Digital analytics

There are many variations of this question. Sometimes it isn't even a question but a statement: “We keep gaining followers and our revenue is growing, so I don't need complex analytics.”

Digital analytics tell you what you are doing right and what you are doing wrong. What works and what doesn't across every facet of your marketing, from social media to content to email marketing. If you don't measure, you are guessing. You might help yourself a little, but you are almost certain to help yourself more with digital analytics. You could discover which content your audience really likes and actually 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 big one, to spend some of those hours on measurement and analysis. That gives you the knowledge to optimise your activities, which in turn delivers better results from them.

Google Analytics is a web analytics service that provides statistics and basic analytical tools for search engine optimisation (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 gather visitor insights. It can help organisations identify the main sources of user traffic, measure the success of their marketing activities and campaigns, track goal completions (such as purchases or adding products to baskets), discover patterns and trends in user engagement and obtain other visitor information, such as demographics.

Small and medium-sized retail websites often use Google Analytics to obtain and analyse various customer behaviour analyses, which can be used to improve marketing campaigns, drive website traffic and retain visitors better. Larger websites and fields serving the public interest produce ‘big data’.

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

That 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 helps you find out how active your channels are compared with your competitors' channels, and which tools are best to use for that.

It provides information on and insight into engagement rates, followers, post types, response times and many other measures. This lets you easily adjust and optimise your social media performance.

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

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

In digital analytics, DGTLbase only delivers tailor-made solutions with communication with the client at the centre. We work closely with the parties involved, whatever the project, so 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 analyses answer the question “what happened?” by summarising 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 ‘why did it happen?’ That is where diagnostic analysis comes in. Diagnostic analysis uses the insights from the descriptive analysis to find the causes of those outcomes. You use this type of analysis because it draws more connections between data and identifies behavioural patterns.

Predictive analysis

Predictive analysis tries to answer the question ‘what is likely to happen?’ This type of analysis uses past data and models to make predictions about future outcomes. It is another step up from descriptive and diagnostic analysis.

A predictive analysis uses the summarised digital data to make logical predictions about the future outcomes of events. This analysis relies on statistical models, which require extra technology and manpower to make predictions.

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

Prescriptive analysis

The last type of analysis is the most sought after, but few organisations are truly equipped to carry it out. Prescriptive analysis is the frontier of data analysis, combining the insight from all previous analyses to determine what action to take on a current problem or decision. Prescriptive analysis uses advanced technology and data practices.

A business intelligence consultant analyses structured data. A data scientist analyses structured and unstructured data. A business intelligence consultant draws conclusions about the (recent) past. A data scientist makes forecasts about the future. Digital analytics at DGTLbase combines these two disciplines.