MARKETING

How to Measure the Impact of Content Based on Intent

Published

2 years ago

March 2, 2022

How to Measure the Impact of Content Based on Intent

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.

When it comes to measuring the impact of content, you might think of KPIs like “sitewide conversion rate”, or picture an upward graph that shows an increase in traffic.

But are those metrics really meaningful? In this piece, I’ll argue that, no, they’re not. Instead, let’s focus on getting you actionable insights that can help your content flourish, by measuring its impact in a meaningful way.

The problem with sitewide conversion rates

Unless your website is a one-pager, the likelihood is that not all of your pages have the same intent. So why do we still measure conversion rates across an entire site?

The quick and honest answer here is that we do this because it’s easy and because that’s the way it’s always been done. But in reality, measuring your conversion rate across an entire site doesn’t give you any actionable insight – even when used in conjunction with volume of traffic.

It’s an oversimplification.

Using a sitewide conversion rate neglects to consider pages where the intent isn’t to buy something. Think about your blog pages, customer services or FAQ pages. A growth in traffic to these sections won’t directly lead to an increase in sales. But what it will do is drop your sitewide conversion rate. That’s not a bad thing, it just means that using sitewide conversion rates on their own isn’t the best way of measuring performance here.

The answer instead, is to make sure you can report on the intent of your pages to be able to understand what’s performing well and what’s not in their own right.

How can you do this? Well… we separate the pages in our reports based on their intent.

Separate pages based on their intent for reporting

Separating out pages based on their intent for reporting might sound like a pain, but there are ways you can automate this.

The biggest trick you can use is the URL structure. If you have a neat hierarchy, then this can work wonders to help you to group your pages in a way that makes sense to you.

Once they’re set up, you’ll be ready to report on your performance in a flash next time!

Here’s how you can do this in Google Analytics, Data Studio and in Excel/Google Sheets.

How to create segments in Universal Google Analytics

Creating custom segments in Universal Google Analytics allows you to pull out your data in a way that makes sense to you. It also allows you to quickly pull these segments into other reports, saving you countless hours.

What about GA4? “Segments” aren’t available in standard reports in GA4. An alternative called “Comparisons” are, but they can’t be saved once you exit the report. The key mechanics of how Comparisons work is similar to Segments, but can only be used as a quick review rather than an in-depth report. For in-depth reports that use Segments in GA4, you’ll need to visit “Explore” from the left hand tab and set up a new report.

If you haven’t used segments yet in Universal Analytics, you’ll find these by clicking on the blue circle of “All Users”. You’ll also see a button for “Choose segment from list” when looking at virtually any report in Google Analytics.

In Universal Analytics, you’ll see a list of segments that have already been created for you. But for now, these aren’t the ones we want to use. We want to create our own almighty segments.

So go ahead and click the big red button of “+ New Segment”.

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Now you’ll need to give your segment a name that will help you find it again later.

Here you can segment your data in pretty much any way you can think of. But for the purposes of today, we’re looking to create a segment to work out your conversion rate based on the intent of the page they landed on. For that, we need to head over to the “Advanced” section under “Conditions”.

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This is the place where the magic happens.

You can first choose whether you want to filter based on sessions or users. As we want to find sessions that started on a particular section of your site, you’ll want to keep this filter to “Sessions” and “Include”.

Next, you need to think about what section of the site you want to look at. One of the easiest ones you can start with is blog traffic, especially if you have /blog/, /news/ or similar as the defining hierarchy in your URLs.

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If you have both sections, then you can lump these together by using the “OR” function of the filter. This will then show you all of the data based on landing pages that contained either the /blog/ or /news/ in the hierarchy.

One tip: be careful which match condition you use. If you choose “exact match”, then this data might not include ALL of your data, as it won’t include any page landings where parameters were appended. Equally, if you have a hierarchy where the URL you’re looking to match is also used in other pages, then you might have to add exclusions to your filter.

When setting up your segment, always double check your data against your expected raw data in Google Analytics to check for accuracy. Small differences in the way you’ve set up your segments can impact the reliability of your data as you could either under- or over-estimate the volume of traffic, conversions or goals by assuming that your segment is giving you an accurate view. So, manually checking the raw data output against your logic can help to find any holes (or you could even create counter-segments using the reverse logic to check that you’ve covered 100% of your raw data).

When you save your segment, you’ll be able to review your subset of data in seconds, and pull them into other external reports.

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Here’s an example of what you’ll typically find when you’re looking at a conversion rate for all users, alongside your segments for commercial pages and blog pages.Your ‘true’ conversion rate for the pages that are designed to convert is much higher than your sitewide conversion rate. You’ll also see that your blog traffic (that might not be designed to convert) has a lower conversion rate – which has impacted your sitewide conversion rate, skewing your outlook on how they’re actually performing.

How to create segments in GA4

To use segments in GA4, you’ll need to visit the “Explore” section. Here, you’ll be able to create your own custom reports and delve deeper into your segmented data. If you’re new to GA4, it’s worth reading Google’s guide to Explorations.

In Explore, segments can be found when setting up your report — you can even add a separate comparative segment to benchmark your data against.

To add a new segment, click on the “Segments” section shown below on the left.

You’ll then be given options to “Include” and “Exclude” your dimensions based on metric values.

As the naming conventions of dimensions in GA4 are different to Universal, you’ll need to include sessions where the “Page location” (URL to me and you) contains “/blog/”. You can add “Or” statements here too if needed.

Once you’ve set up your report, with Explore, you can customize the metrics to view in your reports and choose how to visualize it, unlike Universal Analytics. The world is your oyster to create custom content-based reports here!

How to create Data Studio filters

I love using Google Data Studio. I think it’s an underused tool for content management. Sure, it’s used a lot for top-level reporting, but I’m talking about the real juicy, actionable reports.

When it comes to making deep-diving reports, using Data Studio saves time and allows you to bring together data from different sources like Google Sheets, Search Console, and Google Analytics.

When setting up your data sources from Google Analytics, you’ll be given the option of adding a Google Analytics segment (you’ll have to scroll down to the bottom of your data tab). Here you can import any segment you’ve already made. I’ve imported one of my brand’s Google Analytics segments:Staysure blog.

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As well as being able to import segments, you can also create your own filters when you click on “Add a filter”. Doing this prompts this box:

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Here you can give your filter a name. This isn’t saved back to Google Analytics, and will only ever be found in the Google Data Studio report that you’re working on, so if you want to work on something particularly complex that you want to reuse, it’s worth adding your conditions as a segment in GA.

Above, I’ve replicated the segment in GA to show you what it would look like if I only wanted to create that filter in Data Studio.

Another benefit of using Data Studio for reporting rather than Google Analytics is that you can layer your filters and blend data together to build in-depth reports that you can jump into without having to dig through data time and time again.

So, if I wanted to find out what percentage of organic landings my page contributed to, that answer’s pretty hard to find in GA without writing down numbers somewhere else, or scrolling through a full dataset.

Instead, in Data Studio, you can use the organic segment from GA and add on a custom filter to look at just the page you want to review. To get your magic number, blend the data to pull through:

Left hand side: All organic traffic: Dimension: Page, Metric: entrances (+ add a filter for organic)
Right hand side: Your new ‘page only’ segment: Dimension: Landing page (to act as the key match), Metric: entrances .

To make life easier, rename the fields by clicking on the “ABC” or “AUT” box next to the field name so that it’s something different…

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Once you’ve blended your data, you’ll need to create a new field. To do this, click on the Metric title that’s used for your new blended data chart – this then expands to show you data from table 1, table 2 and a new option at the bottom with a plus mark and “Create Field”. Click this to see this pop up:

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Here you can create your own formulas based off of your datasets. So this is where we do SUM(my chosen page entrances)/ SUM(all organic landings). It’s important to add the “SUM” when adding calculations to blended datasets to amalgamate the data.

Finish by naming your field and boom. You now know – for any date range you’ve chosen, what proportion of organic traffic that page accounts for.

If you want to get really fancy, you can even add a comparison date range to see how this percentage changes over time.

Creating segments in Google Sheets/Excel

If you want to go old-school, you can even filter pages in Google Sheets, or Excel.

Without manually going through each of your data points, you can create a new column and use a nested “if” statement mixed with a “regexmatch” statement.

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This formula has been used on some dummy data to show how you can speed up the categorization of pages based on URL mapping:

=if(REGEXMATCH(A2,”travel-insurance/”),”commercial”,if(regexmatch(A2,”news|blog”),”blog”,if(regexmatch(A2,”/customer-services/”),”customer services”,”other”)))

You can then use pivot tables to compile your data into segments.

Here, I’ve created a new pivot table using the above data, using the “Group” as the rows, and “Traffic” as the values. I’ve then changed the traffic values to show as a percentage of the column instead of as a sum. This now shows me, in a quick snapshot, how much traffic is attributed to each page type. Using this method can help to segment your data and see how your pages perform based on their intent. Add metrics like conversion rates, phone calls and softer metrics to really understand what makes these pages tick.

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What to do if your URLs aren’t clear when intent mapping

If the structure of your site doesn’t make it easy for you to map your intent easily, then you might need to create a master sheet of intent.

This can then be referred to via a VLookup in sheets, or to be used as a blended dataset in Google Data Studio against your other data.

If you want to get really fancy, you can tag your content data in Google Analytics by using a data import into a custom dimension. But you’ll still need to do the hard work in mapping your intent yourself.

Introduction to attribution modeling

Now you know how to review the impact of your content based on its intent, it’s time to make the story a bit more complicated.

Although measures of success with informational intent pages are seen as smaller wins, these pages can also help attribute to sales — eventually. Or, sessions to commercial pages that didn’t convert on a first hit might eventually lead to a sale a while later.

By only reviewing direct conversions in Google Analytics (which is the native metric that’s used), we run the risk of missing opportunities and not seeing the bigger picture of how people use our sites. This could lead to making decisions like culling content that’s actually helpful.

We know that people don’t live in a linear world. We don’t see a product we love and buy it immediately. (Okay, sure, I will put my hand up and admit that SOMETIMES, that’s how the world works.)

But most of the time, we hem and haw over decisions, shop around, look at various sites on our mobiles, searching via Google, social and asking our friends and family for input. We swap devices before we decide what to buy, or we might even walk into a real life shop and talk to someone about it.

To measure this kind of behavior is called multi-channel attribution modeling. It’s an understanding that people don’t simply visit and then buy in a linear way. Their decisions are multifaceted and that means our analytics should reflect that, and attribute leads or sales accordingly. There’s a great introduction to multi-channel attribution modeling by Avinash Kaushik if you fancy wandering down a rabbit hole of discovery there.

You’ll find loads of information on how to use attribution modeling in Google Analytics on a channel basis, but what you often won’t find is how you can do this on a landing page basis.

A search for “attribution modelling” “google analytics” gave me only 17,300 results on Google, suggesting it’s a pretty niche area in itself. Yet adding “landing page” in there, delivered only 2,790 results.

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So, not a lot of people are talking about this super powerful report. The reason why they aren’t talking about it isn’t because it’s a secret. It’s because it’s really hard to find.

Assisted conversions by landing page

To get to your assisted conversions by landing page report in Google Analytics, you’ll need to go to Conversions > Multi-Channel Funnels > Assisted Conversions.

Here, you’ll see a report that shows all of your assisted conversions, based on all of your goals.

Before we get too distracted like a kid in Disney World, let’s set this report up properly with the intention of finding out assisted conversions by landing page.

1. Change the conversions this report sees as a goal from “all” to sales, leads, etc. — whatever you deem as a conversion and are actively tracking. If you don’t change this setting, you’ll also be viewing all of your micro conversions that you’ve set as goals like video views or time on site.

2. Change your lookback window to something meaningful for your business. You can set this at any number of days up to 90.

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3. The report you’ll see will automatically be set to channel groupings. The suggested options for the primary dimension are all focused on channel breakdowns like Source/Medium. To change this, go to “other” and select “landing page URL”.

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What does the assisted conversion report by landing page show me?

Now you’ve got your data, it’s time to learn what you’re looking at.

Assisted conversions: shows you how many times that landing page helped someone to convert (but not in that session).
Assisted conversion value: if you’ve attributed a goal value, this column will show you its value.
Last Click or Direct Conversions: these are the conversions that you’d typically see in other GA reports that were part of the final converting session.
Last click or Direct Conversions value: again, if you’ve added a goal value, you’ll see this here.
Assisted/Last Click or Direct Conversions: this shows you a percentage of assisted conversions versus those that were part of the session that converted. The higher the number, the more important that page is as part of the journey to convert rather than a direct contributor.

How can I use the assisted conversion by landing page report?

You can use the assisted conversion report by landing page to:

Search for the impact of blog pages as part of a converting journey.
Use it to decide if landing pages can be removed without impacting conversion.
Understand the role that different pages have in converting visitors.

In summary:

We’ve learnt that:

Site-wide conversion rates don’t give us actionable insights by themselves.
The impact of a page should be measured based on its intent: informational, customer service, and commercial.
The intent of pages can be segmented using Google Analytics, Google Data Studio or Google Sheets, to give you a top level picture of how they’re performing as a whole towards a common aim.
Before you make any judgment on how a page is performing and whether it should be removed, consider its wider impact and use attribution modeling to better understand its performance.

I really hope you’ve found this useful and you’re now armed to make your own intent-based reports using whatever toolset you feel comfortable with.

Related Topics:Based Content Impact intent Measure

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MARKETING

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

Published

21 hours 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.