Predicting Customer Long Term Value at Eni Belgium

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Slides of the presentation at SAS Forum Belux 2016, Brussels As today's energy market is strictly regulated but very competitive, customers will typically not remain equally valuable over time. To better understand this reality and get an accurate view on future customer value, Eni Gas & Power has built a Long Term Value model. In this presentation, we explain how Predictive Analytics were used to construct this model, share the insights gained through the process and show how the outcome helps Eni Gas & Power to better steer future strategies.

Business

www.eni.it
Predicting Customers' Long Term Value
Elke Coremans - Wouter Buckinx
eni Python Predictions

SAS Forum Belux 2016
2
Eni’s activities
 Active in 66 countries, more than 29 000 employees.
 As integrated energy company and reliable partner we offer our customers
across the world energy solutions.
 Eni is working to build a future where everyone can access energy
resources efficiently and sustainably
Eni worldwide

SAS Forum Belux 2016
3
POWER
What does Eni do in Belgium?
Eni in Belgium
 Active on the Belgian market since 2008.
 Active in all markets
(Power and gas)
and in all segments
(retail, sme and industry).
 In the top 3 of Belgian energy suppliers.
 Retail: >700 000 connections
B2B: >50.000 connections
GAS

SAS Forum Belux 2016
4
Every customer matters. Really?

Long Term Value
The net present value of the profits
linked to a specific customer
once the customer has been acquired,
after subtracting incremental costs associated
with marketing, selling, production and servicing
over a predefined period of time
Source: Database Marketing (2008), Blattberg, Kim & Neslin

SAS Forum Belux 2016
Benefits
Customer value
How much worth?
Acquisition spend
Most and less profitable
Marketing investments

SAS Forum Belux 2016
Benefits
Company value
Focus on long term profitability
Focus on customer relationship
Business plan

SAS Forum Belux 2016
Benefits
Impact
Compare strategies
What-if scenarios
Sensitivity analysis

SAS Forum Belux 2016
Benefits
Monitor
Set objectives
Analyze KPI’s
Traffic lights

SAS Forum Belux 2016
Components
Revenues Retention
Credit
Losses
Service
Costs
How long will
the customer
stay?
Will he
experience
payment
issues?
How much will
the customer
spend?
What are
the costs
to serve?

SAS Forum Belux 2016
Components
RevenuesRetention
Credit
Losses
Service
Costs

SAS Forum Belux 2016
Components
Expected
Duration
Credit Losses
Expected
Volume
Product
Margin
Activity
Costs
Invoicing
Costs
RevenuesRetention
Credit
Losses
Service
Costs
survival
segments
predictive
Model
individual
extrapol.
predictive
Model
Input Input

SAS Forum Belux 2016
Survival Segments
Components
Used to compute 2-year survival probabilities
Computed for different customer segments: product type, channel,...
0 1 2 3 4 5 6 7 8
100%
50%
0%
Lifetime
Survival
Proportion

SAS Forum Belux 2016
Accuracy
PredictedLTV
Real LTV
Real vs Predicted LTV
Does it work?
Perfect Prediction
Previous Estimation
Predicted LTV

SAS Forum Belux 2016
Usage
Revenues Retention
Credit
Losses
Service
Costs

SAS Forum Belux 2016
Usage
All
Household
Business
Existing
New
Existing
New
Electricity
Gas
Electricity
Gas
Electricity
Gas
Electricity
Gas
Product A
Product B
Product C
Product A
Product B
Product C
Product A
Product B
Product C
Product A
Product B
Product C
Product A
Product B
Product C
Product A
Product B
Product C
Product A
Product B
Product C
Product A
Product B
Product C
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..
Channel 1
Channel 2
Channel ..

SAS Forum Belux 2016
Usage
Monthly Dashboard
Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16
LTV evolution
Low Medium High
Segments evolution

www.eni.it
Thanks
Elke Coremans - Wouter Buckinx
eni Python Predictions

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Predicting Customer Long Term Value at Eni Belgium

1. www.eni.it Predicting Customers' Long Term Value Elke Coremans - Wouter Buckinx eni Python Predictions

2. SAS Forum Belux 2016 2 Eni’s activities  Active in 66 countries, more than 29 000 employees.  As integrated energy company and reliable partner we offer our customers across the world energy solutions.  Eni is working to build a future where everyone can access energy resources efficiently and sustainably Eni worldwide

3. SAS Forum Belux 2016 3 POWER What does Eni do in Belgium? Eni in Belgium  Active on the Belgian market since 2008.  Active in all markets (Power and gas) and in all segments (retail, sme and industry).  In the top 3 of Belgian energy suppliers.  Retail: >700 000 connections B2B: >50.000 connections GAS

4. SAS Forum Belux 2016 4 Every customer matters. Really?

5. Long Term Value The net present value of the profits linked to a specific customer once the customer has been acquired, after subtracting incremental costs associated with marketing, selling, production and servicing over a predefined period of time Source: Database Marketing (2008), Blattberg, Kim & Neslin

6. Long Term Value The net present value of the profits linked to a specific customer once the customer has been acquired, after subtracting incremental costs associated with marketing, selling, production and servicing over a predefined period of time Source: Database Marketing (2008), Blattberg, Kim & Neslin Estimation over a period of 2 years

7. SAS Forum Belux 2016 Benefits Customer value How much worth? Acquisition spend Most and less profitable Marketing investments

8. SAS Forum Belux 2016 Benefits Company value Focus on long term profitability Focus on customer relationship Business plan

9. SAS Forum Belux 2016 Benefits Impact Compare strategies What-if scenarios Sensitivity analysis

10. SAS Forum Belux 2016 Benefits Monitor Set objectives Analyze KPI’s Traffic lights

11. SAS Forum Belux 2016 Benefits

12. SAS Forum Belux 2016 Components

13. SAS Forum Belux 2016 Components Revenues Retention Credit Losses Service Costs How long will the customer stay? Will he experience payment issues? How much will the customer spend? What are the costs to serve?

14. SAS Forum Belux 2016 Components RevenuesRetention Credit Losses Service Costs

15. SAS Forum Belux 2016 Components Expected Duration Credit Losses Expected Volume Product Margin Activity Costs Invoicing Costs RevenuesRetention Credit Losses Service Costs survival segments predictive Model individual extrapol. predictive Model Input Input

16. Predictive models

17. SAS Forum Belux 2016 Survival Segments Components Used to compute 2-year survival probabilities Computed for different customer segments: product type, channel,... 0 1 2 3 4 5 6 7 8 100% 50% 0% Lifetime Survival Proportion

18. SAS Forum Belux 2016Accuracy

19. SAS Forum Belux 2016 Accuracy PredictedLTV Real LTV Real vs Predicted LTV Does it work? Perfect Prediction Previous Estimation Predicted LTV

20. SAS Forum Belux 2016 Usage

21. SAS Forum Belux 2016 Usage Revenues Retention Credit Losses Service Costs

22. SAS Forum Belux 2016 Usage All Household Business Existing New Existing New Electricity Gas Electricity Gas Electricity Gas Electricity Gas Product A Product B Product C Product A Product B Product C Product A Product B Product C Product A Product B Product C Product A Product B Product C Product A Product B Product C Product A Product B Product C Product A Product B Product C Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel .. Channel 1 Channel 2 Channel ..

23. SAS Forum Belux 2016 Usage Products

24. SAS Forum Belux 2016 Usage Revenues Retention Credit Losses Service Costs

25. SAS Forum Belux 2016 Usage Monthly Dashboard Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 LTV evolution Low Medium High Segments evolution

26. www.eni.it Thanks Elke Coremans - Wouter Buckinx eni Python Predictions

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