26 June 2018

Data Mining, New Business Tools

A Regional Sales Manager of a FMCG company was worried as their competitor was steadily gaining market share across a range of profitable segments. Despite counter Marketing efforts combined with online promotion and merchandising range sales kept declining.

When the RSM conveyed to his select few group of senior leaders to find the cause or factors i.e. Marketing Intelligence ,  dig into competitors practices, they found the challenge ran deeper than they imagined.

Description: Data1.jpeg 

Summary as follows:
1.   The competitor had made massive investments in it’s ability to collect , integrate and analyse data from each store.
2.   These data was used to run myriad real world experiments.
3.   It had also linked this information to supplier’s database.
4.   This helped them to adjust prices in real time to reorder hot selling items automatically.
5.   This analysis also helped to move slow movers from one  store to another .
6.   Continuous testing , bundling, synthesizing and making information available across the organization was carried out from store floor to CFO’s office.
7.   This made the competitor’s company far nimbler and fast decision  maker , helping it to gain over it’s competitors.

What is Data Mining :

Data Mining refers to the processes and techniques of extracting data patterns to transform into meaningful structure for taking rational business decisions.
It  is cumulation of :

    1. 1.   Machine Learning
    2. 2.   Statistics
    3. 3.   Database Systems.

    Data Mining Objective :  Data mining extracts and forms patterns of knowledge from large data so as to assist business decision.

    Data Mining consists of :

    • 1.   Information collection
    • 2.   Information processing
    • 3.   Artificial Intelligence
    • 4.   Machine Learning
    • 5.   Business Intelligence

    Data Mining is the analysis of “Knowledge Discovery in Database” or KDD.
    Benefits of Data Mining :

    1.   Incremental Revenues : Analyse  the type of products customers have purchased and capitalise on that insight to personalize expense, increase customer loyalty and boost customer lifetime value.

    2.   Improve Brand value : Get feedback on successes and failures of marketing efforts through data mining and take corrective actions.

    3.   Increased Reach : Make the companies outreach the relevant customers with timely and relevant data mining.

    4.   Explore new Markets : use other database to identify potential customers and conduct relevant out reach.

    5.   Trend Analysis : Compare current data to past information to find trends so as take rational business decision.


    RETAIL: 1. Retailers use much of data mining information to make decision on Price, promotions and timings:

    2.   After Data mining they also learn what products sell fast, and might need design / attribute changes.
    3.   Mined data on customer behaviour helps marketing teams appealed promotions to targeted customer groups.

    Ecommerce :


               Ecommerce companies make use of
      information gathered from online purchases and social media habits.
    2        .      Companies tap in to data mining to gain   deeper insights into their                customers.
    3.   Using this technology companies like  Amazon and eBay recommends products
     further and additional sale.

    4.   Policing and Security Agencies :

    1.   Police departments these days use data mining tools to decide where to focus resources.
    2.   The data patterns surges in specific crimes in certain areas are analysed and protective measures taken.
    3.   The data mining tools helps the policing into strategic and scientifically driven practices.
    4.   Local state and federal agencies use data mining in their tracking efforts.