MARKETING
11 Website Page Load Time Statistics You Need [+ How to Increase Conversion Rate]
You may have heard the old saying “patience is a virtue,” meaning waiting for something without getting discouraged is a great quality to have. However, for most of us, that “virtue” goes out the window when we encounter slow page load time.
The faster your website’s load time is, the happier your visitors will be. In other words — when you optimize your web page’s load time, you can expect to see improvements in user experience (UX), conversion rates, and ultimately, sales revenue.
You may be questioning whether or not simply shaving a few milliseconds off of your website’s page load time really has such a major impact on customer experience and business growth.
The truth is, yes, the longer it takes for your website’s page to load, the more likely you are to lose your audience. Read on for everything you need to know about website load time and how it can impact your customers’ experience with your company.
Short on time and need to get straight to the skimmable stats? Click here.
What is website load time?
Website load time — or web page load time — refers to how long it takes for a website, or web page, to fully load and appear on screen. This includes all content on the page such as text, images, and videos. Simply, it’s how fast all content on a web page loads.
Page speed can depend on a number of factors — some examples include: Page type, user behavior, file sizes, website server/host, inefficient code, hotlinking, and too many plugins and/or widgets.
In a 2019 survey by Unbounce, nearly 70% of consumers admitted that page speed impacts their willingness to buy from an online retailer. Furthermore, of all the people surveyed, half said they’d be willing to give up animation and video for faster load times.
Additionally, it’s crucial to remember the importance of your website’s mobile loading speeds. Jillian Streit, a website strategist at Blue Frog, told HubSpot: “Page speed has been a ranking factor for many years, and with Google’s shift to mobile-first indexing, it is even more important to focus on your website’s mobile loading speeds.”
She adds, “Unfortunately, most mobile pages take much longer to load than their desktop counterparts, and mobile users expect pages to load much faster on their mobile devices. If the page takes too long to load, users will immediately bounce, causing your site to lose out on a large number of potential customers.”
Learn about what website optimization is and how to do it effectively with this free course.
What is the average page load time?
In 2018, Google Research reported the average mobile web page takes 15.3 seconds to load. The same report said the problem is due to the majority of mobile sites having too many page elements. This problem persists despite most web traffic occurring on 4G instead of 3G.
What is a good page load time?
According to a 2019 study by Portent, a 0-4 second load time is best for conversion rates, and the first five seconds of page-load time have the highest impact on conversion rates.
In fact, the highest ecommerce conversion rates occur on pages with load times between 0-2 seconds. With each additional second of load time, website conversion rates drop by an average of 4.42%, the study says.
11 Page Load Time Statistics
Here are 11 statistics that will give you a better understanding of how website load time impacts your business and, more specifically, conversion rate.
1. The first five seconds of page-load time have the highest impact on conversion rates. (Portent, 2019)
2. Website conversion rates drop by an average of 4.42% with each additional second of load time (between seconds 0-5). (Portent, 2019)
3. The average mobile web page takes 15.3 seconds to load. (Google Research, 2018)
4. Nearly 70% of consumers admit that page speed impacts their willingness to buy from an online retailer. (Unbounce, 2019)
5. Of all the people surveyed, half said they’d be willing to give up animation and video for faster load times. (Unbounce, 2019)
6. The highest ecommerce conversion rates occur on pages with load times between 0-2 seconds. (Portent, 2019)
7. Website conversion rates drop by an average of 2.11% with each additional second of load time (between seconds 0-9). (Portent, 2019)
8. The highest ecommerce conversion rates occur on pages with load times between 0-2 seconds. (Portent, 2019)
9. The optimal average request count — the number of individual pieces of content needed to display the entire web page — is fewer than 50. (Google, 2018)
10. By compressing images and text, 25% of pages could save more than 250KB and 10% can save more than 1MB (which contributes to page load times). (Google, 2018)
11. Today, even though most web traffic occurs on 4G instead of 3G, the majority of mobile sites are still slow and bloated due to too many page elements. (Google, 2018)
Page Load Time Takeaways for Marketers
Maintaining a speedy page load time is integral to boosting conversion rates and sales revenue. While a few extra seconds may not seem like a big deal, statistics show that as each second passes, the potential to lose out on prospective customers increases.
If you’re concerned your website’s page load speed could be hindering your company’s growth, there are a few solutions to decrease the time it takes for your website to load. Online tools like Pingdom Website Speed Test, GTmetrix, Google PageSpeed Insights allow you to time and test your website’s page speed. You can also cache your website or enable browser caching to speed up your page load time.
Website load times impact conversion rates and, as a result, your business as a whole. Ensuring your load time is as efficient as possible doesn’t necessarily take a long time or a significant amount of effort, but it does require some thought. So, start thinking about how you can optimize your web page speed — you’ll see an improvement in your UX, conversions, time-on-page, and revenue.
Editor’s note: This post was originally published in March 2017 and has been updated for comprehensiveness.
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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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