Figuring out the return on investment (ROI) of marketing efforts has always been a challenge. Companies struggle to quantify the success of individual advertisements and understand which messages resonate with consumers. 

The adoption of A/B testing revolutionized the direct response mailer world in the 1960s and 70s. It pits two different versions of an advertisement against each other to find out which is most successful.   

But, this approach wasn’t adopted by corporate America until the 2000s. The tech startup Google used A/B testing to refine its website’s user interface and become the dominant search engine in the world. After Google’s success, other companies began to take notice. 

Ever since, this type of testing has become an essential part of the modern marketer’s toolkit. It’s now being used to increase the ROI for marketing campaigns and standard website content.  

That’s because statistical testing allows companies to save money and boost profits. It also helps firms avoid content that fails to resonate with their target audience. 

Let’s explain exactly how this type of testing helps companies save money in the long run.

In this example, it costs a company $5,000 per month to launch an email marketing campaign for a new cybersecurity product. Many executives would balk at the option of doubling that budget to $10,000 for an A/B test. 

But it’s much cheaper to spend $10,000 once to understand which message and content format appeals to your target buyers.  

Instead, many firms would spend $5,000 per month for the next six months (a total of $30,000) only to realize the chosen messaging failed to resonate to the degree they could and hence, get better return-on-investment (ROI) from their entire campaign.  

Even more troubling, the campaign’s initial failure may cause leadership to view the new product as a failure. They may even have the development team return to the drawing board to redesign features or create an entirely new product.  

Either response can result in millions of dollars in additional development costs and lost sales. This could also allow the competition to develop and launch a similar product. If their campaign is backed by data-driven insights, they’ll probably do a better job of connecting with consumers too.  

This scenario plays out every day in the corporate world. It’s also why companies are turning to analytics to refine their marketing efforts and get the highest ROI for every dollar. 

Let’s explore the two most popular forms of testing to see which approach is best for your organization.  

A/B testing is a great starting point for businesses who want to test out new messaging strategies and start using analytics to create a competitive advantage.  

This approach allows you to test the effectiveness of two different messaging strategies or content types through randomized trials.  

Anna Vallee of Harvard Business School Online wrote: 

A/B testing—once thought to be exclusive to tech firms—has become a viable and cost-effective way for all types of businesses to identify and test value-creating ideas.

To get started with A/B testing, create a testable hypothesis. For example: 

Passive candidates are more likely to respond to social media ads that highlight company culture and day-in-the-life experiences of individual employees, rather than focusing on output and career outcomes.

• Write two social media ads for this campaign. One can focus on company culture and the second on career outcomes.  
• Have the test groups randomly selected from your target audiences for campaign delivery.
• These groups must be randomly selected to eliminate hidden bias and to generate statistically significant results. If you are using another platform your team may need to randomly separate these groups yourself.  

Next, let’s explore multivariant testing to determine which approach is right for your needs. 

Multivariant testing is a more advanced approach compared to A/B testing. It involves testing 3 or more (sometimes dozens!) messaging strategies or content formats against each other  

Large corporations often test a range of variables at the same time. These include:  

• Website Structure
• Logos
• Website Colors
• Images
• Email Subject Lines
• Form Layouts 

According to HubSpot, this allows businesses to pit “multiple variables and how they interact with one another, giving far more possible combinations for the site visitor to experience.”  

This advanced approach allows companies to perfect their messaging. It also helps increase conversion rates on all marketing, advertising, and social media collateral.  

Companies can also test how effective social media posts or email campaigns are when launched on different days and/or at different times.  

The strategic use of multivariant testing can result in millions of dollars in additional sales, a higher ROI of your overall campaign and a critical competitive advantage.  

The best place to start is a simple A/B test if you’re just beginning with analytics – whether on your website or within the social platform tools. This reduces the number of variables and complexity of the test. Multivariant testing is a powerful tool, but it’s best saved for companies with high data maturity and experience under their belt.  

It’s also critical to use a randomized distribution for both versions. This is regardless of whether you use two-variable A/B testing or the more advanced multivariant method.  

“The randomization aspect of this design is explicitly emphasized because randomization is the gold standard for eliminating biases,” says Vallee.  

Don’t stop at just the written content either. The best marketers use analytics to test a range of variables, including: 

• Landing Page Layout
• Email Paragraph Length & Overall Word Count
• Email Subject Lines
• Calls to Action
• Headers
• Titles and Subtitles
• Fonts and Colors
• Product Images
• Carousel images to show your story
• Social Media & Email Timing
• Opt-in Forms, and More
  

Now, you’ve completed your first test. It’s important to also assess both the results and the overall process. Pay special attention to added value, time and money savings, and other insights. 

So, you’ve completed your first test and you’re sitting in front of a pile of data. How do you transform this raw data into actionable insights? Start with identifying your key performance indicators (KPIs).  

These could be:  

• Website Traffic
• Click-Through Rates
• Conversion Rates
• Bounce Rates
• Email Open Rates
• Email Response Rates
• Social Media Impressions
• Social Media Engagement 
• Social Media Shares
• Form fills
• Number of Job Applicants
• Customer Acquisition Cost  

You should choose a single KPI to focus on. But you should also run tests on secondary KPIs as well. For a social media post, we typically focus on engagement (an active KPI) instead of impressions (a passive KPI).

Website content requires a different set of tests. You can focus on conversion rates as your primary KPI. Plus, you can test bounce rates and overall website traffic to produce even more insights. 

Once you’ve completed your analysis, it’s time to act. Archive the poor performer and build successful messaging into a different area of your marketing arm. 

Ideally, you’ll also perform another A/B test to validate the insight. Then, you can scale this new messaging into the entire marketing strategy. 

Companies can take these initial insights to scale their new approach even further. This is an effective way to connect with consumers and generate more sales.  

Finally, marketing leaders can use these early insights to demonstrate the value of analytics to stakeholders. Successful small-scale testing gives teams access to larger budgets and advanced analytics tools.  

We encourage clients to start small before scaling. Choose a single landing page or email marketing campaign for your experiment. This will serve as a proof of concept.  

You can achieve real results and gain actionable insights in as little as one week with a well-thought-out A/B campaign. Once complete, you can also scale these results throughout your marketing department.  

Vallee says: 

Companies like Google, Amazon, and Facebook have all used A/B testing to help create more intuitive web layouts or ad campaigns, and firms in all industries can find value in experimentation.  

Businesses of any size can use the same approach to unlock hidden value, close more deals, and boost profits. 

At AMG Defense Tech, we help clients accelerate growth and improve marketing ROI with data-driven insights. Contact us to learn how we can integrate these popular tests into your advertisements and help your firm reach new candidates and customers.