Funnel Analysis

Funnel analysis involves using a series of events that lead towards a defined goal, like from user engagement in a mobile app to a sale in an eCommerce platform or advertisement to purchase in online advertising.[1] The funnel analyses "are an effective way to calculate conversion rates on specific user behaviors".[2] This can be in the form of a sale, registration, or other intended action from an audience. The origin of the term funnel analysis comes from the nature of a funnel where individuals will enter the funnel, yet only a small number of them will perform the intended goals.

For more emphasis, it makes sense why a funnel in analytics is called a funnel. An actual funnel, like the ones from a kitchen or garage, gets narrower along its length, allowing less volume to pass through it. An analytics funnel represents a very similar idea, just in regards to users on an eCommerce platform, application or online game.[3]

Real world applications

An example of how a company would use funnel analytics is by focusing on drawing actionable insights from funnels. Funnel analysis can be used to determine conversion and user fallout rates in a given funnel. An analysis to determine the steps that lead to a desired goal in order to improve future interactions in the same funnel can be done for further success. To illustrate further, looking at how many users actually make it to the end of the funnel, for example to make a purchase or register, compared with how many do not.

By continuously monitoring and analyzing funnels, it is possible to assess if changes to an application or platform are having a positive effect on conversion. For instance, one might find that only 10% of users who come to a platform and enter the registration funnel actually reach the goal of completing registration. Using the funnel analytics process, it is then possible to tweak settings or features within the funnel in order to see what makes that number improve. Or when creating a marketing campaign, there is a chance to analyze how well the campaign is working by monitoring a funnel that brings users from the initial event all the way to purchasing a product.[4]

Funnel analysis helps determine the point in which users are dropping off. The next step is to understand why they're dropping off, in order to reduce drop off rates and in turn increase overall conversion.

Industries for Funnel Analytics

  • Ecommerce & Retail- Getting customers to buy more products.
  • Online Gaming- Reducing churn, increasing customer conversion.
  • Mobile apps- Getting customers to engage further.

See also

References

  1. ^ Jansen, B. J. and Schuster, S. (2011) Bidding on the Buying Funnel for Sponsored Search Campaigns. Journal of Electronic Commerce Research. 12(1), 1-18.
  2. ^ Apsalar. "Using Funnel Analysis to Measure User Conversion Rates". 
  3. ^ CoolaData. "Funnel Analysis". Archived from the original on 2014-07-26. 
  4. ^ CoolaData. "Funnels". 

External links


  This article uses material from the Wikipedia page available here. It is released under the Creative Commons Attribution-Share-Alike License 3.0.


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