Data Driven Analytics

Data… it feels a bit scary when you start with that word. To some, data in this digital world might feel a bit like invisible sorcery. We know it’s there but it’s just not tangible. Yet it controls everything. Harnessing the power of data to make decisions based on the performance of your business against KPIs; analysing user behaviour around your digital platforms and social media feeds to improve UX and UI; understanding your target markets intent and category at every single touch point in their user journey – this all happens with data collected from events taking place on your website, around your digital marketing streams and public interfaces. Quite overwhelming…

But, if we start thinking of data as the evidence a detective would use to solve a case or answer a puzzling question, it kind of starts to get fun.

Data Detectives

We have an abundance of data … to sort the data we need to ask the right questions. If you were a detective solving a case your question might be ‘how might we find out who was behind this incident’. At this point you break that question down further into ‘what was the incident that occurred, how did it occur, when did it occur, what were the events that led up to this incident, motive and mode’

Having a clear question that you need answered is the starting point of any data analytics project. This helps us gather, sort, and correlate the right data that we need. If you have a question that is too broad the answer won’t be clear enough to help you make decisions. For example, a question that is too broad ‘how can we understand user acquisition better?’ is not going to give you specific, measurable, or reliable answers. Make that question more specific – ‘How might we calculate our strongest acquisition channels and quantify those results to create KPIs for future improvement?’ This question includes a specific, measurable, attainable, realistic, and time-specific objective.

With our clear objective in question form we can start to look at the information, or data, we have available. But, we can also look at that data that is being collected but might not be easily accessible. This is when data analysts and developers come into their own. Their ability to create algorithms, pull reports or create scripts that pull together data from multiple sources is the sorcery we all wonder about. However, it must start with looking at what we’ve already got and asking the right questions.

Data sources

In the case of self-storage facility management our data sources can be numerous.