Data analytics requires quite a bit of time, energy, and attention, these are vital resources that can significantly enhance your business’s performance. While there are quite a few common mistakes when gathering and utilizing data, you can solve the vast majority of such errors with the help of data governance. Therefore, to avoid these common data analytics mistakes that could be hindering your business’s ability to benefit genuinely, you should consider data governance consulting.

Common Data Analytics Mistakes Your Business Should Avoid

Interpreting Views as Visits

When it comes to your business’s website, there are a few ways to enhance traffic, such as implementing SEO and keeping your content engaging. However, in terms of interpreting the success of your website, you should avoid assuming that views and visits are the same things. This misconception can be a massive mistake as a view is counted each time a user opens a page on your website. Therefore, if a user clicks on a webpage and then clicks on five more, it will be counted as six views. A visitor is determined according to the number of users that visit your site for a substantial period. Google Analytics will generally end a session when the visitor is inactive for about half an hour. Counting views is helpful to your business, although your number of visitors should consider your actual numbers.

Considering Low Numbers As Bad Results

While most marketers and data analysts will perceive low numbers as terrible results, however, this is not always the case as low numbers could confirm an improvement in the campaign. Therefore, you may find low numbers from an email campaign; you may save customer acquisition expenses. What’s more, low numbers will also help you determine what works and what simply doesn’t. Instead of shunning low numbers, you should consider how to utilize these numbers to improve your business.

Merging Leads And Marketing Qualified Leads

Even though leads and marketing qualified leads are similar, confusing and merging the two will result in corrupted and misleading reports. A lead is generated from a customer through a website landing page. In contrast, a marketing qualified lead (MQL) is gathered by marketing tactics that determine whether a lead is a potential customer or not. While the metrics that assess lead qualification can differ, you should avoid merging these two types of leads as you will end up with misleading numbers.

Viewing All your Traffic Together

All your website traffic will come from various sources, and merging this information will not benefit your business. Separating traffic is more beneficial as it will allow your business to identify struggling campaigns, successful campaigns, and campaigns worthless to business growth. Bucketing all your traffic together will confuse your results, and your data analytics strategy will ultimately be useless.

 

Data analytics can enhance almost every area of your business and its performance against competitors in the market. However, various mistakes can render your strategy futile. The most effective way to avoid encountering problems and errors in your data analytics strategy is to implement data governance to interpret your data for your business correctly.