Cartesian Consultingold.nasscom.in/sites/default/files/Cartesian_Corporate...Cartesian Consulting –An Overview What we do We help brands Industrialize their analytics efforts, solve

Copyright © 2016 Cartesian Consulting Pvt. Ltd.Copyright © 2015 Cartesian Consulting Pvt. Ltd.

Cartesian Consulting

June 2016

Copyright © 2016 Cartesian Consulting Pvt. Ltd.

Cartesian Consulting – An Overview

What we do

We help brands Industrialize their analytics efforts, solve complex business problems,

and create a culture that is data and decision sciences driven

The Impact we createOur efforts add 5-7% to the topline

Best service provider for Marketing Analytics – 2016 | Top Boutique analytics companies you wish you worked for - 2015 | Big Data Entrepreneur/ Founder of the Year – 2016 | Top 10 Influential Analytics Leaders - 2015

Founded in 2009, we are a global analytics services firm specializing in three areas:

Data Driven Customer Obsessed

We help organizations be data driven, and customer obsessed

Customer Analytics

Marketing Analytics

Business Analytics

We live by results: Lift, Repeat & Retention, Margin improvement, NPS Scores


Our services

Customer Analytics Marketing Analytics Business Analytics

• Customer One-View building & insight

• Predictive models, Segmentation, Profiling

• Customer Lifecycle management• Lift and ROI measurement

• Marketing Mix modeling & Spends optimization

• Multi touch attribution• Lead to conversion analysis

• Pricing and margin optimization

• Store/ channel analytics• HR analytics• Text mining

• New product/ store decision support

• Network planning & inventory tail management


Headquartered in Mumbai, India we have a presence in 5 locations globally

Our North America office in San Francisco was started in June 2016.

Catering to USA, Canada, Latin America.

3 Sales and Delivery offices in India – Mumbai

(HQ), Bangalore and Delhi.

Sales office in Singapore – catering to the ASEAN region. Clients currently in Singapore, Malaysia,

Indonesia, Thailand.


A Team of over 150 professionals

• A rapidly growing team of 150 professionals

• Offices in Mumbai, Bangalore, Gurgaon, Singapore, and San Francisco

• Expertise across industries and practices

• Very people oriented, amongst the lowest attrition in the Industry


45 Engagements in the last 12 months

Retail, Services & QSR FinancialOnline Others

We work with some of the largest and most prestigious domestic brands in the Indian marketInternational brands include HP, Facebook, Levi’s, Dominos, Dunkin, Marks& Spencer, Tommy Hilfiger, Benetton, LG , Unilever

We tend to work on long term engagements – some of our clients have been with us for over 6 yearsWe have a 95% client renewal rate, and excellent feedback on independent platforms such as Clutch

Client Feedback on


Our work modes

Ongoing Industrialized Deep Dive Advisory

• Retainer services, long term engagements

• Always-on solutions

• These range from owning the customer LTV, building optimization tools, lifecycle management rules engines, visualization tools, scorecards and more.

• Solve for a very specific business problem

• Deep expertise applied for a project

• The problems can range from building an open rate predictor for a Bank, or helping a University improve its student screening process, to helping retailer stock the right product by store.

• Long term strategy around Analytics usage

• CEO Setup advisory

• We assess the tech and skills ecosystem needed, plan the structure and investments, the business stewardship needed for an Analytics COE


Our solutions

CART-CLM™ CART-ORP™

CART-LTV™

A rules engine that adds intelligence to lifecycle management. Can run hundreds of trigger campaigns on millions of customer records.

Rules built using advanced predictive modelsMicro segmentation and customer genome mapping

Built in offer selection and optimizationBuilt in media/ timing optimization

Contact optimization rulesMultiple controls for impact measurement

Learning engine

Delivers 7-10% topline liftImproves customer KPIs – repeat, frequency, retention, winback

Accurately predicts Email open rates based on the Subject Line.

Accurately predicts future value and frequency of customers


Our capabilities

We manage high-intensity needs

160 Mn customers | Over 500 Mn monthly transaction records | 1000+ analytical requests handled monthly |

Working with online and IOT data

We constantly test and apply new methodologies

Regression | Clustering | Random Forests | Markov Chains | Genetic Algorithms | Pareto NBD | SVM | Decision Trees |

Collaborative Filtering

We manage multi-country and Enterprise-wide mandates

Working for a leading QSR brand across 5 countriesWorking for a technology brand for requirements across 11

countriesWorking across 8 brands of a conglomerate

We bring perspective from a depth of experience

We have worked with over 100 brands ranging from a stock exchange to a luxury hotel, a university, and an NGO


Case Studies

The CART-CLM Engine in QSR

Analytics COE setup advisory

Predictive models and text mining in

Insurance

Open Rate predictor in Banking

Mix Modeling and Attribution in Online

Lead Gen.

Predicting future high-value guests in

Hospitality

Improving sell-throughs and

markdown management in Retail

Helping pricing decisions to deliver a

8% margin lift


CART-CLM and the art of driving Frequency in Pizza Delivery

The Need:Drive frequency in a 30 Mn customer base through highly

targeted, automated campaigns

The Solution:CART-CLM, an Engine running the ruleset, using model scores, optimizing

offers, tracking journeys, self learning, integrating with CRM and messaging systems.

Not transacted for 20 days

Upgrade pizza size

Change of crust

20th transaction Milestone

Welcome to a new city

Non-adopter of product A

Anniversary of first order

Lapsed from App

…

Over 100 daily triggers

High Offer

Medium Offer

Low Offer

Offers Optimized

Lapser Track

Digital Track

New customer track

…

Multiple Tracks

Single view

Genome mapping

Paths and nudges

Contact optimization

Segment of One

Propensity to respond

Next best product

Next best offer

Models/ Recommenders

The Impact

Promo Only CRM Only CLM

X%

12X%

12X the response rate from CLM as against bulk Promo messaging

18% Frequency improvement amongst targeted customers

1

2

35%-7% topline contribution of Incremental sales generated by CLM


Going beyond Models to improve Persistency in Life Insurance

The Need:Improve Persistency amongst customers of one of Asia’s largest

private Insurance providers

The Solution:1) Modeling to establish current and future value 2) Segmentation and profiling for precision marketing 3) Text analysis of touchpoint data to

establish Premium at risk 4) Testing of outreach options

The Impact:

3% lift in Persistency | Paths established that drive upto 12% higher Persistency | 45% Premium at risk identified

Models Segments Text Mining Testing

Persistency models built & improved by addition of new variables, separate models for Future Potential

6 distinct customer types identified to communicate with in a relevant manner

Mining of touchpoint data at Surrender + extrapolation through look-alikes to establish premium at risk in the full base

Testing of paths-to-Persistency, different combinations of communication prior to due date


Mix Modeling to optimize marketing spends for Online Lead-Gen.

The Need:Establish the impact of spends on Facebook as a lead-

generation channel. Current last-touch attribution seen to be inadequate.

The Solution:1) Mix Modeling to establish the contribution of different media to the

leads 2) Markov chains to create better MTA rules

The Impact:

Established high ROI of Facebook as an influencer in the Lead-generation process, advanced attribution rules created (not heuristic based)

Mix Modeling Contribution, ROI and Optimization Conversion Paths and Attribution rules

Advanced Mix models built to establish the contribution by media and marketing spend

Channel-wise details of contribution and ROI established, Goal-seeks created for optimization

Markov chains used to improve attribution rules, using conversion path data


CART-ORP and the Open Rate problem

The Need:Improve open rates for the ‘000s of Emails being sent by one of Asia’s top private Banks – by only analyzing the Subject Line

The Solution:1) Subject lines converted to Features 2) Feature scoring 3) Modeling to

predict open rate 4) Simlator

The Impact:

95.6% Accuracy on holdout data | Knowledge of what words and phrases impact open rates

Subject line deconstruction Modeling Simulator

Deconstruction of subject lines to Features, analysis of impact of Features

Random forest, SVM Modeling methods used to build the predictive model

Online simulator deployed for ongoing use by the Bank team


Pricing analytics and Margin lift

The Need:Improve margins by 8-10%, for a QSR brand in Indonesia

The Solution:Pricing Analytics | Menu rationalization | Promo optimization

The Impact:

22% increase in prices | 17% reduction in COGS | 4.5% drop in weekly orders

Pricing Analytics Menu Rationalization Promo Optimization

Each menu item scored on 6 parameters indicating our ability to increase prices

Menu restructuring recommended basis the new prices, estimated impact of price change calculated

Change in structure to drop toxic Promos, targeted marketing to shore up volume loss


Managing in-season markdowns to improve retail margins

The Need:Improve sell-throughs by early interventions and in-season

markdowns for a global apparel brand

The Solution:Product & Store classification | Sell through prediction & tracking |

Intervention push & measurement

The Impact:

6% increase in sell through of Intervened products as compared to Non intervened products

Product & Store Classification Sell through prediction & analysis Intervention Push

Classification trees to classify of Products (Best sellers | Lost opportunities | Duds) and Stores (A | B | C)

Basis product attributes, week-on-week sell through curve predicted, tracking set up

Products identified every week for interventions – Staff incentive | Shop Window | Consolidation | ISMD


Predicting future-star guests for Hospitality

The Need:Identify guests with a potential to become MVG (Most valuable

guests) early for a Luxury hotel chain in India

The Solution:LTV measures | Propensity model builds | Nurturing programs

The Impact:

Increase in MVG base over time, improvement in y-o-y retention of 3%

LTV Measures Propensity Models Nurturing programs & Measurement

Models to identify future value of guests. LTV model to establish the value of a MVG vs. a first-time guest

Regression models to establish what markers esist in the first Stay that indicate future potential – Non Room revenue, Nationality, Payment Mode etc.

Campaigns targeted at cross sell of Leisure stays to first time business travelers, priority list for invites etc.

MVGs are 26X the valueX value on first stay


Analytics COE Advisory

The Need:Put in place a 3-year roadmap for analytics and decision

sciences adoption for a large conglomerate

The Solution:Current State and Readiness | COE setup plan | 3 year roadmap

The Impact:

Establishment of the 3 year roadmap, buy-in of all businesses + senior leadership

Current State and Readiness COE structure & ecosystem 3 year plan

Brands within the conglomerate evaluated on current evolution and readiness

Team, tools, governance, milestones and targets recommended

3 year evolution recommended with budgets

Copyright © 2016 Cartesian Consulting Pvt. Ltd.Copyright © 2015 Cartesian Consulting Pvt. Ltd.

Thank You

www.cartesianconsulting.comMumbai | Bangalore | Delhi | Singapore | San Francisco

http://www.cartesianconsulting.com/

Documents

Cartesian Consultingold.nasscom.in/sites/default/files/Cartesian_Corporate...Cartesian Consulting –An Overview What we do We help brands Industrialize their analytics efforts, solve