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How to build a conversion funnel and track each step

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You're losing money at every step and you don't know where. A hundred visitors land on your site. Ten convert. That means ninety are dropping off. But where? Are they leaving after the homepage? Abandoning halfway through checkout? Never even seeing your pricing page? Without a conversion funnel, you have no idea. You only see the ten conversions. You don't see the ninety failures. You can't optimize what you can't see. A conversion funnel shows you every step visitors take and exactly where they drop off. It reveals which steps leak the most customers and which are working fine. It tells you where to focus optimization effort to recover the most lost sales. One optimization at the biggest drop-off point might recover thirty conversions. The same optimization at a smaller drop-off point recovers five. A funnel shows you which is which. This article explains how to build a conversion funnel and track each step.

What is a conversion funnel?

A conversion funnel is a series of steps a visitor must complete to convert. Each step is a filter that removes some visitors and lets others through. A simple funnel has three steps: awareness, consideration, decision. A detailed funnel breaks these into smaller steps: landing page view, product page view, pricing page view, add to cart, checkout start, checkout complete. The more detailed your funnel, the more precisely you can diagnose where people drop off.

Defining your funnel steps

Start with your actual customer journey. Where do prospects enter? Where do they go next? What pages do they visit? What actions do they take? What form do they fill? What happens last? Map the entire path. A SaaS company's funnel might be: land on homepage, navigate to pricing, sign up for trial, create account, add payment method, activate subscription. An ecommerce company's funnel might be: land on home, browse category, view product, add to cart, checkout, enter shipping, enter payment, confirm purchase.

Building a funnel in your analytics tool

Most analytics platforms have funnel visualization tools. Google Analytics lets you create funnels in the conversion section. You define the steps as page views or events. Conversion happens when someone completes the final step. The tool shows you how many people reach each step and how many drop off. You can compare funnels over time to see if they're improving or getting worse.

Tracking abandonment at each funnel step

Abandonment is where people leave without completing the next step. If a hundred people view your pricing page and ninety leave without clicking the sign-up button, your abandonment rate is ninety percent. High abandonment at a specific step reveals a problem. A high abandonment rate from cart to checkout might mean your checkout is too complex. A high abandonment from pricing to signup might mean your pricing is confusing. Identify high-abandonment steps and investigate why.

Mobile vs desktop funnel performance

A funnel might perform differently on mobile and desktop. Your desktop checkout converts at eight percent. Your mobile checkout converts at two percent. This tells you mobile has a problem. You might simplify the mobile checkout, reduce the number of fields, or use autofill. Track funnels separately by device to catch these issues. Desktop might be optimized while mobile needs work.

Sequential steps vs non-sequential funnels

A sequential funnel requires visitors to complete steps in order. They must view pricing before signing up. They must add to cart before checkout. Most customer journeys are sequential. A non-sequential funnel allows visitors to skip steps. Someone might checkout without adding an item to cart (if they use a buy now button instead). Non-sequential funnels are more flexible but harder to analyze. Start with sequential funnels to understand the standard path. Add non-sequential analysis only if many visitors don't follow the standard path.

Using funnel data to prioritize optimization

Look at where visitors drop off most. If your funnel loses half your traffic between step one and step two, optimize step one. If it loses a quarter between step three and four, optimize step three. Prioritize by the number of visitors affected. An optimization that recovers five percent of visitors lost at step one affects fifty visitors per thousand. An optimization at step three affects twenty-five. The bigger the drop, the bigger the impact of fixing it.