automotive after sales firm
DESCRIPTION
Presentation for Automotive after sales firmTRANSCRIPT
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: [email protected] | Web www.aaumanalytics.com
Analytics
for
Automotive “after sales”
Jan, 2014
- 2 -
Corporate profile
Founded by IIT Madras alumnus having extensive global business experience with Fortune 100
companies in United States and India having three lines of business
Prof Prakash Sai
Dr. Prakash Sai is professor at the Department of Management Studies, Indian Institute of Technology Madras. He has wealth of international consulting experience in Strategy Formulation
Puneet Gupta
Puneet spearheads the IFMR Mezzanine Finance (Mezz Co.), is strengthening the delivery of financial services to rural households and urban poor by making investments in local financial institutions.
Padma Shri Dr. Ashok Jhunjhunwala
Dr. Ashok Jhunjhunwala is Professor at the Department of Electrical Engineering, Indian Institute of Technology Madras India. He holds a B.Tech degree from IIT, Kanpur, and M.S. and Ph.D degrees from the University of Maine, USA.
Analytics
• Appropriate statistical models
through which clients can measure
and grow their business.
Competitive Intelligence
• Actionable insights to clients for
their business excellence
Livelihood
•Services ranging from promotion of
livelihoods, implementation services,
livelihood & feasibility studies.
Key Focus Areas in Advanced analytics and Predictive analytics
Product – geniSIGHTS (Analytics/BI), Ordo-ab-Chao (Social Media)
More than 25 consulting assignments for Businesses & Govt orgs
Partnership – Actuate, IIT Madras, TIE and 3 strategic partnerships
Dedicated corporate office at IIT Madras Research park since 2009
Aaum’s office, IIT Madras Research Park
- 3 -
Competencies in
Advanced analytics
Build appropriate statistical models through
which clients can measure and grow their
business.
Expertise in
• Digital Media
• Finance/Insurance
• Travel & Logistics
• Retail
• Entertainment
• Human Capital
• Government organizations
• Research & training
Competitive
assessment
Competitive intelligence
Provide actionable insights to clients for
their business excellence.
Expertise in
• Business Entry
• Business Expansion
• Market research
Livelihood
Perform livelihood services ranging from
promotion of livelihoods, implementation
services, livelihood and feasibility studies.
Expertise in
• Government organizations
• Non Government organizations
• Corporate with livelihood focus
• Research
- 4 -
Human
Capital
Lifestyle
Retail
Travel/
Logistics
Insurance
Finance
Digital Media
• Strategic partnership with a major Employee Life-cycle
Management firm to provide actionable insights to their
clients
• Analytics support for a major Television network
• Recommendation Engine for Matrimonial company
• Market Basket Analysis & Loyalty Management – Pilot
case proposed to a major retail player
• Catchment prediction - quantitative model that helps
retailers to identify the vantage site.
• Fare analysis, assigning credit limits, Customer scoring, trend analysis,
etc for largest integrated travel & travel related firm
• Agents analytics, customer engagement, churn analysis, customer
acquisition, dynamic pricing, route optimization for major Ticket booking
company
• Lodging analytics for leading global lodging solutions company
• Predicting Ins claims & forecasting revenues in
healthcare industry for a US based vendor
• Household wealth at Risk deployment for a major
financial institute
• BI & analytical capability for major fin institution.
• Credit scoring to grade & monitor the performance of
SHGs – A product in making
• Geographic Dispersion of Business Risks for a financial
research institute
• Mining sentiments from social media – Movie analysis for
a major Television network
• Campaign and Publisher scoring for a major US based
digital media & content platform firm
Training
Research
Government
Organization
Product
Reports
Cloud
Big data
• Analytics for Business sucess & excellence
• Big data workshops/trainings
• Domain specific geniSIGHTS – version 2
• Retail | Travel | Finance | Digital Media
• Big data analytics and emerging technologies
• Periodic assessment of National Rural Employment
Guarantee Act (NREGA) in partnership with IITM’s
RTBI, as part of Ministry’s network | Poverty indicators
• Election Analytics
• geniSIGHTS - Advanced analytics/BI product that is
Customizable, extensible in cloud and big data
environment,
• Ordo-ab-Chao - State-of-the-art social media analytical
tool to predict the Business sentiments
• Reports in the form of intelligent dashboards
• Business reports in the format you like - doc, ppt, excel,
html, pdf, etc
• Partnership with Actuate for world class reports
• BI dashboard/analytics environment specific to clients
on an EC2 instance hosted at AWS.
• Provision to switch on/off the instance at the click of a
button to save the running costs.
• Hadoop – HDFS, Mapreduce, Hive, Pig, Hbase,
Cloudera
• Efficient ways to handle big data using state-of-art
memory mapping techniques and parallelization
techniques
Our past analytical assignments<Livelihood and Competitive intelligence initiatives not discussed here>
- 5 -
Relevant Solutions
for
Automotive After Sales Market
Analytical Advantage Using Mathematical modeling
- 6 -
AAUM’s capability in analytics stems from expertise to extract insights from data sources with the
ability to develop advanced mathematical models aided by experience in using statistical tools
Data sources
Business
Rules
formulation
Analytical
model development
Analytical Advantage Using Mathematical modeling
Secondary
research
Client Primary
research Census
Research
firms
Statistical Tools
R (Statistical
System)
WEKA (Machine
learning software)
SPSS (Multivariate
Statistical Analysis)
SAS (Data mining,
Statistical, and
Econometric
modeling)
Analytical Advantage
Profiling &
Segmentation
Product
/Process
performance
Product
/process
innovation
Valuation,
Loyalty & life
time
Market Intelligence | Finance | Retail | Telecom | Supply Chain | Consulting
- 7 -
Relevant solutions for Automotive after sales market include
Customer Acquisitions
Customer Segmentation & Loyalty
Customer Satisfaction Index
Performance Analytics
Churn Analytics Campaign Analytics
Forecasting & Inventory Management
Margin Analysis Workforce Analytics
Complaints Analytics
Dynamic Pricing Unstructured Data analysis
- 8 -
Customer Acquisitions
Customer Segmentation & Loyalty
Customer Satisfaction Index
Performance Analytics
Churn Analytics Campaign Analytics
Forecasting & Inventory Management
Margin Analysis Workshop Analytics
Complaints Analytics
Cross selling / Up selling Unstructured Data analysis
Analytical integration will yield significant results!
Relevant solutions for Automotive after sales market include
- 9 -
Customer Acquisitions
Determining the existing customer
acquisition rate
Identifying the qualified leads in the sales
funnel through various techniques such as
AB testing, propensity and uplift modelling
Survey data
- 10 -
Customer Segmentation leading to Loyalty
Customer Segmentation for Budget
Conscious Buyers and Premium Buyers
Customer segmentation using decision tree
Marketing Response Analysis with Gains &
Profit Charts
Customized Offerings to customers from
their needs
Identifying and rewarding long term
customers with special offers
Past business history, Customers' past business track records | Psychographic segmentation variables | Demographic variables
- 11 -
Customer Satisfaction Index
Develop Customer Satisfaction Scores from real time data instead of the
current “one time” approach
Index based on few key questions that could be asked to every customer
who comes in for servicing like:
Was the sales man receptive?
Are you satisfied with the service?
Have we been successful in meeting all your requirements?
How do you rate the service on an overall level?
How do you rate our service compared to other businesses in this industry?
Integrated findings of CSI with RFM, Loyalty, Demographics, etc
Survey data | Transaction data | Customer Profile information
- 12 -
Vehicle Specific
• New car/Pre-owned car
• Engine capacity
• Purchase date
• Fuel type
• (Petrol/Diesel/LPG)
• Kms driven
• Mileage
Service Expectation
• Service initiation attributes • center location, work force etc.
• Service Advisor • courtesy, promptness etc.
• Service Quality • parts availability, use of
certified products etc.
• Vehicle Pickup & Delivery • on time delivery, competitive
• price, vehicle care suggestions
Overall Satisfaction
• Rate the satisfaction level
• Recommend to
friends/relatives
• Come back for service
• Weight based rating
Customer Satisfaction Index (cont ...)
- 13 -
Net Promoter Score (NPS) measures the loyalty that
exists between a service provider and a consumer.
“How likely are you to recommend our service/product
to your friends, relatives and colleagues?”
Net Promoter Score is used to evaluate customer
loyalty to a brand or company
The ability to measure customer loyalty is a more
effective methodology to determine the likelihood that
the customer will buy again
Net Promoter Score
Advantage over CSI
Satisfaction of a customer with a particular service subject to the mood of the customer, environmental factors which in
turn effects CSI.
Net Promoter score can be used to motivate an organization to become more focused on improving products and services
for consumers.
Net Promoter Score correlates with revenue growth.
- 14 -
Performance analytics
In order to better analyze the performance,
one needs to ensure following steps are
followed.
Gathering data
Analyzing data
Presenting information in a meaningful way
Sales data
- 15 -
Churn analytics
Determining the existing churn rate in
business from lifts curves and logistic
regression
Qualifying churn with probability statistic
Identifying customers with high probability
of churn and preventing them from churning
Sales data Customer database for past few years | Demographic records as well as transaction history
- 16 -
Campaign Analytics
Analytics to track key performance metrics,
such as visits, leads, conversion rates, and
return on investments (ROI) on marketing
efforts
Profiling the ideal campaign for the right
customer to attract potential customers
Campaign survey data | Customer transaction data base
- 17 -
Forecasting and Inventory Management
Sales forecasting for optimal management
of showroom inventory to ensure the
business has best inventory mix
Forecasting through techniques such as
Moving Averages, Smoothening, ARIMA,
GARCH, etc
Macroeconomic Data | Industry Data | Company Sales Data
- 18 -
Margin Analysis
Identify the channel partner segments
responsible for various levels of margin,
commission.
Relating to the prisoner’s dilemma problem
Channel partner registration database | Transaction database
- 19 -
Workshop Analytics
Improving maintenance Efficiency by examining the
history of machine breakdowns and obtaining actual
MTBF & MTTR data.
Identifying repetitive failures and finding root causes
Reducing unplanned maintenance related downtime
Detecting patterns and trends in product problems.
Reducing warranty related costs.
Root cause analysis of warranty denials to arrive
appropriate preventive/corrective actions.
Transaction database
- 20 -
Cross selling / up selling
Identification of cross-sell and upsell opportunities
by evaluating and matching customer needs and
means
Examining the customer database through Market
Basket Analysis and Predictive models to reveal
insights on association rules that can maximize sales
force efficiency
Tying Cross Sell / Up sell opportunities with
Customer Segmentation and Loyalty to service the
right offering to the right customer
Historical Transaction Data
- 21 -
Complaints Analytics
Granularly segregating the complaints data on a common taxonomy, based on a standard lexicon of definitions of terminology and types of complaints.
Qualifying the raw data in more granular terms by adding parameters like severity of problem, periodicity of occurrence, type of fault detected etc
Run statistical analysis across parameters and help derive intelligent insights from the data either as predictive models, or as behaviour model or segment the data into intelligent patterns
The system identifies new issues in the field and flags higher-than-normal rate faults and notifies the appropriate analyst to let them know there is a problem that needs investigating.
Customer care complaints database.| Complaints on the products.
- 22 -
Unstructured Data Analysis
Text mining on unstructured data to derive patterns
Integrating text mining analysis with RFM, Loyalty,
Demographics, etc
Survey data | Transaction data |Customer Profile information
- 23 -
Aaum Research and Analytics founded by IIT Madras alumnus brings in
extensive global business experience working with Fortune 100
companies in North America and Asia Pacific. Established at IIT Madras
Research Park with a focus on researching and devising the
sophisticated analytical techniques to solve the pressing business
needs of corporations ranging from travel & logistics, finance,
insurance, HR, Health Care, Entertainment, FMCGs, retail, Telecom.
“Organizations are competing on analytics not just because they can- but because they should…”
01 N, 1st floor IIT Madras Research Park, Kanagam road, Chennai – 600113
+91 44 66469877 +91 44 66469887 +91 44 66469877
[email protected] b.rajeshkumar
AaumAnalytics http://www.youtube.com/aaumanalytics
http://www.facebook.com/AaumAnalytics www.aaumanalytics.com
http://www.linkedin.com/company/aaum-research-and-analytics-iit-madras