Gmid Associates provides analytics and data solutions to help clients make better business decisions. The document discusses Gmid's capabilities which include data mining, descriptive analytics, predictive analytics, and dashboard tools. It also outlines their service offerings tailored for industries like financial services, telecom, retail, and others. Case studies demonstrate how Gmid has helped clients with challenges like customer profiling, churn prediction, cross-sell strategies, and inventory management.

2. The Power of Analytics…
Clarity on constantly
evolving Business Dynamics
Data Disabled Decisions
Data backed decisions
are more contemplative
and thus wiser
Data Enabled Decisions
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3. Agenda
About the Company
Capabilities
 Data Mining & Cleansing
 Descriptive Analytics Solutions
 Predictive Analytics Solutions
 MIS / Executive Dashboard/ Simulation Tools
Service Offerings (by industry)
Case Studies
Clientele
Contact Details
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4. About the Company
Gmid Associates combines industry knowledge, advanced analytics, and technology to
deliver solutions that enable our clients take better business decisions. Using
techniques in statistics, econometrics, and operations research we help embed Data
Driven capabilities into the decision making processes of our customers.
Some of the benefits of associating with us are -
 In-depth domain expertise across industries
 Superior product and service quality
 Highly qualified and experienced team
 Significantly less turnaround time
 Price advantage over established players
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5. About the Company
Experienced Team – Delivery Across the
Professionals with a decade of
International Experience Globe – Analytics Partner
Industry Knowhow – Best Talent –
Graduates from IITs and IIMs
Complete Lifecycle of Industry
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6. Not just Support, WE are a part of YOU
• Prompt Client
Communication
• Round The clock
Delivery
• Strict Quality Control
Mechanisms
• Process-Oriented Work
Environment
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7. Gmid Associates has a global footprint
London
Germany
California
Delhi
Mumbai
Bangalore
Australia
HQ
Gmid Rep office
Tie ups/networks
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8. Capabilities
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9. Capabilities: Data Mining & Data Cleansing
Data Cleansing and Enrichment
• We help organizations transform and combine disparate data, remove inaccuracies,
standardize on common values, parse values and cleanse dirty data to create consistent,
reliable information
Contactability Improvement Tools
• Your customer contact numbers are buried in a dataset that has all sorts of text entries.
This makes contactability on those datasets very difficult
• We have tools that dig valid phone numbers from deep into the text data, intelligent
enough to complete incomplete numbers (i.e. adding STD codes)
• Tools can be customized to suit your business requirements
Data De-duplication Solutions
• We have proven tools and expertise to run customer de-duplication algorithms on data,
identifying unique customers/ households/ relationships and establishing mappings
amongst them
• This helps you understand your customer data, draw critical conclusions and make
meaningful business decisions
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10. Capabilities: Descriptive Analytics Solutions
Data Audit
• Our Data Audit service provides you with a comprehensive analysis of your database,
highlighting inaccuracies or incomplete data. It helps you understand the finer details of
the information available within your data.
• It saves on the operations time, reduces load and speeds up processes, and delivers rich
intelligence and control on your business
Historical Data Analyses
• We have the skill set and domain knowledge required to dive deep into your historical data
and come up with trends and patterns that empower you to run your business more
efficiently and proactively
• It provides you a single point of view into the diverse data through implementation of data
mining and data analytics techniques such as pattern identification, trend analysis,
segmentation, discriminate analysis etc.
Segmentation and Clustering solutions
• We use advanced statistical and econometric techniques and overlay them on your
business knowledge to segregate sets of customers that behave similarly. We help you
make business plans at segment level
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11. Capabilities: Predictive Analytics
Propensity Scorecards
A Scorecard is a statistical model developed using historical data to predict the propensity of
occurrence of a certain future ‘event’
Maximize the divergence between Use scores to calculate probability of
the distributions of good and bad Analyze consumer preferences and
behavior to study the efficiency of default, expected loss, unexpected
accounts loss etc to help perform effective
processes and strategies
portfolio management
Estimate the unknown population
characteristics based on sample Identify trends , sub-groups and do Develop score based strategies that
information customer profiling using multivariate are simple and result oriented
statistics
Forecasting Solutions
Gmid Associates supports companies across various industry verticals to better understand and
manage demand by providing world class forecasting and planning capabilities taking into account
industry specific challenges. its advanced collaboration functionality allows for coherent process to
obtain a single realistic view of demand.
Key Services: Demand forecasting, Inventory management, Optimal sales order recommendations
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12. Capabilities: MIS/ Dashboards/ Simulation Tools
We use advanced Analytical techniques to make sure that the
techniques which best captures the business problem is used. The
outcome algorithm is built into scenario analyzer tools.
Ability to make more informed decisions based on
collected business intelligence
 Measure efficiencies/inefficiencies Enables better decisions
 Ability to identify and correct negative trends making by building
 Ability to generate new business opportunities monitoring systems that are :
 Align strategies and organizational goals • Real time,
 Save time over running multiple reports • Correct, and
 Gain total visibility of all systems instantly • Efficient
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13. Services
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14. Solutions by Industry: Financial Services
Customer Relationship Collection /
Acquisition Management Retention
Inbound Marketing Cross-Sell/ Up-Sell Collections/ Recovery
 Lead generation and fulfillment tracking • Cross-sell Strategy Design (with product • Collections Propensity Scorecard
 Fulfillment Process Improvement sequencing) • Recovery Scorecard
 Campaign Design and Tracking • Multi Media Campaign Design • Target Planning
 Segmentation and Targeting • New/Inline Product Forecasts • Portfolio Value Assessment
 Sales Performance Management
 Incentive Plan Design and Implementation
Marketing Channel Analytics Lifetime Value Analytics Retention/ Revival
 Channel Effectiveness Optimization • Customer Segmentation • Retention Prediction Scorecard and
 Multi media Acquisition Campaign Design • Customer Satisfaction Analysis Segmentation
and Optimization • Customer reach-out Multi Media programs • Revival prediction scorecard and
Designs Segmentation
• Sales Forecasting Model • Capacity Planning
• Spend Analytics
Data Mining and Data Cleansing
Reporting, Dashboarding & Visualization
Model Development and Recalibration
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15. Solutions by Industry: Banking & Insurance
Identification
Authentication
Validation
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16. Solutions by Industry: Telecom
Application
Fraud/Bad
Debt Scorecard
Cross Sell/Up- Credit Risk
Sell Management
Pre-
Paid Campaign
Market
Basket Management
Analysis 1 2 3
Post-Paid
4 5 6
7 8 9
* 0 #
Customer Lifetime Value
Segmentation of customer
Churn
/Retention
Analysis
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17. Solutions by Industry: Retail & FMCG
Analytics in Retail
Descriptive Analysis Predictive Analysis
Sales Analysis Customer profiling
Category Trends Demand Forecasting
Brand Dynamics Lifetime Value Analysis
Out of Stock Analysis Churn Analysis
Promotional Effectiveness Market Basket Analysis
Benchmarking Analysis Response Modeling
* Targeting customers more effectively for campaigns
* Improving response time to market changes
* Increasing employee productivity, and
* Improving customer service at stores.
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18. Solutions by Industry: Market Research Analytics
Research Data Processing & Analytics Services
Data Processing is a systematic process that transfers raw data to intelligent data and requires
the application of an integrated process. Gmid can bring life to your data by transforming it
into meaningful insights that will drive positive and enduring results.
Key Services: Verbatim Coding, Survey Data Entry, Tabulations, Banners Creation, Charting
Statistical Data Analytics Solutions
From Standard Statistical tools to high end decision focused multivariate statistical techniques;
Gmid provides you a one stop solution for all your Data Analytics and decision support
requirements.
Key Services: Cross-tab, Banner tables, Clustering, Segmentation, Regression, Max Differential
Analysis, Key Driver Analysis etc.
Data Posting, Charting, Analytics & Reporting Solutions
We prepare customized presentations for our clients that drive the message across to the
listener. Our team goes beyond presenting chunks of data to ensuring it reflects the brand in a
positive manner to the end user. We love to keep presentations simple but direct.
Key Services: Presentation including quantitative and descriptive summaries, charts from
tabulated data, automated dashboards
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19. Solutions by Industry: Travel and Hospitality
Efficient Customer Acquisition
We offer help with inbound marketing services for businesses so they can get found on the internet through the
creation of a comprehensive inbound marketing strategy. Our services enable small businesses improve the return
on investment (ROI) for their marketing dollars.
Key Services: Online PPC campaign management, Social media optimization, Cross-sell models
Deeper Guest Knowledge through Effective Segmentation
Gmid Associates uses analytical techniques like Recency, Frequency, and Monetary Value (RFM) Analysis (using guest
history data), Basket Analysis are used as starting points to assess customer lifetime value and help estimate the
profitability and revenue potential of segments.
Cluster: Analyze: Profile: Size:
Segment by Identify Guest Define segments Estimate segment
Demographics, Segments who are based on ways size by revenue
Guest Behavior, similar useful for target potential, Cross
Occasions marketing sell other services
Maximize Revenue through Yield Management
Yield management maximizes profits from the sale of perishable assets such as hotel rooms or airline seats by
controlling price and inventory and differentiating product and service. Unique customer segments, based on
behavior, price sensitivity, usage pattern, etc are identified. Appropriate products are then created along with
targeted price and service levels.
Segment: Offer: Forecast: Plan:
Define Segments Create Seasonal Forecast demand Allocate capacity
based on pricing calendars based on trends, to various
behavior, usage, & targeted pricing seasonal patterns, segments to
price mkt. maximize revenue
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20. Solutions by Industry: e-Commerce
e-
Revenue Channel Strategic Planning
Maximization Management & Customer Service
New Customer Acquisition Marketing Channel Analytics Customer Service
 Lead generation and fulfillment tracking  Supply Vendors Selection and Management • Managing customer requests, building
 Fulfillment Process Improvement  Supply Chain effectiveness Improvement better processes for fulfillment requests
 Campaign Design and Tracking and Vendor Satisfaction Indexing • Identification of key pain points of
 Segmentation and Targeting  Channel Effectiveness Optimization customers
 Sales Performance Management  Multi media Acquisition Campaign Design • Early warning churn prediction model
and Optimization
 Incentive Plan Design and Implementation
Cross-Sell/ Up-Sell Product Planning Lifetime Value Analytics
• Cross-sell Strategy Design (with product • Demand, Supply, and Target Planning • Customer Segmentation
sequencing) • Product Value Assessment • Customer Satisfaction Analysis
• Multi Media Campaign Design • New Products Identification • Customer reach-out Multi Media programs
• New/Inline Product Forecasts • Capacity Planning Designs
• Sales Forecasting Model
• Spend Analytics
Data Mining and Data Cleansing
Reporting, Dashboarding & Visualization
Demand Forecasting and Inventory Planning
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21. Case Studies
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22. Case Studies: Predictive Analytics
Outline Project Description Benefits
‘Bad’ Application  A leading auto finance company from Texas wanted to devise effective  Early Write off losses
strategies to separate good applications from bad ones to improve the have gone down by 12%
Prediction system for portfolio quality and minimize future credit losses within 4 months of
US Auto Loan company
 We developed two predictive scorecards- write off prediction and early pay model implementation
off prediction. Since both of these were loss making scenarios for the
business, we clubbed them together and devised “high/ Medium/Low” risk
bands. Every application is given scores and risk segment and business
makes effective acquisition strategies
Monthly default  A 100 year old leading vehicle finance company from US with a sub prime  After implementing the
portfolio wanted to make scientific and optimal collection strategies. model, the monthly
prediction models
 We developed an early warning delinquency predictor scorecard on the default rates are down by
for active Auto Loan 16%
portfolio and implemented the same on the client’s system. The scorecard
portfolio runs on the last day of every month and gives scores to all the accounts
based on their propensity to default on the payments in the next month. It
also categories the accounts into risk segments, using which the company
can make effective, targeted collection strategies
 Cross-sell penetration
Cross-sell Strategies on  A global financial services firm needed to develop effective and easily increased from ~1% to
implementable cross-sell strategies on a diversified portfolio containing
a diversified financial ~4% on a base of
mutual funds, life insurance, general insurance and mortgage loans
portfolio 2,50,000 accounts in 8
 Developed multiple statistical models and used clustering techniques, months time after
overlaid with business rules to design efficient cross-sell strategies implementation
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23. Case Studies: Predictive Analytics
Outline Project Description Benefits
Sales Forecast Model  The client, a large textile manufacturer in UK, wanted to build a reliable  80% accurate forecast
for one of the fastest model that complements or takes over their in house traditional approach to figures within 3 months
forecasting primarily driven by gut instinct. of model deployment
growing Textile
Company of UK  Developed a multi variable time series forecasting model for all of the  Increased service level by
product categories. The model uncovered patterns caused by seasonal about 41%
variations, lead times, minimum quantities, re-order quantities,
extraordinary usage (special orders) etc.
Marketing-Sales  A global online retailer which did all their marketing through Facebook  The company was able
Linking Model for an wanted to link their Facebook Fan growth to their sales trends. They needed to make target based
this to understand how their marketing efforts translated into sales marketing plans and
Online Retailer
 Developed non-linear models predicting sales as a function of Fan growth hence manage their
marketing efforts in a
 Developed a tool which, on giving sales targets as input, would give Fan
better manner
growth needed in the coming weeks to achieve the targets
Inventory  A global retail company had problems in optimizing the inventory levels in  Reduced the storage
Management System the warehouses so as to not missing out on demand while avoiding cost by 30% while
cannibalization increasing the service
for a Leading Multi
 Prepared a smart order processing and inventory management system to levels by 15%
National Retail Player
identify alert stock levels, place and track orders automatically ensuring high
service level with low overall storage cost.
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24. Case Studies: Data Mining & Cleansing
Outline Project Description Benefits
Data Cleansing on a  Our client, a leading Insurer needed to increase phone number • As a result of improved
Life Insurance contactability on their database. The phone numbers were not in machine contactability, cross-sells
dialable format s hence dialer machines could not be used directly for went up by 11% in a
portfolio database
customer reach out/ cross-sell/ renewal campaigns. year’s time
 Developed an algorithm which picks correct phone numbers from text
strings and modifies them into machine dialable format (adds std code on
landlines, if required). Automated it in an excel tool to be used on
incremental data.
De-duplication of  A leading private sector Insurer was having troubles managing their data  The client was able to
Records on a Multi warehouse (DW) because there was no unique identifier at client level. Every know exactly how many
new acquisition was a new relationship at DW level. customers it had
Product Financial
Portfolio  Developed a de-dup algorithm by using matching algorithms like levenshtein  As a result of customer-to-
distance, soundex, metaphone etc. Created a new client level UID. account mapping, they
are able to make better
informed business plans
Intensity  A multinational bank’s cards collection business needed help to identify • The collections unit was
Optimization for a optimum reach out intensity/ channel at bucket and segment levels. able to reduce their
 Using statistical and econometrics techniques on historical data, we devised costs by 15% for the
Cards Collections
optimum channels and intensities at bucket and segment levels. same collection
Campaign revenues.
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25. Case Studies: MIS/ Dashboards
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26. Clientele
Our Partners
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27. Mudit Chandra
Sales and Marketing Head
Gmid Associates
Mobile Number
+91-98107-96148
Email
mudit.chandra@thegmid.com
Web
www.thegmid.com
Thank You
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