Common Mistakes Digital Marketers Make When Analyzing Data
Data analysis is the most important for getting results in digital marketing. However, misinterpretation of data insights from analytics tools can mislead
Data analysis is the most important for getting results in digital marketing. However, misinterpretation of data insights from analytics tools can mislead the digital strategy.
Anybody can make these mistakes, and it does not matter whether you are an experienced marketer or a fresher. The most important thing is to be aware while observing data or reaching wrong conclusions.
Here is the list of Common mistakes digital marketers make when analyzing data:
Ignoring micro-conversions: Traffic on your platform converts through micro and macro conversions. Interactions like newsletter sign-ups, video view, time on site, bounce rate reduction, etc., are called micro-conversions.
Macro-conversion includes activities like an e-commerce transaction or a lead form fill. For marketers, macro conversions are the actual goal, and therefore they pay attention to macro conversions. However, the key to successful macro-conversion is micro-conversions. Improving micro-conversion can improve your macro conversion.
Analysis of segmented data
When analyzing traffic data, it is essential to first segment data based on their sources. Traffic from different sources behaves differently on the website.
User behavior like bouncing rate and session time differs for organic and paid search; therefore, analyzing traffic from different sources in the segmented form helps create the right course of action.
Usage of back-end data
An organized workflow and a proper setup are essential for successfully converting the traffic into the lead and processing the process ahead. It would be helpful for you to attribute revenue back to a specific campaign, keyword, and ad.
To measure lead’s movement through the sales process, a UTM tagging and attribution of sources in CRM should be in place.
Also, to check whether your keywords and campaign are doing well, use back-end sales data of e-commerce to compare with your analytics report.
4.Concluding out of a tiny sample of data:
As we deep dive into data, we apply multiple filters. As a result, datasets get smaller. It is essential to remember that when your session numbers are three-digit, do not rely on a single dataset for conclusions.
5.Being biased about selecting data:
When you are in the middle of a lot of data, sometimes your personal opinion may hinder your capability of looking at the bigger picture. As a result, you may cherry-pick data.
It is the biggest mistake that you can make as it leads to wrong analysis and ultimately wrong course of action. In such a situation, it better to let a fresh set of eyes analyze your data.
6. Seasonal Trends:
The most common mistake a marketer makes is not accounting for seasonal trends when making a year-long projection. When marketers do not consider festive seasons like Christmas, a drop in the expected result becomes a reason for panic for both clients and marketers. So, while planning for a long duration like a year, it is essential to consider festive seasons.
After going through these mistakes, you can reflect on your process and find where you can improve. These points can help you like a checklist as well.
Hariom Balhara is an inventive person who has been doing intensive research in particular topics and writing blogs and articles for Tireless IT Services. Tireless IT Services is a Digital Marketing, SEO, SMO, PPC and Web Development company that comes with massive experiences. We specialize in digital marketing, Web Designing and development, graphic design, and a lot more.
SOURCE : Digital Marketers