“The song will never work. Its too long, too complex, too confusing and doesnt fit into any musical genre.”
Radio stations feedback to Queen about Bohemian Rhapsody
The search of greater return on Big Data investment or generating alternative revenue streams for your organization is important to all companies. However, it is not that easy with Big Data. Therefore, lets go through some of the most common myths on data monetization.
Not Every Bit Counts
Yesterday I was working with a client. They collect everything from users birth-date to current position hoping they can monetize it. However, if their only goal is to sell the data to traffic management to display ads to current traffic, then our age, school, email, phone-no, birth-date, name etc are useless data which will cost extra storage and processing in the most of cases.
Strategic planing of collecting data can reduce costs of making data products and increase your profit via three steps:
- Select a use case in your niche that solves others problem;
- Now collect data according to that use case;
- Scale the use case.
Winning is Simpler When You Don’t Complicate Things.
Similar Data Already Exist
“We come too late to say anything which has not been said already.”
– Jean de la Bruyere
But thats a lie.
Every outline has already been written. Just putting that fingerprint on an outline makes it yours, different, unique.
Even though similar data already exist in the same category it will differ in accuracy, depth, volume, velocity etc. Companies often use more than one dataset to take decision(see the Power of Three).
Your product predicts your users behavior. For example; advertisers want to display different ads to Iphone users than Android users, because Apple’s users spend approx 4X as much as Google’s.
It doesn’t mean Android user are a waste. Android has a larger market share that provides large volume of data to analyze market trends etc.
Data Monetization Can Reveal Trade Secrets
Sorry but I will give you an MBA answer to this
“IT Depends!”
What are the dimensions of the data you want to share and with whom? De-identification works. Often data buyers want a complete solution rather than your raw data. Raw data is little valuable and we may require external data to create a data product.
Governments have been beating the drum about open datasets to help citizens. Open datasets are going to play an effective role in data monetization.
There are also cases where raw data is more valuable but it doesn’t mean you have to give all your data and trade secrets to generate alternative revenue streams.
So what about you have you started Monetizing your data yet? Do you have any additional tips or notes on myth of ‘Data Monetization’ ? Any comments gladly appreciated.
