Avoid These 7 Common Mistakes in Data Analysis

Avoid These 7 Common Mistakes in Data Analysis!

Many of us do a lot of effort during the research for accurate and reliable statistics and figures to make good decisions in our company. However, sometimes we discover that we’ve probably pursued the wrong approach by using unsuitable criterions standards that will not drive us the right information we are really seeking.

In this article, we’ve identified 4 common mistakes in data analysis you need to avoid immediately while digging in your data and analytics, in order to save a lot of time and bad experiences.

Small Numbers aren’t always a bad Performance Indicator

It’s sometimes frustrating and disappointing when we see small numbers on the statistics dashboard for any marketing campaign (Advertising Reach, Email Open Rates, Website Views, etc.. )

Yes Sure, small numbers are great in many things like: bounce rates, opt-outs from email list, Conversion costs, etc..

However, what we want to say here is that they are not a bad sign everywhere else. It’s always better to have more qualified audience than more audience. It’s always to have a small targeted email list than a huge list of contacts with wide interests.

Confusion between the number of visits and views

It may seem that both terms are similar to some extent (maybe for non-google analytics persons), but in fact, there is a huge difference between them.

Visits represent the number of times the website was visited, without regard to repeat visitors. Page views represent the total number of pages that visitors looked at on our site. Visitors represent the number of actual people that visited our site.

For example: You (1 Visitor) visit an article on Lucidya’s Blog (1 Visits), and then you clicked on another 2 articles on the blog to read them (2 Page Views).

Choosing the wrong charts to represent your data

The visual representation of the data is one of the most effective ways to connect and display your team’s results, we all know that.

However, if you displayed them improperly this will result in distracting the audience and perhaps misleading decision-making process.

There are many ways in which you can represent your target audience and how your campaigns reached them.

There is a big difference between asking yourself “What I want to connect through this data” and “What I want to prove through this data.”

Ignoring the details

Unfortunately, most marketers are collecting data only for the purpose of displaying it in front of their manager or to communicate it on Monday’s meetings.

During the year, marketers are collecting tons of data from traffic sources, number of visits to conversions, open rates, etc.… without precisely tying those data with the actual profits.

You have to ask yourself, which email campaign was more successful? Which Ad you’ve spent on delivered more leads to your services? Which landing page is converting more and why?

You have to connect each marketing activity and its contribution in the high-level company goals.

Doing all the analysis operations manually

In general, social networks and digital marketing analysis tools are one of the fastest-growing markets in the recent period, and this is clear evidence of the importance of these tools and their role in facilitating the task of obtaining concrete data from various marketing activities.

Not using these tools, will lead you to spend more money, time, and effort to get primitive data that will not even help you taking savvy decisions to boost your business.

Ignoring the difference between traffic types

Traffic or visits coming to your website are varied and different. Traffic sources can be organic sources, such as referrals, email, social media, or search engines. They can be paid, in case you are running some advertising campaigns whether on social networks, Google, or any other sources. All these traffic channels are not with the same value.

If you have 1000 visits to your site during a given month, you have to divide that number into smaller parts according to different marketing channels and ask yourself the following:

What percentage of visits is coming through search engines? and what about the e-mail campaigns you are running? What are the growth rate and increase of these figures during the months? And so on.

Knowing these numbers will help in understanding where you should invest your money, time, and effort to get the best out of each channel.

Wrong Comparison Criteria

In the world of analysis and statistics, you can’t compare an orange with an apple, instead, you should compare it with another orange.

When it comes to digital marketing, the most difficult part is to know the difference between data types to make a good and healthy comparison that drives decisions.

For example: if a page X on your site has more traffic than another page Y on the same website, this doesn’t mean that page X was performing better than page Y.

There are tons of factors you should take into consideration to actually have a judgment whether this page is contributing to your goals from online presence/marketing?
For example, suppose you have 200 visits to page Z on your site through email marketing and 150 other visits to the same page through mobile phones. Does this necessarily mean that you should increase investment in marketing e-mail marketing rather than mobile phones?

Well not necessarily.

Maybe you allocated less budget to target mobile phones. and maybe the page is not rendering correctly on mobile devices. Maybe the email got extra shares within some other client’s organization, etc.

Believe me; you should dig deeper into your data to have good future decisions.

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