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5 Social Media Predictions Marketers Got Wrong Last Year

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5 Social Media Predictions Marketers Got Wrong Last Year

The world around us is constantly changing — it only makes sense that the marketing world does too.

Every year, marketers pull out the crystal ball to predict trends and shifts in the coming year. Sometimes we’re right on the tail — and other times the social media marketing landscape surprises us.

Here, we’ll cover 5 social media predictions marketers got wrong in 2021 and strategies for making better predictions in the future.

5 Bad Social Media Predictions of 2021

1. The TikTok craze will reach its peak.

Despite threats of being banned in the U.S. — and actually being banned in India — TikTok continues to defy the odds and grow at a steady rate. In fact, the app hit a remarkable milestone at the end of 2021 — one billion monthly active users.

Despite its popularity, some marketers may have dismissed TikTok entirely, reducing it to a platform for lighthearted dances and lip-synching. However, it’s become a viable option for brands willing to get creative with their digital marketing. So much so, it launched TikTok for Business in 2021, allowing marketers to create and manage ad campaigns on the platform.

Need more convincing? According to the HubSpot Blog’s survey of 1,000+ marketers, a whopping 85% cited short-form videos (like those on TikTok) as the most effective social media format in 2021. In fact, more than half of marketers (52%) plan to increase their investment in TikTok this year.

5 Social Media Predictions Marketers Got Wrong Last Year

It’s not too late to leverage TikTok in 2022. Check out this helpful guide on how to get started.

2. Facebook will become obsolete.

We’ve all heard the jokes about Facebook’s aging audience — and there is some truth to it. A recent study found that Snapchat, Instagram, and TikTok were the platforms of choice for Gen Zer’s, with Facebook falling into 6th place.

But we can’t write off Facebook just yet. It still pulls over 1.5 billion daily active users, making it the most popular social media platform worldwide. It largely holds sway with millennials, the biggest demographic group on the platform.

When it comes to social media marketing, Facebook packs quite a punch. According to HubSpot Blog’s survey of 1,000+ marketers, Facebook led the pack as the platform with the highest ROI and engagement in 2021. It’s no surprise that 25% of social media marketers plan to invest more in it than any other platform in 2022.

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From these stats alone, it’s clear Facebook is still a booming business for digital advertising. With its expansion into live video, along with Facebook Shops and Stories, marketers can also experiment with new ad formats in one central location.

3. TikTok will become the preferred platform for influencer marketing.

Despite its popularity, TikTok fell short when it came to influencer marketing in 2021.

Instead, the title belongs to Instagram, which was ranked the platform of choice for inking deals with influencers. So much so, a staggering 97% of marketers plan to increase their investment in influencer marketing on Instagram this year.

Our survey also revealed influencer marketing as the most popular trend with the biggest ROI in 2021. The most notable reason for this uptick is an increase in micro influencers. Micro influencers provide smaller, highly-engaged audiences without the hefty price tag of a mainstream celebrity — making this type of marketing more accessible to a variety of brands.

Want to try your hand at influencer marketing but don’t know where to start? Check out this handy checklist.

4. Audio chat rooms will yield huge ROI

2021 saw a wave of live audio apps — including Clubhouse and Twitter Spaces. We were all intrigued — was it a viable marketing channel? Could this content go viral?

It turns out, audio chat rooms were great for engagement but not so much for ROI. According to our survey, Clubhouse fell to the bottom of the list regarding ROI. Further, 15% of marketers plan to decrease their investment in audio chat rooms this year.

However, there’s a redemption arc — despite having low ROI, many marketers report high engagement rates. If your social media marketing goals are to boost engagement and brand awareness, these audio apps could be the secret ingredient. In fact, 44% of marketers plan to leverage podcasts and audio-based content for the first time this year.

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5. Remote events will lose steam as we return to the workplace.

Most people — myself included — thought the workforce would finally return to the office in 2021. But this prediction was a little premature.

Instead, many workplaces have adopted a hybrid work model where employees can work in-office or remote. This could become a permanent arrangement — 51% of organizations are considering a move to hybrid work in a post-COVID world.

As a result, remote and hybrid events are here to stay, and marketers must adapt. 64% of marketers plan to increase their investment in live video and streaming — like Facebook Live, Instagram Live, and YouTube Live — in 2022.

How to Make Better Social Media Marketing Predictions

In the marketing sphere, trends move in light years. As marketers, it’s essential to make predictions to equip ourselves for the future. Here, let’s cover three ways to make better social media marketing predictions:

  • Keep up-to-date: A great forecaster keeps a pulse on new trends and technology. When making social media predictions, staying informed in small — but frequent — bouts is better than in an end-of-year rush.
  • Cast a wide net: Seek out a variety of sources for your news. In doing so, you’re more likely to get a holistic view of the current climate. Further, you may discover contradictory information — which may call for a second glance.
  • Know your biases: We all have biases — and recognizing them is half the battle. Confirmation bias, in particular, can heavily influence how we make predictions. This is the tendency to interpret new evidence as confirmation of an already existing belief. To prevent this, you’ll need to seek differing viewpoints that challenge your assumptions. It’s also important not to jump to conclusions, which creates a false picture of the marketing landscape.

The only constant in the marketing world is change. As a social media marketer, the best thing you can do is stay current on trends and tech, seek out new opinions and viewpoints, and identify trends in your own marketing.

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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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