MARKETING
Aspirational Analysis: Competitive Research for New (or Small) Sites
Competitive SERP analysis (including our recently launched Competitive Analysis Suite) is — by design — based on understanding the broader ecosystems of your ranking keywords. This is great if you’re an established business, but what if you’ve got a brand new site or are still developing your SEO strategy and aren’t ranking for many keywords?
Consider, for example, the fictional site, Dice-E-Shop.com (shh.. just let me have this one). We plug it into True Competitor, wait for some magic to happen, and voila!
Look at all the time you saved!
Okay, it’s not ideal, but there is a solution, and I call it “Aspirational Analysis”. The basic idea is simple — find a few aspirational but realistic keywords (ones that you can hope to compete for in the mid-term), use those SERPs to find aspirational competitors, and analyze those competitors to chart your competitive course.
1. Aspirational keywords
Let’s assume that you don’t know your competitive SEO landscape very well or that you want a fresh perspective on it. What you do know, hopefully, is the general topic and keyword space you want to compete in.
Let’s take our fictional business, Dice-E-Shop.com, and let’s pretend that it’s an online store specializing in handmade tabletop gaming dice. The key to step one is being aspirational but realistic — no vanity keywords allowed.
I’m not trying to make you feel bad. This is purely pragmatic. For example, let’s plug the keyword “dice” into our Keyword Explorer tool. You should get something like this:
That volume may look nice, but not only is the Keyword Difficulty pretty high, but look at that estimated CTR. Let’s take a quick look at the SERP itself …
The #1 organic position is occupied by a job search brand called Dice.com, which also has expanded sitelinks and other brand-specific rankings (such as their LinkedIn page). That brand is going to soak up most of the clicks on page one. This is neither a realistic nor desirable keyword.
I’m going to simplify this process to keep the workflow reasonable, but the next step is a blend of SERP analysis and intuition. We could go down many descriptive paths (“wooden dice”, “DnD dice”, “artisan dice”, etc.), but let’s try out “handmade dice”:
Don’t get hung up on the volume — our aspirational keyword(s) is all about finding a relevant, realistic competitor. It’s not about building a target keyword list. In this case, just by moving to a two-word phrase, we’re in a more reasonable Keyword Difficulty range with a much more attractive potential for organic clicks. In a more competitive market, we might need to reach deeper into the long tail of search, but “handmade dice” will do nicely for now.
2. Aspirational competitors
Let’s dig into the SERP for “handmade dice” a bit. The #1 result is for Etsy, but while they’re probably a good source of competitive intelligence for our new shop, they’re obviously not a realistic SEO competitor.
Here are the next three organic results. I’ve turned on the MozBar Chrome extension to quickly gain some additional insight:
The #2 site has a pretty low Domain Authority (13), and might not have a lot of ranking data. Honestly, though, as a marketer, I’m stuck on the #4 site because of this:
Love it or hate it, that’s certainly a unique selling proposition. What’s great about this analysis is that you can’t really pick the wrong site. This is an exploration of the competition, and you can always loop back and take another path and journey.
So, let’s go back over to True Competitor and plug in ArtisanDice.com. You’ll get back something like this (edited for size):
Due to a high keyword overlap (at 22%), Etsy scores high on our Rivalry metric, but, as previously discussed, is out of reach. Immediately after, though, we get a number of sites that look pretty viable, and we could easily visit those sites or research them in Keyword Explorer to learn more. Even the site that doesn’t look relevant at first glance (Help-action.com) turns out to be a blog for Dungeon Master resources and might have useful content ideas.
3. Aspirational analysis
I’d argue that we’ve already unearthed some pretty interesting information, but let’s take it a step further. I’m going to plug those top three aspirational competitors (after Etsy) into our new Keyword Gap tool. Here’s a sampling of the competitive keyword gap:
Note that, because we’re using an aspirational competitor (and not our own site), the “Traffic Lift” and “Your Rank” data have to be interpreted differently. This report is from the perspective of our aspirational competitor (ArtisanDice.com).
That said, we’ve got a solid start to finding opportunities in the space and keywords our soon-to-be competitors are targeting. We can easily start to piece together themes, like popular materials, which may even inform our product decisions.
The “Top Competing Content” report gives us a glimpse at some of the most effective content from our aspirational competitors, including a sampling of ranking keywords. I’ve edited this list down to show a few patterns, including pages themed around stone dice and d20s:
Now, we can explore these pages directly for inspiration. We could even put these pages back into our “Explore by Site” tool in Keyword Explorer and get keywords for the exact URL:
This niche page (targeting oversized d20s) ranks for 43 keywords in our data, including:
-
oversized d20
-
giant d20s
-
large 20 sided dice
-
jumbo 20 sided dice
-
oversized d20 dice
-
massive d20
-
huge 20 sided dice
-
giant d20 die
Even a sampling of this list is rich with synonyms and the kind of natural-language terms you should consider when building content around this niche.
4. Aspirational automation
While I’ve written this workflow around Moz tools, there are many ways to go about it, including manually using the SERPs themselves. There are two benefits to automation, though, and why I hope our Competitive Analysis suite can empower you to do better work faster.
First, even knowing very little about this space (other than being an occasional gamer and owning a few d20s in my time), the analysis in this post took less than an hour. If I were building a business in this space, I’d have been able to get at critical insights quickly.
Second, automation allows us to quickly branch and iterate. Let’s say that, after this first analysis, we decided to focus on stone dice or specifically on the DnD market — we could easily repeat this analysis to find niche competitors, keywords, and content. We could even start over with an entirely new aspirational keyword — as many times as it was useful. We could separately analyze product and content competitors, providing future direction for both our shopping pages and blog/marketing pages.
One last thing: aspirational analysis isn’t just for new sites. Sometimes, we all need to escape our own biases, and performing competitive analysis on other, diverse sites in our industry can open up new insights or areas we may be missing entirely.
Sign up for a free trial to access the Competitive Research Suite!
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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