DIGITAL ANALYTICS

Digital analytics is the analysis of qualitative and quantitative data from your business to drive a continual improvement of the online experience that your customers and potential customers have which translates to your desired outcomes.

FREE ANALYTICS CONSULTING

Are your online marketing goals driven by data; or just a shot in the dark? Either way, we can help you gather the qualitative and quantitative data you need to make better decisions.

Let us help you with your analytics challenge, any question on website analytics using Google analytics, Google Tag Manager, or other tools.

FREE IMPLEMENTATION PLANNING

We will happy to hearing from you if you have any technical problem in Analytical code implementation
Web Analytics implementations are never ending stories, there is always a small fix or a new feature that requires changes to the code or to the settings of your Analytics tool, always.

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How We Do It ?

Digital analytics should run in parallel with other marketing activities providing business with real-time information. Here is our step:
  • Analytics Process

    However business analytics is applied, the key outcome is the same: The solving of business problems using the relevant data and turning it into insights, providing the enterprise with the knowledge it needs to proactively make decisions. In this way the enterprise will gain a competitive advantage in the marketplace.

Defining the business needs

Understanding what the business would like to improve on or the problem it wants solved.

Explore the data

This stage involves cleaning the data, making computations for missing data, removing outliers, and transforming combinations of variables to form new variables

Analyse the data

At this stage, using statistical analysis methods such as correlation analysis and hypothesis testing, the analyst will find all factors that are related to the target variable

Predict what is likely to happen

At this stage, the analyst will model the data using predictive techniques that include decision trees, neural networks and logistic regression.

Optimise

At this stage the analyst will apply the predictive model coefficients and outcomes to run ‘what-if’ scenarios, using targets set by managers to determine the best solution, with the given constraints and limitations.

Make a decision and measure the outcome

The analyst will then make decisions and take action based on the derived insights from the model and the organisational goals.

Update

Finally the results of the decision and action and the new insights derived from the model are recorded and updated into the database.

A few clients I've worked with