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

Effective Communication in Business as a Crisis Management Strategy

Published

3 hours ago

April 25, 2024

Entireweb News Bot

Effective Communication in Business as a Crisis Management Strategy

Everyday business life is full of challenges. These include data breaches, product recalls, market downturns and public relations conflicts that can erupt at any moment. Such situations pose a significant threat to a company’s financial health, brand image, or even its further existence. However, only 49% of businesses in the US have a crisis communications plan. It is a big mistake, as such a strategy can build trust, minimize damage, and even strengthen the company after it survives the crisis. Let’s discover how communication can transform your crisis and weather the chaos.

The ruining impact of the crisis on business

A crisis can ruin a company. Naturally, it brings losses. But the actual consequences are far worse than lost profits. It is about people behind the business – they feel the weight of uncertainty and fear. Employees start worrying about their jobs, customers might lose faith in the brand they once trusted, and investors could start looking elsewhere. It can affect the brand image and everything you build from the branding, business logo, social media can be ruined. Even after the crisis recovery, the company’s reputation can suffer, and costly efforts might be needed to rebuild trust and regain momentum. So, any sign of a coming crisis should be immediately addressed. Communication is one of the crisis management strategies that can exacerbate the situation.

The power of effective communication

Even a short-term crisis may have irreversible consequences – a damaged reputation, high employee turnover, and loss of investors. Communication becomes a tool that can efficiently navigate many crisis-caused challenges:

Improved trust. Crisis is a synonym for uncertainty. Leaders may communicate trust within the company when the situation gets out of control. Employees feel valued when they get clear responses. The same applies to the customers – they also appreciate transparency and are more likely to continue cooperation when they understand what’s happening. In these times, documenting these moments through event photographers can visually reinforce the company’s messages and enhance trust by showing real, transparent actions.
Reputation protection. Crises immediately spiral into gossip and PR nightmares. However, effective communication allows you to proactively address concerns and disseminate true information through the right channels. It minimizes speculation and negative media coverage.
Saved business relationships. A crisis can cause unbelievable damage to relationships with employees, customers, and investors. Transparent communication shows the company’s efforts to find solutions and keeps stakeholders informed and engaged, preventing misunderstandings and painful outcomes.
Faster recovery. With the help of communication, the company is more likely to receive support and cooperation. This collaborative approach allows you to focus on solutions and resume normal operations as quickly as possible.

It is impossible to predict when a crisis will come. So, a crisis management strategy mitigates potential problems long before they arise.

Tips on crafting an effective crisis communication plan.

To effectively deal with unforeseen critical situations in business, you must have a clear-cut communication action plan. This involves things like messages, FAQs, media posts, and awareness of everyone in the company. This approach saves precious time when the crisis actually hits. It allows you to focus on solving the problem instead of intensifying uncertainty and panic. Here is a step-by-step guide.

Identify your crisis scenarios.

Being caught off guard is the worst thing. So, do not let it happen. Conduct a risk assessment to pinpoint potential crises specific to your business niche. Consider both internal and external factors that could disrupt normal operations or damage the online reputation of your company. Study industry-specific issues, past incidents, and current trends. How will you communicate in each situation? Knowing your risks helps you prepare targeted communication strategies in advance. Of course, it is impossible to create a perfectly polished strategy, but at least you will build a strong foundation for it.

Form a crisis response team.

The next step is assembling a core team. It will manage communication during a crisis and should include top executives like the CEO, CFO, and CMO, and representatives from key departments like public relations and marketing. Select a confident spokesperson who will be the face of your company during the crisis. Define roles and responsibilities for each team member and establish communication channels they will work with, such as email, telephone, and live chat. Remember, everyone in your crisis response team must be media-savvy and know how to deliver difficult messages to the stakeholders.

Prepare communication templates.

When a crisis hits, things happen fast. That means communication needs to be quick, too. That’s why it is wise to have ready-to-go messages prepared for different types of crises your company may face. These messages can be adjusted to a particular situation when needed and shared on the company’s social media, website, and other platforms right away. These templates should include frequently asked questions and outline the company’s general responses. Make sure to approve these messages with your legal team for accuracy and compliance.

Establish communication protocols.

A crisis is always chaotic, so clear communication protocols are a must-have. Define trigger points – specific events that would launch the crisis communication plan. Establish a clear hierarchy for messages to avoid conflicting information. Determine the most suitable forms and channels, like press releases or social media, to reach different audiences. Here is an example of how you can structure a communication protocol:

Immediate alert. A company crisis response team is notified about a problem.
Internal briefing. The crisis team discusses the situation and decides on the next steps.
External communication. A spokesperson reaches the media, customers, and suppliers.
Social media updates. A trained social media team outlines the situation to the company audience and monitors these channels for misinformation or negative comments.
Stakeholder notification. The crisis team reaches out to customers and partners to inform them of the incident and its risks. They also provide details on the company’s response efforts and measures.
Ongoing updates. Regular updates guarantee transparency and trust and let stakeholders see the crisis development and its recovery.

Practice and improve.

Do not wait for the real crisis to test your plan. Conduct regular crisis communication drills to allow your team to use theoretical protocols in practice. Simulate different crisis scenarios and see how your people respond to these. It will immediately demonstrate the strong and weak points of your strategy. Remember, your crisis communication plan is not a static document. New technologies and evolving media platforms necessitate regular adjustments. So, you must continuously review and update it to reflect changes in your business and industry.

Wrapping up

The ability to handle communication well during tough times gives companies a chance to really connect with the people who matter most—stakeholders. And that connection is a foundation for long-term success. Trust is key, and it grows when companies speak honestly, openly, and clearly. When customers and investors trust the company, they are more likely to stay with it and even support it. So, when a crisis hits, smart communication not only helps overcome it but also allows you to do it with minimal losses to your reputation and profits.

MARKETING

Should Your Brand Shout Its AI and Marketing Plan to the World?

Published

1 day ago

April 24, 2024

Entireweb News Bot

To use AI or not to use AI, that is the question.

Let’s hope things work out better for you than they did for Shakespeare’s mad Danish prince with daddy issues.

But let’s add a twist to that existential question.

CMI’s chief strategy officer, Robert Rose, shares what marketers should really contemplate. Watch the video or read on to discover what he says:

Should you not use AI and be proud of not using it? Dove Beauty did that last week.

Should you use it but keep it a secret? Sports Illustrated did that last year.

Should you use AI and be vocal about using it? Agency giant Brandtech Group picked up the all-in vibe.

Should you not use it but tell everybody you are? The new term “AI washing” is hitting everywhere.

What’s the best option? Let’s explore.

Dove tells all it won’t use AI

Last week, Dove, the beauty brand celebrating 20 years of its Campaign for Real Beauty, pledged it would NEVER use AI in visual communication to portray real people.

In the announcement, they said they will create “Real Beauty Prompt Guidelines” that people can use to create images representing all types of physical beauty through popular generative AI programs. The prompt they picked for the launch video? “The most beautiful woman in the world, according to Dove.”

I applaud them for the powerful ad. But I’m perplexed by Dove issuing a statement saying it won’t use AI for images of real beauty and then sharing a branded prompt for doing exactly that. Isn’t it like me saying, “Don’t think of a parrot eating pizza. Don’t think about a parrot eating pizza,” and you can’t help but think about a parrot eating pizza right now?

Brandtech Group says it’s all in on AI

Now, Brandtech Group, a conglomerate ad agency, is going the other way. It’s going all-in on AI and telling everybody.

This week, Ad Age featured a press release — oops, I mean an article (subscription required) — with the details of how Brandtech is leaning into the takeaway from OpenAI’s Sam Altman, who says 95% of marketing work today can be done by AI.

A Brandtech representative talked about how they pitch big brands with two people instead of 20. They boast about how proud they are that its lean 7,000 staffers compete with 100,000-person teams. (To be clear, showing up to a pitch with 20 people has never been a good thing, but I digress.)

OK, that’s a differentiated approach. They’re all in. Ad Age certainly seemed to like it enough to promote it. Oops, I mean report about it.

False claims of using AI and not using AI

Offshoots of the all-in and never-will approaches also exist.

The term “AI washing” is de rigueur to describe companies claiming to use AI for something that really isn’t AI. The US Securities and Exchange Commission just fined two companies for using misleading statements about their use of AI in their business model. I know one startup technology organization faced so much pressure from their board and investors to “do something with AI” that they put a simple chatbot on their website — a glorified search engine — while they figured out what they wanted to do.

Lastly and perhaps most interestingly, companies have and will use AI for much of what they create but remain quiet about it or desire to keep it a secret. A recent notable example is the deepfake ad of a woman in a car professing the need for people to use a particular body wipe to get rid of body odor. It was purported to be real, but sharp-eyed viewers suspected the fake and called out the company, which then admitted it. Or was that the brand’s intent all along — the AI-use outrage would bring more attention?

This is an AI generated influencer video.
Looks 100% real. Even the interior car detailing.
UGC content for your brand is about to get really cheap. ☠️ pic.twitter.com/2m10RqoOW3
Advertisement

— Jon Elder | Amazon Growth | Private Label (@BlackLabelAdvsr) March 26, 2024

To yell or not to yell about your brand’s AI decision

Should a brand yell from a mountaintop that they use AI to differentiate themselves a la Brandtech? Or should a brand yell they’re never going to use AI to differentiate themselves a la Dove? Or should a brand use it and not yell anything? (I think it’s clear that a brand should not use AI and lie and say it is. That’s the worst of all choices.)

I lean far into not-yelling-from-mountaintop camp.

When I see a CEO proudly exclaim that they laid off 90% of their support workforce because of AI, I’m not surprised a little later when the value of their service is reduced, and the business is failing.

I’m not surprised when I hear “AI made us do it” to rationalize the latest big tech company latest rounds of layoffs. Or when a big consulting firm announces it’s going all-in on using AI to replace its creative and strategic resources.

I see all those things as desperate attempts for short-term attention or a distraction from the real challenge. They may get responses like, “Of course, you had to lay all those people off; AI is so disruptive,” or “Amazing. You’re so out in front of the rest of the pack by leveraging AI to create efficiency, let me cover your story.” Perhaps they get this response, “Your company deserves a bump in stock price because you’re already using this fancy new technology.”

But what happens if the AI doesn’t deliver as promoted? What happens the next time you need to lay off people? What happens the next time you need to prove your technologically forward-leaning?

Yelling out that you’re all in on a disruptive innovation, especially one the public doesn’t yet trust a lot is (at best) a business sugar high. That short-term burst of attention may or may not foul your long-term brand value.

Interestingly, the same scenarios can manifest when your brand proclaims loudly it is all out of AI, as Dove did. The sugar high may not last and now Dove has itself into a messaging box. One slip could cause distrust among its customers. And what if AI gets good at demonstrating diversity in beauty?

I tried Dove’s instructions and prompted ChatGPT for a picture of “the most beautiful woman in the world according to the Dove Real Beauty ad.”

It gave me this. Then this. And this. And finally, this.

She’s absolutely beautiful, but she doesn’t capture the many facets of diversity Dove has demonstrated in its Real Beauty campaigns. To be clear, Dove doesn’t have any control over generating the image. Maybe the prompt worked well for Dove, but it didn’t for me. Neither Dove nor you can know how the AI tool will behave.

To use AI or not to use AI?

When brands grab a microphone to answer that question, they work from an existential fear about the disruption’s meaning. They do not exhibit the confidence in their actions to deal with it.

Let’s return to Hamlet’s soliloquy:

Thus conscience doth make cowards of us all;

And thus the native hue of resolution

Is sicklied o’er with the pale cast of thought,

And enterprises of great pith and moment

With this regard their currents turn awry

And lose the name of action.

In other words, Hamlet says everybody is afraid to take real action because they fear the unknown outcome. You could act to mitigate or solve some challenges, but you don’t because you don’t trust yourself.

If I’m a brand marketer for any business (and I am), I’m going to take action on AI for my business. But until I see how I’m going to generate value with AI, I’m going to be circumspect about yelling or proselytizing how my business’ future is better.

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Cover image by Joseph Kalinowski/Content Marketing Institute

MARKETING

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

Published

3 days ago

April 22, 2024

Entireweb News Bot

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

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

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

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

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

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

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

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

Let’s jump into it.

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

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

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

Benefits of AI in Social Media Strategy

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

AI to Conduct Customer Research

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

This is where AI thrives.

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

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

But that’s not all.

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

The response that ChatGPT provided back is quite good:

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

Demographics
Psychographics
Consumer behaviors
Needs and preferences

And best of all…

It also included marketing recommendations.

The power of AI is unbelievable.

Social Media Content Using AI

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

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

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

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

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

It can also help you navigate hashtags:

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

Enhanced Personalization

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

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

What do I mean?

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

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

Analytics and Insights

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

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

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

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

Now …

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

Improved Customer Service

Want 24/7 support for your customers?

It’s now possible without human touch.

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

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

Advertising on Social Media with AI

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

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

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

Brands can use AI tools to support their bidding strategies.

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

How to Implement AI into Your Social Media Strategy

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

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

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

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

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

1. Identify Your AI and Social Media Goals

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

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

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

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

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

Recommended Resources:

2. Validate Your AI-Related Assumptions

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

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

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

3. Conduct Persona and Audience Research

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

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

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

4. Select the Right Social Channels

Not every social media channel is the same.

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

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

The audiences are different.

The content formats are different.

So operate and create a plan accordingly.

Recommended Tools and Resources:

5. Identify Key Metrics and KPIs

What metrics are you trying to influence the most?

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

These are a few that matter most:

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

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

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

6. Choose the Right AI Tools

The AI landscape is filled with trash and treasure.

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

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

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

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

7. Evaluate and Refine Your Social Media and AI Strategy

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

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

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

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

Make AI Work for You — Now and in the Future

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

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

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