What is funnel analysis? 

Funnel analysis is the process of identifying where and why people drop off before moving to the next stage of the customer lifecycle. B2C marketers use funnel analysis to address points of friction in their marketing funnel, so they can ultimately increase conversion rates and time to purchase.

For example, a study by the Baymard Institute says the average documented online shopping cart abandonment rate is 70.19%. If a funnel analysis reveals that a brand’s cart abandonment rate is much higher than that, it’s time for that brand to re-evaluate its checkout experience, from shipping rates to accepted methods of payment.

The benefits of funnel analysis for B2C marketers

Funnel analysis is a way to visualise and analyse the conversion path consumers take, from awareness to purchase. When B2C marketers invest in an evidence-based approach to marketing funnel adjustments, they can expect to see:

  • A more personalised customer journey: When conducted alongside cohort analysis and segmentation analysis (see below), funnel analysis can reveal why different types of people drop off at different stages of the customer lifecycle. This analysis naturally reveals more opportunities to personalise marketing funnels for different sets of people. 
  • Higher conversion rates: You can think of funnel analysis like a diagnostic test that can tell you how to treat a problem in your marketing funnel. With the knowledge of how to treat the problem—why people aren’t converting—you can issue the right treatment and start to see higher conversion rates. 
  • Higher marketing return on investment (ROI): Funnel analysis leads to more marketing efficiency because “plugging holes” in a marketing funnel can make budgets go further. For example, if you’re spending a lot of money on search ads that don’t yield conversions, funnel analysis can tell you whether you’re targeting the wrong keywords or there’s something wrong with your check-out process. Solving the right problem means conversions increase, ad spend goes further, and marketing ROI improves.

Funnel analysis vs. other marketing analyses

Funnel analysis can reveal a lot of important insights, but it also works best when conducted alongside other types of analyses. Marketing strategies are often also informed by:

Cohort analysis

Cohort analysis is the process of grouping customers by shared behaviours or traits to learn more about their purchase habits over a long period of time. Whereas funnel analysis emphasises why people are or aren’t moving to the next stage of the customer lifecycle, cohort analysis emphasises who is behaving a certain way compared to other types of customers.

Segmentation analysis

Marketers use segmentation analysis to understand their audience in greater detail, by comparing and contrasting the behaviours of different audience groups. Segmentation analysis can amplify funnel analysis with a more granular level of detail about why some people do or don’t move to the next stage of the customer lifecycle.

RFM analysis

Recency, frequency, and monetary values (RFM) analysis can tell brands how recently a customer made a purchase, how frequently they purchase, and how much they spend on each purchase. Whereas funnel analysis addresses the entire customer lifecycle, RFM analysis specifically serves post-purchase and loyalty stages.

How to conduct a funnel analysis

  1. Identify the key stages of your funnel. There’s the standard customer lifecycle, and then there’s your customer lifecycle. Start your analysis by identifying key conversion events for your brand. Depending on how many events you identify—and remember, most customer lifecycles are messy and nonlinear—you’ll likely group multiple events together to form one stage in your customer lifecycle. Here are a few examples:
    • Marketing engagement: subscribed to email → received email → opened email → clicked email → active on site
    • SMS to purchase: delivered SMS → active on site → add to cart → placed order
    • Repeat purchase: placed order → add to cart → placed order 
    • Order to review: placed order → received order → submitted review 
  2. Gather the necessary data. Map each event to an action. Some examples include landing on a product page, placing an item in a cart, and completing a purchase. Use integrations for your analytics software, your online store, and your marketing automation platform to consolidate and visualise your data in one place, with reports that are easy to read and share.
  3. Analyse your funnel performance. Your reports will calculate conversion rates for each milestone. Compare your results between different segments or different timeframes. Lower conversion rates represent drop-off points that need to be addressed.  
  4. Implement improvements. You may need to test multiple theories against each other to reach a solution to your drop-off issue. For example, if people are dropping off at check-out, it could mean your shipping rates are too high or you don’t accept enough payment options. Solving marketing funnel problems requires isolating potential solutions, running those solutions for a period of time, then continuing to improve with ongoing funnel analysis.

Klaviyo makes it easy for brands to conduct funnel analyses with consolidated customer data and easy-to-read reports. Sign up for Klaviyo and get started today.