Predictive Churn Predictive Churn ModelModel

Segment 9Segment 9

20th Nov ‘ 2014

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Slide: 3

Content

Definition, Objective and Scope

Modeling Process ABT Creation Variable Selection Model Iterations

Final Model – Select Variables

Model Performance

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Churn Definition, Objective & Scope

Definition – A subscriber who moves from REC base to Non-REC base in a period of one month (Performance period)

Objective – To predict probability of moving from REC base to Non-REC base over the next 1 month for each of the subscriber

Scope – REC baseSegment 9: “FEATURE PHONE + VOICE+DATA(1 Mb+) + Single S ”AON >90 days

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# of Subscribers

Total Population 6,77,367

# of Churners 48,09

Churn Rate 1.%

Start Date End Date

M2 30-JULY-14 30-AUG-14

M1 31-AUG-14 30-SEP-14

Performance Period 01-OCT-14 30-OCT-14

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Modeling Process (1/4)

Multiple CMDM tables (IN Dump, Leg-wise, Usage, Recharge etc.) are referred and daily level data is extracted for the defined time period.

ABT is created at Subscriber level from the above extracted data ~300 variables are created

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ABT Creation Variable SelectionModel Iteration

RATIO/PERCENTAGE

TOTAL

MIN, MAX

COUNT

RANK / PERCENTILE

TEMPORAL FIELDS

BINNING

MEAN, MEDIAN, MODE

ABT VariablesRaw Variables

MOU

REVENUE

SMS

VAS

RECHARGE

DECREMENT

LEG-WISE USAGES

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Modeling Process (2/4)

The variables are screened through multiple techniques (Correlation, GINI, Variable Clustering, Chi-sq. etc.) to arrive at more significant and select list of variables

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ABT Creation Variable SelectionModel Iteration

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Modeling Process (3/4)

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30 to 40 iterations are performed , with key iteration mentioned above Through selection and rejection of variables, a manageable no of variables and

desired lift is achieved through these iteration. Reds mark the variables dropped in subsequent iterations . Highlighted the red oval shows the number of variables used in a particular iteration.

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ABT Creation Variable SelectionModel Iteration

Modeling Process (4/4)

At each stage of iteration variables are removed / added basis statistical significance of variable, multicollinearity, VIF and biz importance.

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ABT Creation Variable SelectionModel Iteration

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Featured Variables and Impact on Churn

Slide: 9Business Analytics – Corporate Marketing | Confidential

In order of impact on churn

Variables Description Impact on Churn

TOT_PRR_D123_W1 Avg Recharge Amount in Month 1 Inversely Proportionate

TOT_REC_CNT_M1 No of days Since last Recharge Inversely Proportionate

TOT_PRR_W2 Ration of PRR for Last 3 days and week 1 Inversely Proportionate

Days_Since_Last_Rech Total PRR incured in week 2 Directly Proportionate

AVG_REC_AMT_M1 Recharge count in Month 1 Inversely Proportionate

Model Performance

Slide: 10Business Analytics – Corporate Marketing | Confidential

Thank you

Business Analytics – Corporate Marketing | Business Analytics – Corporate Marketing | ConfidentialConfidential

For any query or concerns please contact: Ankur Shrivastava – ankur.shrivastava@tatatel.co.in or call +91-8655007666

List of Abbreviations frequently used

Business Analytics – Corporate Marketing | Confidential

Chi-square :A statistical test used for comparison of goodness of fit. In other words, the difference between observed and expected outcomeClustering :A group of elements shows similar characteristics put together giving a certain statistical inferenceCo-relation :A mutual linear relationship between any two elements without infer to causal impact.GINI Ordering/Index A statistical measurement of dispersion or inequality of populationGVC : Good value customer segment HVC : High value customer segmentLVC : Low value customer segmentMulticolinearity/VIF : A statistical event to measure the multiple relationship of predictor/independent variables and target variablePCM: Predictive Churn modelSegment -1: SmartPhone - V+D (300MB+)-SSegment -10: Data Phone - V+D (1MB+)-MSegment -11: Data Phone - V/D only-SSegment -12: Data Phone - V/D only-MSegment -13: Basic - V/D only-SSegment -14: Basic - V/D only-MSegment -2: SmartPhone - V+D (300MB+)-MSegment -3: SmartPhone - V+D (1MB+)-SSegment -4: SmartPhone - V+D (1MB+)-MSegment -5: SmartPhone - V/D only-SSegment -6: SmartPhone - V/D only-MSegment -7: Data Phone - V+D (300MB+)-SSegment -8: Data Phone - V+D (300MB+)-MSegment -9: Data Phone - V+D (1MB+)-SuHVC – Ultra high value customer segmentuLVC – ultra low value customer segment