MARKETING

15 Steps for the Perfect Split Test

Published

2 years ago

March 3, 2022

When marketers like us create landing pages, write email copy, or design call-to-action buttons, it can be tempting to use our intuition to predict what will make people click and connect.

However, you’re much better off conducting A/B testing than basing marketing decisions off of a “feeling”, as this can be detrimental to your results.

Keep reading to learn how to conduct the entire A/B testing process before, during, and after data collection so you can make the best decisions from your results.

What is A/B testing?

A/B testing, also known as split testing, is a marketing experiment wherein you split your audience to test a number of variations of a campaign and determine which performs better. In other words, you can show version A of a piece of marketing content to one half of your audience, and version B to another.

A/B testing can be valuable because different audiences behave, well, differently. Something that works for one company may not necessarily work for another. In fact, conversion rate optimization (CRO) experts hate the term “best practices” because it may not actually be the best practice for you. But, this kind of testing can be complex if you’re not careful.

Let’s go over how A/B testing works to ensure that you don’t make incorrect assumptions about what your audience likes.

How does A/B testing Work?

To run an A/B test, you need to create two different versions of one piece of content, with changes to a single variable. Then, you’ll show these two versions to two similarly sized audiences and analyze which one performed better over a specific period of time (long enough to make accurate conclusions about your results).

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A/B testing helps marketers observe how one version of a piece of marketing content performs alongside another. Here are two types of A/B tests you might conduct in an effort to increase your website’s conversion rate:

Example 1: User Experience Test

Perhaps you want to see if moving a certain call-to-action (CTA) button to the top of your homepage instead of keeping it in the sidebar will improve its click-through rate.

To A/B test this theory, you’d create another, alternative web page that uses the new CTA placement. The existing design with the sidebar CTA — or the “control” — is Version A. Version B with the CTA at the top is the “challenger.” Then, you’d test these two versions by showing each of them to a predetermined percentage of site visitors. Ideally, the percentage of visitors seeing either version is the same.

Learn how to easily A/B test a component of your website with HubSpot’s Marketing Hub.

Example 2: Design Test

Perhaps you want to find out if changing the color of your call-to-action (CTA) button can increase its click-through rate.

To A/B test this theory, you’d design an alternative CTA button with a different button color that leads to the same landing page as the control. If you usually use a red call-to-action button in your marketing content, and the green variation receives more clicks after your A/B test, this could merit changing the default color of your call-to-action buttons to green from now on.

To learn more about A/B testing, download our free introductory guide here.

A/B Testing in Marketing

A/B testing has a multitude of benefits to a marketing team, depending on what it is you decide to test. Above all, though, these tests are valuable to a business because they’re low in cost but high in reward.

Let’s say you employ a content creator with a salary of $50,000/year. This content creator publishes five articles per week for the company blog, totaling 260 articles per year. If the average post on the company’s blog generates 10 leads, you could say it costs just over $192 to generate 10 leads for the business ($50,000 salary ÷ 260 articles = $192 per article). That’s a solid chunk of change.

Now, if you ask this content creator to spend two days developing an A/B test on one article, instead of writing two articles in that time period, you might burn $192 because you’re publishing one fewer article. But if that A/B test finds you can increase each article’s conversion rate from 10 to 20 leads, you just spent $192 to potentially double the number of customers your business gets from your blog.

If the test fails, of course, you lost $192 — but now you can make your next A/B test even more educated. If that second test succeeds in doubling your blog’s conversion rate, you ultimately spent $384 to potentially double your company’s revenue. No matter how many times your A/B test fails, its eventual success will almost always outweigh the cost to conduct it.

There are many types of split tests you can run to make the experiment worth it in the end. Here are some common goals marketers have for their business when A/B testing:

Increased Website Traffic: Testing different blog post titles or webpage titles can change the number of people who click on that hyperlinked title to get to your website. This can increase website traffic as a result.

Higher Conversion Rate: Testing different locations, colors, or even anchor text on your CTAs can change the number of people who click these CTAs to get to a landing page. This can increase the number of people who fill out forms on your website, submit their contact info to you, and “convert” into a lead.
Lower Bounce Rate: If your website visitors leave (or “bounce”) quickly after visiting your website, testing different blog post introductions, fonts, or featured images can reduce this bounce rate and retain more visitors.
Lower Cart Abandonment: Ecommerce businesses see an average of 70% of customers leave their website with items in their shopping cart. This is known as “shopping cart abandonment” and is, of course, detrimental to any online store. Testing different product photos, check-out page designs, and even where shipping costs are displayed can lower this abandonment rate.

Now, let’s walk through the checklist for setting up, running, and measuring an A/B test.

How to Conduct A/B Testing

Follow along with our free A/B testing kit with everything you need to run A/B testing including a test tracking template, a how-to guide for instruction and inspiration, and a statistical significance calculator to see if your tests were wins, losses, or inconclusive.

Before the A/B Test

Let’s cover the steps to take before you start your A/B test.

1. Pick one variable to test.

As you optimize your web pages and emails, you might find there are a number of variables you want to test. But to evaluate how effective a change is, you’ll want to isolate one “independent variable” and measure its performance. Otherwise, you can’t be sure which variable was responsible for changes in performance.

You can test more than one variable for a single web page or email — just be sure you’re testing them one at a time.

To determine your variable, look at the elements in your marketing resources and their possible alternatives for design, wording, and layout. Other things you might test include email subject lines, sender names, and different ways to personalize your emails.

Keep in mind that even simple changes, like changing the image in your email or the words on your call-to-action button, can drive big improvements. In fact, these sorts of changes are usually easier to measure than the bigger ones.

Note: There are some times when it makes more sense to test multiple variables rather than a single variable. This is a process called multivariate testing. If you’re wondering whether you should run an A/B test versus a multivariate test, here’s a helpful article from Optimizely that compares the two processes.

2. Identify your goal.

Although you’ll measure several metrics during any one test, choose a primary metric to focus on before you run the test. In fact, do it before you even set up the second variation. This is your “dependent variable,” which changes based on how you manipulate the independent variable.

Think about where you want this dependent variable to be at the end of the split test. You might even state an official hypothesis and examine your results based on this prediction.

If you wait until afterward to think about which metrics are important to you, what your goals are, and how the changes you’re proposing might affect user behavior, then you might not set up the test in the most effective way.

3. Create a ‘control’ and a ‘challenger.’

You now have your independent variable, your dependent variable, and your desired outcome. Use this information to set up the unaltered version of whatever you’re testing as your control scenario. If you’re testing a web page, this is the unaltered page as it exists already. If you’re testing a landing page, this would be the landing page design and copy you would normally use.

From there, build a challenger — the altered website, landing page, or email that you’ll test against your control. For example, if you’re wondering whether adding a testimonial to a landing page would make a difference in conversions, set up your control page with no testimonials. Then, create your challenger with a testimonial.

4. Split your sample groups equally and randomly.

For tests where you have more control over the audience — like with emails — you need to test with two or more audiences that are equal in order to have conclusive results.

How you do this will vary depending on the A/B testing tool you use. If you’re a HubSpot Enterprise customer conducting an A/B test on an email, for example, HubSpot will automatically split traffic to your variations so that each variation gets a random sampling of visitors.

5. Determine your sample size (if applicable).

How you determine your sample size will also vary depending on your A/B testing tool, as well as the type of A/B test you’re running.

If you’re A/B testing an email, you’ll probably want to send an A/B test to a subset of your list that is large enough to achieve statistically significant results. Eventually, you’ll pick a winner and send the winning variation on to the rest of the list. (See “The Science of Split Testing” ebook at the end of this article for more on calculating your sample size.)

If you’re a HubSpot Enterprise customer, you’ll have some help determining the size of your sample group using a slider. It’ll let you do a 50/50 A/B test of any sample size — although all other sample splits require a list of at least 1,000 recipients.

ab testing sample size settings in hubspot

If you’re testing something that doesn’t have a finite audience, like a web page, then how long you keep your test running will directly affect your sample size. You’ll need to let your test run long enough to obtain a substantial number of views. Otherwise, it will be hard to tell whether there was a statistically significant difference between variations.

6. Decide how significant your results need to be.

Once you’ve picked your goal metric, think about how significant your results need to be to justify choosing one variation over another. Statistical significance is a super important part of the A/B testing process that’s often misunderstood. If you need a refresher, I recommend reading this blog post on statistical significance from a marketing standpoint.

The higher the percentage of your confidence level, the more sure you can be about your results. In most cases, you’ll want a confidence level of 95% minimum — preferably even 98% — especially if it was a time-intensive experiment to set up. However, sometimes it makes sense to use a lower confidence rate if you don’t need the test to be as stringent.

Matt Rheault, a senior software engineer at HubSpot, likes to think of statistical significance like placing a bet. What odds are you comfortable placing a bet on? Saying “I’m 80% sure this is the right design and I’m willing to bet everything on it” is similar to running an A/B test to 80% significance and then declaring a winner.

Rheault also says you’ll likely want a higher confidence threshold when testing for something that only slightly improves conversion rate. Why? Because random variance is more likely to play a bigger role.

“An example where we could feel safer lowering our confidence threshold is an experiment that will likely improve conversion rate by 10% or more, such as a redesigned hero section,” he explained.

“The takeaway here is that the more radical the change, the less scientific we need to be process-wise. The more specific the change (button color, microcopy, etc.), the more scientific we should be because the change is less likely to have a large and noticeable impact on conversion rate.”

7. Make sure you’re only running one test at a time on any campaign.

Testing more than one thing for a single campaign — even if it’s not on the same exact asset — can complicate results. For example, if you A/B test an email campaign that directs to a landing page at the same time that you’re A/B testing that landing page, how can you know which change caused the increase in leads?

During the A/B Test

Let’s cover the steps to take during your A/B test.

8. Use an A/B testing tool.

To do an A/B test on your website or in an email, you’ll need to use an A/B testing tool. If you’re a HubSpot Enterprise customer, the HubSpot software has features that let you A/B test emails (learn how here), calls-to-action (learn how here), and landing pages (learn how here).

For non-HubSpot Enterprise customers, other options include Google Analytics, which lets you A/B test up to 10 full versions of a single web page and compare their performance using a random sample of users.

9. Test both variations simultaneously.

Timing plays a significant role in your marketing campaign’s results, whether it’s time of day, day of the week, or month of the year. If you were to run Version A during one month and Version B a month later, how would you know whether the performance change was caused by the different design or the different month?

When you run A/B tests, you’ll need to run the two variations at the same time, otherwise you may be left second-guessing your results.

The only exception here is if you’re testing timing itself, like finding the optimal times for sending out emails. This is a great thing to test because depending on what your business offers and who your subscribers are, the optimal time for subscriber engagement can vary significantly by industry and target market.

10. Give the A/B test enough time to produce useful data.

Again, you’ll want to make sure that you let your test run long enough to obtain a substantial sample size. Otherwise, it’ll be hard to tell whether there was a statistically significant difference between the two variations.

How long is long enough? Depending on your company and how you execute the A/B test, getting statistically significant results could happen in hours … or days … or weeks. A big part of how long it takes to get statistically significant results is how much traffic you get — so if your business doesn’t get a lot of traffic to your website, it’ll take much longer for you to run an A/B test.

Read this blog post to learn more about sample size and timing.

11. Ask for feedback from real users.

A/B testing has a lot to do with quantitative data … but that won’t necessarily help you understand why people take certain actions over others. While you’re running your A/B test, why not collect qualitative feedback from real users?

One of the best ways to ask people for their opinions is through a survey or poll. You might add an exit survey on your site that asks visitors why they didn’t click on a certain CTA, or one on your thank-you pages that asks visitors why they clicked a button or filled out a form.

You might find, for example, that a lot of people clicked on a call-to-action leading them to an ebook, but once they saw the price, they didn’t convert. That kind of information will give you a lot of insight into why your users are behaving in certain ways.

After the A/B Test

Finally, let’s cover the steps to take after your A/B test.

12. Focus on your goal metric.

Again, although you’ll be measuring multiple metrics, keep your focus on that primary goal metric when you do your analysis.

For example, if you tested two variations of an email and chose leads as your primary metric, don’t get caught up on open rate or click-through rate. You might see a high click-through rate and poor conversion rates, in which case you might end up choosing the variation that had a lower click-through rate in the end.

13. Measure the significance of your results using our A/B testing calculator.

Now that you’ve determined which variation performs the best, it’s time to determine whether your results are statistically significant. In other words, are they enough to justify a change?

To find out, you’ll need to conduct a test of statistical significance. You could do that manually … or you could just plug in the results from your experiment to our free A/B testing calculator.

For each variation you tested, you’ll be prompted to input the total number of tries, like emails sent or impressions seen. Then, enter the number of goals it completed — generally you’ll look at clicks, but this could also be other types of conversions.

hubspot ab testing calculator

The calculator will spit out the confidence level your data produces for the winning variation. Then, measure that number against the value you chose to determine statistical significance.

14. Take action based on your results.

If one variation is statistically better than the other, you have a winner. Complete your test by disabling the losing variation in your A/B testing tool.

If neither variation is statistically better, you’ve just learned that the variable you tested didn’t impact results, and you’ll have to mark the test as inconclusive. In this case, stick with the original variation, or run another test. You can use the failed data to help you figure out a new iteration on your new test.

While A/B tests help you impact results on a case-by-case basis, you can also apply the lessons you learn from each test and apply it to future efforts.

For example, if you’ve conducted A/B tests in your email marketing and have repeatedly found that using numbers in email subject lines generates better clickthrough rates, you might want to consider using that tactic in more of your emails.

15. Plan your next A/B test.

The A/B test you just finished may have helped you discover a new way to make your marketing content more effective — but don’t stop there. There’s always room for more optimization.

You can even try conducting an A/B test on another feature of the same web page or email you just did a test on. For example, if you just tested a headline on a landing page, why not do a new test on body copy? Or a color scheme? Or images? Always keep an eye out for opportunities to increase conversion rates and leads.

You can use HubSpot’s A/B Test Tracking Kit to plan and organize your experiments.

Download This Template Now

How to Read A/B Testing Results

As a marketer, you know the value of automation. Given this, you likely use software that handles the A/B test calculations for you — a huge help. But, after the calculations are done, you need to know how to read your results. Let’s go over how.

1. Check your goal metric.

The first step in reading your A/B test results is looking at your goal metric, which is usually conversion rate. After you’ve plugged your results into your A/B testing calculator, you’ll get two results for each version you’re testing. You’ll also get a significant result for each of your variations.

2. Compare your conversion rates.

By looking at your results, you’ll likely be able to tell if one of your variations performed better than the other. However, the true test of success is whether the results you have are statistically significant. This means that one variation performed better than the other at a significant level because, say, the CTA text was more compelling.

Say, for example, Variation A had a 16.04% conversion rate and variation B had a 16.02% conversion rate, and your confidence interval of statistical significance is 95%. Variation A has a higher conversion rate, but the results are not statistically significant, meaning that Variation A won’t significantly improve your overall conversion rate.

3. Segment your audiences for further insights.

Regardless of significance, it’s valuable to break down your results by audience segment to understand how each key area responded to your variations. Common variables for segmenting audiences are:

Visitor type, or which version performed best for new visitors versus repeat visitors.
Device type, or which version performed best on mobile versus desktop.
Traffic source, or which version performed best based on where traffic to your two variations originated.

Let’s go over some examples of A/B experiments you could run for your business.

A/B Testing Examples

We’ve discussed how A/B tests are used in marketing and how to conduct one — but how do they actually look in practice?

As you might guess, we run many A/B tests to increase engagement and drive conversions across our platform. Here are five examples of A/B tests to inspire your own experiments.

1. Site Search

Site search bars help users quickly find what they’re after on a particular website. HubSpot found from previous analysis that visitors who interacted with its site search bar were more likely to convert on a blog post. So, we ran an A/B test in an attempt to increase engagement with the search bar.

In this test, search bar functionality was the independent variable and views on the content offer thank you page was the dependent variable. We used one control condition and three challenger conditions in the experiment.

In the control condition (variant A), the search bar remained unchanged.

In variant B, the search bar was made larger and more visually prominent, and the placeholder text was set to “search by topic.”

Variant C appeared identical to variant B, but only searched the HubSpot Blog rather than the entire website.

In variant D, the search bar was made larger but the placeholder text was set to “search the blog.” This variant also searched only the HubSpot Blog

We found variant D to be the most effective: It increased conversions by 3.4% over the control and increased the percentage of users who used the search bar by 6.5%.

2. Mobile CTAs

HubSpot uses several CTAs for content offers in our blog posts, including ones in the body of posts as well as at the bottom of the page. We test these CTAs extensively for optimize their performance.

For our mobile users, we ran an A/B test to see which type of bottom-of-page CTA converted best. For our independent variable, we altered the design of the CTA bar. Specifically, we used one control and three challengers in our test. For our dependent variables, we used pageviews on the CTA thank you page and CTA clicks.

The control condition included our normal placement of CTAs at the bottom of posts. In variant B, the CTA had no close or minimize option.

variant B of the hubspot mobile CTA AB test In variant C, mobile readers could close the CTA by tapping an X icon. Once it was closed out, it wouldn’t reappear.

variant C of the hubspot mobile CTA AB test

In variant D, we included an option to minimize the CTA with an up/down caret.

variant d of hubspot's mobile cta A B test

Our tests found all variants to be successful. Variant D was the most successful, with a 14.6% increase in conversions over the control. This was followed by variant C with an 11.4% increase and variant B with a 7.9% increase.

3. Author CTAs

In another CTA experiment, HubSpot tested whether adding the word “free” and other descriptive language to author CTAs at the top of blog posts would increase content leads. Past research suggested that using “free” in CTA text would drive more conversions and that text specifying the type of content offered would be helpful for SEO and accessibility.

In the test, the independent variable was CTA text and the main dependent variable was conversion rate on the content offer form.

In the control condition, author CTA text was unchanged (see the orange button in the image below).

variant A of the author CTA AB test

In variant B, the word “free” was added to the CTA text.

variant B of the author CTA AB test

In variant C, descriptive wording was added to the CTA text in addition to “free.”

variant C of the author CTA AB test

Interestingly, variant B saw a loss in form submissions, down by 14% compared to the control. This was unexpected, since including “free” in content offer text is widely considered a best practice.

Meanwhile, form submissions in variant C outperformed the control by 4%. It was concluded that adding descriptive text to the author CTA helped users understand the offer and thus made them more likely to download.

4. Blog Table of Contents

To help users better navigate the blog, HubSpot tested a new Table of Contents (TOC) module. The goal was to improve user experience by presenting readers with their desired content more quickly. We also tested whether adding a CTA to this TOC module would increase conversions.

The independent variable of this A/B test was the inclusion and type of TOC module in blog posts, and the dependent variables were conversion rate on content offer form submissions and clicks on the CTA inside the TOC module.

The control condition did not include the new TOC module —control posts either had no table of contents, or a simple bulleted list of anchor links within the body of the post near the top of the article (pictured below).

variant A of the hubspot blog chapter module AB test

In variant B, the new TOC module was added to blog posts. This module was sticky, meaning it remained onscreen as users scrolled down the page. Variant B also included a content offer CTA at the bottom of the module.

variant B of the hubspot blog chapter module AB test

Variant C included an identical module to variant B but with the CTA removed.

variant C of the hubspot blog chapter module AB test

Both variants B and C did not increase the conversion rate on blog posts. The control condition outperformed variant B by 7% and performed equally with variant C. Also, few users interacted with the new TOC module or the CTA inside the module.

5. Review Notifications

To determine the best way of gathering customer reviews, we ran a split test of email notifications versus in-app notifications. Here, the independent variable was the type of notification and the dependent variable was the percentage of those who left a review out of all those who opened the notification.

In the control, HubSpot sent a plain text email notification asking users to leave a review. In variant B, HubSpot sent an email with a certificate image including the user’s name.

variant B of the hubspot notification AB test

For variant C, HubSpot sent users an in app-notification.

variant C of the hubspot notification AB test

Ultimately, both emails performed similarly and outperformed the in-app notifications. About 25% of users who opened an email left a review versus the 10.3% who opened in-app notifications. Emails were also more often opened by users.

Start A/B Testing Today

A/B testing allows you to get to the truth of what content and marketing your audience wants to see. Learn how to best carry out some of the steps above using the free e-book below.

Editor’s note: This post was originally published in May 2016 and has been updated for comprehensiveness.

MARKETING

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

Published

1 day 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.

1713626763 903 Battling for Attention in the 2024 Election Year Media Frenzy

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.

1713626764 197 Battling for Attention in the 2024 Election Year Media Frenzy

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.