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Author's profile photo Former Member

Data Mining and changing Marketing strategies:

Data Mining and changing Marketing strategies:

Once during my onsite assignment on a project for a big telecom giant in USA, I got the Opportunity to interact with one of its executive director.  He was using an executive dashboard with some very nice looking charts. I discussed with him about the dashboard and the piece of information which will be generated as our project’s goal. He informed me about the few sets of number and asked me to find out the way to put out a pattern which could help his Business in making an informed decision.

It’s very common now to hear about the KPIs (Key performance indicatrs), Importance of Metrics, their measurements etc. People normally overuse these terms for Business intelligence.   This is so much important to businesses as they can’t run without the future forecasts and these measurements.Someone has summarized the business philosophy:

  • If you can’t measure something, you really don’t know much about it.
  • If you don’t know much about it, you can’t control it.
  • If you can’t control it, you are at the mercy of chance.

This sums up the importance of data mining, and how measured data  translates into information, which finally outcomes the knowledge. This knowledge is what is used to run any business.

Over the last decade the technology has played the major role in defining the Marketing strategies. For example In one of the SAP CRM Service marketing assignment at a Big Auto Giant, we have derived the Target group or audience for e-campaign using their historical transactions The forecast or prediction that these customers would need the specific service was purely based on the data collected from their last transactions. This is the case of linear marketing or as per the best practices.

With changing times the customer is more informed with multi channels availability for information and collaborations on social sites. The marketing strategy for businesses are required to embrace these changes and have to now work in the proactive mode rather that reactive, as based on their historical transactions.

Now we have to work with customer intent during their browsing on our retail websites or visiting our store or querying at the Call Center. Requirement is to drive instant insight across lines of business, connect with business and social networks, and plug into the Internet of Things in real time?

There are many digital real time solutions available in market with the newer technologies. It’s not only the requirement but mandatory reflux to change the marketing strategies. The information derived needs to be implemented in marketing real-time (at the moment) and this information of customer intent, could change the buying decisions.

Our marketing strategies need to be enabled with these newer technologies which can derive Information in real time. SAP has enabled the SAP C4C solution and HANA platform as the new generation product which market is embracing. SAP Hybris provides us the e-marketing enablement. It also has the advance audience targeting and detection which could realize these real time marketing scenarios.

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      Author's profile photo Former Member
      Former Member

      I agree with you, that Data Mining (DM) will change the marketing and further more the business. With DM you can to predict the future based on previous patterns. As well it is possible to take influence on the future, if you are able to derive the right actions from the past patterns.

      Author's profile photo Niels Weigel
      Niels Weigel

      I fully agree, that the Data Mining technologies are key for better understanding of all of the available data and to identify and find valuable patterns out of the data for right decisions or predictions.

      However the thing that is still underestimated is the fact that the Data Mining technologies rely on the completeness and correctness of the data itself.

      While in some projects we have seen Data Mining algorithms used to increase the data quality of Master Data ("if 99,5% of the apartments in the same street have a specific electricity supply, shouldn't the other 0,5% have the same value in that column?"), we also have to agree on the fact that Data Mining projects are likely to fail, when they are running on incomplete or wrong data.

      For that reason, Data Quality Management should be an essential part for any Data Mining activity.