MARKETING

SEO Recap: PageRank – Moz

Published

1 year ago

December 31, 2022

What Are the Best Tools for Storytelling With Data Visualization?

The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

Have you ever wondered how Moz employees learn internally? Well, here’s your chance to get a sneak peek into never seen before, internal webinar footage with Tom Capper! Learning is important at Moz, and the sharing of information amongst employees is crucial in making sure we stay true to our core values. Knowledge sharing allows us to stay transparent, work together more easily, find better ways of doing things, and create even better tools and experiences for our customers.

Tom started these sessions when everyone was working remotely in 2020. It allowed us to come together again in a special, collaborative way. So, today, we give to you all the gift of learning! In this exclusive webinar, Tom Capper takes us through the crucial topic of PageRank.

Video Transcription

This is actually a topic that I used to put poor, innocent, new recruits through, particularly if they came from a non-marketing background. Even though this is considered by a lot people to be an advanced topic, I think it’s something that actually it makes sense for people who want to learn about SEO to learn first because it’s foundational. And if you think about a lot of other technical SEO and link building topics from this perspective, they make a lot more sense and are simpler and you kind of figure out the answers yourself rather than needing to read 10,000 word blog posts and patents and this kind of thing.

Anyway, hold that thought, because it’s 1998. I am 6 years old, and this is a glorious state-of-the-art video game, and internet browsing that I do in my computer club at school looks a bit like this. I actually didn’t use Yahoo!. I used Excite, which in hindsight was a mistake, but in my defense I was 6.

The one thing you’ll notice about this as a starting point for a journey on the internet, compared to something like Google or whatever you use today, maybe even like something that’s built into your browser these days, there is a lot of links on this page, and mostly there are links to pages with links on this page. It’s kind of like a taxonomy directory system. And this is important because if a lot of people browse the web using links, and links are primarily a navigational thing, then we can get some insights out of looking at links.

They’re a sort of proxy for popularity. If we assume that everyone starts their journey on the internet on Yahoo! in 1998, then the pages that are linked to from Yahoo! are going to get a lot of traffic. They are, by definition, popular, and the pages that those pages link to will also still get quite a lot and so on and so forth. And through this, we could build up some kind of picture of what websites are popular. And popularity is important because if you show popular websites to users in search results, then they will be more trustworthy and credible and likely to be good and this kind of thing.

This is massive oversimplification, bear with me, but this is kind of why Google won. Google recognized this fact, and they came up with an innovation called PageRank, which made their search engine better than other people’s search engines, and which every other search engine subsequently went on to imitate.

However, is anything I said just now relevant 23 years later? We definitely do not primarily navigate the word with links anymore. We use these things called search engines, which Google might know something about. But also we use newsfeeds, which are kind of dynamic and uncrawlable, and all sorts of other non-static, HTML link-based patterns. Links are probably not the majority even of how we navigate our way around the web, except maybe within websites. And Google has better data on popularity anyway. Like Google runs a mobile operating system. They run ISPs. They run a browser. They run YouTube. There are lots of ways for Google to figure out what is and isn’t popular without building some arcane link graph.

However, be that true or not, there still is a core methodology that underpins how Google works on a foundational level. In 1998, it was the case that PageRank was all of how Google worked really. It was just PageRank plus relevance. These days, there’s a lot of nuance and layers on top, and even PageRank itself probably isn’t even called that and probably has changed and been refined and tweaked around the edges. And it might be that PageRank is not used as a proxy for popularity anymore, but maybe as a proxy for trust or something like that and it has a slightly different role in the algorithm.

But the point is we still know purely through empirical evidence that changing how many and what pages link to a page has a big impact on organic performance. So we still know that something like this is happening. And the way that Google talks about how links work and their algorithms still reflects a broadly PageRank-based understanding as do developments in SEO directives and hreflang and rel and this kind of thing. It still all speaks to a PageRank-based ecosystem, if not a PageRank-only ecosystem.

Also, I’m calling it PageRank because that’s what Google calls it, but some other things you should be aware of that SEOs use, link equity I think is a good one to use because it kind of explains what you’re talking about in a useful way. Link flow, it’s not bad, but link flow is alluding to a different metaphor that you’ve probably seen before, where you think of links as being sent through big pipes of liquids that then pour in different amounts into different pages. It’s a different metaphor to the popularity one, and as a result it has some different implications if it’s overstretched, so use some caution. And then linking strength, I don’t really know what metaphor this is trying to do. It doesn’t seem as bad as link juice, at least fine, I guess.

More importantly, how does it work? And I don’t know if anyone here hates maths. If you do, I’m sorry, but there’s going to be maths.

So the initial sort of question is or the foundation of all this is imagine that, so A, in the red box here, that’s a web page to be clear in this diagram, imagine that the whole internet is represented in this diagram, that there’s only one web page, which means this is 1970 something, I guess, what is the probability that a random browser is on this page? We can probably say it’s one or something like that. If you want to have some other take on that, it kind of doesn’t matter because it’s all just going to be based on whatever number that is. From that though, we can sort of try to infer some other things.

So whatever probability you thought that was, and let’s say we thought that if there’s one page on the internet, everyone is on it, what’s the probability a random browser is on the one page, A, links to? So say that we’ve pictured the whole internet here. A is a page that links to another page which links nowhere. And we started by saying that everyone was on this page. Well, what’s the probability now, after a cycle, that everyone will be on this page? Well, we go with the assumption that there’s an 85% chance, and the 85% number comes from Google’s original 1998 white paper. There’s an 85% chance that they go onto this one page in their cycle, and a 15% chance that they do one of these non-browser-based activities. And the reason why we assume that there’s a chance on every cycle that people exit to do non-browser-based activities, it’s because otherwise we get some kind of infinite cycle later on. We don’t need to worry about that. But yeah, the point is that if you assume that people never leave their computers and that they just browse through links endlessly, then you end up assuming eventually that every page has infinite traffic, which is not the case.

That’s the starting point where we have this really simple internet, we have a page with a link on it, and a page without a link on it and that’s it. Something to bear in mind with these systems is, obviously, web pages don’t have our link on them and web pages with no links on them are virtually unheard of, like the one on the right. This gets really complex really fast. If we try to make a diagram just of two pages on the Moz website, it would not fit on the screen. So we’re talking with really simplified versions here, but it doesn’t matter because the principles are extensible.

So what if the page on the left actually linked to two pages, not one? What is the probability now that we’re on one of those two pages? We’re taking that 85% chance that they move on at all without exiting, because the house caught fire, they went for a bike ride or whatever, and we’re now dividing that by two. So we’re saying 42.5% chance that they were on this page, 42.5% chance they were on this page, and then nothing else happens because there are no more links in the world. That’s fine.

What about this page? So if this page now links to one more, how does this page’s strength relates to page A? So this one was 0.85/2, and this one is 0.85 times that number. So note that we are diluting as we go along because we’ve applied that 15% deterioration on every step. This is useful and interesting to us because we can imagine a model in which page A, on the left, is our homepage and the page on the right is some page we want to rank, and we’re diluting with every step that we have to jump to get there. And this is crawl depth, which is a metric that is exposed by Moz Pro and most other technical SEO tools. That’s why crawl depth is something that people are interested in is this, and part of it is discovery, which we won’t get into today, but part of it is also this dilution factor.

And then if this page actually linked to three, then again, each of these pages is only one-third as strong as when it only linked to one. So it’s being split up and diluted the further down we go.

So that all got very complicated very quick on a very simple, fictional website. Don’t panic. The lessons we want to take away from this are quite simple, even though the math becomes very arcane very quickly.

So the first lesson we want to take is that each additional link depth diluted value. So we talked about the reasons for that, but obviously it has implications for site structure. It also has implications in some other things, some other common technical SEO issues that I’ll cover in a bit.

So if I link to a page indirectly that is less effective than linking to a page directly, even in a world where every page only has one link on it, which is obviously an ideal scenario.

The other takeaway we can have is that more links means each link is less valuable. So if every additional link you add to your homepage, you’re reducing the effectiveness of the links that were already there. So this is very important because if you look on a lot of sites right now, you’ll find 600 link mega navs at the top of the page and the same at the bottom of the page and all this kind of thing. And that can be an okay choice. I’m not saying that’s always wrong, but it is a choice and it has dramatic implications.

Some of the biggest changes in SEO performance I’ve ever seen on websites came from cutting back the number of links on the homepage by a factor of 10. If you change a homepage so that it goes from linking to 600 pages to linking to the less than 100 that you actually want to rank, that will almost always have a massive difference, a massive impact, more so than external link building could ever dream of because you’re not going to get that 10 times difference through external link building, unless it’s a startup or something.

Some real-world scenarios. I want to talk about basically some things that SEO tools often flag, that we’re all familiar with talking about as SEO issues or optimizations or whatever, but often we don’t think about why and we definitely don’t think of them as being things that hark back quite so deep into Google’s history.

So a redirect is a link, the fictional idea of a page with one link on it is a redirect, because a redirect is just a page that links to exactly one other page. So in this scenario, the page on the left could have linked directly to the page on the top right, but because it didn’t, we’ve got this 0.85 squared here, which is 0.7225. The only thing you need to know about that is that it’s a smaller number than 0.85. Because we didn’t link directly, we went through this page here that redirected, which doesn’t feel like a link, but is a link in this ecosystem, we’ve just arbitrarily decided to dilute the page at the end of the cycle. And this is, obviously, particularly important when we think about chain redirects, which is another thing that’s often flagged by the SEO tools.

But when you look in an issue report in something like Moz Pro and it gives you a list of redirects as if they’re issues, that can be confusing because a redirect is something we’re also told is a good thing. Like if we have a URL that’s no longer in use, it should redirect. But the reason that issue is being flagged is we shouldn’t still be linking to the URL that redirects. We should be linking directly to the thing at the end of the chain. And this is why. It’s because of this arbitrary dilution that we’re inserting into our own website, which is basically just a dead weight loss. If you imagine that in reality, pages do tend to link back to each other, this will be a big complex web and cycle that is, and I think this is where the flow thing comes around because people can imagine a flow of buckets that drip round into each other but leak a little bit at every step, and then you get less and less water, unless there’s some external source. If you imagine these are looping back around, then inserting redirects is just dead weight loss. We’ve drilled a hole in the bottom of a bucket.

So, yeah, better is a direct link. Worse is a 302, although that’s a controversial subject, who knows. Google sometimes claim that they treat 302s as 301s these days. Let’s not get into that.

Canonicals, very similar, a canonical from a PageRank perspective. A canonical is actually a much later addition to search engines. But a canonical is basically equivalent to a 301 redirect. So if we have this badgers page, which has two versions, so you can access it by going to badgers?colour=brown. Or so imagine I have a website that sells live badgers for some reason in different colors, and then I might have these two different URL variants for my badger e-com page filtered to brown. And I’ve decided that this one without any parameters is the canonical version, literally and figuratively speaking. If the homepage links to it via this parameter page, which then has canonical tag pointing at the correct version, then I’ve arbitrarily weakened the correct version versus what I could have done, which would be the direct link through. Interestingly, if we do have this direct link through, note that this page now has no strength at all. It now has no inbound links, and also it probably wouldn’t get flagged as an error in the tool because the tool wouldn’t find it.

You’ll notice I put a tilde before the number zero. We’ll come to that.

PageRank sculpting is another thing that I think is interesting because people still try to do it even though it’s not worked for a really long time. So this is an imaginary scenario that is not imaginary at all. It’s really common, Moz probably has this exact scenario, where your homepage links to some pages you care about and also some pages you don’t really care about, certainly from an SEO perspective, such as your privacy policy. Kind of sucks because, in this extreme example here, having a privacy policy has just randomly halved the strength of a page you care about. No one wants that.

So what people used to do was they would use a link level nofollow. They use a link level nofollow, which . . . So the idea was, and it worked at the time, and by at the time, I mean like 2002 or something. But people still try this on new websites today. The idea was that effectively the link level nofollow removed this link, so it was as if your homepage only linked to one page. Great, everyone is a winner.

Side note I talked about before. So no page actually has zero PageRank. A page with no links in the PageRank model has the PageRank one over the number of pages on the internet. That’s the seeding probability that before everything starts going and cycles round and figures out what the stable equilibrium PageRank is, they assume that there’s an equal chance you’re on any page on the internet. One divided by the number of pages on the internet is a very small number, so we can think of it as zero.

This was changed, our level nofollow hack was changed again a very, very long time ago such that if you use a link level nofollow, and by the way, this is also true if you use robots.txt to do this, this second link will still be counted in when we go here and we have this divided by two to say we are halving, there’s an equal chance that you go to either of these pages. This page still gets that reduction because it was one of two links, but this page at the bottom now has no strength at all because it was only linked through a nofollow. So if you do this now, it’s a worst of both world scenario. And you might say, “Oh, I don’t actually care whether my privacy policy has zero strength,” whatever. But you do care because your privacy policy probably links through the top nav to every other page on your website. So you’re still doing yourself a disservice.

Second side note, I said link level nofollow, meaning nofollow in the HTML is an attribute to a link. There is also page level nofollow, which I struggled to think of a single good use case for. Basically, a page level nofollow means we are going to treat every single link on this page as nofollow. So we’re just going to create a PageRank dead-end. This is a strange thing to do. Sometimes people use robots.txt, which basically does the same thing. If I block this page with robota.txt, that’s the same in terms of the PageRank consequences, except there are other good reasons to do that, like I might not want Google to ever see this, or I might want to prevent a massive waste of Google’s crawlers’ time so that they spend more time crawling the rest of my site or something like this. There are reasons to use robots.txt. Page level nofollow is we’re going to create that dead-end, but also we’re going to waste Google’s time crawling it anyway.

Some of the extreme scenarios I just talked about, particularly the one with the privacy policy, changed a lot for the better for everyone in 2004 with something called reasonable surfer, which you occasionally still hear people talking about now, but mostly implicitly. And it is probably actually an under-discussed or underheld in mind topic.

So these days, and by these days, I mean for the last 17 years, if one of these links was that massive call to action and another one of these links was in the footer, like a privacy policy link often is, then Google will apply some sense and say the chance people click on this one . . . Google was trying to figure out probabilities here, remember. So we’ll split this. This 0.9 and 0.1 still have to add up to 1, but we’ll split them in a more reasonable fashion. Yeah, they were doing that a long time ago. They’ve probably got very, very good at it by now.

Noindex is an interesting one because, traditionally, you would think that has nothing to do with PageRank. So, yeah, a noindex tag just means this should never show up in search results, this page at the bottom, which is fine. There are some valid reasons to do that. Maybe you’re worried that it will show up for the wrong query that something else on your site is trying to show up for, or maybe it contains sensitive information or something like this. Okay, fine. However, when you put a noindex tag on something, Google eventually stops crawling it. Everyone sort of intuitively knew all the pieces of this puzzle, but Google only acknowledged that this behavior is what happens a couple of years ago.

So Google eventually stops crawling it, and when Google stops crawling on it, it stops passing PageRank. So noindex follow, which used to be quite a good thing or we thought quite a good thing to do for a page like an HTML sitemap page or something like that, like an HTML sitemap page, clearly you don’t want to show up in search results because it’s kind of crap and a poor reflection on your site and not a good UX and this kind of thing. But it is a good way to pass equity through to a bunch of deep pages, or so we thought. It turns out probably not. It was equivalent to that worst case scenario, page level nofollow in the long run that we talked about earlier. And again, this is probably why noindex is flagged as an error in tools like Moz Pro, although often it’s not well explained or understood.

My pet theory on how links work is that, at this stage, they’re no longer a popularity proxy because there’s better ways of doing that. But they are a brand proxy for a frequently cited brand. Citation and link are often used synonymously in this industry, so that kind of makes sense. However, once you actually start ranking in the top 5 or 10, my experience is that links become less and less relevant the more and more competitive a position you’re in because Google has increasingly better data to figure out whether people want to click on you or not. This is some data from 2009, contrasting ranking correlations in positions 6 to 10, versus positions 1 to 5. Basically, both brand and link become less relevant, or the easily measured versions become less relevant, which again is kind of exploring that theory that the higher up you rank, the more bespoke and user signal-based it might become.

This is some older data, where I basically looked at to what extent you can use Domain Authority to predict rankings, which is this blue bar, to what extent you could use branded search volume to predict rankings, which is this green bar, and to what extent you could use a model containing them both to predict rankings, which is not really any better than just using branded search volume. This is obviously simplified and flawed data, but this is some evidence towards the hypothesis that links are used as a brand proxy.

Video transcription by Speechpad.com

MARKETING

How to Use AI For a More Effective Social Media Strategy, According to Ross Simmonds

Published

2 days ago

April 22, 2024

Entireweb News Bot

How to Use AI For a More Effective Social Media Strategy, According to Ross Simmonds

Welcome to Creator Columns, where we bring expert HubSpot Creator voices to the Blogs that inspire and help you grow better.

It’s the age of AI, and our job as marketers is to keep up.

My team at Foundation Marketing recently conducted an AI Marketing study surveying hundreds of marketers, and more than 84% of all leaders, managers, SEO experts, and specialists confirmed that they used AI in the workplace.

If you can overlook the fear-inducing headlines, this technology is making social media marketers more efficient and effective than ever. Translation: AI is good news for social media marketers.

In fact, I predict that the marketers not using AI in their workplace will be using it before the end of this year, and that number will move closer and closer to 100%.

Social media and AI are two of the most revolutionizing technologies of the last few decades. Social media has changed the way we live, and AI is changing the way we work.

So, I’m going to condense and share the data, research, tools, and strategies that the Foundation Marketing Team and I have been working on over the last year to help you better wield the collective power of AI and social media.

Let’s jump into it.

What’s the role of AI in social marketing strategy?

In a recent episode of my podcast, Create Like The Greats, we dove into some fascinating findings about the impact of AI on marketers and social media professionals. Take a listen here:

Let’s dive a bit deeper into the benefits of this technology:

Benefits of AI in Social Media Strategy

AI is to social media what a conductor is to an orchestra — it brings everything together with precision and purpose. The applications of AI in a social media strategy are vast, but the virtuosos are few who can wield its potential to its fullest.

AI to Conduct Customer Research

Imagine you’re a modern-day Indiana Jones, not dodging boulders or battling snakes, but rather navigating the vast, wild terrain of consumer preferences, trends, and feedback.

This is where AI thrives.

Using social media data, from posts on X to comments and shares, AI can take this information and turn it into insights surrounding your business and industry. Let’s say for example you’re a business that has 2,000 customer reviews on Google, Yelp, or a software review site like Capterra.

Leveraging AI you can now have all 2,000 of these customer reviews analyzed and summarized into an insightful report in a matter of minutes. You simply need to download all of them into a doc and then upload them to your favorite Generative Pre-trained Transformer (GPT) to get the insights and data you need.

But that’s not all.

You can become a Prompt Engineer and write ChatGPT asking it to help you better understand your audience. For example, if you’re trying to come up with a persona for people who enjoy marathons but also love kombucha you could write a prompt like this to ChatGPT:

The response that ChatGPT provided back is quite good:

Below this it went even deeper by including a lot of valuable customer research data:

Demographics
Psychographics
Consumer behaviors
Needs and preferences

And best of all…

It also included marketing recommendations.

The power of AI is unbelievable.

Social Media Content Using AI

AI’s helping hand can be unburdening for the creative spirit.

Instead of marketers having to come up with new copy every single month for posts, AI Social Caption generators are making it easier than ever to craft catchy status updates in the matter of seconds.

Tools like HubSpot make it as easy as clicking a button and telling the AI tool what you’re looking to create a post about:

The best part of these AI tools is that they’re not limited to one channel.

Your AI social media content assistant can help you with LinkedIn content, X content, Facebook content, and even the captions that support your post on Instagram.

It can also help you navigate hashtags:

With AI social media tools that generate content ideas or even write posts, it’s not about robots replacing humans. It’s about making sure that the human creators on your team are focused on what really matters — adding that irreplaceable human touch.

Enhanced Personalization

You know that feeling when a brand gets you, like, really gets you?

AI makes that possible through targeted content that’s tailored with a level of personalization you’d think was fortune-telling if the data didn’t paint a starker, more rational picture.

What do I mean?

Brands can engage more quickly with AI than ever before. In the early 2000s, a lot of brands spent millions of dollars to create social media listening rooms where they would hire social media managers to find and engage with any conversation happening online.

Thanks to AI, brands now have the ability to do this at scale with much fewer people all while still delivering quality engagement with the recipient.

Analytics and Insights

Tapping into AI to dissect the data gives you a CSI-like precision to figure out what works, what doesn’t, and what makes your audience tick. It’s the difference between guessing and knowing.

The best part about AI is that it can give you almost any expert at your fingertips.

If you run a report surrounding the results of your social media content strategy directly from a site like LinkedIn, AI can review the top posts you’ve shared and give you clear feedback on what type of content is performing, why you should create more of it, and what days of the week your content is performing best.

This type of insight that would typically take hours to understand.

Now …

Thanks to the power of AI you can upload a spreadsheet filled with rows and columns of data just to be met with a handful of valuable insights a few minutes later.

Improved Customer Service

Want 24/7 support for your customers?

It’s now possible without human touch.

Chatbots powered by AI are taking the lead on direct messaging experiences for brands on Facebook and other Meta properties to offer round-the-clock assistance.

The fact that AI can be trained on past customer queries and data to inform future queries and problems is a powerful development for social media managers.

Advertising on Social Media with AI

The majority of ad networks have used some variation of AI to manage their bidding system for years. Now, thanks to AI and its ability to be incorporated in more tools, brands are now able to use AI to create better and more interesting ad campaigns than ever before.

Brands can use AI to create images using tools like Midjourney and DALL-E in seconds.

Brands can use AI to create better copy for their social media ads.

Brands can use AI tools to support their bidding strategies.

The power of AI and social media is continuing to evolve daily and it’s not exclusively found in the organic side of the coin. Paid media on social media is being shaken up due to AI just the same.

How to Implement AI into Your Social Media Strategy

Ready to hit “Go” on your AI-powered social media revolution?

Don’t just start the engine and hope for the best. Remember the importance of building a strategy first. In this video, you can learn some of the most important factors ranging from (but not limited to) SMART goals and leveraging influencers in your day-to-day work:

The following seven steps are crucial to building a social media strategy:

Identify Your AI and Social Media Goals
Validate Your AI-Related Assumptions
Conduct Persona and Audience Research
Select the Right Social Channels
Identify Key Metrics and KPIs
Choose the Right AI Tools
Evaluate and Refine Your Social Media and AI Strategy

Keep reading, roll up your sleeves, and follow this roadmap:

1. Identify Your AI and Social Media Goals

If you’re just dipping your toes into the AI sea, start by defining clear objectives.

Is it to boost engagement? Streamline your content creation? Or simply understand your audience better? It’s important that you spend time understanding what you want to achieve.

For example, say you’re a content marketing agency like Foundation and you’re trying to increase your presence on LinkedIn. The specificity of this goal will help you understand the initiatives you want to achieve and determine which AI tools could help you make that happen.

Are there AI tools that will help you create content more efficiently? Are there AI tools that will help you optimize LinkedIn Ads? Are there AI tools that can help with content repurposing? All of these things are possible and having a goal clearly identified will help maximize the impact. Learn more in this Foundation Marketing piece on incorporating AI into your content workflow.

Once you have identified your goals, it’s time to get your team on board and assess what tools are available in the market.

Recommended Resources:

2. Validate Your AI-Related Assumptions

Assumptions are dangerous — especially when it comes to implementing new tech.

Don’t assume AI is going to fix all your problems.

Instead, start with small experiments and track their progress carefully.

3. Conduct Persona and Audience Research

Social media isn’t something that you can just jump into.

You need to understand your audience and ideal customers. AI can help with this, but you’ll need to be familiar with best practices. If you need a primer, this will help:

Once you understand the basics, consider ways in which AI can augment your approach.

4. Select the Right Social Channels

Not every social media channel is the same.

It’s important that you understand what channel is right for you and embrace it.

The way you use AI for X is going to be different from the way you use AI for LinkedIn. On X, you might use AI to help you develop a long-form thread that is filled with facts and figures. On LinkedIn however, you might use AI to repurpose a blog post and turn it into a carousel PDF. The content that works on X and that AI can facilitate creating is different from the content that you can create and use on LinkedIn.

The audiences are different.

The content formats are different.

So operate and create a plan accordingly.

Recommended Tools and Resources:

5. Identify Key Metrics and KPIs

What metrics are you trying to influence the most?

Spend time understanding the social media metrics that matter to your business and make sure that they’re prioritized as you think about the ways in which you use AI.

These are a few that matter most:

Reach: Post reach signifies the count of unique users who viewed your post. How much of your content truly makes its way to users’ feeds?
Clicks: This refers to the number of clicks on your content or account. Monitoring clicks per campaign is crucial for grasping what sparks curiosity or motivates people to make a purchase.
Engagement: The total social interactions divided by the number of impressions. This metric reveals how effectively your audience perceives you and their readiness to engage.

Of course, it’s going to depend greatly on your business.

But with this information, you can ensure that your AI social media strategy is rooted in goals.

6. Choose the Right AI Tools

The AI landscape is filled with trash and treasure.

Pick AI tools that are most likely to align with your needs and your level of tech-savviness.

For example, if you’re a blogger creating content about pizza recipes, you can use HubSpot’s AI social caption generator to write the message on your behalf:

The benefit of an AI tool like HubSpot and the caption generator is that what at one point took 30-40 minutes to come up with — you can now have it at your fingertips in seconds. The HubSpot AI caption generator is trained on tons of data around social media content and makes it easy for you to get inspiration or final drafts on what can be used to create great content.

Consider your budget, the learning curve, and what kind of support the tool offers.

7. Evaluate and Refine Your Social Media and AI Strategy

AI isn’t a magic wand; it’s a set of complex tools and technology.

You need to be willing to pivot as things come to fruition.

If you notice that a certain activity is falling flat, consider how AI can support that process.

Did you notice that your engagement isn’t where you want it to be? Consider using an AI tool to assist with crafting more engaging social media posts.

Make AI Work for You — Now and in the Future

AI has the power to revolutionize your social media strategy in ways you may have never thought possible. With its ability to conduct customer research, create personalized content, and so much more, thinking about the future of social media is fascinating.

We’re going through one of the most interesting times in history.

Stay equipped to ride the way of AI and ensure that you’re embracing the best practices outlined in this piece to get the most out of the technology.

MARKETING

Advertising in local markets: A playbook for success

Published

2 days ago

April 21, 2024

Entireweb News Bot

Advertising in local markets: A playbook for success

Many brands, such as those in the home services industry or a local grocery chain, market to specific locations, cities or regions. There are also national brands that want to expand in specific local markets.

Regardless of the company or purpose, advertising on a local scale has different tactics than on a national scale. Brands need to connect their messaging directly with the specific communities they serve and media to their target demo. Here’s a playbook to help your company succeed when marketing on a local scale.

1. Understand local vs. national campaigns

Local advertising differs from national campaigns in several ways:

Audience specificity: By zooming in on precise geographic areas, brands can tailor messaging to align with local communities’ customs, preferences and nuances. This precision targeting ensures that your message resonates with the right target audience.
Budget friendliness: Local advertising is often more accessible for small businesses. Local campaign costs are lower, enabling brands to invest strategically within targeted locales. This budget-friendly nature does not diminish the need for strategic planning; instead, it emphasizes allocating resources wisely to maximize returns. As a result, testing budgets can be allocated across multiple markets to maximize learnings for further market expansion.
Channel selection: Selecting the correct channels is vital for effective local advertising. Local newspapers, radio stations, digital platforms and community events each offer advantages. The key lies in understanding where your target audience spends time and focusing efforts to ensure optimal engagement.
Flexibility and agility: Local campaigns can be adjusted more swiftly in response to market feedback or changes, allowing brands to stay relevant and responsive.

Maintaining brand consistency across local touchpoints reinforces brand identity and builds a strong, recognizable brand across markets.

2. Leverage customized audience segmentation

Customized audience segmentation is the process of dividing a market into distinct groups based on specific demographic criteria. This marketing segmentation supports the development of targeted messaging and media plans for local markets.

For example, a coffee chain might cater to two distinct segments: young professionals and retirees. After identifying these segments, the chain can craft messages, offers and media strategies relating to each group’s preferences and lifestyle.

To reach young professionals in downtown areas, the chain might focus on convenience, quality coffee and a vibrant atmosphere that is conducive to work and socializing. Targeted advertising on Facebook, Instagram or Connected TV, along with digital signage near office complexes, could capture the attention of this demographic, emphasizing quick service and premium blends.

Conversely, for retirees in residential areas, the chain could highlight a cozy ambiance, friendly service and promotions such as senior discounts. Advertisements in local print publications, community newsletters, radio stations and events like senior coffee mornings would foster a sense of community and belonging.

Dig deeper: Niche advertising: 7 actionable tactics for targeted marketing

3. Adapt to local market dynamics

Various factors influence local market dynamics. Brands that navigate changes effectively maintain a strong audience connection and stay ahead in the market. Here’s how consumer sentiment and behavior may evolve within a local market and the corresponding adjustments brands can make.

Cultural shifts, such as changes in demographics or societal norms, can alter consumer preferences within a local community. For example, a neighborhood experiencing gentrification may see demand rise for specific products or services.
- Respond by updating your messaging to reflect the evolving cultural landscape, ensuring it resonates with the new demographic profile.
Economic conditions are crucial. For example, during downturns, consumers often prioritize value and practicality.
- Highlight affordable options or emphasize the practical benefits of your offerings to ensure messaging aligns with consumers’ financial priorities. The impact is unique to each market and the marketing message must also be dynamic.
Seasonal trends impact consumer behavior.
- Align your promotions and creative content with changing seasons or local events to make your offerings timely and relevant.
New competitors. The competitive landscape demands vigilance because new entrants or innovative competitor campaigns can shift consumer preferences.
- Differentiate by focusing on your unique selling propositions, such as quality, customer service or community involvement, to retain consumer interest and loyalty.

4. Apply data and predictive analytics

Data and predictive analytics are indispensable tools for successfully reaching local target markets. These technologies provide consumer behavior insights, enabling you to anticipate market trends and adjust strategies proactively.

Price optimization: By analyzing consumer demand, competitor pricing and market conditions, data analytics enables you to set prices that attract customers while ensuring profitability.
Competitor analysis: Through analysis, brands can understand their positioning within the local market landscape and identify opportunities and threats. Predictive analytics offer foresight into competitors’ potential moves, allowing you to strategize effectively to maintain a competitive edge.
Consumer behavior: Forecasting consumer behavior allows your brand to tailor offerings and marketing messages to meet evolving consumer needs and enhance engagement.
Marketing effectiveness: Analytics track the success of advertising campaigns, providing insights into which strategies drive conversions and sales. This feedback loop enables continuous optimization of marketing efforts for maximum impact.
Inventory management: In supply chain management, data analytics predict demand fluctuations, ensuring inventory levels align with market needs. This efficiency prevents stockouts or excess inventory, optimizing operational costs and meeting consumer expectations.

Dig deeper: Why you should add predictive modeling to your marketing mix

5. Counter external market influences

Consider a clothing retailer preparing for a spring collection launch. By analyzing historical weather data and using predictive analytics, the brand forecasts an unseasonably cool start to spring. Anticipating this, the retailer adjusts its campaign to highlight transitional pieces suitable for cooler weather, ensuring relevance despite an unexpected chill.

Simultaneously, predictive models signal an upcoming spike in local media advertising rates due to increased market demand. Retailers respond by reallocating a portion of advertising budgets to digital channels, which offer more flexibility and lower costs than traditional media. This shift enables brands to maintain visibility and engagement without exceeding budget, mitigating the impact of external forces on advertising.

6. Build consumer confidence with messaging

Localized messaging and tailored customer service enhance consumer confidence by demonstrating your brand’s understanding of the community. For instance, a grocery store that curates cooking classes featuring local cuisine or sponsors community events shows commitment to local culture and consumer interests.

Similarly, a bookstore highlighting local authors or topics relevant to the community resonates with local customers. Additionally, providing service that addresses local needs — such as bilingual service and local event support — reinforces the brand’s values and response to the community.

Through these localized approaches, brands can build trust and loyalty, bridging the gap between corporate presence and local relevance.

7. Dominate with local advertising

To dominate local markets, brands must:

Harness hyper-targeted segmentation and geo-targeted advertising to reach and engage precise audiences.
Create localized content that reflects community values, engage in community events, optimize campaigns for mobile and track results.
Fine-tune strategies, outperform competitors and foster lasting relationships with customers.

These strategies will enable your message to resonate with local consumers, differentiate you in competitive markets and ensure you become a major player in your specific area.

Dig deeper: The 5 critical elements for local marketing success

Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.

MARKETING

Battling for Attention in the 2024 Election Year Media Frenzy

Published

3 days ago

April 20, 2024

Entireweb News Bot

Battling for Attention in the 2024 Election Year Media Frenzy

As we march closer to the 2024 U.S. presidential election, CMOs and marketing leaders need to prepare for a significant shift in the digital advertising landscape. Election years have always posed unique challenges for advertisers, but the growing dominance of digital media has made the impact more profound than ever before.

In this article, we’ll explore the key factors that will shape the advertising environment in the coming months and provide actionable insights to help you navigate these turbulent waters.

The Digital Battleground

The rise of cord-cutting and the shift towards digital media consumption have fundamentally altered the advertising landscape in recent years. As traditional TV viewership declines, political campaigns have had to adapt their strategies to reach voters where they are spending their time: on digital platforms.

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According to a recent report by eMarketer, the number of cord-cutters in the U.S. is expected to reach 65.1 million by the end of 2023, representing a 6.9% increase from 2022. This trend is projected to continue, with the number of cord-cutters reaching 72.2 million by 2025.

Moreover, a survey conducted by Pew Research Center in 2023 found that 62% of U.S. adults do not have a cable or satellite TV subscription, up from 61% in 2022 and 50% in 2019. This data further underscores the accelerating shift away from traditional TV and towards streaming and digital media platforms.

As these trends continue, political advertisers will have no choice but to follow their audiences to digital channels. In the 2022 midterm elections, digital ad spending by political campaigns reached $1.2 billion, a 50% increase from the 2018 midterms. With the 2024 presidential election on the horizon, this figure is expected to grow exponentially, as campaigns compete for the attention of an increasingly digital-first electorate.

For brands and advertisers, this means that the competition for digital ad space will be fiercer than ever before. As political ad spending continues to migrate to platforms like Meta, YouTube, and connected TV, the cost of advertising will likely surge, making it more challenging for non-political advertisers to reach their target audiences.

To navigate this complex and constantly evolving landscape, CMOs and their teams will need to be proactive, data-driven, and willing to experiment with new strategies and channels. By staying ahead of the curve and adapting to the changing media consumption habits of their audiences, brands can position themselves for success in the face of the electoral advertising onslaught.

Rising Costs and Limited Inventory

As political advertisers flood the digital market, the cost of advertising is expected to skyrocket. CPMs (cost per thousand impressions) will likely experience a steady climb throughout the year, with significant spikes anticipated in May, as college students come home from school and become more engaged in political conversations, and around major campaign events like presidential debates.

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For media buyers and their teams, this means that the tried-and-true strategies of years past may no longer be sufficient. Brands will need to be nimble, adaptable, and willing to explore new tactics to stay ahead of the game.

Black Friday and Cyber Monday: A Perfect Storm

The challenges of election year advertising will be particularly acute during the critical holiday shopping season. Black Friday and Cyber Monday, which have historically been goldmines for advertisers, will be more expensive and competitive than ever in 2024, as they coincide with the final weeks of the presidential campaign.

To avoid being drowned out by the political noise, brands will need to start planning their holiday campaigns earlier than usual. Building up audiences and crafting compelling creative assets well in advance will be essential to success, as will a willingness to explore alternative channels and tactics. Relying on cold audiences come Q4 will lead to exceptionally high costs that may be detrimental to many businesses.

Navigating the Chaos

While the challenges of election year advertising can seem daunting, there are steps that media buyers and their teams can take to mitigate the impact and even thrive in this environment. Here are a few key strategies to keep in mind:

Start early and plan for contingencies: Begin planning your Q3 and Q4 campaigns as early as possible, with a focus on building up your target audiences and developing a robust library of creative assets.

Be sure to build in contingency budgets to account for potential cost increases, and be prepared to pivot your strategy as the landscape evolves.

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Embrace alternative channels: Consider diversifying your media mix to include channels that may be less impacted by political ad spending, such as influencer marketing, podcast advertising, or sponsored content. Investing in owned media channels, like email marketing and mobile apps, can also provide a direct line to your customers without the need to compete for ad space.

Owned channels will be more important than ever. Use cheaper months leading up to the election to build your email lists and existing customer base so that your BF/CM can leverage your owned channels and warm audiences.

Craft compelling, shareable content: In a crowded and noisy advertising environment, creating content that resonates with your target audience will be more important than ever. Focus on developing authentic, engaging content that aligns with your brand values and speaks directly to your customers’ needs and desires.

By tapping into the power of emotional triggers and social proof, you can create content that not only cuts through the clutter but also inspires organic sharing and amplification.

Reflections

The 2024 election year will undoubtedly bring new challenges and complexities to the world of digital advertising. But by staying informed, adaptable, and strategic in your approach, you can navigate this landscape successfully and even find new opportunities for growth and engagement.

As a media buyer or agnecy, your role in steering your brand through these uncharted waters will be critical. By starting your planning early, embracing alternative channels and tactics, and focusing on creating authentic, resonant content, you can not only survive but thrive in the face of election year disruptions.

So while the road ahead may be uncertain, one thing is clear: the brands that approach this challenge with creativity, agility, and a steadfast commitment to their customers will be the ones that emerge stronger on the other side.