In previous post I wrote a brief introduction of data monetization. In this post I will add some details
about data analytics monetization.
Companies and retailers are
working together with wireless carriers in order to gain insights into
geo-location data, customers movements at shopping stores are getting tracked
and companies are using that data to make marketing campaigns programs that are
loyalty designed on relevant and frequency.
Nowadays, data
is becoming easily available and gathered in digital world than ever before.
Companies or retailers have the ability to track customers’ transactions and
interactions across different channels and devices and invest in their data in
new and innovative ways.
According to
Chris Twogood, usually, monetizing data is indirect action. starts by making
the operation run in efficient way, '' incentivizing certain types of behavior,
or revealing the true value of an asset.'' Each company has their own way to
monetize their data. and he identified five essential ways that can move
companies to monetize their data:
1.
Start
with Questions: companies usually start by looking to the data. They need first
asking their staff about questions that give the right level of detail in the
right time which give the most impact performance. by asking these questions
would help the companies evaluate whether they have enough data or they need
more data.
2.
Look
for Patterns: Professor Russell Walker of the Kellogg School of Management at
Northwestern University identifies trends of big data that indicate to patterns
for monetizing data. At the Teradata Partners conference, Walker examined how
the velocity of data, new forms of precision, and opportunities for fusing
different data sets can lead to data monetization.
3.
Search
for External Data: According to Chris Twogood, large organizations should
dedicate one team member to searching for valuable external data.
4.
Sharpen
the skills of analytics: by using traditional methods, big data becomes
impossible to analyze data probationary, companies must comprehend the nature
of machine learning and advanced analytics. monetizing data will become easy to
apply by understanding of machine learning and advanced analytics.
5.
Understand
the identity of data monetization
6.
In
order to find ways for data monetization, organization should understand the
role they play. an expert consumer of data, an aggregator, or the creator of a
new data product. Each organization has their own goals and objective which
lead them to find the right way to monetize data.
" the two
researchers from Gartner, Doug Laney an Olive Hung define monetizing data as
actions as direct like traded or data sold or indirect like data that becomes
the foundations for new product or services offerings "
Examples of
companies that is successfully built data monetization opportunities.
- Wal-Mart by
Retail Link trading portal
- Alibaba by
targeted personal finance offerings
Barbara H.
Wixom, principal research scientist at the MIT Center for Information Systems
Research mentions in her research "Cashing in on your Data," 2014
three methods of data monetization which are selling, bartering or wrapping.
retailers have
been selling data for years with data of loyal customers or point-of-sale which
is new income flows to the company.
retailers have
been selling data for years with data of loyal customers or point-of-sale which
is new income flows to the company.
According to
Wixom, when bartering, reports or benchmark metrics are services for data
exchanged.
To sum up,
according to Wixom's report "companies that include data offerings with
their products at no added charge are wrapping products in data. The desired
outcomes of wrapping include increased market share, wallet share, switching
costs and prices."
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