Every business collects Data. Some do Analytics, but how many of them really derive Insights? Let's look into what these mean individually.
Every business collects Data. Some do Analytics, but how many of them really derive Insights?
Let's look into what these mean individually. For the purpose of illustration, let's look into the journey of data collected on an eCommerce website.
Data
This is the information you collect. There is also a difference between data and information. In a general sense organized/structured data is information. Lets, for now, assume our data is organized (dealing with unorganized data in itself is a different discussion)
For our eCommerce example: The location, demography, time, the purchased items, etc are the data collected here. The collected data typically sits in a database. When you collect huge volumes of such data, some call it "big data" (if I oversimplify it!). The mere collection of this data is not of much use unless we do the next steps.
Analytics
Just the collected data sitting in a database is of no use. We need to consume it. Consuming this data in a convenient manner is Analytics. The experience of consumption is key here. Compare downloading an excel sheet of data vs seeing a visual interface.
For our eCommerce example: You may use a tool like Google Analytics to browse the data. This part is called Analytics. You will get a lot of value here. You will know for example "Which age group is my primary customer base?", "Which geography gives me the best sale?", "What is the time of day when my website has maximum users?" etc.
Analytics helps you to react better (eg: Increase the website capacity during weekends)
Insights
Insights are the next level. It helps you ask and get answers to many more not-so-obvious questions. Artificial intelligence and machine learning is the key focus area here.
For our website example: You can get an answer to a question like "Which is the geographical area where I should start selling now?" If you notice, this data is not directly available to us (note that we have only data from the regions we already sell).
Now the tool we are using is predicting, not just showing us past data). Human beings have always been good at intuitively predicting things. but we are limited by our ability in processing large volumes of data. So, the AI/ML-based systems come in here. They are good at consuming a huge amount of data and giving us answers using mathematical models.
Summary
So, what is it for you?
- You have to start collecting data if you are not already. Your competition is already doing it. Respect users' privacy while doing this. Anonymous data is also of huge value.
- Start using an analytics tool. Many tools are commonly available. Start building a culture of data-driven decisions in your business.
- Be on the lookout for what gives you insights. Some analytics tools have started to do this. The insights you are looking for are not likely what I am looking for. So the chances are that it takes substantial time and effort before you reach your ideal Insights setup.