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Reinventing the digital experience platform

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Reinventing the digital experience platform

Over the past couple of years, research firms Gartner, Forrester, and others have heralded the arrival of digital experience platforms (DXPs); the future is now and all that (for a DXP primer, you might enjoy Pamela Parker’s article). But practically speaking, is there such a thing as a digital experience platform? As Tony Byrne of the Real Story Group (and a MarTech contributor) said in 2018, referencing Gartner’s Magic Quadrant for DXPs, put it: “No enterprise digital leader in her right mind would actually purchase ‘digital experience’ as a platform. DX is a strategy and approach, and no single platform or vendor on this chart will get you there.”

Digital experience platform evolution

The days of monolithic all-in-one platforms are fading. Marketing technology vendors are moving toward “composability,” which offers marketers the freedom of choice they want by selecting best-of-need products that best suit their marketing organization and business needs. This is a shift from the monolithic approach, where companies rely on a single vendor for their system. Of course, the single-vendor method might be suitable for the procurement folks, but it can introduce risk to the business, as I discussed in this article. Plus, in many cases, customers are not getting the full breadth of features, functionality and ROI from their single-vendor martech investments.

An early example of DXP evolution comes from web content management (WCM) vendors, creating complex suites that combine features of WCM, digital asset management (DAM), portal, personalization, analytics, and more. In some cases, these “integrated” suites are natively nothing more than a collection of acquired point solutions that form what the vendor calls a digital experience platform.

Stitching those disparate products together to create a unicorn solution is an integration partner’s dream but, in too many cases, a CMO’s nightmare. The work can be complex, time-consuming and expensive, and the results frequently fail to deliver on the promise. In the 2021 CMSWire State of Digital Customer Experience report, 80% of the 1,300+ digital customer experience execs surveyed responded that their digital experience was “very” to “extremely important” to their organizations. That said, only 11% believed their tools were “working well,” while 42% said their tools “need work.”

Introducing composability

An excellent example of composability in action is the evolution of the legacy content management system (CMS). The monolithic CMS integrates content, images, HTML, and CSS and provides a Graphical User Interface (GUI) to help non-technical users create and publish content. Unfortunately, it’s virtually impossible to leverage a content re-use strategy since code and content are combined.

To remedy this problem and provide developers with a composable method of flexing their innovation chops, vendors introduced the decoupled CMS. This flexible front-end and structured back-end model promoted faster development, redesigns, upgrades, and new site rollouts, leaving content and development teams to work independently and more efficiently. In this CMS incarnation, the front and back ends are separate, which means developers could try new frameworks and tools without impacting the site’s content.

Then came the headless CMS, a back-end-only solution that stores content and distributes it via RESTful API. Using a headless approach, marketers could syndicate centrally-managed content to websites, mobile apps, digital signage, car dash displays, or other endpoints. There’s no presentation layer provided with a headless CMS, leaving developers the latitude to handle presentation in whatever way best suits the requirements du jour. 

Meanwhile, throughout this evolutionary process, the need to create and manage remarkable customer experiences to acquire, convert, and retain customers continued to explode. The lines between decoupled and headless blurred, and even monolithic CMS offerings began to morph. Legacy CMS vendors returned to the drawing board while innovative new players entered the market. More martech vendors were adopting the concept of composable solutions.

Composable DXP adoption: Resistance is futile

The aggressive push to drive DXP adoption is underway, and it’s working. Global research and consulting firm Verified Market Research says the Global Digital Experience Platform Market size was valued at USD 15.88 Billion in 2020 and projected to reach USD 43.43 Billion by 2028, growing at a CAGR of 13.4% from 2021 to 2028. 

However, along with all the hype, there’s some confusion. Gartner defines the DXP thus: “A digital experience platform (DXP) is an integrated set of core technologies that support the composition, management, delivery and optimization of contextualized digital experiences.” But as mentioned above, there’s a big question; should those “core technologies” be integrated into a monolithic, all-in-one platform, or should the “core technologies” be represented by a collection of point solutions assembled on a best-of-breed basis?

Composability and the martech stack

Over time, some legacy CMS vendors like Sitecore, Optimizely (formerly Episerver) and Progress Software’s Sitefinity have reinvented their platforms to fit into a DXP box, while newcomers like Contentful, Contentstack and Storyblok are driving in new directions. One thing is sure; it looks like composability is here to stay.

The concept is even finding its way into the board room as a future-proof schema for the post-COVID enterprise. Gartner says, “Composable business means creating an organization made from interchangeable building blocks. The modular setup enables a business to rearrange and reorient as needed depending on external (or internal) factors like a shift in customer values or sudden change in supply chain or materials.” 

Gartner identifies three building blocks of the composable business: composable thinking, composable business architecture and composable technologies. COVID seems to have accelerated this model in companies that may have lagged in building out their functional digital knowledge and martech muscles.


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Modular is better

Building modular, or composable, technology stacks has always been a great idea, though early on, it wasn’t as palatable as it is today. Plus, as I’ve said here, there’s been some advancement of functional digital knowledge in many organizations that’s driven new ways of thinking and working, including selecting various best-of-need martech tools from different vendors to build out the martech stack.

As Mark Demeny, director of product management at Optimizely, says, “Dealing with one vendor is perhaps a little bit safer. For example, the customer can work with one vendor and one renewal cycle instead of six. But while it’s easier for procurement, it may not be easier from an implementation perspective, depending on how well the martech vendor has assembled its product offering. Ultimately, it comes down to the preference of the buyer and the skill set of their organization.”

Keep in mind that things could get complex — expensive — when rolling your own composable DXP. In fact, according to Real Story Group’s Byrne, some customers “are spending 2-6x more on initial implementation services than they do on licensing costs. Same for outbound marketing and e-commerce projects. SaaS vendors with more productized, multi-tenant solutions talk about ‘quick start’ projects with light professional services fees, but the ‘MVPs’ that results tend to be long on the M and light on the V.”

Read next: Does your marketing team need a digital experience platform?

Avoiding the composable DXP trap

To increase your chances of success and reduce risk when building out your composable DXP, consider the following:

Choose your best-of-need solutions carefully. That includes following the advice in this article, including:

  • Understand your long-term priorities and those of your chosen martech vendor(s). For example, are they focusing on innovation, growth, and new customers, or are they focusing on keeping existing customers happy and prosperous?
  • De-couple software from services. Sure, the vendor might offer hosting or implementation/consulting services, but that doesn’t necessarily mean they are the best fit to deliver those services for your organization.
  • Always be thinking about a migration strategy. Composable means flexibility, but even upgrades can require a lot of planning, consideration, and cost. Stay on top of the constantly shifting market by researching and engaging with new vendors on a monthly (or bi-monthly) basis. That’ll help you keep your finger on potential products and services that are fit-for-purpose in your composable DXP stack.

Choose your outside consultants carefully. While vendors may provide professional services, they usually focus on implementing own their products and services.

  • Know before you go. “Whenever you start a technology project, get clear about what you need from any outside consultants. There’s a good chance you may need various ‘soft skills’ such as information and process analysis, user experience, and change management, along with migration support.” says Real Story Group’s Byrne. Consider conducting a standardized review to understand the available individual and team skills and experience required to build and use a composable DXP. This will not only help you determine current skills and skill gaps but prepare hiring managers for potential recruiting and the outside consultant selection process.
  • Make sure they’ll focus on your best interests. Luma Partners 2021 Full Year Market Report showed strong growth in martech M&A deals, springing back from pandemic lows to achieve a 95% YoY growth. With big deals come big expectations from investors, often translating into mandates of 40-50% growth per year. A fierce quest for revenue might make one partner hyper-focused on your needs and another on their own. Mitigate potential risk and exposure by doing your homework, including reviewing the partner’s financials.
  • Pick composable tools first. Most services partners you’ll engage with are themselves partnered with several martech vendors. These relationships often involve commissions or co-op funds for advertising and events based on sales by the services partner of the martech vendor’s products. Thus, the outside consultant might have a vested interest in recommending specific products or services. Before choosing a service partner, prudence dictates developing solid business and technology requirements and performing vendor research (including demos and a proof-of-concept) to select your composable DXP components. As Byrne says, “If changing integrators is like switching plumbers, then changing vendors is like remodeling your bathroom completely. Get a blueprint, select the fixtures, then find the plumber.”

The composable DXP for the win

For companies and their marketing organizations seeking a way to create, deploy, and manage remarkable customer experiences, the composable, modular DXP can be a desirable approach. Instead of leveraging only 10-15% of the features and functions of an all-in-one solution, consider point solutions that best meet your business, marketing, and technology needs.

A purpose-built composable DXP can evolve with your business, customers, industry, and the endless shifting martech landscape. Once that’s in place, the focus can shift to creating remarkable composable customer experiences. But that’s another article.


Does your marketing team need a digital experience platform DXP

Explore platform capabilities from vendors like Sitecore, Optimizely, Pantheon, WordPressVIP and more in the full MarTech Intelligence Report on digital experience platforms.

Click here to download!



Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Reinventing the digital experience platform

Gene has been a Martech Healer for three decades, inventing the future while helping organizations and leaders ‘Ride the Crest of Change.’ A serial entrepreneur since his first newspaper delivery start-up, Gene developed early innovations in social media networks, digital-out-of-home narrowcasting, and SMS mobile marketing. He currently serves as the chief strategy officer and head of consulting at GeekHive, a New York-based marketing technology consultancy helping clients maximize their investments in martech.


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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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