Business of Propensity Models

7/28/2019 Business of Propensity Models

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Copyright 2008 Cartesian Consulting 1

Smart-Calling

Using propensity modeling to boosttelesales response rates


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Situation

If you are sourcing cold lists and undertakingmassive telecalling activity to generate leadsand sales, this case is for you

Were going to look at how one can usestatistical models to boost response rates by afactor of 3-4, with a corresponding bottomlineimpact


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The Hard sell

Before:

You have 100 seatscalling 100,000 prospectsfor 500 successes

After:

You have 30 seats call30,000 prospects for 450successes


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Step 1: Sample

When you go list-shopping,dont buy it all, but take asample

If you havent done anymodeling in the past, take arandom sample

If you KNOW what profiles

give you better response thenapply those filters Try keeping the sample large

enough to capture 50+successes in it, as that will be

the profile that is modeled Run your telesales exerciseon this sample, capturing win-loss data

Sample

Model

Score/ Profile


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Step 2: Model - a

Build a Logistic Regression modelon the sample dataset to model for

Wins (Win = 1, Loss = 0) The target variable is theDichtomous Success variable

The Explanatory variables includeall the details you can on theprofile of the prospect city, age,gender, income and lifestyleindicators etc., the source of theprospect record , the day andtime of the call, the agent whomade the call, the script that wasused (if you are testing multiple),

the offer made If youre getting into responsemodeling, its a good time to alsoget into testing offers and callscripts!

Sample

Model

Score/ Profile


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Step 2: Model - b

The model is built on a trainingdataset which is your sampledata

You could, if you have thedata, hold out a Test dataset tocheck the robustness of yourmodel

Your Model statistics tell you ifyou have insufficient data, orinsufficient variables

Look at both Lift (explanatorypower) and Robustness(predictive power). It is VERYimportant that the model canbe applied to new datasetswith good confidence ofsuccess!

Sample

Model

Score/ Profile


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Step 2: Model - c

The Gain and Lift curves showyou how useful your model isto you from a businessperspective

They tell you: How many ofyour successes are you likelyto capture targeting prospectsbased on the Model scores

Eg. You can capture 80% ofyour good prospects within the

top 20% (by propensity score)of your dataset

Sample

Model

Score/ Profile

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Random Validation

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Random Validation


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Step 3: Score

Once your model has beenbuilt, score your freshdatabase with propensityscores

Now target the top prospectsby probability score for betterresponse rates

Use model outcomes to mapprospects to telesales agents,time slots, scripts and offers in

order to maximize on theresponses

Sample

Model

Score/ Profile


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Wheres the money?

By taking a random sample, perhaps you get a

1% response to your telesales By going to a Depth-of-File of 25% into you

modeled database, you wean out the 25%

good prospects with a high success probability You could get practically all (80%+) the

respondents by targeting 25% of the base, at 3 -

4 times the success of a random selection


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The ROI in it all

The ROI is hence in: Fewer calls to be made Fewer agents needed Better list sourcing/ rentals

Better control over the quality of the process More ability to test and make offers

Importantly, better insight into what works


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Thank You!

http://www.cartesianconsulting.com

Documents

Business of Propensity Models