MARKETING
What’s an API and how are they connected to a headless CMS
We all know the situation: when you can’t hear what someone’s saying, but after three “sorry, what was that?” attempts, you end up cutting your losses and respond with a hesitant “Oh… yeah!”.
Perhaps you’ve already experienced this with APIs. The term gets tossed around on a group meeting, so you ask what they are and maybe even ask a second time, but soon follows the slow “I get it, but I don’t get it” head nod.
Or maybe you haven’t asked about APIs at all – that’s totally fine, too.
Either way, there’s no denying it: headless is hot right now. So, let’s chat about APIs and microservices, what they are, and what in the world they have to do with headless CMS.
What’s an API?
The tech industry loves its three-letter acronyms, so let’s start there. API stands for Application Programming Interface. An API is simply the middleman that allows two different software systems to interact with each other. So, how do APIs work?
A good API design gets data and functionality from one place to another without exposing you to the complexity behind the curtain. They’re facilitators, request takers, deliverers, messengers – they’re responsible for the hyper-connected world we’ve come to know and expect.
The restaurant analogy is a classic explanation of API use wherein you (you = the user) look at a thoughtfully designed and formatted menu (menu = the front-end interface of software system #1, like a mobile app or a website).
You tell the waiter (waiter = service API) what you’d like to order (order = data), but the waiter doesn’t know how to cook your meal, how to operate the kitchen appliances, or how to manage backstock ingredients. They simply give instructions to the kitchen (kitchen = the backend of software system #2), where your order is then prepared, passed to the waiter, and delivered to you just as requested.
That’s an API: a convenient waiter waiting to take your request so they can optimize and deliver everything just how you like it, without you having to lift a finger.
What are some real-life examples of APIs?
APIs play an essential role in the automation of everything from mobile apps to e-commerce sites, and you probably interact with public APIs much more often than you think. If you’ve booked a trip online, ordered food on a delivery app, or called a rideshare at any time in your life, you’ve used an open API. And if you checked your weather app this morning… you guessed it, you used an API.
In all of these instances, the information you’re looking for lives somewhere else. But because your API is a loyal messenger, it starts to exchange data. On your behalf, it asks a third party about flight prices, hotel availability, menu items, driver locations, weather forecasts and then reports back – all so you didn’t have to.
Ok… so what do APIs have to do with headless CMS?
Unlike a traditional CMS – sometimes called a monolithic CMS, like WordPress – a headless CMS separates the backend (where the content is stored and managed) from the frontend (everything you see and interact with, like this article you’re reading right now). There’s a great overview of coupled vs. decoupled vs. headless here.
Because the frontend (head) is chopped off from the backend (body), headless content management systems use an API-first approach, relying on those little messengers to deliver anything in your content repository to different front-end channels and devices like webpages, mobile apps, web browsers, and social media platforms.
Basically, no APIs = no headless CMS
I’ve heard about RESTful APIs, what are those?
We know that an application programming interface is how one software system talks to another, so now REST (short for Representational State Transfer) is a set of standard rules that programmers follow to build an API. And if an API is built to adhere to those REST rules, that API is what we call a RESTful API. There are other standard rules and types of APIs like web API, but REST is the most popular.
This standard makes sure that your API speaks the same language as the application it’s trying to communicate with on operating systems, and RESTful APIs are necessary to keep that application active. RESTful APIs use a standard set of requests (get, put, post, patch, delete) to retrieve and manipulate data.
Note: there’s a lot more to the RESTful API story, but we’d ideally need a full programming crash course to encompass the entire picture.
Here are some headless CMS RESTful API examples:
- Content Delivery API allows you to send content to display in different channels, like mobile apps or other non-HTML applications.
- Content Management API allows you to create, edit, update, or delete your content.
Why is headless CMS such a hot topic right now?
Headless CMS has gained a lot of attention in recent years due to its most attractive traits: flexibility and scalability for the end user. Some are even open source. In a climate where speed, agility, and quick delivery is sink or swim, headless can be a win-win situation if you’re in search of a platform that will scale with you as you grow, without having to start from scratch every time you launch a new product or service. Responding to changing market trends becomes both easy and quick, and you can tailor omnichannel content delivery to specific use cases or API requests– it’s the perfect recipe for a great customer experience.
Creators
Headless CMSs give content creators and content editors the space they need – and crave – to focus solely on authoring, creation, and management. They can work closely with the CMS without worrying about the technical aspects of the presentation layer or relying heavily on a workflow of developer involvement. Headless also allows for greater reuse and repurposing of already-existing content, meaning their hard editorial work stretches a lot further. However, this is not true for all vendors. Some heavily focus on the developer experience, often neglecting the creator experience.
Developers
In the world of software development, a headless architecture lets mobile and web developers quickly and easily build composable, engaging digital experiences that can be customized for different channels and tailored to the needs of specific users. It also means their relationship with any headless CMS is relatively non-committal – if the CMS itself ever needs to change, the front end of the system (and all the developer’s hard work) stays intact. Going headless also creates a church-state divide between front-end and back-end developers. Less conflict, more focus on areas of expertise. For their own internal APIs and user interface, developers can use programming languages such as Java, Python, JavaScript, etc.
How do I know if a headless CMS is the right option for my organization?
Headless CMS solutions aren’t always for everyone, and they may or may not be the right option for your organization. API management is about understanding your business and tech stack requirements. Before making an investment, look at your web application complexities, digital experience goals, and the resources within your dev and marketing teams to mark your API specifications.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
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!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
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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