MARKETING
Crucial Steps to Converting Browsers into Buyers
There’s something comforting and enjoyable about creating a routine where people know you, whether that’s a favorite coffee shop or place to walk or a local beer store where they call your dog by name.
Many businesses can create this personalized shopping experience to convert more browsers into buyers. But, it can be tough to do that online where you can’t look into a customer’s eyes or easily ask what they need as they browse digital shelves. Still, we regularly hear about the need for eCommerce personalization.
To tackle that opportunity, let’s define personalization, the best way to start implementing it, and methods to optimize your efforts.
Defining “personalization” in eCommerce
Personalization and customization can feel like the same thing, but some important distinctions exist. Breaking these out makes it easier to understand personalization and how it can apply in eCommerce operations.
For your website and sales efforts, personalization uses data and customer insights to craft a specific shopping experience for every customer. These efforts may include showing relevant products, serving recommendations, and adjusting content based on the customer’s past behavior.
Companies may also try personalizing service levels or selecting specific pop-ups and overlays based on customer status.
Customization, on the other hand, generally refers to customer-driven choices. These range from the obvious (selection or sorting by size, color, price, etc.) to detailed efforts specific to the individual (a customer chooses not to see certain types of products). When you think of customization as something helmed by the customer, you’ll start identifying ways to use their selections to craft personalized experiences.
How personalization creates a better shopping experience
To create a personalized shopping experience, eCommerce businesses need to invest in audience research. By understanding your customers and what they want, you can create an individualized experience that will convert browsers into buyers.
You’ll want to create as complete a picture of the shopper as possible. Ask core experience questions, including:
- What are their needs that you can and can’t address?
- What are their wants or things that tip them over the edge to make a purchase?
- What motivates them to make this purchase at this time?
- Why should they choose you to meet their specific needs and wants?
Once you understand your customers well, you can start creating a shopping experience tailored to them. Take learning about their immediate needs and wants. I
t’s easier to suggest the right products when you know what they’ve recently viewed or what ad they clicked on to get to your site. You’re building based on their tastes and refining suggestions based on what gets that second purchase.
Understanding why someone values your brand can also help you create personalized discounts or special deals that gain shoppers. If you’re known for customer service, you might leverage this for an ad tagline: “World-class customer service meets free shipping on every order over $20.”
It’s more than just a deal; it’s one couched in the language you know they appreciate. Tying it back to shipping and order support also reinforces your brand as one that cares about the customer.
Finally, it is important to ensure the customer feels valued and appreciated. Thank them for their business and promptly take care of any issues they may have. Creating a positive relationship with your customers ensures they keep returning for more.
3 steps to take to get started with personalization
To get started with personalization, businesses need to take three steps: collecting data, analyzing data, and implementing personalization.
1. Collect data
The first step is to collect data about your customers. This could include information such as their demographics, location, what devices they use, what pages they visit on your site, and what products they are interested in. There are a number of ways businesses can collect this data, such as through website cookies, surveys, and customer loyalty programs.
2. Analyze data
Once you have collected data about your customers, it is important to analyze it to understand their needs and preferences. This will help you determine how to best personalize their shopping experience. Several tools are available to help with this analysis, such as analytics software and customer segmentation tools.
3. Implement personalization
The final step is to implement personalization into your eCommerce store. This could include creating a personalized homepage, recommending similar products, using data to segment customers into different groups, or offering discounts. By personalizing the shopping experience, businesses can increase conversion rates and average order value.
The top 5 ways to personalize the shopping experience
Personalization can be an incredibly complex experience or a simpler operation based on your tech stack and the amount of data you use. To get started, there are some core efforts to implement that can start with minimal, current-session data and then move to longer-term tracking and utilization.
1. Use data to recommend products
One of the most effective ways to personalize the shopping experience is to use data to recommend products. This could include data from past purchases, browsing history, and social media activity.
By understanding what customers have bought in the past, businesses can make recommendations for similar or complementary products. This helps customers find what they’re looking for more easily and allows businesses to upsell and cross-sell effectively.
2. Create a personalized homepage
Another way to personalize the shopping experience is to create a personalized homepage. This could include features such as recommended products, recently viewed items, and even a custom welcome message.
By creating a personalized homepage, businesses can make sure that each customer feels valued and that they can easily find what they’re looking for — reinforcing your brand identity as helpful and in-the-know.
Consider tying homepages to traffic and referral sources so that someone looking at your Instagram account hits a page filled with both products and the videos you create. It’s an easy way to start the fruitful process of understanding customer behavior across channels.
3. Use data to create targeted marketing campaigns
Another effective way to personalize the shopping experience is to use data to create targeted marketing campaigns. This involves using customer data to segment customers into different groups and then creating marketing messages that are tailored to each group. This could include offering discounts or special promotions to specific groups of customers.
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Don’t neglect small lifts here. Greet customers directly by name. Adjust messages based on user region. Adapt to local events and other broader experiences that keep your content from feeling too general, even if it isn’t hyper-personalized.
4. Use data to segment your email list
You can also personalize the shopping experience by segmenting your email list. This involves grouping customers together based on their interests, demographics, or purchase history. Most email marketing tools track detailed customer information you can leverage.
For example, monitoring when customers last visited allows you to email people about how “it’s been a while”.
By segmenting your email list, you can send more targeted and relevant messages to each group of customers. This can lead to higher open and click-through rates, as well as increased sales and revenue.
5. Personalized product pages by creating variants
The final way to personalize the shopping experience is to use data to create a personalized product page. Or, at least create a page that feels catered to the individual based on broader context and information.
When you can get very detailed, this involves using customer data such as purchase history and browsing behavior to recommend similar or complementary products. You’ll need a dynamic site that can adapt to their history and habits in real-time.
If you don’t have a robust site, consider building blocks for each section of your landing pages or product pages for each SKU. Then, you can create groupings that feel customized because the pre-existing blocks you use match what people see in broader marketing campaigns. As you get more sophisticated, these blocks can then be what you dynamically insert into different elements as the customer shops around your site.
By creating a personalized product page, businesses can enhance conversion rates and have a better chance for higher order values because of the relevance of up-sell and cross-sell promotions.
The benefits of personalization for businesses
There are many benefits of personalization for businesses. By creating a personalized shopping experience, businesses can increase conversion rates, average order value, and customer loyalty.
Conversion rates improve because customers are more likely to buy from a store that recognizes them and offers products they are interested in. If you’re marketing to the same people, small efforts like using someone’s first name in an email can increase conversion rates.
Companies that personalize offers also tend to see average order values increase in multiple ways. These incentives help push people to make more impulse purchases and reach higher overall orders — a benefit you can compound when making traditional online offers like free shipping on orders of a certain value.
Finally, studies also show that personalization can improve customer loyalty. Studies have found that more than half of people are open to receiving personalized experiences, and 72% who get these end up spending more or buying more often. This is because customers feel appreciated and valued when they are recognized and offered products they look at or follow.
Overall, personalization is a powerful tool that can help businesses improve conversion rates, average order value, and customer loyalty. When used correctly, it can be a key driver of success for eCommerce businesses.
Create an experience you’d enjoy
When it comes to personalizing the shopping experience, businesses must take a few steps to ensure they are doing it correctly.
First and foremost, they need to collect data about their customers so they can understand their needs and preferences. Once they have this data, they need to analyze it to determine how best to personalize the shopping experience for each customer.
Then, they need to implement personalization into their eCommerce store, which could include creating a personalized homepage, recommending similar products, using data to segment customers into different groups, or offering discounts.
The final piece, however, is reviewing the effort and ensuring that it adds value to the shopping experience. Ask if it is something you’d enjoy or if the elements and personalization get in the way. You don’t want to be overly burdensome or overly creepy. The aim is to show people what they want to see without them feeling like you’re crunching a lot of data behind the scenes.
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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