This document contains information and data that AAUM considers confidential. Any disclosure of Confidential Information to, or use of

it by any other party (i.e., a party other than Aaum), will be damaging to AAUM. Ownership of all Confidential Information, no matter in

what media it resides, remains with AAUM.

AAUM Confidential

AAUM Research and Analytics Private Limited 01 N, 1st floor IIT Madras Research Park, Kanagam road, Chennai – 600113

Tel +91 44 66469877 | Fax +91 44 66469877 Email: info@aaumanalytics.com | Web www.aaumanalytics.com

Affordable, customizable, scalable & insightful BI/advanced analytics solutions for your business

- 2 -

Extended arm of customers to identify right metrics to solve their pain areas

Services mature from basic reporting to advanced analytics initiatives

accomplished exclusively for retail/eTail domain

http://genisights.com/retail/

http://genisights.com/ecommerce/

- 3 -

Case illustration # 1 Exploring cross sell/ up sell opportunities through “Market

Basket Analysis”

- 4 -

Demo

Case illustration # 1 Exploring cross sell/ up sell opportunities through “Market

Basket Analysis”

- 5 -

Case illustration # 2 Enhanced loyalty through “Customer Segmentation”

- 6 -

Demo

Case illustration # 2 Enhanced loyalty through “Customer Segmentation”

- 7 -

Demo

Case illustration # 3 “Unstructured data analysis” on social media/Org data

- 8 -

Demo

Case illustration # 3 “Unstructured data analysis” on social media/Org data

- 9 -

Case illustration # 4 “Attrition Prediction” to prevent customers from churning

- 10 -

Demo

Case illustration # 4 “Attrition Prediction” to prevent customers from churning

- 11 -

Case illustration # 5 Effective production strategies through “Sales Forecasting”

- 12 -

Demo

Case illustration # 5 Effective production strategies through “Sales Forecasting”

- 13 -

Case illustration # 6 “Cohort analysis” to measure engagement effectiveness

- 14 -

Demo

Case illustration # 6 “Cohort analysis” to measure engagement effectiveness

- 15 -

Case illustration # 7 “loyalSIGHT” – A 360o view of my customer base and the

marketing strategies needed to revive them

- 16 -

Demo

Case illustration # 7 “loyalSIGHT” – A 360o view of my customer base and the

marketing strategies needed to revive them

- 17 -

Case illustration # 8 Dynamic Pricing” to maximize revenue from ticket sales

- 18 -

Problem Statement: • How can I analyze my web traffic data? • On what days and time slots do I experience

maximum traffic on my website?

Data required

Web traffic data on sites and campaigns

Case illustration # 9 ”Heat Maps” to visualize web traffic

- 19 -

Demo

Case illustration # 9 ”Heat Maps” to visualize web traffic

- 20 -

Data required

Clickstream data

Cookie data on attributes if captured

Problem Statement: • How can we identify which touch point is more

dearer to me in contributing to conversions? • How can I calculate my channel contributions to

conversions to channelize my yield effectively?

Case illustration #10 Better assignment of credit to marketing channels through

“Attribution Modelling”

- 21 -

Demo

Case illustration #10 Better assignment of credit to marketing channels through

“Attribution Modelling”

- 22 -

Problem Statement: • How do we decompose the sales to key drivers

like Price, Competition, Market channels such as TV, Press, Internet, etc to understand their combination to sales?

• How do we calculate the efficiency or ROI from these market channels?

Data required:

Past sales data

Past market channel data

Case illustration #11 “Market Mix Modelling” to track ROI from marketing

channels on sales

- 23 -

Sales = Base_sales x Incremental_Sales1 x

Incremental_Sales2 x…x Random_effect

Demo

Case illustration #11 “Market Mix Modelling” to track ROI from marketing

channels on sales

- 24 -

Data required

Web traffic data on sites and campaigns

Problem Statement: • Would marginal improvements/changes in my

marketing strategy or on campaigns/site layouts, images, colors, text, etc bring in significant improvements on my yield?

• How can I calculate my channel contributions to

conversions to channelize my yield effectively?

Case illustration #12 “AB Testing” to evaluate the most preferred campaigns

and sites

- 25 -

Demo

Case illustration #12 “AB Testing” to evaluate the most preferred campaigns

and sites

- 26 -

Problem Statement: • Are my marketing campaigns targeted to the

right customers? • Which of the customers would respond

positively to my market campaigns?

Data required:

Marketing channel transactions data

Demographic, Psychographic data

Case illustration #13 “Uplift modelling to predict the “persuadables” for your

marketing channels

- 27 -

The Persuadable: customers who only respond only because they were targeted

The Sure Things: customers who would have responded whether they were

targeted or not

The Lost Causes: customers who will not respond irrespective of whether or not

they are targeted

The Sleeping Dogs: customers who are less likely to respond because they were

targeted

Demo

Case illustration #13 “Uplift modelling to predict the “persuadables” for your

marketing channels

- 28 -

Problem Statement: • A media company wants to allocate campaign ads

so that the clicks are maximized. The company has different sites to which it can allocate impressions. How much of impressions should be distributed among these sites so that the clicks for the campaign is maximized?

Data required

Past transaction data

Case illustration #14 “Optimization” for efficient allocation of impressions across sites

- 29 -

Demo

Case illustration #14 “Optimization” for efficient allocation of impressions across sites

- 30 -

Problem Statement: • How well do my campaigns perform across sites

over time? • Can I compare the performance of my campaign

with that of the industry performance? • How do I evaluate if my campaigns appeal well to

my audience?

Data required

Past transaction data

Case illustration #15 “Campaign/Publisher scoring” to focus on campaigns

generating the most pipeline, revenue and return at a glance

- 31 -

Demo

Case illustration #15 “Campaign/Publisher scoring” to focus on campaigns

generating the most pipeline, revenue and return at a glance

- 32 -

1 Follow up discussions

2 Identifying requirements

3 Business collaborations

- 33 -

geniSIGHTS

Scalable big data advanced analytics solution INDUSTRIES •Retail •Travel •Finance •Insurance •Ecommerce •Telecom •HR •Health care • FMCGs •Entertainment LINES OF BUSINESS •Analytics consulting •Analytics Research HIGHLIGHTS Predictive analytics Big data platform Cloud-based BI/Reporting

Live link • www.genisights.com/

Contact

Request for demo specific to your business

Mail info@aaumanalytics.com

Call 8754577385/6/7/8/9

www.aaumanalytics.com

rapid data mining

& advanced analytics

• geniSIGHTS is very affordable and customizable platform that helps the business scale analytics as per their requirements.

• Precanned advanced analytics solutions that fit common business needs

• Provisions to build and integrate specific analytical solution for your firm

• geniSIGHTS is offered in three modes • Reporting – basic customer needs like

reporting • Analytics – intermediate requirements

like reporting, data analysis • Analytics + – advanced analytics like

prediction, big data analytics, etc

• Can be quickly deployed and scaled in premise and (or) cloud

geniSIGHTS – big data advanced analytics platform by Aaum

COMPANY Founded by IIT Madras alumnus brings in extensive global business experience working with Fortune 100 companies in North America & Asia Pacific. Established at IIT Madras Research Park with a focus on researching and devising sophisticated analytical techniques to solve pressing business needs of corporations ranging from travel & logistics, finance, insurance, hr, health care, entertainment, FMCGs, retail, telecom.

improved business

performance

lowers costs for businesses