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Campaign Effectiveness: Target Group - Control Group (TG - CG) Match Panel

IP.com Disclosure Number: IPCOM000244733D
Publication Date: 2016-Jan-06
Document File: 9 page(s) / 209K

Publishing Venue

The IP.com Prior Art Database

Abstract

This articles teaches to provide an effective way to bifurcate campaign / segment base into target group (TG) and control group (CG) base using an statistical stratified sampling method. TG - CG bifurcation of campaign / segment base is an method to measure the campaign effectiveness in which campaign system communicate the offer to TG base only and after campaign execution system measure the effectiveness by comparing the revenue / usage behavior of TG & CG base. Today market conditions are very dynamic in nature and to maintain the continuous revenue growth and customer satisfaction an intelligent campaign system which allow micro segment level personalized campaigning would require and the effectiveness of each of these campaigns being run needs to be understood so that the campaigns resulting in higher ROI should be increased or repeated where as those for which the ROI is less should be discontinued. Target – Control group (TG - CG) selection is one of the important parameter of any campaign system where control group base represent the behavior of target base. If the base of TG - CG group are not identical in behavior then ROI results would leads to an incorrect output. So the key to measure the effectiveness of campaigns is proper control group selection from campaign. Advantage is that the implementation & integration of any analytical tool with existing campaign system would not suffice the result in terms of campaign performance & cost. And getting output on run time of every campaign would also a challenge with analytical model implementation.

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Campaign Effectiveness: Target Group - Control Group (TG - CG) Match Panel

Problem Area:

     Campaign TG - CG are not comparable as no stratification / match panel mechanism for campaign CG selection
Generally all campaign systems provide TG CG functionality for base bifurcation using general base selection method but this approach would not bifurcate the base into identical target & control groups. Idea to select proper control group is to apply an stratified random sample selection & match panel method in an automated way which bifurcate the campaign eligible base into target & control group on the run time of campaign and also checks whether the bifurcated base qualify the TG CG criteria and

measuring of ROI results of those campaigns would suffice business objective or not.

Solution Summary:

As described the disclosed embodiment relates to the method of TG CG bifurcation of campaign base at run time of campaign execution. This article teaches to provide accurate information to management to decide their strategy about campaign execution whether to continue a particular set of campaign or to terminate the campaign execution as per the ROI results of campaigns. Thus the overall objective is to improve the effectiveness of campaigns and provide meaning full correct information to management to decide the strategy around promotional campaigning.

Overall solution would got implemented in three steps:


1. MCG Selection


2. TG CG calculation for every communication on run time of camapign.

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3. Offline campaign tagging

MCG Selection:

MCG selection is the first step of this TG CG bifurcation process. MCG (Monthly control group) denotes a set of subscribers which are used by campaign system to identify the campaign level control group. And after campaign completion this base will used to measure the effectiveness of campaign system against the rest of customer base.

Below is the list of steps needs to perform to calculate the MCG base. (Using telecom key performance indicators)

1. Bucketing/tagging of subscribers: Subscriber level tagging would be require base on below KPIs (Telecom KPIs) and their all permutation / combinations (Any set of key performance KPIs can be used for this as per industry standard).


a. AON: 0 - 90, 90 - 180, 180 - 360, 360 - 720, >720

b. ARPU: Average ARPU of last three months with

300 bands


c. Data Usage: Monthly User, Sachet User, VBC User, Accidental User, Rest


d. Fav Leg: ROAMING, STD, A2A, A2M, BALANCED

e. Purchase Affinity: Purchase Affinity 1, Purchase Affinity 2, Purchase Affinity 3


f. Data Arpu: 0 - 10, 10- 70, 70 - 160, 160 - 240, >240

2. M1 Month MCG Selection: Exclude DND from overall base and select 0.7% stratified random sample of each bucket and use them as MCG for campaigns


3. M2 Month MCG Selection:


a. Tagging / Bucketing of complete base as per M2 data


b. Redistribute M1 MCG data as per new M2 tagging.

c. Identify the deficit / shortfall in each bucket to make it 1.4 % (0.7 * 2). Defi...