MARKETING
3 Productive hacks for DXP integration & extensibility
There’s a reason Julia’s a loyal customer of Clean Getaway Corp. She loves its cleaning products, receiving push notifications to resupply and emails when her favorite items go on sale. For any issues, customer service quickly responds and has all the transaction information, so Julia can dive into the problem and receive a speedy resolution. What’s the secret to Clean Getaway’s success? DXP integration.
Since Digital Experience Platforms (DXP) accounted for 65% of the market share in 2021 and will only continue to grow, companies can’t afford to lose out on employing this aspect of digital transformation.
So, let’s see how to integrate this solution seamlessly. Before that, let’s define a DXP.
Key takeaways:
- Digital Experience Platforms support organizations using content management systems, AI and machine learning to leverage customer data to deliver personalized digital experiences.
- Integrating a DXP means the removal of data silos, increased customer satisfaction from the personalized experiences and reliable data for business decision-making.
- When integrating a DXP, first evaluate your digital maturity level. Then, create a roadmap with an MVP. Finally, choose the right DXP provider for your business.
What’s a Digital Experience Platform?
Each interaction an individual has with your business is called an experience. The more experiences the audience has with your brand, the better you get to know their likes, dislikes and needs. Digital Experience Platforms support organizations by using AI and machine learning to leverage customer data to deliver the best possible digital experiences.
Content Management Systems (CMS) are the foundation for DXPs. A CMS is a solution for creating, managing and publishing the content which makes up the customer’s experience. Then, every time your customer interacts with your company, the DXP creates a data point. With enough data points, the DXP understands your customer and can enhance your to deliver a personalized experience. Personalization means tailoring every interaction directly to a customer’s interest.
The DXP isn’t a single platform. It connects to solutions you already use for content creation and customer relationship management. What sets the DXP apart is its ability to analyze the data and turn it into a personal experience delivered across all channels (e.g., websites, mobile apps, IoT devices and social media).
Advantages of DXP integration
There are at least four benefits to implementing DXPs within your organization:
- Unified touchpoints – The omnichannel nature of the DXP means that digital interaction across all touchpoints contributes to the overall customer experience. There are no data silos on a given digital channel.
- Extensibility – DXPs can easily connect with other company solutions, such as marketing software and CRMs, providing a real-time and comprehensive view of each customer. Furthermore, this modularity means the platform can scale and grow with the business instead of turning into a legacy system.
- Artificial intelligence – DXPs collect user data (e.g., browsing habits, marketing campaign responses and product purchases) across all digital channels. Then, the built-in AI interprets the data and automatically applies recommendations to drive better results, such as which products to feature on the homepage or which content to highlight. This technology ensures each customer receives a personalized experience.
- Data-driven decision-making – DXP data is trustworthy. Businesses can analyze it to see which campaigns were most effective and see each touchpoint’s return on investment (ROI) to make decisions on future efforts.
Productivity hacks for effortless DXP integration
Planning is essential when it comes to implementing a DXP. Let’s review four steps a business can take regarding DXP integration.
1. What is your business maturity level?
There are four levels that businesses fall under when it comes to digital maturity, as shown in the table below:
Maturity Level |
Classification |
Description |
1 |
Nascent |
Uses data quality to connect data silos between departments and requires strong leadership and stakeholder engagement. |
2 |
Emerging |
They focus on improving experiences, deploying new technologies and developing strategies to scale between departments. |
3 |
Connected |
Uses data-driven methods to improve productivity, employing offline and online info to drive sales and support common objectives across the company. |
4 |
Multi-Moment |
Utilizes data-driven integrations, optimizing across all digital channels, touchpoints and departments. |
Where is your business in this digital maturity model? The answers to these questions can help you determine your level:
- Can you see buyer behavior and engagement across multiple digital channels?
- Are your marketing, sales, and service teams accessing unified customer data?
- Does your company effortlessly and decisively integrate new technologies?
- Do you see significant business results from those integrations?
- Do you frequently assess the impact of new technologies?
- Can your team quickly shift strategies and tactics based on evolving business intelligence?
The more you answer YES to these questions, the more digitally mature your organization is. Understanding where you are helps map out where you need to be with the DXP.
2. Create a roadmap and an MVP
A roadmap states the project goal and then breaks down that project into small stages that ultimately reach that goal. And, when setting a goal, choose your minimum viable product (MVP). An MVP is a version of the product that meets the needs of customers or users with the least amount of effort. For example, when integrating a DXP, the project’s goal or MVP could be eliminating data silos—only that. Later, another layer to add would be incorporating new technology into the DXP. By working on one aspect at a time, people can provide feedback to optimize that implementation before tackling another layer.
3. Choose the right DXP provider
The right DXP provider will review your digital maturity and roadmap to gain insight into your technological requirements and deliver your ideal platform. Here are some considerations for choosing the best provider:
- No company is the same. The provider should have in-depth knowledge of their product to tailor the integration for your business needs.
- They should have a robust portfolio of successful integrations.
- When looking at quotes, examine the details of the offer. What are the deliverables? What’s the scope of the work or their approach to the project? Weigh the price by the quality of work.
Partner with Optimizely for your DXP integration
Does your business need to create personalized customer experiences, break down data silos and plan for evolving technology? Then it’s time to incorporate a DXP into your digital transformation efforts, and Optimizely is the perfect partner for you.
Request a DXP demo today!
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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