How can you optimize pop-up forms with multivariate testing?

Having a clear goal is key and communicating the same to other business units so everyone is on the same page as to what's being tested, for how long and what hypothesis is being explored. To start your goal can simply be to increase sign ups. To achieve this goal you could test different imagery, a better offer than what's live or simply where / how the subscriber form is shown. Most importantly it's important to keep a record of your tests and results so the data speaks for itself and assumptions are removed.

I would recommend stepping back another level and consider how the micro-goal of this test impacts and/or connects to a much larger goal, like a departmental level goal. For example, if your hypothesis and test is related to increasing conversion rates on a high-value landing page, how would this increase feed into a larger marketing goal, such as increasing net new customer acquisition? If you find it hard to figure out how to connect a micro-goal to the bigger picture, there may be an argument to be made that this is not worth a large time investment.

Before testing, establish a clear goal and hypothesis for your pop-up form. Your goal defines what you aim to achieve, like increasing newsletter subscriptions. Your hypothesis predicts what will improve performance, such as changing the headline. For instance, if your goal is to boost ebook downloads, your hypothesis might be that a pop-up with a catchy headline, relevant image, and green button will increase downloads.

Multiple variations is one of the best strategy to determine the most effective elements. After defining your goal (it may be lead generation, promo, newsletter subscription etc.), identify the elements within pop-up form which you would like to optimize. This could include the headline, call-to-action, CTA button color, form fields, images, and overall design/layout etc.

Hypothesis forming starts with assumptions. In a multivariate testing strategy, assumptions can be grounded on the following factors: 1. Desirability TG, Problems to Solve, Current Solutions etc. 2. Viability How big is the TG, how can this hypothesis be tied to our goal, what formats are viable to test etc. 3. Feasibility Technical and execution limitations, feasible formats, right tools etc., 4. Adaptability Will this testing be adaptable for users and for marketers? Will this testing allow to increase the conversion (Install/download/click)

Goal & Guess: Set SMART goals & hypothesize what improves pop-up performance. Pick Your Variables: Choose elements to test (headline, image, color, etc.) and create variations. Test & Track: Use A/B testing tools to run the experiment and measure results. Analyze & Apply: Identify the winning variation and implement it for conversions.

Next, select the variables and variations for testing on your pop-up form. Variables are changeable elements like headline, image, color, button, and trigger. Variations are different versions of each variable to compare, such as short vs. long headlines, ebook cover vs. person reading, and blue vs. white backgrounds.

Connect back the hypothesis to your variations. What are the hypotheses that I'd want to achieve by this testing? Do we want to: 1. Change the communication and repackage the Value Proposition to increase the downloads? 2. Change the copy or a headline or CTA to increase CTR? 3. What combination of testing is suitable to test the hypothesis? Establishing a clear connection of hypothesis would allows us to build more concrete variations

To conduct a multivariate test, use a tool like Google Optimize, Optimizely, or Unbounce to create and track pop-up variations. Depending on the tool, add code to your website or use a drag-and-drop editor. Decide how to split traffic among variations, test duration, and measurement method. For instance, evenly split traffic, run the test for two weeks, and measure results by downloads per variation.

After running your test, analyze and apply results. Determine which pop-up variation performed best based on your goal and hypothesis. Ensure results are statistically significant, not due to chance. Use tools like Optimizely's Stats Engine or VWO's SmartStats for this. Apply the winning variation to your website for optimization benefits.

You can use a multivariate testing tool to set up your experiment. It will randomly display pop-up form(s) variations to visitors and track their interactions and conversions. Some of the multivariate testing tools are: - Optimizely - VWO (Visual Website Optimizer) - Adobe Target - Split.io - Convert

One thing to consider before starting on any of the above recommended steps, which are all good points, is to take a look at any data that would point to an area that is not currently performing to your expectations. This may help you avoid going down a rabbit hole of endless A/B testing, which can also take a long time to do to test all variants.

Define Goals: Set clear objectives for your pop-up forms (e.g., increase sign-ups). Identify Variables: Choose elements to test, like headlines, colors, CTA buttons, timing. Create Variations: Develop multiple versions with different combinations of your variables. Segment Audience: Split traffic to show each version to a part of your audience. Run Test: Use multivariate testing tools to simultaneously test variations. Analyze Results: Review data to see which version performs best towards your goals. Implement: Apply the most effective elements to your pop-up form. Repeat: Continuously test and refine to keep optimizing performance.