Let’s get right to it!<\/p>\n
What is conversion analysis?<\/h2>\n
Conversion analysis is the process of tracking and assessing how users move along the customer journey.<\/a> Its goal is to help marketing, sales, and product teams understand and optimize the key conversion points <\/a>and events.<\/p>\n These events normally represent important user actions like visiting the website, signing up<\/a>, or upgrading to a paid plan.<\/p>\n Conversion analysis allows product managers <\/a>to make data-driven <\/a>decisions to improve the customer experience<\/a> and foster its growth.<\/p>\n How exactly?<\/p>\n For starters, it allows them to identify the best ways to optimize the important touchpoints in the user journey<\/a>. Consequently, users are able to achieve their goals quickly and efficiently. This normally translates into higher customer satisfaction and retention.<\/p>\n An optimized customer journey also means better financial performance.<\/p>\n For example, it can increase the conversion rate from free trial or freemium to paid plans <\/a>or from lower to higher ones. In each case, it increases the MRR and customer lifetime value.<\/a><\/p>\n How exactly the conversion funnel analysis<\/a> process works may be different from product to product and organization to organization. However, it normally consists of a few common steps. Let’s check them out.<\/p>\n How you carry out conversion analysis depends on your goals<\/a>, so setting them is the first step.<\/p>\n For example, for an e-commerce business, the goal could be boosting sales. For a B2B SaaS product, it could be optimizing the website to boost free trial sign-ups<\/a> or demo bookings or improving free-to-paid conversions.<\/p>\n To help you set the right goals, use a goal-setting framework<\/a> like SMART or OKR<\/a>.<\/p>\n Whichever framework you go with, make sure that your goals are specific and measurable. For example, increase the conversion rate by 3.3%.<\/p>\n How do you set your desired conversion rate?<\/p>\n If you’re only starting, aim for industry-specific benchmarks. For example, according to Shopify<\/a>, an average e-commerce website conversion rate is 2.5-3%. For a B2B SaaS product, the average free trial and freemium conversion rates<\/a> are around 18.2% and 2.6%<\/a> respectively.<\/p>\n Once you have enough of your own data, use it to set goals tailored to the nature of your product and niche.<\/p>\n Having set your goals, it’s time to map out the funnel and set the conversion events.<\/a><\/p>\n This will include the key conversion events, aka macro conversions<\/a>, like the purchase or sign-up. In addition to these, you also need to identify the micro conversions. That’s the events leading up to the main ones.<\/p>\n Let’s imagine you’re carrying out a landing page conversion analysis to boost sign-ups.<\/p>\n The sign-up is the macro event. The micro conversions will be all the steps before, like visiting the site.<\/p>\n How about conversions inside the product?<\/p>\n If your goal is to increase product activation, you first need to define what qualifies as activation<\/a>. For example, it could be using a specific feature. That’s your macro conversion.<\/p>\n What if there are more activation events? Simple. Bundle them up into a custom event.<\/p>\n If you’re finding it difficult to identify user interactions with the product leading up to the macro conversion, use Paths analysis.<\/p>\n With all the steps mapped out, it’s time to collect the event data <\/a>and visualize it in a funnel chart.<\/p>\n Funnel charts consist of bars, each representing a different stage in the funnel. In the demo booking example above, there would be one bar for ‘visit the page’, one for ‘watch video demo’, and one for ‘sign up’.<\/p>\n This kind of chart is very easy to interpret. If the drop-off rate is particularly high at one stage, you will see it immediately as the next bar will be noticeably narrower.<\/p>\n Based on the insights from the analysis, it’s time to implement strategies<\/a> to boost conversions.<\/p>\n For example, if users cannot find a feature that is essential to activate them, you can create a tooltip <\/a>that will help them discover <\/a>it.<\/p>\n Another example: if you’re users are struggling to find the right template, you could provide a search bar or personalize<\/a> their dashboard with shortcuts to templates that are most relevant to their use cases.<\/p>\n Let’s look at examples of conversion analysis in the context of e-commerce and SaaS B2B products.<\/p>\n Here’s an example of a conversion analysis for an online clothes retailer aiming to optimize its website.<\/p>\n Step 1. <\/strong>Goal: boost sales by 1% to reach 2.5%<\/p>\n Step 2.<\/strong> The macro conversion is the purchase, while the micro conversion events are:<\/p>\n Step 3. <\/strong>Your conversion funnel analysis <\/a>reveals that lots of users drop off when they’re about to provide payment details.<\/p>\n An exit survey some of them complete reveals they didn’t have their credit card details handy to complete the purchase, while others say they simply ‘can’t be asked’ to enter them.<\/p>\n Step 4. <\/strong>To boost the conversion rate at this touchpoint<\/a>, you decide to add ‘Check out with Amazon’ and ‘Check out with PayPal’ buttons to remove the friction.<\/p>\n In this example, we’re analyzing the conversion funnel<\/a> inside a social media management platform to increase free-to-paid conversions.<\/p>\n Step 1. <\/strong>Goal: increase conversions<\/a> from 11% to 18%<\/p>\n Step 2. <\/strong>The macro conversion is the upgrade to the paid plan, while the conversion funnel consists of these actions:<\/p>\n Step 3. <\/strong>From the funnel analysis<\/a>, we see that a large percentage of users reach the adoption and retention stage but don’t convert into paying customers. In-app surveys<\/a> and interviews show that users see no value <\/a>in the paid plan.<\/p>\n Step 4. <\/strong>To improve conversions, the product team imposes usage limits on the free plan and lowers the price of the premium plan. They also introduce reverse trials<\/a> so that users can try out the premium functionality themselves.<\/p>\n Now that you know how to conduct conversion analysis, let’s look at a few tricks of the trade to get the best out of the process.<\/p>\n Tracking conversion data trends<\/a> over time serves a number of purposes.<\/p>\n First, it allows you to track the overall performance of the product and establish benchmarks for future goal setting. It also enables you to assess the impact of product changes and updates on your KPIs<\/a>.<\/p>\n Second, you can use it to identify seasonal patterns in customer behavior.<\/a><\/p>\n For example, when you see increased B2B sales at a particular time in the year, you can use the insights to double down on your marketing efforts around this period.<\/p>\n In the same way, tracking conversion trends can help you find anomalies indicative of changes in user needs<\/a> or competitive landscape.<\/p>\n In addition to conversion and drop-off rates for each stage, most analytics tools provide the time to convert data.<\/p>\n Why is this useful?<\/p>\n While the conversion rates can be decent, users may still be experiencing unnecessary friction that will slow their progress down the conversion path<\/a>. By looking at the time-to-convert, you can identify the stage that needs optimizing.<\/p>\n For example, if it takes users too long to complete your welcome survey<\/a>, you could review the questions to make sure they’re clear and leave only the ones that are absolutely essential to personalize the customer experience.<\/a><\/p>\n Overall, by optimizing the time to convert, you reduce the risk of users churning.<\/p>\n While quantitative conversion analysis can help you find the friction points, it’s usually not enough to find out what causes friction.<\/p>\n For that, you will need a more in-depth qualitative analysis of user behavior.<\/p>\n User surveys and interviews are good sources of qualitative data, <\/a>but they’re also subjective.<\/p>\n For more reliable insights, consider using session recordings to see exactly how they interact with UI elements on a particular page.<\/p>\n Such analysis can help you discover usability<\/a> issues and find ways to improve the product experience.<\/a><\/p>\n Imagine you’ve discovered that users cannot find a button on the screen and that’s why they fail to complete a conversion event.<\/p>\n You decide to use an in-app UI pattern<\/a> to help them with that. Which one shall you use though? A tooltip or a hotspot?<\/p>\n An easy way to decide is by A\/B testing <\/a>them. Just create both patterns, trigger each for one half of your test group, and compare the conversion rates for each of them.<\/p>\n Is it the tooltip<\/a>?<\/p>\n Great!<\/p>\n Let’s repeat the process for different versions of the microcopy. A multivariate test <\/a>might be more suitable here though, so that you can test a number of options at once.<\/p>\n To reduce the risk and maximize impact, carry out such experiments on a small segment<\/a> before rolling out the strategies for all users.<\/p>\n Product teams use conversion analysis to make informed product decisions leading to improved customer experience and satisfaction – and better overall business performance of the product.<\/p>\n If you want to see how to conduct conversion analysis in Userpilot<\/a>, book the demo!<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Wondering how you can use conversion analysis to optimize your user funnels and increase conversions? In today’s article, we’ll talk about what conversion analysis is, and its benefits. You will also learn how to conduct a conversion analysis and 3 of the best tools that can improve conversions and boost your product growth.<\/p>\n","protected":false},"author":56,"featured_media":16768,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[770],"tags":[979,5672,554,5673,60,57,52,1688,497],"class_list":["post-16767","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ux-analytics","tag-ab-testing","tag-analysis-tool","tag-analytics-tools","tag-conversion-analysis","tag-conversion-rate","tag-free-trial-conversion-rate","tag-product-experience","tag-qualitative-feedback","tag-trial-to-paid-conversion-rate"],"acf":[],"yoast_head":"\nWhy is it important to conduct conversion funnel analysis?<\/h2>\n
What does the conversion analysis process look like?<\/h2>\n
Define goals and success metrics<\/h3>\n
![\"OKR](\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/11\/okr-conversion-analysis_8d21f4b9133ffcf399241b99edf5ff9c_800.webp)
<\/picture>Set up important conversion events<\/h3>\n
![\"Custom](\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/11\/custom-events-conversion-analysis_005c6e385f2ed2cde0d5ed8455085b7f.gif)
<\/picture>Visualize and analyze the conversion analysis report<\/h3>\n
![\"Funnel](\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/11\/funnel-conversion-analysis_9ca3fc7dc3dfe305cfac9cb05376241f_800.png)
<\/picture>Implement strategies to increase conversions<\/h3>\n
![\"Tooltip](\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/11\/tooltip-builder-conversion-analysis_3b52d9cb2b48eca0e6ae06e4a6165718_800.png)
<\/picture>What are conversion analysis strategy examples?<\/h2>\n
E-commerce conversion analysis example<\/h3>\n
\n
SaaS B2B conversion analysis example<\/h3>\n
\n
Best practices to follow when performing conversion analysis<\/h2>\n
Track conversion data trends over time<\/h3>\n
![\"Conversion](\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/11\/trends-conversion-analysis_3549987288d86a9f07c76aa186238cbb_800.png)
<\/picture>Optimize the average time to convert<\/h3>\n
![\"Time-to-convert](\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/11\/time-to-convert-conversion-analysis_45bcf78f6431f2867e3a5f80b82413e1_800.png)
<\/picture>Carry out qualitative user behavior research<\/h3>\n
A\/B test strategies before implementing them to boost conversions<\/h3>\n
![\"A\/B](\"https:\/\/blog-static.userpilot.com\/blog\/wp-content\/uploads\/2025\/11\/ab-test-conversion-analysis_8ee294451c4f2f3674f508d5b6cc96a9_800.png)
<\/picture>Conclusion<\/h2>\n