Marketing Analytics with SQL Server

Copyright (c) 2007, Responsys, Inc.

Speaker: Sandeep Giri

Presentation forSan Francisco SQL Server User Group

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Agenda

� Introductions

� Part One: Marketing Analytics Framework

4Problem Statement

4Solution Framework

� Break

� Part Two: SQL Server & Analysis Services Deep Dive

4Marketing Data Mart Schema

4Marketing Cubes

4 Interactive Analysis

� Summary/Q&A

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Speaker & Company Bio

� Sandeep Giri

• Senior Director, Responsys, Inc..

• 15 years in software product development

• Focus:

4Marketing databases

4Business intelligence

� Responsys, Inc. recently acquired Loyalty Matrix, Inc.

• Recently acquired San Francisco based; founded in 2001

• On-demand marketing analytics to optimize direct marketing

• Clients include Apple, 24 Hour Fitness, Chicago Sun-Times

• Sponsors openi.org – : open source BI app

• http://www.responsys.com


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Part One

Marketing Analytics Framework

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Direct Marketing: An industry that does cartwheels on

“achieving” 99% failure

� “How do I know which customers and prospects are most likely to respond to my marketing programs?“

� “Who are my most valuable customers?”

� “How much should I spend on marketing in each segment?”

� “I’d like to know in advance exactly which customers I’m at risk of losing so I can at least do something about it in time”

Common questions NOT being answered effectively


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Black Box of Marketing:

Identify Optimal Segments & Tactics

Identify most relevant segments…

… and the most optimal

tactics for each segment

Black Box

of

Marketing

AnalyticsCampaign

& Response

3rd Party

Appends

Behavioral

(Usage,

Txn’s)

Customer/

Prospect

List

Leverage data

Segment A Segment B Segment C

Program

4

Program

1

Program

2Program

3

Program

5


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Build

Marketing

Data Mart

Response

LTV

Retention

Find

Predictive

Triggers

Define

Lists

Analyze Past

Campaigns

Tactical

Segments

Contact

Strategy

Test

Plans

Test

Execute

Learn

Segments

Tactics

Phase I.

WHAT is going on?

Phase II.

WHY is this occurring?

Phase III.

HOW do you improve?

Define

KPI’s

What Happens Inside the Black Box?

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Segments: What Separates the Best from Worst?

� Before you segment

• What you are segmenting for?

• Identify events you want to control: response, attrition

� Define Key Performance Indicators (KPI’s)

• Response: response rate, volume

• Value: annual sales, LTV, profit

• Propensity:

4To attrite

4To purchase (up-sell/cross-sell)

� Find predictive triggers for each KPI

• Consolidate all data attributes related to the event/customer

• Find strongest predictors of the event (predictive analytics)

• Define segments based on the strongest predictors

Customers

& Prospects

Segment A Segment B Segment C


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Example: Segmentation Candidate Attributes


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Example: Model Identifying Strongest Predictors

Among the Candidates


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Tactics: What Works the Best for Each Segment?

� Right offer to the right person at the

right time with the right media

• Segmentation answers “who” (person)

• Next up is “how” (offer, time, media, etc.)

� “History repeats itself, it is a good thing”

• Consolidate past campaign data

• Overlay segment definitions

• Apply predictive analytics to

identify optimal mixes of tactics

• Create tactical segments

� Contact Strategy & Test Plan based on tactical segments

Media

Offer

Creative

FrequencyList

Marketing

Programs

Program

4

Program

1

Program

2Program

3

Program

5


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Example: Response Rates on Multiple Contacts for

Different Tactical Segments …


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… Results into Executable Direct Marketing Plan

Former Weekend

(Segment A3)

Former Weekday

(Segment A7)

Former Weekend

(Segment B3)

Former Weekday

(Segment B7)

Former Weekend

(Segment C3)

Former Weekday

(Segment C7)

Former Weekend

(Segment D3)

Former Weekday

(Segment D7)

Month 1 Weekly 3D WB1 Weekly 7D WB1 Weekly 3D WB1 Weekly 7D WB1 Weekly 3D WB1 Weekly 7D WB1 Weekly 3D WB1 Weekly 7D WB1

Month 2

Month 3 Weekly 3D WB2 Weekly 3D WB2 Weekly 3D WB2 Weekly 3D WB2 Weekly 3D WB2 Weekly 3D WB2

Month 4

Month 5 Weekly 3D Weekly 7D Weekly 3D Weekly 7D Weekly 3D Weekly 7D

Month 6 Annual 3D Annual 7D Annual 3D Annual 7D Annual 3D Annual 7D

Month 7 Weekly 3D Weekly 3D Weekly 3D Weekly 3D Weekly 3D Weekly 3D

Month 8 Annual 3D Annual 3D Annual 3D Annual 3D Annual 3D Annual 3D

Month 9 Annual + 3D Annual + 7D Annual + 3D Annual + 7D Annual + 3D Annual + 7D

Month 10 Weekly 3D Weekly 7D Weekly 3D Weekly 7D

Month 11 Annual 3D Annual 7D Annual 3D Annual 7D

Month 12 Annual + 3D Annual + 3D Annual + 3D Annual + 3D

Ongoing

Rule

Ongoing 3 Month

Cycle as in Weeks 7-

9 and 10-12

Ongoing 6 Month cycle

as in Weeks 7-12

To segment 5 after

month 12

To segment 5 after

month 12

To Segment 5 After

Month 9

To Segment 5 After

Month 9

To segment 5 After

month 1

To segment 5 After

month 1

Segment A Segment B Segment C Segment D


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Test-Learn-Execute-Repeat

� How do you determine the effectiveness of your marketing analytics?

� Test

• Create test plans for each recommendation

• Models available to calculate sizes for test and control groups

� Learn

• Actual lift versus predicted lift

• Champion models

� Execute, and test again!

Test

Execute

Learn


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Break

Warriors up by 10

3:26 to go in 2nd

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Part Two

SQL Server & Analysis Services Deep Dive

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Design and Build

� Marketing Data Mart

• ETL: Extract, Transform, and Load

• Star Schema (versus Snowflake): Denormalization

• Facts = events

• Dimensions = slicer attributes

� OLAP

• Cubes – Facts, Dimensions, and Measures

• Careful of the joins

� Visualization: Reporting Services, open source options such as OpenI

� Walkthrough


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Summary

� Marketing Analytics = Segmentation & tactical optimization based on marketing data (customer/prospects, commerce, campaign)

� Microsoft SQL Server and Analysis Services provide:

• ETL: DTS, SSIS

• Marketing data mart: star schema in SQL database

• OLAP: Analysis Services cubes organized by marketing facts and dimensions (Campaign, Sales, etc.)

� As always, setting analytics objectives as important (if not more) as designing/building the solution


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Questions/Comments?

� Now would be the time

� Feel free to email me: [email protected]

� This presentation will be downloadable at baadd.org

� This conversation will continue at

http://sandeep-giri.blogspot.com


Marketing Analytics with SQL Server

Technology

Transcript of Marketing Analytics with SQL Server