customer analytics for startup and smes

Customer Analytics Solutions for SMEs

Listen2Data Consultancy

March 2015

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About Listen2Data

About Listen2Data Consultancy

Listen2Data Consultancy

Listen2Data Consultancy is an IIT-IIM-ISI alumni initiative dedicated in serving various industries in the market research, analytics and decision support

processes.

Listen2Data has clients from Fortune 500 companies to startups and has catered to industries such as automobiles, BFSI, retail, e-commerce, IT,

media, services, chemical and manufacturing, logistics, telecom etc.

About Listen2Data Consultancy (contd.)

Our Business Offerings: Our Network:

Offerings

Analytics

Research

Digital marketing

Consulting

Product Development

Training

HQ: Bangalore

Mumbai Delhi Chennai

Development Office: Kolkata

Operations

Sales

Data Analytics - An Inter-functional and Interdisciplinary Field

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Big Data Analytics

Software Developmen

t and Implementa

tion

Data Capturing & Engineering

Statistical Analysis

Manufacturing Telecom

Banks Investment and

Trading

Logistics …

Big Data Analytics

Data Analytics/Science has applications in all industries and in different departments/functions/verticals within the same

industry/company…

Analytics enable higher growth…

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Internal Data

External Data

External Scores

Data Integration

Production

Finance

Manpower

Marketing

Logistics

Decision Making

& Resource Optimization

• Strategic Decisions

• Sustainable Solns

• Cost optimization

• Increased Turnover

• Higher PAT

• Higher Satisfaction

• Retention

Using big data tools

Extraction

Metadata Data

Cleaning

Data Variable

Generation

Architecture

Integrate Models

Integrate Decisions & Metrics Analytics Engine

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Customer Analytics for SMEs by Listen2Data

UnChurnTM

Solution 1: Churn Management

• Know why your customers do not continue

• Early identification of vulnerable customers

• Reduction of switching

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Customer Data / Transactional

Data

Predictive Analytics

Churn Predictions

Basic (Rs. 10000 / $200 per

year)

• Unique customer Base up to 1000 customers for B2C and 50 customers for B2B

• Yearly predictions

Enterprise (Rs 25000 / $500 per

year)


• Bi-annually predictions

Premium (Rs 50000 / $1000 per

year)


• Quarterly predictions

Results: • Chances of churning for individual

customers • Key touch points • Ranking based on vulnerability and

profitability

Interested? Please call us at +91-9343931795 or write to us at [email protected]

Solution 2: Divide and Rule

• Know what are the different types of customers you have

• Why they are different

• How you can influence them

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Data

Classification Analysis

Segments

Basic (Rs. 5000 / $100 per

year)


• Yearly classifications


year)


• Bi-annually classifications


year)


• Quarterly classifications

Results: • Characteristics of different

segments • Key touch points • Ranking based on profitability


AimGameTM

Solution 3: Targeting the customers

• Which of your customers will be most influenced by your next campaign

• What are the salient features for a campaign that should be designed

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Data

Predictive Analytics

Target group and campaign design

Basic (Rs. 15000 / $300 per

year)


• Up to 6 campaigns


year)


• Unlimited campaigns


year)



Results: • Ranking of customers or

customer groups based on their vulnerability towards a campaign

• Design of the campaign that will have best impact


Any Analytics Services

• Why hire an analyst when you can use us?

• We are suitable for you when you have less than 160 hours of work in analytics every month

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Data Analytics Reporting and

Predictions

Basic (Rs. 50000 / $1000 per

month)

• Work up to 40 man hour a month

• Job from remote location

Enterprise (Rs 100000 / $2000

per month)

• Work up to 80 man hour a month

• Job from remote location

Premium (Rs 150000 / $3000

per month)

• Work up to 1 man month


Advantages: • No need to hire a full time analyst but

get your analytics works done • On demand availability of analysts • Switch off with 1 month notice


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Other Services and Case Studies

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Strategic Reporting Services

Strategic reporting

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Source 1

Source 2

Data sources

Source 3

Using big data

tools

Extraction

Metadata

Data cleaning

Architecture

Data variable

generation

Reporting

Analysis

Assess data – utilize data

Extract information from unstructured data

Architecture and

Framework selection

Reporting and business intelligence

Assess realized value &

effectiveness

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Marketing Analytics by Listen2Data

• Track brand image, brand awareness, brand memory, brand

association

Performance Tracking

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• Methodology used:

• Old and classic methods, like qualitative study like focus

group interview, sample testing experiments etc. • Track the position of the brand with respect to its

competitions and with respect to its own goal • New methods with the use of analytics

• Online/Social media tracking (YouTube, Facebook)

• Text analytics

• Sentiment Analytics

Effectively designed performance tracking systems place essential, relevant information at decision makers’ fingertips. These systems can streamline data entry and reporting, increase efficiencies, and reduce inconsistencies.

Case Studies

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YouTube tracking:

• Tracked the performance of

YouTube videos for various TV

serials for 6 months.

• Like, dislike, views and comments

• Used as a predictor of the TRP of

the next day

Google play tracking:

• Tracked the performance of 200

competitive mobile applications

• Ratings, Google+ shares,

comments, up gradations etc.

• Used to know the key variables

for adoption and retention in the

category

• Used for competitor analysis

Brand comparison:

• Digital performance of

brands of two major call taxi

companies in Bangalore

• Client: A hospitality service provider

• Business problem –

• Performance of the company in online space?

• How to improve eWOM?

• How to encourage positive eWOMs and discourage negative eWOMs

• Methodology:

• Web scraping, Data analytics using mixed methods

• Results:

• Strategy which reduces the negative impact of service failure and improves the

hedonism of experiential outcomes resulting in improvement in WOM over a

period of four months

Case study: Word of Mouth

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• What impacts consumers purchase intention?

• Which promotional element has highest impact on

awareness, memory or association?

• Which promotional mix has higher impact than the

other?

Methodology:

• Old and classic market research, mostly survey based

• Predictive analytics and other analytical modeling on

consumer purchase behavior to find promotional

effectiveness

• Promotional mix optimization

Marketing Mix Solutions

Marketing Mix

Price

Product

Promotion

Place

• Client: A telecom service provider

• Objective:

To find which data plan goes best

which smartphone model to

provide best value to the

consumers and increase purchase

intention

Case studies

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• Methodology:

• Perceptual mapping using attribute level variables

• Conjoint analysis to find highest value

• Results

• Best sales promotion suggestions were given to increase product purchase

• Which customers are potentially more profitable?

• What are the major segments of my customer base?

• How can I strategically build a campaign to target my

customers?

• What are the major pain points of my service that is creating

most loss of sales? How can I prioritize them for taking actions?

• Old methodology:

• Survey, Focus Group Discussions, Interviews etc.

• New Methodology

• Market Basket Analysis and Hierarchical clustering

• Text analytics, sentiment analytics

Customer Relationship Management (CRM) solutions

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Client Customer

Customer Customer Customer

Customer

Customer

Customer

Customer

Customer

Customer

Customer

Customer

Customer

Competitor Supplier

Case Profile:

• Client: A retail giant in Bangalore

• Business problem:

• What are the various ‘mission segments’ for a

particular product category? (why consumers come to

buy)

• How these segments are characteristically different?

• How to plan the promotional campaigns to ensure

optimal reach, awareness and activation of these

segments?

• Deliverables:

• Segmentation

• Targeting and Position optimization

Case study on CRM analytics KYC (Know Your Customer) Solution in Retail

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Methodology Used:

• Data Source: 6 months scanner data from retail shop

• Segmentation: k means, decision tree

• Promotion mapping with segments based on feature

elasticity

• Tracking of the performance of the promotional initiatives by

qualitative and quantitative analysis

Result:

• The retail chain found 6 major mission segments from the

incoming consumers

• They have also found 4 major sub-segments in the product

category of apparel and fashion accessories

• Available promotion plans and timings were matched with

the segments and sub-segments

• New KPIs such as cross-selling, referral etc. also been tracked

Case Profile:

• Client: An IT service provider to auto-retail chains


Creating an analytics engine that gives a 360 degree view of

the consumers along with his probable choices and touch

points

• Qualifying customers for a product/offer from the database

• Deliverables:

• KYCD (Know Your Customer in Depth)

• Qualified customer set

• Choice probabilities

Case study on CRM analytics: KYCD Solutions in Auto

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Methodology used:

• Data Source: 6 years scanner data from auto-dealer shop and

auto-repair shop

• Data extraction and structuring using Big Data techniques

• Multiple segment choice modeling using latent class

• Qualification of consumers by big data analysis

Result:

• Various auto dealers found the major target segments for

their upcoming product offers

• The auto dealers also got a 360 degree view of the

customers stepping in their retail shop

Case Profile:

• Client: A telecom service provider


• Finding why a consumer adopts a product offered

• How such adoption changes the usage behavior

• When and why the consumers drops from service

• Deliverables:

• 360 degree view of consumer segments based on

adoption and reneging reasons

Case study on CRM analytics: Customer Lifetime Value (CLV) Solutions in Telecom

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Methodology Used:

• Data Source: 6 months usage data of the consumers along

with promotional communications data

• Data extraction and structuring using Big Data techniques

• K-mean clustering to find the segments

• Finding the reasons of dropping out from exit surveys and

consumer surveys

Result:

• Various segments with different pattern of consumer life

cycle was found

• Major reasons of adoption and dropping out was found from

analysis

• Change of usage of other services was predicted

Marketing Analytics - Sample Questions and Methods

Domain Business Question Old Method New Methods used by

us

Product development Which feature will be most profitable addition to an existing product?

Survey Conjoint Analysis

Retention Why are consumers not renewing the medi-claim or insurance products?

Exit survey Churn Analytics

Positioning How your product is perceived in comparison to competitive products?

Survey Text analytics, segmentation

Social media tracking How tracking of the changes of life stages can improve sales?

No idea Web scraping

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Market Research

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Find out performance of each unit

• Divide the market served by SCUF into different

units.

• Find out the performance of each unit

• Allocate manpower accordingly

Market Research

Help in implementing strategy

• Based on management strategy we will help SCUF to

find out potential customers for both existing and

new products and services.

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Data Security Measures

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Service offerings Capacity building

• Executives workshop

• Educate and experience sharing

•Reading materials and References

Risk and Compliance

•Develop process to manage risk through big data analytics

• Establish and foster overall compliance and corporate governance

Platform architecture

•Develop overall platform architecture for Big Data analytics

Market Research

• End to end market research

• Product development studies

•Advertising effectiveness

Data Modelling

•Descriptive Analysis

• Inferential and Predictive Modelling

•Graphical Models , Path analysis

Analysing Text Data

•Develop & Integrate search solutions

• Text mining, NLP

• Packaged and custom solutions

Statistical and Machine Learning

•Classical Statistics, Spatial Statistics, Temporal Statistics

• Simulation, Machine Learning, & Optimization

Data Solutions

•Data entry and processing

•Data warehousing and integration

•Business analytics and report generation

Contact

Name Swagato Chatterjee

Designation Partner, Listen2Data Consultancy

Tel: +91 9343931795

Email [email protected]

Address 102, Abhilasha Building, 4th Cross, Venkatadri Layout, Bangalore-

560076

mailto:[email protected]