What are the best ways to quantitatively test your messaging?
Quantitatively test your messaging through experimentation:
A/B test different types of messages on your website
A/B test different types of messages through paid social & organic social
A/B test different types of messages through SEM — I find this to be the easiest channel to experiment with given all you have to do is change copy.
A/B test different types of messages through email
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A/B test different types of messages through in-product experiments — for example, our product is offered through a self-serve platform where we can set up in-product onboarding modals, notifications, and tooltips.
Measure things like CTR, open rate, CVR, average budget size, and revenue. While engagement metrics like open rate and CTR are instructive, I wouldn't put too much stock in them, given people can be clicky but ultimately not convert or not convert at higher spends. Definitely take the time to confirm that the messaging that is driving the most initial engagement is also driving the most adoption and revenue.
Quantitative testing is probably best done as an A/B test. Some ideas:
Email subject lines: Weave your messaging into subject lines and compare open rates
CTAs: Use messaging for CTAs on web or email compare CTRs (click-through rates)
Webpage copy: Try A/B testing webpage headlines and see which drives higher click-through rates and lower bounce rates
Display ad copy: Test different messages on display ads and test CTRs
Social copy: Same as above, but for organic or paid social
Basically, anything you can A/B test and put two different messages in market will help you get some quantitative metrics behind your message.
There are several ways to get quantitative data on your messaging using online testing tools and A/B tests. However, you need time and volume to get an accurate read and marketers rarely have either. I recommend you get scrappy and find ways to get an initial pulse on some messaging - it doesn’t have to be a science.
Online user testing platforms that make this so fast and easy. Wynter is my favorite. It’s cost effective and fast, especially for smaller companies.
Low lift A/B tests - You can do an A/B test with emails. Performance metrics such as click through rate and engagement will help you determine which messaging resonates best.
Sales insights - Work with your sales team to test different messaging through sales assets and live calls.
Customer insights - Set up some low lift customer interviews. They will tell you what resonates with them.
Ideally you're a/b testing in-market so you get a read on actual user behavior: headline testing on your website or paid landing pages, or subject line testing in email. Take really big swings in your messaging concepts and try to test ideas that are very different so the results will be clear. Incremental messaging changes aren't likely to be understood by customers and you'll probably get results that aren't stat sig in test vs control.
If you don't have any in-market tools at your disposal, there's always quant research -- whether that's a more complex max diff or just a simple survey. Where I've seen this work best is where you've got very different messages that you are trying to prioritize (vs doing a messaging optimization.) If that's the case, doing survey based work will allow you to quickly test a range of messages, which would take much longer if you were to a/b test your way into it. The downside is that you won't have a read on the messages which will drive actual buying behavior in the same way you get when you a/b test.
There's validity in both approaches so just be clear on what you're solving for to guide which way you go.
Message testing is really important and often overlooked, however there are several ways to qualitatively test your messaging that are rather easy to implement.
A/B Testing: Conduct A/B tests where you create two or more variations of your messaging and expose them to different segments of your audience. Measure key metrics such as click-through rates, conversion rates, and engagement to determine which messaging resonates best with your audience. There are great and affordable tools out there that help implement this as well.
Surveys and Questionnaires: Design surveys and questionnaires to gather feedback from your target audience about your messaging. Ask specific questions to assess comprehension, appeal, relevance, and clarity of the messaging. Use quantitative scales to measure responses and identify trends.
Website Analytics: Utilize website analytics tools to track user behavior on your website in response to different messaging variations. Monitor metrics such as bounce rates, time on page, and conversion rates to understand how visitors are interacting with your messaging.
Heatmaps and User Testing: Use tools like heatmaps and user testing platforms to visually analyze how users interact with your messaging on web pages, landing pages, and digital assets. Identify areas of interest, patterns of engagement, and points of friction in the user experience.
Most of the above can be done affordably and in a self-serve manner that give quick feedback that you can marry against your qualitative feedback.
It doesn't just matter what you're saying but when. ABCD test your messaging content and when you are sharing that messaging with your users and review engagement metrics.
At the end of the day, A/B testing messaging in the wild will get you the furthest, fastest. There are several ways to do this.
You can argue for some test budget to test messages in paid ads. Especially if you’re planning on using this messaging for brand marketing or demand gen, it makes sense to validate it via the channels you plan to use.
You can also A/B test messaging on your site itself if you get high enough traffic to run your tests relatively quickly. Most companies have A/B testing tools available, but if you don't I highly recommend advocating for your eng team to help build a simple self-service codeless copy test tool to enable you to run tests without significant product and engineering lift.
If you don’t have the luxury of being able to test messaging in situ, the next best thing for getting quantitative insights is validating messages through a market survey to your target audience. If you use a statistical technique like MaxDiff, you can get stronger forced rankings of the best and worst messages than through other survey formats. You often need an advanced survey tool for this, but it lets you increase your confidence on the most resonant messages and value props within just a week or two.
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