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Better customer experience is on the way

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Better customer experience is on the way

Marketers will improve customer experience in 2024 so brands can remain competitive and demonstrate to customers that they matter. Every year the bar gets raised. In 2024, keys to customer success will include better personalization delivered at scale by ramped-up automation and generative AI. And better digital content will surface, if organizations put in place the necessary guardrails for generative AI to fuel the anticipated content surge.

More personalized experiences by humans and AI working together

Humans aren’t going to be taken out of the customer experience entirely in 2024. Instead, look for AI-augmented systems to help make experience and service more efficient for marketers and agents.

“Organizations realize that for more challenging issues, customers want to have the ability to connect with a human,” said Keith Kirkpatrick, research director, enterprise applications for The Futurum Group. “And when you do that, you want to make that interaction as efficient and as quick as possible. If you have AI helping, you’re going to be able to make sure that agent has the information right in front of them, served up in context, and they don’t need to go hunting around for it.”

This added context gives customers, as well as marketers, more confidence for higher-priced sales. With AI assistance, B2B and high-end retail will see an overhaul of personalized customer experiences in the year ahead.

Dig deeper: Salesforce updates Einstein 1 Platform with unified business data

Translating in-person experiences virtually

Whether using improved AI-powered chatbots, or delivering more informed experiences fueled by customer data, brands will provide more quality customer interactions traditionally associated with high-end retail.

“A key focus for retailers and ecommerce brands in 2024 will be transforming great in-person conversations and purchase experiences into natural interactions through messaging apps — in other words, mimicking the in-store experience in our virtual world,” said Joscha Koepke, head of product at conversational marketing company Connectly.

He added, “As retailers increasingly embrace new ways of online and mobile shopping, brands need to bring this luxury brand experience to a broader set of consumers through two-way communication.”

AI driving experience and customer support

“In 2024, companies that incorporate AI into the customer experience in the right ways will set themselves apart,” said Chris Savage, CEO and co-founder of video marketing platform Wistia.

AI-generated chat, increasingly, will take the burden off human agents providing customer support. However, the margin of error is slim for assisting customers who just want their problems fixed. But as AI chatbots improve, customers will increasingly welcome these assistants.

“The minute this technology is more refined and helpful, every customer will be looking for AI chat support as it will provide instantaneous responses to questions 24/7 in any language,” Savage said. “At the same time, having humans available to supplement these chatbots will quickly become a differentiator. There will be questions and issues that only humans can answer, and if customers can’t easily gain access to a support team when needed, their company loyalty may begin to waver.”

Customer expectations will climb, demanding more personalization across all channels, including mobile apps.

“AI will allow for so many more edge cases and ways to personalize the customer experience, and we’ll start to expect all apps to feel like they have a much better understanding of us and our preferences,” said Savage.

B2B marketers will use video for better trust and accessibility

Generative AI has applications that extend far beyond intelligent chatbots. The technology can be used to power transcription and make video more successful. As a result, B2B marketers will have more meaningful, accessible videos to help drive customer experiences.

“It’s becoming clear that the B2B marketing landscape will undergo a transformative shift around accessibility, video and AI in 2024,” said Jennifer Griffin Smith, CMO for digital experience company Acquia. “Further, as businesses recognize the diverse needs of their audience, digital and communication accessibility will be paramount.”

Expect the wider use of subtitles and voiceover in video to build trust with customers who have disabilities and preferences for captions. Meeting these expectations will help build customer trust in the new year, even as marketers face challenges to trust related to data security and privacy.

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Using AI to pre-screen experience as content surges

One of the promises made in 2023 by the rise of generative AI is the ability to scale content. With content surging, the need for quality control also increases. To meet this challenge, AI will come to the rescue again.

“We’re seeing the beginning of an onslaught of AI-generated content,” said Bryan Whitaker, CEO of data technology company Statara. “Unless AI prompts are topnotch, or human editors are involved, content still runs the risk of having embarrassing errors, coming off as robotic, and being glaringly inauthentic.”

“The surge in content production means that existing approval workflows will become unsustainable,” said Levi Matkins, CEO of mobile marketing platform LifeStreet. “Traditionally bogged down by multiple checkpoints and a lengthy creative process, generative AI will compel companies to reevaluate and streamline these processes. Brands serious about leveraging AI might train models to pre-screen content for brand compliance, using AI as a first line of defense.”

The result is that brands will be able to produce more content confidently. And with more efficient content production workflows, marketers will be able to concentrate on compelling ideas instead of the nuts and bolts of approval and distribution.

“With the increasing ease and affordability of content creation, the focus will shift from execution to ideation,” said Matkins. “The quality (versus the quantity) of content ideas becomes the differentiating factor in a market where execution is no longer a barrier. This shift will put a premium on creativity and strategic thinking, pushing brands to invest more in developing unique and resonant concepts that can be quickly brought to life through AI.”

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AI will boost marketing and sales readiness

In the new year, marketers and sales representatives will be using AI in important client meetings, improving readiness.

“Whether it’s using AI to instantaneously surface the most compelling pitch deck, talk track or playbook, AI will enable sellers to show up as trusted advisors, earning buyer confidence and becoming indispensable to the customer journey,” said Hendrik Isebaert, CEO of sales enablement platform Showpad. “In addition to sales meetings, AI will also be leveraged to augment the role of the internal sales coach, making sales development programs smarter and more scalable.”

CMOs more hands-on with service

“In 2024, the role of the CMO will become more heavily entwined in the efforts to build stronger customer experience and interactions,” said Josh Mueller, CMO for cloud-based technology company Avaya. “In the contact center, specifically, expect to see CMOs closer to the content delivered in the contact center through campaign messaging, contact center agent training, or hands-on roles in applying AI to call routing.”

The other side of this development is that service data will have a bigger voice internally.

“The customer will have a stronger voice in the boardroom thanks to the power of AI,” said Cynthia Sener, President GTM at brand intelligence company Chatmeter. “AI is poised to revolutionize marketing by turning large volumes of unsolicited customer feedback into actionable, strategic insights. Brands embracing the power of AI to extract key themes and sentiments about customers’ real-time, honest experiences with their products and services will outshine competitors.”

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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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