MARKETING
How to Get Bard to Show Your Local Business: Advice from the Source
The author’s views are entirely their own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.
We’re all Bard beginners right now, and so there are no foolish questions. Unsurprisingly, I’ve started out with Bard by asking it local business questions. As I chatted, I learned some useful things from and about Google’s nascent AI chat that you’ll need to know if this technology becomes part of your customers’ lives. My main goal was to learn three things:
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How much is Bard like Google search in a local use case?
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Would I be able to get any tips for local business inclusion in Bard?
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Do local SEOs need to change tactics to adjust for Bard?
Advisory: Bard’s own system warns you to take its statements with a grain of salt, so to speak, so do bear that in mind.
Because it was lunchtime and I was hungry, I began by asking about tacos.
When I asked Bard for the “best tacos near me”, it had no idea where I was, beyond apparently recognizing that I’m in the state of California. It showed me tacos in San Francisco (which is sort of near me) and tacos in Los Angeles (which would be quite a long drive for me, even for the best tacos). Interesting to note the plug for Doordash and UberEats. Mainly, though, pay attention to the fact that Bard is not like the local search environment Google has long accustomed us to in which it knows our geolocation without us having to modify our search term. With Bard, I realized I’d need to specify a city instead of just stating “near me”:
Getting more local with Bard
So, here we receive a list of six restaurants that are, indeed, in Novato. Bard shows me the average star rating (note the qualifier of 4+ stars) and gives me a sentiment analysis summary of customers praising taco quality, service, and prices. Next, I clicked on the “Google it” button to see if these 6 restaurants match Google local rankings. It took me to the local pack, from which I clicked through to the local finder to get the complete list of the top 6 restaurants
One of these things is not like the other
You see it immediately: the two lists don’t match.
With only 3 of the restaurants appearing on both lists and all the others being different, Bard’s recommendations are only a 50% match for Google’s local finder results. Moreover, the ranking order of the individual entities is a 0% match. Look at La Carreta at the bottom of Bard’s recommendations, but the top of Google’s local rankings, for example.
Another word to the wise: the Google organic rankings also didn’t match the order of either list. So, of course, I was curious as to why Bard is selecting its list of six. I asked:
To thine own self be true, Bard!
Local business owners and marketers, take note that Bard lists authenticity, affordability, convenience, variety, and friendly staff as the six contributors to its recommendations. This made me very curious as to how AI knows these six restaurants have all these good features, and I wasn’t prepared for Bard’s answer:
Bard says it has read their reviews (again, business owners and marketers take note) and that’s all fine and good. But when a robot claims to have “spoken to people who have eaten there”, we have a problem. So, I had to ask:
When pressed to explain, Bard did not share that Google has sent a speaking robot to the town of Novato to converse with people in Mexican restaurants. Instead, it completely reversed its position and admitted, “I can’t speak to people in the real world, but I can access and process information from the real world through Google Search and keep my response consistent with search results.”
I think it’s vital to mention here that Bard lying and backtracking could be quite problematic for local business customers who attempt to use AI chat as an alternative to local search. It doesn’t inspire trust in the content and Google will need to address this error sometimes called “hallucination” but which should more clearly be termed “disinformation”. Perhaps Bard’s failure to tell the truth inspired me to make up a “story” of my own and invent a fictitious business that I’m trying to get included in the AI list:
I found Bard’s advice to be extremely interesting and worthy of sharing because it matches, almost point for point, the tips you’ll get from a good local SEO consultant: get listed in Google’s local environment, get positive reviews, invest in community involvement, offer a unique product, provide great customer service, and don’t expect instant results. Encouraged by Bard’s initial tips for performing within its ecosystem, I decided to shake the bottle to see if any Google local ranking secret sauce would come out:
Local search ranking factors, according to Bard
Unfortunately, no revelations here. Bard suggests having a complete and accurate listing and warns of the tie between inaccurate local business info and negative reviews. It advises you to get positive reviews and respond to them, and to optimize your website. So far, so good, but there are three problems here that again lead to that creeping feeling of being led astray by Bard:
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Outdated information – I bet you noticed Bard using the outmoded branding “Google My Business” instead of “Google Business Profile”. The re-brand happened two years ago and stale information does not inspire trust for customers who use this tech to try to find local businesses like yours.
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Incitement to spam – It’s excellent advice to optimize your website with local keywords, but telling users to do this with their Google listings is another matter. The main place I see this activity happening is within the GBP title; owners add extraneous keywords to their names because it can boost local rankings, in violation of the Guidelines for Representing Your Business on Google. Adding keywords any place else on the listing (like the description or in Google Updates) is unlikely to have any impact on your local search rankings, so this advice is not merely suspect, but it could actually lead to people engaging in forbidden practices.
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Misrepresentation of other brands – Bard advising business owners to encourage customers to leave reviews on Yelp is a misrepresentation of the policies of a third party. Yelp infamously forbids this activity, but Bard is encouraging it. Google has a long and frustrating history of misrepresenting the businesses in its local index, and unfortunately, Bard appears poised to do the same. As always with local search, online misinformation directly impacts real-world people.
I wrote a Twitter thread on asking AI multiple local SEO FAQs in which Bard scored a low C vs. the F I had earlier given ChatGPT. Given the ongoing disinformation we’re encountering, both in terms of Bard claiming it had spoken to restaurant diners and of it mixing in some very bad advice with the good, we’re not at a place of trust with this “answering machine” at this point.
Yet, local business owners are still going to want to know how to be recommended by Bard if it becomes deeply embedded in customers’ online lives. And that brings us back to the question: why is La Carreta number #6 with Bard but #1 with Google? Why does Bard love Tommy’s Salsa best? Let’s do a very quick side-by-side audit (not a more complete one) and see if we can find any clues, and I’ll highlight obvious wins in light blue.
A mini competitive audit of Bard vs Google’s favorite tacos
What we see here is that the at-a-glance wins on the Google local search side are coming from the extraneous keywords in the title and from the very interesting fact that this restaurant pointing their GBP to a Facebook page is then apparently deriving DA/PA benefit from the behemoth authority of that platform (a stealth local search ranking factor?). As for Bard, the wins are all on Tommy’s Salsa’s side, with a higher star rating, more reviews, more links earned, an older listing, a shorter distance to the city centroid, a higher Yelp rank and – notably – a #1 adjusted organic rank.
This is, of course, a single query, and a very new technology, but given Bard’s stated emphasis on customer service and reviews, it does check out that the chat listed Tommy’s Salsa before La Carreta, and overall, Tommy’s Google Business Profile components are making its Maps presence a bit more impressive than the competitor’s.
In conclusion – does the coming of Bard change what you should be doing as a local business marketer?
In major news right now, AI creators and promoters are claiming that ChatGPT, New Bing and Bard will change the world forever. These individuals even fall back on the utopian fiction that, because of their invention, no human being will ever have to work again. The reality check is that inventors and investors built similar hype around the Rapid Marmalade Cutter which was meant to release humanity from the endless toil of…shredding oranges. 1930s ad copy reads, “Home marmalade making is easier today than it has ever been! The Rapid Marmalade Cutter revolutionizes this money-saving, health-giving occupation!” Sounds familiar, doesn’t it?
Inventions can make some tasks easier for some people, but unless there’s a real demand and use for them, they can end up gathering dust in garages. At the moment, I suggest thinking of AI chat as just one more online space in which local businesses should act with awareness to see how they are being represented by a third party. The fact that this technology tells lies is a good reason to see if it mentions your brand. Only recently, Google weirdly began listing products on Google Business Profiles as being free or costing $1, and you can imagine the phone calls local businesses had to field over that fiasco. So, practice awareness.
As for seeking Bardic inclusion, my first impression is that you’ll still be doing the same tasks: making your GBP as fully-filled out as possible, earning good reviews via good customer service, growing and optimizing your website on the basis of consumer research. You’ll notice that Bard’s recommendations for getting mentioned in its lists of favorites didn’t contain a single surprise or novel notion for how to create visibility for local businesses. In other words, I see nothing game-changing here, but I do see a ton of room for your own research if your business isn’t included and wants to be.
We’ll keep studying this together as things move along with the “revolution” of AI chat. In the meantime, just keep taking good care of your customers, because, contrary to headlines, we’re all still counting on the people at your business to show up for the vital work of serving our communities.
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.”