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How to Analyse Data in 5 Easy Steps

Is it possible to crunch complex data without knowing the all-too-complex strategies  of data analysis?

With the help of this blog, you'll be able to confidently analyse data and derive significant information in your marketing reports.

What is Data Analysis, and Why Does It Matter?

Data analysis is the process of extracting useful information from large data sets so that you may use it in your decision-making.

These business decisions, as you are aware, might be large or minor. It's about providing more material on a recently popular topic and garnering more conversions for marketers.

It's about shifting a product's stance and boosting sales in an unique market market for C-suite stakeholders.

This report template displays the Google Analytics performance of a website.

How to Analyze Data 

Step 1: Establish Your Objectives

Is the data you need to acquire specific enough to your goals?

Let's imagine you've recently signed up two new clients who want to boost their blog's sales. You assumed you'd be gathering the same data as them, but after chatting with them on a finding call, you found that wasn't the case.

(Example) Client A is a well-established business with a solid domain authority website (DA). It has a good ranking in the SERPs. It receives a consistent stream of conversions, but consumers frequently leave owing to bad customer service.

Client B is a new business with a poor DA website. It has been producing numerous articles, but just a few are searchable. As a result, very few leads are created.

However both customers have the same objectives (i.e., improve sales), the core causes of their difficulties are vastly different.

Step 2: Define Your Key Performance Indicators (KPIs).

A KPI measures how well you're accomplishing your objectives. Let's continue with the same examples as before.

Clients A and B will have KPIs that are both comparable and dissimilar.

Each will want to keep track of organic search traffic and key rankings, for example.

Client A, on the other hand, is likely to need to measure and prioritise customer satisfaction scores, but client B is unlikely to.

Step 3: Gather Information

In the agency business, there are often two techniques to data acquisition.

The first method entails manually collecting data from various sources and assembling it in Microsoft Excel or Google Sheets.

The second is the use of automation!

Step 4: Analyse the Information

During your search, you may have encountered these nerve-wracking sorts of data analysis. Don't be concerned! You don't have to grasp all of these data analysis methodologies at once as a marketer.

Here's a quick rundown of what they're all about.

Data cleaning: 

It is the process of identifying and removing data that is irrelevant or erroneous from a data set.

Predictive analysis:

Forecast future outcomes to identify dangers and opportunities using predictive analysis. Historical data, machine learning, and data mining techniques are used in predictive analysis.

Statistical analysis: 

Gather data samples to look for patterns and trends. Regression, mean, and standard deviation are examples of statistical analysis techniques.

Descriptive analysis: 

Organize and summarise data points from previous quantitative data (a.k.a. "what"). Data analysis tools like Excel's descriptive statistics tool can help you disentangle these unstructured data.

Diagnostic analysis: 

Examine descriptive analysis data to determine "why."

Prescriptive analysis: 

Using raw data analysis, determine the optimum course of action (also known as the "how"). This necessitates the use of business intelligence software such as Tableau.

Text analysis:

It is the process of extracting text information (i.e., qualitative data). Extraction of important phrases and sentiment analysis of poll replies and customer questionnaires are two examples.

Step 5: Propagate Your Ideas

You're getting close to the finish line. As you may be aware, there are a range of methods to share your knowledge. You may use a video chat to walk your customers through their business data, add comments to a linked spreadsheet, or email the important results to them.

Wrapping up: Analyse Data Easily With MyDash 

To recap, you don't have to be a data analyst to analyse your data with MyDash. With MyDash, grabbing data from numerous channels at once and distilling actionable insights in the form of Dashboards takes only seconds.

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