Funnel Analysis: A Catalyst for Conversions

Funnel analysis is crucial for product managers, marketing managers, and product teams, in general, in order to comprehend the customer's journey as they use their specific goods and services. Any attempt to increase conversion or activation for your product or offering is futile if you don't have any insight into how customers really utilize it.

What is the Funnel Analysis?

“Funnel analysis involves mapping and analyzing a series of events that lead towards a defined goal, like an advertisement-to-purchase journey in online advertising, or the flow that starts with user engagement in a mobile app and ends in a sale on an e-commerce platform.”

In the wider context, it refers to a technique for understanding the steps your consumer takes to reach the path of conversion or activation. The AIDA model, an abbreviation for Awareness/Attention, Interest, Desire, and Action, serves as the foundation for the funnel framework most frequently used today. This model in marketing explains the process a consumer goes through before buying any

Awareness/Attention: When a potential customer learns about your product or service by any external trigger, such as advertisements, this is known as the awareness or attention stage (web, tv, social media, etc.)

Interest: If the first step is successful in gaining the required focus or motivation, the user will attempt to interact with your product or service out of interest.

Desire: If the first point of contact or engagement looks to provide the user with real value, it increases the incentive to convert.

Action: The user takes this action as their last step before converting. Examples include product purchases, successful sign-ups, trial-to-paid conversions, etc.

The ultimate objective of funnel analysis is to locate holes in your bucket, product, or service along the customer journey. Once these leaks are located, the product team may take the required steps to close them by continuously experimenting with potential fixes in order to attract more customers.

Types of Funnels

There are primarily two sorts of funnels, namely, Strict funnels, and Loose Funnels if we define funnels broadly. Let's examine each of them individually below:

Strict Funnels: In a strict funnel mode, users must adhere strictly to the predetermined steps or paths in order to be recorded as converted users. The checkout or payment process is a well-known illustration of a stringent funnel since it requires users to follow a specific path in order to be counted as successful conversions.

Loose Funnels: Users do not need to follow a specific path or set of actions in a loose funnel mode in order to be recorded as converted users. Even if they don't follow the funnel's exact order of events, they are still considered to have been converted. The discovery process a user goes through when looking for a hotel or booking a flight is an example of this type of funnel because the user is going to consider many possibilities before completing the final steps to become a converted user.

Let’s look at a funnel and try to dig deeper

A funnel analysis reveals where users are losing interest during the conversion process. We can examine the funnel to identify the touches or interactions where these drop-offs are occurring and then optimize by modifying the user flow as needed. Let's take a look at an example of a Google Analytics funnel view that illustrates the number of user steps from a shopping cart to the actual purchase and review. The visualization will also display the number of users who began with the cart and the number who finished when it came time to make the final payment.

Step 1 (Shopping Cart)

Out of the total prospects/users, or 2366, only 333 moved on to the following stage, "Billing & Shipping data," as seen in the visualization above. 2033 or so prospects dropped off from the shopping cart.

Step 2 (Billing & Shipping)

Only 204 of the 333 prospects that completed the billing and shipping details area continued to the next step.

Step 3 & 4 (Review & Final Payment)

Out of the 204 prospects, only 62 were in this section, and by the time we got to the last step, only 14 had finalized the payment and the product purchase.

Final Result:

The Purchase goal checkout funnel only had 14 completed sessions out of 2366 total sessions, and its conversion rate is 0.59%. What factors might contribute to a relatively low conversion rate? Let's examine the typical problems that lead to checkout abandonments:

Too difficult or lengthy checkout process.

The website made account creation mandatory during the checkout.

During the checkout process, the website made account creation mandatory.

High shipping costs

Lack of trust in the site and inability to share payment info.

Too long and complicated checkout process

The website didn’t share the return policy or maybe the return policy was not satisfactory.

Fixing the aforementioned common issues can result in a higher conversion rate, but in order to consistently deliver a smooth experience, the product team must continue to analyze and optimize the funnel so that dropoff rates can be gradually reduced.

Conclusion

Product teams use funnel analysis to measure the level of engagement and retention, in addition to improving conversions. For a funnel to bear fruit, a clear goal must be established regarding what should be measured while keeping user context and behavior in mind. So, whether it's measuring user onboarding or the checkout/payment process, funnel analysis can be the catalyst that leads to improved conversions, ensuring the success of your app or website.