6 Risks with Using Predictive Analytics for Conversion Rate Optimization

Conversion rate optimisation is very important, but it is also a very imprecise science. The biggest challenge is that customer behaviour is constantly evolving. The practices that customers responded to five years ago may not be effective today.

Marketers must use the latest tools and strategies to maintain a decent ROI. Predictive analytics models are highly effective, but they aren’t foolproof by any means. If you are planning on using predictive analytics to boost your online conversion rate, you will want to avoid making the following mistakes.

1. Be Wary of Your Ability to Understand Changes in Social Psychology at a Macro-Level

Some experts attempt to use predictive analytics models to identify future fads or predict changes in customer behaviour. You need to be cautious with these models because they are notoriously unreliable.

Even the most insightful predictive analytics model cannot account for unplanned variables. New events or product offerings can change customer perception overnight.

This doesn’t mean that predictive analytics tools are useless for conversion rate optimisation. However, there is a large margin of error, so you should only focus on variables that are easiest to analyse.

2. Don’t Extrapolate Data to Unrelated Campaigns

Many different variables affect your campaigns. These variables can include:


Marketing mediums or ...


Read More on Datafloq

Comments

Popular posts from this blog

Underwater Autonomous Vehicles Helping Navy Get More for the Money 

Canada regulator seeks information from public on Rogers-Shaw deal