Reena Tiwari

Sr. IT Manager

@retiwari

retiwari@cisco.com

March, 2015

How Cisco Improved Marketing Productivity Using Big Data

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Disclaimer

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BUSINESS TECHNOLOGY

Problem Statement

THE BUYING PROCESS HAS CHANGED…

BUT HAS MARKETING

ADAPTED?

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Access

MySql

Oracle

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Idea!!!

Reduce Complexity

Improve Operational Efficiency

Drive Productivity

Start with Technology

Define the Art of Possible

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• Live in Nov 2013 • Award @ Innovation Summit in Apr 2014 • Data Science Program

Opportunities

• Prospect / Customer (Individual) Journey

• New Incremental Business

• Digital Analytics

• Revenue Generation

• Marketing Activities to Sales

Marketing Big Data Platform

Integration and Governance

Data StorageAny type of data

Call CenterContact

Data

Machine Learning / Models• Auto Qualified Leads• Engagement Scores

• Buying Patterns• Marketing Contributed Revenue Forecasting• Social Behavior

Batch

Processing / SQLExploration /

Interactive AnalyticsFunctional

Apps

3d Party

Apps

Syste

m

Ma

na

ge

me

nt

Da

taM

an

ag

em

en

tUnderstanding Customers in a New Marketing World

(Led by Data)

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Horizon 1

Pilots, Infrastructure

Horizon 2

Transform

Horizon 3

Enhance

Identify & Move Business Capabilities to new Platform

Business Architecture• Governance Develop skills (IT + Biz)

internally• Change Management• Training & Adoption

• New Business Capabilities• Enhance Platform based

on feedback

• Enhance skills (IT + Biz)

Technology Architecture Develop yearly roadmap 1-2 Pilots Create Data Foundation

platform Get familiar with Data

technology

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Behavior Scoring Automated Qualified LeadsTracking Conversion

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What is Behavior Scoring?

level of interest in what products, services

likelihood to purchase, when they will purchase, and how much they will purchase relative to past purchase history

Virtual Profile… who your customer and prospects are.

(Partners, customers, segment, geography, industry, etc.)

1

2

3

A methodology for discovering a company or individual's……

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How ?

By understanding every click on the website

Converting a person’s activity into profiles, targeting:

Interests (Topic Interest Scores)

• Is a visitor interested in a particular Topic

Level of Buying Intent (Engagement Scores)

• Does the visitor exhibit behaviors that suggests they are in “buy mode?”

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Behavior Scoring Automated Qualified LeadsTracking Conversion

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Automated Qualified Leads (AQL)

• “No-Touch” leads. Big Data statistical models create leads instead of

humans.

• An Auto Qualified Lead is a prospect determined through advanced

predictive analytics to be someone in a buying cycle for Cisco technology.

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BIG DATA PLATFORM

(AQL Engine)Source Data

(Web traffic,

Marketing, sales,

etc)

AQL – HIGH LEVEL

AQL

Output

Preparatio

n

Response

Management

AQL

Feedback

AQL

Data

Preparation

AQL

Model

AQL feedback

AQL listRaw data

feed

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AQL Engine

AQL Data Preparation: • Collect data from different source

• Incomplete data is completed using missForest algorithm

AQL Model:• Use Propensity to Buy scores and Behavior scores to identify

contacts

• Use Gradient Boosting Machine (GBM) model to predict and flag a contact as “Likely to Buy”

AQL Output Preparation:• Format the data of “Likely to Buy” contact in a manner that can

be absorbed by CRM Platform

Ref: GBM Model

Ref: missForest Model

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Behavior Scoring Automated Qualified LeadsTracking Conversion

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Tracking Conversion

Track the activities of a “contact”

Map the activities to a Buyers Journey

Provide visibility to how many “contacts” are not moving ahead in the

Journey

Investigation on drop outs drives changes in Marketing

Thank you.

Reena Tiwari

@retiwari

retiwari@cisco.com