Machine Learning and Digital Data for business

Machine learning has evolved to a point where we can use its capabilities to provide some extra benefit to our business.
According to research , our client and ideal customer have two separate identity. One is the physical persona and another is digital persona. To understand its impact, let’s compare this two client:

1. One experienced worker earned 10K a month, but rarely used social media, owned an Android phone.

2. One newly graduate worker earned about 3k a month, and highly engaged in social media, own an IphoneX.

Between those two, if you were to target for new product lunch which one would be more higher success rate ? provided your product would be useful to someone who would spend more money on trivial stuff.

Clearly the first one would be harder to impress and convincing them to pay for our product would be taking extra resource.
Targeting the 2nd type of people would require similar effort but with better success rate and if you’re able to make them happy enough you may get exposure that you need in most of social media.

And guess what, this is where the machine learning come into play.

Yes, at the moment the effort in this one is marketing-driven effort. You can now provide personalised ads for specific target of customer.

In order to get start, it come down to the data source.
From where we are getting the ideal customer profiles or also known as customer ‘avatar’ . For a corporation that have huge customer base, you may think this is not an issue.

However, the truth is, with these legacy data, the data need to be cleansed first, before it can be use for anything meaningful.

In this case, new startup may have advantage if they’re starting on right foot on what data to be collected from the beginning. And it may not to be full-blown machine learning.
Some tools are free to obtains and use.

Options are :

d3.js
qwiksense.

The above is the excerpt from the GECommunity Lab that I attended last week. It was very lovely and fun to be attended.

Thanks to organiser and host on the events.

1. It was casual, highly engaged audiences.

2. The host, outlined the expectation from the floor.

3.Executive summary.

4. The cycle.

5. Data driven decision making.

6. The architecture.

8. Data protection. (trust)

So, how would use digital data to improve your business?