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The trends underlying a record-breaking Cyber Week

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The trends underlying a record-breaking Cyber Week

In 2021, the Javits Center in New York city completed construction of a $1.5 billion expansion on the north side of its campus, adding over one million square feet spread over five floors — with a working rooftop farm. This week, the Salesforce World Tour took over the behemoth space for one day. It had previously touched down in Boston and Tokyo.

We took the opportunity to sit down with Rob Garf, VP and GM retail, to talk about prospects for retail and ecommerce coming off of a booming Cyber Week in late November.

Why the World Tour? The Salesforce World Tour is not something new, but it’s less familiar than Dreamforce, of course, and arguably Salesforce Connections, the annual conference with a focus on marketing and commerce.

“It’s really about bringing the magic to areas where we have a high concentration of customers,” Garf said. “Not everyone can get to some of our cornerstone events, so we just want to bring our community together. It’s also really nice for our partners too because they haven’t necessarily been able to get out there in the world and see their customers — or our mutual customers — so they’re using this as a bit of a halo event and having other peripheral events around it.”

The retail roller coaster. While ecommerce soared during the pandemic, brick-and-mortar retail faced challenges. Since then, despite the ongoing supply chain crisis and rumors of recession, ecommerce and retail seem to be resilient. Cyber Week saw a record-breaking $281 billion in global online sales.

This insight, and others described below, is based on aggregated data from the online activity of over 1.5 billion global shoppers in more than 60 countries powered by Commerce Cloud, as well as Marketing Cloud and Service Cloud data from retailers.

Dig deeper: Online retail kicks off holiday season with record sales

“A roller coaster is a good way to describe it,” said Garf. “We saw a real surge in digital because people, unless it was essential, were unable to go into physical stores. Over the course of 2020, we saw a 40% increase in net new digital shoppers according to our Shopping Index. These were people who would go online, send emails, check out social, but they weren’t clicking the buy line. And these people were buying whole new categories as well — think about grocery.”

There’s been a levelling off in digital commerce over the last year, but Garf doesn’t believe digital and physical stand in opposition any more. “What I’m talking with retailers about more and more is how they streamline the experience the consumer has on mobile out of the store, to when they actually come into the store so it’s not this disjointed experience.”

The journey works in the other direction too. “Our research shows that 60% of digital orders are now influenced by the physical store.” As an industry we’ve looked at it the other way, which makes sense; but we’re now seeing the reverse phenomenon.”

A quiet start to the holiday season. After a spike ahead of Amazon’s Prime event — likely caused by other retailers discounting ahead of Amazon — there was a dip in sales approaching Cyber Week. Over Cyber Week itself, however, there was a 9% increase in sales YoY in the U.S. (2% globally).

“The reason was that retailers started the season with lackluster deals,” Garf explained. “Consumers noticed; they waited and were patient; and it paid off.” Garf regards this as a game of “discount chicken.” Retailers start the holiday season with a planned discount calendar. “After the first weekend, they rip it up, call an audible and chase the deal — which is a race to the bottom.”

After the last two years of delivery and inventory problems, retailers thought consumers were now conditioned to buy early. That’s why they didn’t kick-off with their best deals. “Consumers snapped back to their pre-pandemic buying. With the aggressive deals we saw during Cyber Week, there was a correlation, more than we’ve ever seen, between discounts and purchases.

Mobile and social commerce trends. “People weren’t on the go the last couple of years during the holidays,” said Garf. “We saw a re-balancing toward desktop. This year we saw a spike, compared to the last two years, in mobile traffic and purchases — and traffic referrals through social on mobile devices.”

Around Cyber Week, roughly 75% of traffic was mobile, and — dependent on category — around 60% of orders. The reason? People are traveling again. “On Thanksgiving, we saw a spike in sales between 6 p.m. and 10 p.m. and on mobile in particular.”

Dig deeper: What is ecommerce and which trends are shaping its future?

Slack for retail. Salesforce now sees a key role for Slack, acquired two years ago, in the retail space. “We see retailers taking it beyond the technology function for collaboration and bringing it into the store for collaboration and communication,” said Garf. Not only can there be in-store communications, but stores can communicate with each other.

“We’re seeing some stores and service agents communicate with suppliers to establish visibility into when products will be available. They’re swarming on it immediately; you don’t have to wait two weeks for an email.”

Why we care. The lesson for all marketers, not just those in commerce is, first, that the pendulum is still swinging; second, that it’s a multi-dimensional pendulum. During the pandemic, it swung from mobile to desktop, and — okay — it’s swinging back again. But although it swung from physical to digital, it’s now swinging in a different direction, towards a bidirectional relationship between physical and digital (research on mobile, buy in store; or, see in store, buy digitall).

That pendulum is going to keep swinging. That is, unless we’re on the brink of an extended period of peace and well-being for the planet — and who’s betting on that? It’s incumbent upon marketers to observe very closely the direction in which buyers are headed and understand that the customer journey still has levels of complexity yet to be achieved.


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About The Author

Kim DavisKim Davis

Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.

He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020.

Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.

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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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