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Harnessing Consumer Data >> (Data Mining)U(Predictive Analytics) Consumer Data Gathering EngineData Mining+Predictive AnalyticsConsumer Reach-Out ApplicationWhen 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 cant 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 its success is critical to the over-all success of the approach.

BehavioralDataIntentDataPsychographicDataCampaignResponsesPurchaseHistoryDemographicData$$$$$$$

Dependencies for Harnessing Consumer Data Effectively Consumer Data Gathering EngineConsumer Reach-Out Application

(1/Identities)

Reach

FrequencyIdeally 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.

Need for Collaboration to Harness Consumer DataConsumer Internet Brands (Mobile & Web)Supply Side Platforms (Mobile & Web)0IdentityFrequency

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 Platforms impressions outnumbering a Consumer Brands page-views/sessions reflects in its 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.

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 Brands 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

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