MARKETING
The Top Channels Consumers Use to Learn About Products [New Data]
Imagine you’re scrolling through Instagram and see an ad for a product you might be interested in.
While your first thought might be that ad targeting is getting too advanced, you still want to find out more about the product and the company that makes it. So where do you look next?
Are you going straight to their Instagram page, visiting their website, searching for online reviews, or watching a YouTube unboxing video?
These are the questions we asked 1,000 consumers in our 2022 State of Consumer Trends Survey to find out how people behave after discovering a product they might want.
Of course, this will vary drastically by generation, so we’ll include some insights split by age group as we go. You can also check out our full report on consumer shopping habits by generation for more age-specific info.
How Do Consumers Want to Learn About Products in 2022?
Consumers are learning about products and their features through a wide variety of channels. Among the most popular are searching the web, going to retail stores, TV ads, word of mouth, and online reviews.
While social media, YouTube ads, unboxing videos, and streaming services are less popular when we look at all generations combined, splitting this up by age group paints a very different picture.
Gen Z, Millennials, and Gen X set themselves apart from Boomers through their preference for learning about products through social media and YouTube ads. Gen Z also favors unboxing videos more than any other generation.
Meanwhile, Gen X and Boomers show a clear preference for learning about products through TV ads and in retail stores. Boomers also favor word of mouth more than any other generation.
But there are also some similarities — learning about products by searching the internet and through online reviews is popular among all generations.
So let’s dive deeper into each of the most popular channels consumers are using to learn about products.
SEO is Key for Product Discovery
36% of consumers prefer to learn about products by searching the internet, highlighting the importance of optimizing your website for SEO.
Searching the internet is the number one way to learn about products among all age groups, except for Gen Z, who prefer to use social media by just 1 percentage point. While online search is extremely popular among all age groups, it progressively gets more favor with each older generation.
Since we know consumers are searching the web to better understand products and their features, it’s also key to get a sense of which devices they are using to create the best user experience.
Not only are mobile phones the device of choice for over 50% of consumers when searching up a question online, but they are also the most used device when they shop online.
Especially when it comes to younger generations, the use of mobile devices for search dwarfs searching on a computer, meaning you should optimize your website to be mobile-first.
Retail Is Still Relevant, Especially for Older Generations
Coming in second place, 27% of consumers say they prefer to learn about products in retail stores. Unsurprisingly, the in-person approach is most popular among older age groups, though it isn’t completely lost on Gen Z and is still favored by almost one in five Millennials.
TV Ads Are Key for Boomers and Gen X
One in four consumers say TV ads are their preferred way of learning more about a product and its features. TV ads rank in the top three most preferred channels to learn about products for Gen X and Baby Boomers, but lose favor with Gen Z and Millennials who strongly prefer other digital channels like social media.
Word of Mouth Is Relevant, But Gen Z Looks to Influencers Instead
23% of consumers say they prefer to learn about products through word of mouth. Interestingly, word of mouth ranks in the top 5 channels for learning about products for every generation except Gen Z. Our Consumer Shopping Report 2022 even found that Gen Z places more importance on recommendations from influencers than their friends and family.
Online Reviews Are Sought By All Generations
One in five consumers say they prefer to learn about products through online reviews, regardless of generation. Of course, whether they go to YouTube, Amazon reviews, or a dedicated blog to get those insights will depend on their age.
Social Media Is Key For Gen Z and Millennials
Overall, just 17% of consumers say social media is their preferred channel for learning about products and their features. However, social media comes in at #1 for Gen Z, second for Millennials, and fourth for Gen X.
Next, let’s take a look at how consumers want to learn about products on social media.
Feed posts, ads, and stories are the top three formats for learning about products on social media. 36% of consumers want to learn about products through short-form videos like TikToks or Reels, and another 27% prefer to go through influencers, which is especially popular among younger generations.
You might also be wondering what kind of content consumers want to see from brands on social media.
Almost half of consumers say funny content is the most memorable, followed by content they can relate to. Making content that showcases your product or service is also highly memorable to 36% of consumers.
YouTube Ads are Key For Gen Z and Millennials
Overall, just 13% of consumers say they prefer learning about a product and its features through YouTube ads, but the video platform ranks among the top channels for Gen Z and Millennials.
Unboxing Videos are a Gen Z Thing
While just 9% of consumers prefer to learn about a product and its features through unboxing videos, they are uniquely popular with Gen Z.
Making Sense of Consumer Data
Want to learn more about the latest trends and shopping habits consumers are navigating, and how your brand can leverage them to better meet your targets in 2022?
Check out our consumer shopping report as well as our State of Consumer Trends Report, coming in late July.
In the meantime, see how marketers are navigating 2022 with our State of Marketing Trends Report below.
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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