There are many variations on this question. Sometimes it’s not even a question, sometimes it’s a statement: “We’re getting more and more followers, and our revenue is growing, so I don’t need complex analytics.”

Digital Analytics tell you what you’re doing right and what you’re doing wrong. What works, and what doesn’t work in all facets of your digital marketing strategy, from social media to content, to email marketing. If you don’t measure, you are guessing. You could help yourself a little bit, but it is almost certain that you will help yourself more with Digital Analytics. You could find out what content your audience really likes, and really shares. You could see which social networks and activities drive the most traffic to your site.

If you spend a lot of time on social media activities, it is usually a net benefit, and in many cases, a great advantage, to spend some of those hours on measurement and analysis. That gives you the knowledge to optimize your activities. And that, in turn, will produce better results from those activities.

Google Analytics is a web analytics service that provides statistics and basic analytical tools for search engine optimization (SEO) and marketing purposes. The service is part of the Google Marketing Platform and is available free of charge to anyone with a Google account.

Google Analytics is used to track website performance and collect insights from visitors. It can help organizations determine the top sources of user traffic, measure the success of their marketing activities and campaigns, track the completion of goals (such as purchases, adding products to carts), discover patterns and trends in user engagement and obtain other visitor information, such as demographic data.

Small and medium-sized retail websites often use Google Analytics to obtain and analyze various customer behavior analytics, which can be used to improve marketing campaigns, drive website traffic, and improve visitor retention. ‘Big data’ follows from larger websites and disciplines that serve the public interest.

To better understand how social media analytics works, it is useful to look at the mechanisms behind the analysis process. A social media analytics tool retrieves all data from the APIs of the social network (TikTok, Facebook, Instagram, Snapchat, YouTube and Pinterest), stores it in a database and creates visualizations in the form of tables or metrics.

This is the basic concept of a social media analytics platform, but what is the real value behind a solution like this? Social media analytics helps create benchmark reports, and aids the process of finding out how active your channels are compared to your competitors’ channels and which tools to use.

It provides information and insight into interaction rates, followers, post types, response times and many other measures. This allows you to easily adjust and optimize your social media performance.

At DGTLbase, we are omnichannel experts who use Digital Analytics insights to deliver benefits across your business. We have experience with a wide range of industries and companies, both B2B and B2C.

Our approach means we are close to you to understand your needs and challenges. We are proud of the long-term relationships we have built with our customers. Because we believe that the closer you are to a company, the better you can understand the nuances of its data. By nurturing these long-term relationships, we ensure our clients get the most out of our expertise.

With regard to digital strategy, DGTLbase only supplies tailor-made solutions where communication with the customer is central. We work closely with the parties involved, regardless of the project, so that the end result delivers the best return on investment (ROI) for the client.

Descriptive analysis

The first type of data analysis is descriptive analysis. This forms the basis of the final data overview. Descriptive analytics answer the question “what happened” by summarizing past data, usually in the form of dashboards.

Diagnostic analysis

After asking the main question ‘what happened’, the next step is a deep dive into the question ‘why did it happen?’ This is where the diagnostic analysis comes into play. In diagnostic analysis, the insights from the descriptive analysis are used to discover the causes of those outcomes. You use this type of analysis because it makes more connections between data and identifies behavioral patterns.

Predictive analytics

Predictive analytics tries to answer the question ‘what is likely to happen’. This type of analysis uses previous data and models to make predictions about future outcomes. This type of analysis is another step above the descriptive and diagnostic analyses.

Predictive analytics uses the summarized digital data to make logical predictions about the future outcomes of events. This analysis relies on statistical models, which require additional technology and manpower to make predictions.

It is important to realize that these data-based predictions are only an estimate; the accuracy of predictions depends on the quality, detail and focus of the data.

Prescriptive analysis

The latter type of analysis is the most sought after, but few organizations are really equipped to perform it. Prescriptive analysis is the frontier of data analysis, combining the insight of all previous analysis to determine the action to take on a current problem or decision. Prescriptive analytics uses advanced technology and data practices.

A business intelligence Consultant analyzes structured data. A Data Scientist analyzes structured and unstructured data. A business intelligence consultant formulates conclusions about the (recent) past. A Data Scientist formulates forecasts for the future. Digital analytics at DGTLbase combines these two disciplines.