MARKETING
5 Retail SEO Tips for Converting Traffic Into Customers
![5 Retail SEO Tips for Converting Traffic Into Customers search engine optimization 586422 640](https://articles.entireweb.com/wp-content/uploads/2020/02/search-engine-optimization-586422_640.jpg)
Effective retail SEO strategies to help marketers optimise across complex consumer journeys and convert as much traffic as possible.
Optimising a retail website for search is one of the most challenging things you can do in SEO. For one thing, you’re not only competing against other retailers but Google’s own products too – Google Ads, Google Shopping and local search to name a few.
This is just to get your brand seen by consumers.
Then, you have to optimise for a complex consumer journey that takes shoppers from casual browsers all the way to the checkout, often across multiple sessions and different device types. Leads are precious in this business and success largely depends on converting as much traffic into paying customers as possible.
Here are five retail SEO strategies that will help you do this.
#1: It all starts with navigation
Aside from being a ranking factor, the navigation of a retail website dictates the browsing experience for users. The challenge for retail brands is to create a navigation system that makes it easy to find, sort and filter products while also providing categories, related products and other contextual navigation features that allow shoppers to move from one place to the next.
The more products and pages you have, the harder it is to create a seamless navigation that ties everything together.
Website structure isn’t the only thing you need to think about though. You also need to decide how people are going to compare different products on your website, continue shopping after adding an item to their basket and complete the checkout process when they’re ready to pay.
There are a lot of gaps for users to slip through on a retail website, but a highly-optimised navigation system will keep them moving in the right direction i.e. adding more products to the basket and completing the purchase while minimising the number of quit sessions and cart abandonments.
#2: Prioritise mobile browsing
According to Wolfgang Digital’s KPI Report 2019, 53% of traffic comes from mobile devices. However, this doesn’t tell the whole story about the role of mobile traffic in digital retail. This stat is skewed by the fact that mobile and desktop browsing habits change along the consumer journey. The same study shows that, despite a small majority of traffic coming from mobile, only 32% of conversions take place on mobile.
What’s actually happening here is that the significant majority of early browsing and first visits to retail websites are happening on mobile. In other words, when users aren’t really sure what they want to buy, they’re often browsing or researching on mobile or their attention is being caught by ads on social media.
When things get serious, the majority of users move over to desktop, which brings the average share of traffic closer to 50/50.
The takeaway here is to prioritise mobile browsing, attribute traffic across sessions and then prioritise desktop conversions. For example, you might create separate landing pages for mobile that focus on getting users to browse your products and deliver pages that focus on conversions for desktop users. You can also target returning mobile visitors with your “desktop” pages to cater for those who are more inclined to convert on mobile.
#3: Optimise for E-A-T & YMYL
Just in case you’re not 100% familiar with these terms:E-A-T is an acronym for expertise, authoritativeness and trustworthiness.YMYL stands for “your money or your life” pages (which includes eCommerce pages) and Google is more strict about its E-A-T requirements for these.
So, essentially, E-A-T (expertise, authoritativeness and trustworthiness) is important for every website, but especially for retail websites. Google considers eCommerce as YMYL.
In July 2018, Google updated its Search Quality Rating Guidelines telling its human quality raters the five key things it wants to see from web pages:The purpose of each pageExpertise, authoritativeness & trustworthiness (E-A-T)Main content quality and amountWebsite/publisher informationWebsite/publisher reputation
This gives you an idea of how important E-A-T is for websites. You can learn how to optimise eCommerce stores for this in an article we wrote for The Drum.
#4: Use structured data
Structured data provides Google with important information about your pages/content. Google can use this information to deliver your content to more relevant users and create more contextually relevant, visually compelling results listings (rich results).
Google has dedicated rich results for product listings (above). You can also make use of other formats for content types like blog posts, product reviews and other parts of your eCommerce SEO strategy.
#5: Get ready for organic product listings
Google has just announced a new search feature rolling out in the US that shows organic product listings in the SERPs. Users can already see product listings in search results but retail brands can only feature in these by paying for Google Shopping campaigns. The new “popular products” feature presents an opportunity for brands to get their products organically ranking on results pages.
This feature is only just rolling out in the US, so it’s not much help to retailers in the UK for the moment. However, this move is a response to declining product searches on Google, as Amazon is now the most popular place to search for products. So it’s only a matter of time before this feature rolls out beyond the US.
More importantly, this is a clear sign that Google may be forced to provide retail marketers with more organic opportunities as it squares up to Amazon. This kind of competition can only be good news for retail search marketers.
Stay tuned and get ready to optimise for new opportunities as they emerge.
Retail SEO is one of the most challenging areas in search marketing, but the good thing about this is that you can climb above a lot of competitors by getting the finer details right.
The most common mistake retail brands make is focusing all of their search marketing efforts on maximising visibility and traffic without paying enough attention to the quality of traffic, on-site UX, multichannel marketing and other aspects that determine how many of those visitors convert and return in the future.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
![YouTube Ad Specs, Sizes, and Examples [2024 Update] YouTube Ad Specs, Sizes, and Examples](https://articles.entireweb.com/wp-content/uploads/2024/06/YouTube-Ad-Specs-Sizes-and-Examples.jpg)
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
![Why We Are Always 'Clicking to Buy', According to Psychologists Why We Are Always 'Clicking to Buy', According to Psychologists](https://articles.entireweb.com/wp-content/uploads/2024/05/Why-We-Are-Always-Clicking-to-Buy-According-to-Psychologists.pngkeepProtocol.png)
Amazon pillows.
MARKETING
A deeper dive into data, personalization and Copilots
![A deeper dive into data, personalization and Copilots A deeper dive into data, personalization and Copilots](https://articles.entireweb.com/wp-content/uploads/2024/05/A-deeper-dive-into-data-personalization-and-Copilots.jpg)
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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