorporate multiple rules in sequences that tap into shifting conditions and actions in search marketing campaigns.

For example, ready-made recipes help PPC pros uncover expensive keywords or product groups and then automatically adjust bids associated with those PPC campaigns. The pre-built recipes can also analyze conditions to help manage bids against target cost per acquisition (CPA) or target return on ad spend (ROAS), and other specific objectives.

“There is more pressure than ever on PPC pros to deliver results across the primary search engines, due to the immediate COVID-19 crisis. It’s more important than ever that we offer tools to help search marketing pros be more effective, agile, and strategic when working across platforms,” said Frederick Vallaeys, co-founding CEO of Optmyzr. “While the main search engines have automated many core PPC functions, our tools allow PPC pros to go much deeper setting up their own rule-based automations with point-and-click ease. We want to help PPC pros navigate these challenging times with more insight and powerful tools to adjust quickly against changing dynamics.”

Sprinter is a popular sporting goods retailer based in Spain. With online and retail presence, it serves customers across multiple geographies in a hyper-competitive industry. The paid search team is continually tasked with a need to align keyword strategies with inventories, promotions, seasonality, economic dynamics, and a wide range of other factors that impact revenue. Sprinter was among the early users of Rule Engine for Bing.

“We like to bid manually in our Brand campaigns, as we prefer not using automated strategies to achieve the minimum CPC,” said Manuel Vilella, senior paid social executive with Sprinter. “As we have some dozens of brand keywords, we need a solution to adjust the bid according to the viewability. Rule Engine allows us to forget about implementing these changes, as it does this automatically.”

The Rule Engine for Microsoft Advertising is now generally available as part of the full Optmyzr PPC Management Suite. Users can take advantage of the added functionality at no additional cost. Optmyzr has created several capabilities for Microsoft Advertising over the last few years, bringing greater alignment of overall PPC management across the leading search engines.

Rule Engine for Microsoft Advertising. ” data-reactid=”22″ type=”text”>Find more information about the Rule Engine for Microsoft Advertising.

About Optmyzr

www.optmyzr.com.” data-reactid=”24″ type=”text”>Optmyzr’s PPC management platform provides intelligent optimization suggestions that help advertisers across the world manage their online advertising more effectively. It includes a full-featured PPC reporting tool that connects with Google Ads, Microsoft Ads, Facebook Ads, Google Analytics, Google Merchant Center and many other data sources through Google Sheets. The company was founded in 2013 by former Google and Microsoft executives, including Google’s AdWords Evangelist, Frederick Vallaeys. The Optmyzr PPC suite includes over 30 tools to improve Quality Score, manage bids, find new keywords, A/B test ads, build new campaigns, manage placements, and automate budgets. Optmyzr’s excellence in PPC management software was recognized as Best PPC Management Suite for the 2019 US Search Awards and UK Search Awards. More information is available at www.optmyzr.com.

Joe Thornton

Aimclear

612-355-9692

[email protected]

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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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