Extracting Information from Data

Someone said, ‘Look at data like you’re looking at your Girlfriend’. Yeah, to get information from a data set, you need to look at it in a different way!

Data could be in any format. Most of the times, you’ll see it in an excel sheet or may be in database like MySQL, PostgreSQL etc. Few thousands of rows in an excel sheet or rows in a table need a lot of good look and representation to find an important information.

Data doesn’t come processed automatically, it needs to be processed, purified, organized and presented to find what one is looking for.

Representation of data is one of the most important thing you’ll ever see while dealing with data. Bad representation of data won’t show you anything but some garbage. So, always focus on representation.

Presentation of data in a Pie Chart

Data could be presented in a lot of ways. It could be a simple pie chart or line charts, in a tabular format or many other ways based on your requirement and goal. But make sure it shows the real information or tells the viewer something that lies inside the data. The best way of finding it is by asking question. Asking what’s the goal of the representation, what’s the final result should be., what do you want to find out? Decorate according to that.

To extract information from data, you must need to have a set of goals. The goal could be acquisition of new customers, the goal could be engagement that increases user’s stay time at your platform, the goal could be conversion (purchases something from your platform or subscribes) or the goal could be making customer’s experience (something personalized) better.

Let’s say you have a data set of your customers. Your business is selling ‘Diaper for Kids’. The set contains metrics like Name, Email, Age, Gender etc. Assume, you have a goal to achieve while you’re looking at these data. The goal is increment of conversion. That means, your customers who already bought from you and now challenge is to sell to them again and finding something from the data that helps the cause.

First metric you can take on count is the age and the second one is gender. There’s a good chance that male parent will buy diapers more than the female parent. Not discussing the reason. Then the age group. Shoppers in the 25–34 age group are likely to purchase more than the 18–24 or 35–44 age group people.

From here, if you do segmentation of ages in more little groups, you might find out something more interesting like ‘25–28’ age groups are purchasing most and a pack of diapers goes for a month. So you can re-target them and increase your conversion. That’s one thing I have told you but if you yourself do segmentation might something else!

A real life example of looking at data:

Me and my team at office, we were looking at data of location based shoppers and what they purchased. FYI, our company is an renowned eCommerce company at Dhaka that has customers all across the country. As expected, the shoppers from the capital Dhaka and major cities purchase the geeky gadgets and advanced trendy products. They are more smart in picking their products than other part’s shoppers.

Customers from the most far part of the country are not much interested in fancy gadgets or geeky things. Interesting thing we noticed, the customers of areas close to the capital and major cities are very much interested in fancy gadgets that actually helps them to bit smarter and cooler in looks and behavior.

So here it stands:

  • Shoppers of major cities: Smart, picks products wisely, compares before purchasing
  • Shoppers of country side: Purchases mostly what’s not available in their region.
  • Shoppers of area that are near by major cities: Fancy gadgets, cool stuffs.

For example, they often purchases fancy colorful headphones, Virtual Reality products, VR card board, interesting mobile gadgets. On the other hand City habitats are more choosy in their shopping.

VR card board (Image courtesy :Ali express)

Get the idea of New trend from data:

Whatever the trend is, you’ll notice it in your data. It could be in visitor’s browsing patterns, could be in their search history and could be in their queries.

A mobile game named PUBG has become damn famous in recent times! Before that there were famous mobiles games like Clash of Clans, Clash Royale and many others.

Not just mobiles games but whatever the trend is, you’ll get to see it in your data. I look at data almost everyday. Data like search term, browsing pagers, conversion pages.

I often notice the trendy terms are searched and browsed in our platform. Like, for PUBG, people are trying to find out gadgets that helps them to play the game.

Pubg mobile controller (Image copyright: amazon.in/Leoie)

So, find the trend and try to offer them what they are looking for. Even if the trend if some public exam results or general elections they might look for relevant products in your platform.

So, value the trend if you find it in your data.

Try to segment the Journey

If you track the footsteps of your visitors or customers. You might find a pattern among the same funnel walkers. As a guide of the customer’s walk, it will be easy to see if they’re going in a right way or if they’re looking for something and not getting it.

You can make a funnel of footsteps of visitors/customers. See where they fall most and what they failed to find out. Remember, people don’t have a lot of time these days. If they don’t get what they’re looking for, they have got a lot of other platforms, lot of other options. So, it’s very crucial to find if they’re getting what they are looking for. You’re data will tell you these.

A representation could be,

  • Where are customers coming from?
  • Where are they going?
  • What are they looking for?
  • Are they getting what they are looking for?
  • Are they purchasing what they looked for?
  • What’s the experience of them if they get it?
  • Will they comeback if they go through this?

Representation of these and finding out the answers will give you a boost. And definitely you will be able to extract information from a great representation of data.

That’s all for today. Hope this helps to find out your information from data.

Don’t forget to clap if you love it ;)

Feel free to ask any question you have in your mind.

Artificial Intelligence Enthusiast, Teacher & Quickest adopter of new hot tech!

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