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How to improve customer relationships with personalized messaging

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How to improve customer relationships with personalized messaging

“The first things we always want to think about in the customer journey are what the customer is doing and how they are interacting with us as a brand,” said Ben Tepfer, senior technical evangelist at Adobe, at our MarTech conference. “As marketers, we need to be thinking about what the channels look like today and what the channels are going to look like in the future.”

He added, “Customers demand experiences that are consistent and personalized across every one of these channels.”

comparison of traditional and digital customer lifecycles
Source: Ben Tepfer

The days of the traditional customer journey are long gone. Now, brands are responsible for delivering messages of value across multiple platforms, devices and channels. Without a personalization strategy in place, these companies will have a difficult time attracting and retaining customers.

“There’s a financial benefit for you as an organization when you start thinking about personalization,” he said. “It takes more effort in some cases, but it has a greater return on investment.”

Here are some effective ways marketers can leverage personalization in their customer messaging efforts.

Equip your team for great conversations

Your marketing team needs as full of a view as possible of a customer to deliver high-quality communication. Bring them into the loop by providing customer data and insights from your various platforms.

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“You need a view of the customer that’s tied across sales, service, support, etc.,” Tepfer said, “Then you can personalize the journey.”

But data is just one piece of the puzzle. Conversations are a two-way street, and brands need effective technologies that create foundations for ongoing high-quality customer messaging .

“You need the technology to be able to execute this,” he said. “You need technology that acts and listens in real-time, that follows through with customer engagements, and that lets customers drive their conversations.”


Why brands must embrace responsible marketing practices

Practice active listening with customers

“We have to remember that the customer journey is the customer’s journey, not us marketers’,” Tepfer said. “And it’s not always going to be good. Sometimes something happens that’s not ideal.”

Paying attention to these discrepancies in the customer journey is vital to understanding their needs. But more than that, active listening calls for action on the brand’s side that addresses the concern.

“The most important thing is responding to them,” he said. “We need to be reactive and conversational in the way that we talk to our customers.”

Produce conversations of value

“If you’re not delivering value, then you’re not succeeding,” said Tepfer. “It’s about centralizing decisioning so that you can make great decisions about what the best experience is right now and what the best experience is going to be down the road. It means responding at the right time and on the right channels.”

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“It’s important that you have a technology framework that lets you adjust in real-time because that’s how your customers are interacting,” he added.

While customer data, insights and active listening provide the foundation for personalized messaging, brands need technology solutions to prove what they have to offer is valuable. Marketers may consider using customer experience platforms to deliver these real-time communications.

“When you have all these foundational pieces together and you’re responding and delivering value, that’s when you’re able to deliver experiences at scale that are highly personalized,” Tepfer said.

He added, “We can think about one-to-one journeys all day, but we also need to think about how we scale and bring those forward.”

Customer journey analytics: A snapshot

What it is. Customer journey analytics software lets marketers connect real-time data points from across channels, touchpoints and systems, allowing users to gain insights into the customer journey over time. This allows marketers to explore the customer journey using data.

Why it’s hot today. Businesses know they need to be customer-focused in each aspect of their marketing operations. As a first step, brands need to understand how consumers are finding them. Whether it be via search, advertisement, or word of mouth, the medium used will set the trajectory for the rest of their journey.

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Meanwhile, the average person uses many devices to access the internet, and Cisco forecasts that the number of devices connected to IP networks will increase to more than three times the global population by 2023. With so many devices, people shift back and forth depending on the task at hand and their current environment. Consumers and business buyers turn to an average of nine channels to browse product inventory, look for advice, and make purchases.

Capturing their interactions post-discovery, such as communication with a call center or visit to a retail outlet, helps brands see which of their assets are helping them along their path. What’s more, brands need to know what those who convert do post-purchase–this information helps companies win repeat business and encourage customer advocacy. Customer journey analytics tools do just that.

What the tools do. The majority of vendors offer one or more of the following capabilities to give marketers an understanding of the customer journey: data gathering from a wide variety of channels and touchpoints; analysis using artificial intelligence and machine learning, and customer journey visualization.

Many vendors also offer customer journey orchestration (CJO) capabilities, which allow users to act upon the insights and actually deliver the next step in the customer journey in real-time.

Why we care. Customers expect to have consistent experiences at each of these touchpoints. They want personalization, a trend that continues to grow. Tools like customer journey analytics software give brands the ability to gain insights from their audience and act on them.

Read Next: What is customer journey analytics and how are these tools helping marketers?

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About The Author

1640828540 338 Why brands must embrace responsible marketing practices

Corey Patterson is an Editor for MarTech and Search Engine Land. With a background in SEO, content marketing, and journalism, he covers SEO and PPC to help marketers improve their campaigns.


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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.”

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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.”

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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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