3 Mistakes You May be Making with Analyzing Your Data

3 Mistakes You May be Making with Analyzing Your Data

Written by Professional Academy Guest Blogger Robert Cordray

Data analysis can help you do a lot for your business. The statistics for your business can give an understanding of what is going on; right or wrong. It is a chance to figure out errors in strategies and find solutions for them.

Although some decisions are purely by instinct, others call for more tangible metrics than your “gut feeling.” With the influx of web analytics tools on the market today, data analysis seems easy enough, right? Wrong. Taking analysis lightly is one of the reasons that website owners end up with frequent mistakes. Embarking on an A/B testing project without a comprehensive understanding of what it entails results in ill-informed decisions that end up costing your company. Data analysis requires skills, and over time, it evolves, so it becomes necessary to keep learning. Knowing the basics will help keep you grounded. So, what are some of the common missteps that people make with web analytics?

Concentrating too much or not Enough on Outliers

Concentrating too much or not Enough on Outliers

Dealing with outliers can be tricky when conducting an analysis of your site data. Web data is inherently complex, and for that reason, outliers are introduced when mining information. Factors such as erroneous processes and incorrect data can also lead to outliers. You can expect to come across a variety of outliers when collecting website information. It could be a spikier in web visitors or a fall in lead volume. What happens when most people encounter this kind of data is that they ignore it or concentrate too much on it. Assuming that a sudden decrease in the number of web visitors to your site is just a one-time thing may land you in trouble. Sometimes outliers can be an indication of an error with your web form. For instance, a broken URL link may be causing a drop in the number of visitors. Neglecting such a problem is a recipe for a much worse outcome than just a decrease in visits.

On the flip side, giving outliers a lot of attention may lead to unprecedented problems. For example, taking a spike in lead volume from your data analysis and using it as the basis of your whole marketing campaign can blow up in your face. Unless you can prove that the results are nothing more than coincidental, do not give them more focus than they warrant.

Focusing on the Wrong Metrics

Focusing on the Wrong Metrics

Even the best web analytic tools will entail data that is of no use to you. Data collection incorporates a myriad of elements and it so easy to end up with an overload. These range from sales to customer satisfaction to web response time. You have to consider data coming in from social media, your web analytics platforms, call centers, and CRM just to mention a few. Remember, though it is not about the volume of data but the quality and variety. Spending too much time on all this data will just leave you with a project that takes up too many resources.

From the data you collect, the metrics will tell you where the wins and the losses are. Don’t make the mistake of fixating on results that don’t do much for the bottom-line. Before you can use your web response time data to restructure the marketing strategy, ask yourself, does this metric matter to the well-being of my business? Proceed if the answer is yes. The problem with paying unnecessary attention to meaningless metrics is that you end up ignoring the crucial ones. Wrong metrics increase your chance of making wrong decisions tenfold.

This mistake is one that most start-ups make, especially by focusing too much on the results. Because an entrepreneur wants to see profits instantly, they end up using the wrong analytics to achieve them. The trick is prioritizing business outcomes correctly so you can have a less complicated time figuring out the datasets that make the most sense. It will give you a start point for getting actionable insights for your web analytic tools.

Another product of using the wrong data metric is ending up with a chart or database that does not explain what you need to. For example, you may have a presentation about new consumer trends in relation to social media, but the content on your charts just raises more questions from colleagues.

Failure to Factor in Seasons

Failure to Factor in Seasons

It is easy to get misleading information when you don’t account for the time of year when gathering data. Numerous aspects influence web analytic metrics such as back to school trends, holidays, and tax season among many others. If you run an online shopping site, for instance, you can expect that the number of visitors will spike dramatically during Black Friday or Cyber Monday depending on the type of merchandise you have. Failing to include the time of year when modelling data means that the conclusions are insufficient.

Seasonality plays a very significant task in a majority of businesses. By incorporating this element into your analytics, marketers can have solid conclusions to base their strategies. Besides, seasonality data can help you time your conversation rate optimization. The best period to improve conversions is when everything is quiet. It gives you a chance to implement small and subtle tests that don’t interfere with business operations because it is off-peak.

Site analytics have become the bread and butter of entrepreneurs because online visibility is the currency in today’s business world. Through the use of analytic tools, you can gather data from different sources and use it to model a successful business plan. Web analytics give you useful insights into the performance of your site such as your most successful/failed campaigns, consumer behavior, and the volume of visitors. The secret to capitalizing on web analytics is first to have goals for your website. Are you looking to increase conversions? Are you rebranding? Are you targeting a new audience? All these are objectives that will lay down the blueprint for your data analysis. Learning more about web analytics and the potential pitfalls they come with will prepare you when mining data, consequently making it less challenging to gain actionable insights.

If you would like further information, you can visit our Digital Marketing Qualification (DMI) information pagedownload a copy of our DMI Qualifications brochure or contact a qualifications adviser today


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