The document discusses how data mining and predictive analytics alone are not sufficient to deliver solutions when harnessing consumer data, and that data gathering is a critical first step. It emphasizes that to be effective, consumer data gathering must establish strong consumer identities and the ability to frequently reach out to consumers to obtain additional relevant data points or drive desired actions. This requires collaboration between consumer brands and supply side platforms to improve identity association and reach.

1. What a REGULAR DATA SCIENTIST doesn’t tell you about
CONSUMER DATA?
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2. Harnessing Consumer Data >> (Data Mining)U(Predictive Analytics)
Consumer Data Gathering
Engine
Data Mining
+
Predictive Analytics
Consumer Reach-Out
Application
When it comes to “Data Sciences”, much emphasis has been laid on the
importance of data mining & predictive analytics. While they are
necessary and pivotal elements of the solution, they are not sufficient on
their own to deliver the solution.
Garbage In Garbage Out is among one of the most loved adages that can
be associated with “Consumer Data Science”. The impact of quality and
comprehensiveness of the data gathering techniques can’t be overstated.
As the flow-chart for harnessing consumer data gets completed, the
importance of a Consumer Reach-Out Application becomes self-evident.
Understanding the factors that impact it’s success is critical to the over-all
success of the approach.
Behavioral
Data
Intent
Data
Psychographic
Data
Campaign
Responses
Purchase
History
Demographic
Data
$$$$$$$

3. Dependencies for Harnessing Consumer Data Effectively
Consumer Data Gathering Engine Consumer Reach-Out Application
(1/Identities)
Reach
Frequency
Ideally there should be a 1:1 relationship between a
Consumer Identity & a Consumer. But in a multi-device,
multi-ad server, multi-browser online world, with its
multiple cookies, ad-server ids and device ids, this 1:1
relationship between Identity & Consumer, degenerates
into a m:n relationship.
The fewer the identities associated with a consumer, the
more the number of data points associated with that
consumer, resulting in a better input to Data
Mining/Predictive Analytics engines.
In contexts, where the relevance of a data point is short lived
– which is the case more often than not, the frequency at
which a consumer can be reached out to, to collect other
associated data points and/or drive a desired action, plays an
extremely crucial role in making use of data already
collected.
Identifying a consumer with relevant data points is hardly useful, unless supported by
the ability to reach him/her at will, whether the objective is to collect more data or
drive a desired action. Interestingly, a stronger identity – which is function of
Consumer Data Gathering Engine, plays a significant role in improving reach – which
is usually believed to be a function of Consumer Reach-Out Application.

4. Need for Collaboration to Harness Consumer Data
Consumer Internet Brands (Mobile & Web) Supply Side Platforms (Mobile & Web)
0
Identity
Frequency
Reach
• Having a more consistent Consumer Identity like email or phone number helps Consumer Brands in associating
more data points appropriately to a particular consumer.
• The higher likelihood of a Supply Side Platform’s impressions outnumbering a Consumer Brand’s page-
views/sessions reflects in it’s ability to reach a consumer at a higher frequency.
• In case of reach, dependency of reach on strong identity is a limitation for Supply Side Platforms. Whereas in case
of Consumer Brands, their fewer impressions (when compared with a Supply Side Platform) limit their ability to
gain the necessary reach.

5. Collaboration Between Consumer Brands (Mobile & Web)
• While collaboration between a Consumer Internet Brand and Supply Side Platforms helps in improving the
frequency of communicating with a consumer (& similarly in gaining reach), collaboration with other Consumer
Internet Brands helps in improving the “Identity” association for that Consumer Internet Brand’s audience (&
similarly in gaining reach).
• Impact of this collaboration in improving “Identity” association is illustrated in the above image.
• While building such collaborative set-up, enough emphasis should be laid on “User Convenience & Motivation”
involved in the process of capturing consumer identity.
All Consumer Brand Visitors
Visitors Identified from Collaboration Between Brands
Visitors Identified/Registered by Consumer Brand
Y
X

6. For understanding metrics to track and
optimize your data management
Mcounts Consumer Solutions,
#22, BOB Colony, JP Nagar – 7th Phase,
Bangalore - 560078
For building collaborative data platforms to
maximize impact of your data
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