Connect with us

MARKETING

The Plain English Guide to Demand-Side Platforms (DSP)

Published

on

The Plain English Guide to Demand-Side Platforms (DSP)

As a marketer, you might be focused on creating organic content most of the time. But you should keep in mind that paid advertising is just as important.

When you manage the paid ads for your business, you can go through individual ad managers such as Google Ads or Facebook Ads. However, that’s not the only option. You can also use demand-side platforms (DSP), which are automated, as a way to purchase and manage your online ads.

According to a 2021 study published by Statista, the US was the largest programmatic advertising market worldwide, spending an estimated $70 billion in 2020. Marketers are increasingly using DSPs as a way of purchasing, managing, and tracking online advertising. Below, let’s review all the basics about DSP advertising.

With a DSP, you can purchase mobile ads on apps, banner ads on search engines, and video ads on Facebook, Instagram, Google, and even more platforms. Instead of using both Google Ads and Facebook Ads, for instance, you can purchase those ads in one place on a DSP.

The purpose of this is to make ad buying faster, cheaper, and more efficient. Now, let’s dive into how DSP platforms work and why you should use one.

How do DSPs work?

DSPs work by using programmatic advertising, which is the buying and selling of ads in real-time through an automated system. With real-time bidding, ad placements are auctioned off in milliseconds.

When you get started with DSP advertising, you’ll need to begin strategizing how much you want to spend. Think about what an effective cost per click and cost per action might be. This will help you set up your online ads so the platform knows how much to spend in any given auction.

The best DSP platforms will allow you to include multiple rich media ads, including video, images, and animation.

Why use a DSP?

The main reason for using a DSP is that it makes your digital ad experience easier and more cost-effective. You can control, track, and maximize all your digital ads in one place. This means you can manage an entire ad campaign across sites on one dashboard. For example, you can show someone an ad on Google, then show them ads on Facebook, and then across other sites they visit — all in one campaign. Before DSPs, those would be separate campaigns on Google and Facebook Ads.

This means you can advertise on many networks, including all the major publishers, in addition to more. With the number of networks, you’ll have a more global reach.

Additionally, DSPs often partner with third-party data providers, giving you better tracking and reporting capabilities than a single network usually provides. And in the planning process, the targeting options are more personalized, meaning you can get better conversion rates.

When you’re choosing a platform to work with, you’ll want to look at how many ad exchanges the DSP has access to because that affects how many people you can reach. Plus, you’ll want to consider cost, training (full service or self-service), support, and ease of use.

Now that you know more about DSP advertising and how it works, let’s discuss the platforms that can help you do it.

1. Basis Technologies

DSP example Basis Technologies

Image Source

Best for: Large or enterprise level companies

Basis Technologies is an omnichannel DSP built to generate better outcomes for your ad campaigns. One of the best features is that it uses AI machine learning to automatically analyze data from numerous campaign parameters to optimize your ads.

With this DSP, you’ll be able to target hyper-local audiences across devices and multiple touchpoints. You’ll also get access to the industry’s leading exchanges, along with 25,000+ audience segments across over 30 different data providers.

Why we like it: Basis Technologies harnesses the power of machine learning to analyze data and automate processes.

2. Google Marketing Platform

DSP example Google Marketing Platform

Image Source

Best for: Small to large businesses or agencies

Google Marketing Platform is Google’s unified advertising and analytics platform for smarter marketing and better results. This DSP has several products for both small businesses and enterprise companies, including Campaign Manager 360 and Display & Video 360 (formerly DoubleClick).

With this product, you can save time with cross-channel ad management to maximize insights and optimize media and creative performance across all your digital campaigns. The flexibility is the standout feature of this DSP. You can use third-party features and integrations so you can choose the capabilities that best help you manage and measure your campaigns.

Why we like it: Google’s products are designed to work together, but also give the flexibility to use third-party features and server to server integrations.

3. Knorex

DSP examples Knorex

Image Source

Best for: Mid-sized to large advertising agencies

Knorex is a universal advertising platform that automates personalized marketing across channels, devices, and ad formats. You can market on Google Search, Facebook, Instagram, and LinkedIn all in one place.

This DSP also uses AI to learn from past data to predict and adjust ad budgets dynamically in real-time to drive higher efficiency.

Why we like it: Knorex values security, offering a variety of brand privacy and security tools out of the box.

4. Jampp

DSP example Jampp

Image Source

Best for: Gaming apps and companies looking for a mobile DSP solution

Jampp is a DSP that leverages unique contextual and behavioral signals to deliver customers and in-app purchases through programmatic advertising.

The key features of this platform are user acquisition, app retargeting, geolocated ads, dynamic ads, and predictive bidding. This is mainly a mobile user acquisition and app retargeting DSP where you can focus on mobile-first ads.

Why we like it: Jampp’s app retargeting helps re-engage existing customers and uses their previous behavior to predict whether or not they will convert.

5. Smadex

DSP example Smadex

Image Source

Best for: Companies needing a mobile-first DSP solution

Smadex is a mobile DSP engineered for growth. The platform uses a combination of its own programmatic advertising technology, machine learning, and first-party data.

With this platform, you can reach global audiences at scale and re-engage audiences with its retargeting capabilities.

Why we like it: Smadex values security just as much as helping your brand scale. It ranked #1 for fraudless DSP installations by Kochava Traffic Index and holds an IAB (Internet Advertising Bureau) Gold Standard certification.

6. MediaMath

DSP examples MediaMath

Image Source

Best for: Mid-sized to large agencies that want a custom solution

MediaMath is a customizable DSP that provides brands with a myriad of options for managing their campaigns. Opt to use their built-in creative tools to run ads on their server or choose one of your own. You can even use APIs to run on top of your core foundation.

Why we like it: MediaMath’s product is not a one-size-fits-all DSP. Brands can tailor their components to build an advertising solution that suits their needs.

7. Amazon DSP

Amazon DSP

Image Source

Best for: Ecommerce brands that want to advertise on Amazon (and Amazon-owned sites)

Amazon is one of the world’s largest online retailers, so it’s no surprise that brands would want to tap into their advertising audience. Both advertisers who sell products on Amazon and those who don’t can use Amazon DSP. They offer two options: self-service and managed service. With self-service, brands are in full control of their ad campaigns. Those who are new to programmatic advertising or need guidance are advised to use the managed option, however that comes with a $35,000 minimum spend.

Why we like it: Amazon DSP can greatly increase brand awareness for sellers on and off Amazon.

DSPs Still Require Research

When you choose a DSP, make sure you understand how many inventory sources it accesses, which third-party data integrations it offers, and what targeting criteria are available. To successfully run programmatic ads on a DSP, you’ll need to reach global audiences with personalized ads. While using a DSP simplifies paid ad management, it won’t replace customer research and having a clear idea of who your target audience is.

This article was originally published March 5, 2021, and has been updated for comprehensiveness.

paid media template


Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address

MARKETING

YouTube Ad Specs, Sizes, and Examples [2024 Update]

Published

on

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!

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

Why We Are Always ‘Clicking to Buy’, According to Psychologists

Published

on

Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

(more…)

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

A deeper dive into data, personalization and Copilots

Published

on

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.”

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

Trending