Custome satisfaction proposal

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Benchmarking Customer Satisfaction :ING vs. Competition

Prepared for

Prepared by

August, 2010

ING Vysya Bank

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• ING wishes to carry out a benchmarking exercise viz. its major competition, on certain key customer service delivery parameters.

• This exercise specifically aims at evaluating where ING stands with respect to competition on the turnaround times relating to the:

– Opening of savings and current accounts– Disbursement of business and car loans– Handling of customer complaints

• In this context, ING has requested Hansa Research to submit a proposal for research

• This document outlines Hansa Research’s approach to the proposed benchmarking exercise.

Research Background

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• The primary goal of this research is to measure turnaround times with respect to the following :

– Opening of savings and current accounts– Disbursement of business and car loans– Handling of customer complaints

• However, in addition to this, a customer survey such as this should also do the following for each of these services:

– Identify the process that constitute a customer’s experience – Compare the satisfaction level of ING’s customers with that of competition’s

– Unearth the weaker areas in the product / service offering that leads to customer dissatisfaction and strengths that reinforce satisfaction and loyalty

– Hence, provide strategic input to identify focus areas

• In order to fulfill above objectives, HRG proposes to use ACT - its proprietary ‘Customer Satisfaction model’

Research Objectives

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Information Areas

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• Demographics• Banks dealt with• Types of services availed from the various banks deal with

– Opening of current a/c– Disbursement of business loan – Opening of savings a/c– Disbursement of car loan– Lodging of customer complaints

• If deals with more than one bank– Main bank; reasons for being the main bank (do most of the transactions from this bank, keep most of money in this

bank, most of the products taken from this bank etc…)Rest of the information areas would then be asked only for the services availed from the main bank– Overall satisfaction with the bank; Reasons– For each financial service availed from the bank

• Overall performance rating; Reasons• Total turnaround time• Expected turn around time• Rating on the speed of delivery• Likelihood to recommend; Reasons• Willingness to continue in future; Reasons• Ratings on various service dimensions

– Each service would be broken down in to key service dimensions across the various stages of customer relationship. These dimensions would be further broken down in to parameters. Ratings on criticality of and satisfaction on each of these dimensions and parameters would then be taken. Identifying these service dimensions and parameters would be done in consultation with the Client. An e.g. of this exercise is given on the next pages (7 and 8)

Information Areas

SMB only

Individuals only

SMBs & Individuals

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Account Opening

Account opening Stage Issue ATM pin

Overall Impression of account opening officer

Politeness and courtesy

Appearance and Grooming

Punctuality

Documentation

Ease of documentation process

Options of alternate documents

Flexibility in the documentation process

Sections (Stages of relationship)

Providing Welcome kit

Issue of ATM card

Identification of the service dimensions for opening Account

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Loans

Initial Contact Stage

Application Processing Loan Sanction Loan

Disbursement

Overall Impression of Sales Manager Politeness and courtesy

Appearance and Grooming

Punctuality

Knowledge and Competence

Understanding requirements

Knowledge of company and process

Communication skills

Knowledge of competition products

Sections (Stages of relationship)

Post disbursement

Identification of the service dimensions for disbursement of loans

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Research Methodology

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Research Methodology

• Target Group– As per the Client’s brief, there are two broad target groups of interest

– Small business enterprises who have-– Availed of the services of interest, namely, current account, business loans or customer

complaints in the last six months (6 months is taken to ensure the recency of the experience)

– An annual revenue between 15 lakhs to 4 crores

– Individuals who have– Availed of the services of interest, namely, savings account, car loans or customer

complaints in the last six months (6 months is taken to ensure the recency of the experience)

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Research Methodology (cont’d…)

• Research Design– Face to face Interviews would be conducted using semi structured questionnaires

– There may be cases where a customer has availed all the 3 relevant services in the last 6 months. Questioning them in detail on all the three, however, would burden them beyond acceptable levels. In such cases, we suggest taking responses on the overall satisfaction and turn around time for all the 3 services and detailed questioning on only 2 out of the 3 services. This design would ensure that our prime question of the turnaround time is answered for all the services experienced by the respondents without making the interview too long.

– The order of service exposure would of course be rotated across respondents, so as to minimize any order bias

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• Sampling – Client sample: ING would provide the database of the customers who have availed the

services of interest in the last six months• A random sampling method would be employed in order to select respondents from the Client

database. • A telephonic screener questionnaire would be done to assess the eligibility of the selected

respondent. If eligible, a Hansa interviewer would fix time and location as per respondent’s convenience for the detailed interview.

– Competition sample• A list of branches of competition banks will be obtained through the internet for each research

center . • The total sample size would be spread across all the branches per center so that the geographical

spread of the city would be maintained.

Hansa will define the competition with the help of the Client. However, as already discussed, the Client has to ensure that the competition is adequately present in the cities proposed for this research


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• Research Centers– As per the client’s suggestion, this research is to be undertaken in the North, South and

West zones. However, in keeping with their business strategy, the Client would like this research to focus more on the North zone .

• The centers chosen within each of these zones need to ensure the representation of the different tiers of towns, geographical spread and the Client’s presence. Keeping these factors in mind, Hansa proposes the following centers


Town Selection

North South West

Tier 1 Delhi Chennai Mumbai

Tier 2 Lucknow and Ludhiana Vizag Bhopal

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• Sample Sizes - SMBs

– The total no. of interviews may be lesser than the above mentioned nos if respondents qualify for questioning on more than one service


Option 1: City wiseReporting

Option 2 : Zone wiseReporting

Zones Town Per service /per bank

Total sample size (3 services and assuming 5

banks to be covered)

Per service /per bank



North

Delhi 30 450

30 450Lucknow 30 450

Ludhiana 30 450

SouthChennai 30 450

30 450Vizag 30 450

WestMumbai 30 450

30 450Bhopal 30 450

Total Sample sizes 210 3150 90 1350

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• Sample Sizes - Individuals

– The total no. of interviews may be lesser than the above mentioned nos if respondents qualifies for more than one service


Option 1: City wiseReporting

Option 2 : Zone wiseReporting

Zones Town Per service /per bank



Per service /per bank



North

Delhi 30 450

30 450Lucknow 30 450

Ludhiana 30 450

SouthChennai 30 450

30 450Vizag 30 450

WestMumbai 30 450

30 450Bhopal 30 450

Total Sample sizes 210 3150 90 1350

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Hansa’s approachACT Measurement Indices

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10 09 08 07 06 05 04 03 02 01

Excellent Ext. Poor

PERFORMANCE MEASUREMENT :

10 Point Scale with anchored end points

Performance Measurement - HANSA’s Approach

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Let the customer specify how ‘Critical’ (not just important) is a dimension to him in keeping a relationship going – in the context of the service

CRITICALITY MEASUREMENT :This is an extremely

important dimension and if some other company delivers

beyond my expectation on this dimension, I will definitely switch to the

product of that company

This is a very important dimension

and if some other company delivers

beyond my expectation on this

dimension, I will probably switch to the product of that

company

This is an important dimension, but even if some other company delivers beyond my expectation on this

dimension, I may not switch to the product

of that company

This is not so important dimension, and even if some other company delivers beyond my expectation on this

dimension, I will definitely not switch to

the product of that company

4 3 2 1

Criticality Measurement - HANSA’s Approach

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Analyze to see if these have been over invested in

Maintain

Low priority areas - tackle later Key action areas

PERF

ORM

ANCE

CRITICALITY High

High

Low

Low

Performance x Criticality = ACT WINDOW

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Customer ACT Deliverables

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I. Executive Summary

II. Customer SatisfactionI. Turnaround TimeII. Overall Customer Satisfaction

I. For customersII. Across various dimensions of service delivery (Time taken, Competence, Impression etc.)

III. Relative CriticalityIV. ACT Actionable Window - Criticality vs. Performance

III. Diagnostics into customer satisfaction I. Reasons for Satisfaction / DissatisfactionII. Likes / Dislikes with relevant dimensionsIII. Dimensions in service delivery that need improvementIV. How can delivery on service dimensions be improved?

IV. Action Plan to improve satisfaction among customer segments

The ACT Blue Print that has the following components:

ACT DETAILED SCORE CARD - The ACT Blue Print©

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REPORT CARD - Turnaround Time

ING Vysya vs. Bank 1




Savings A/c ++ ++ -- +Current A/c = -- ++ =Business Loan - = - -Car Loan + + - +Customer Complaint + = - =

“++” indicates “significantly lower turnaround time”

“--” indicates “significantly higher turnaround time”

“+” indicates “directionally lower turnaround time”

“-” indicates “directionally higher turnaround time”

“=” indicates “significantly lower turnaround time”

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TURNAROUND TIME - In Days

Turnaround (TA) time (In Days) ING Vysya Bank 1 Bank 2 Bank 3 Bank 4

Savings A/cActual TA time (Mean) 4.8 3.4 5.4 4.6 6.7

Expected TA time (Mean) 4 3 5 4 6

Current A/cActual TA time (Mean) 3.5 3.9 6.9 5.5 7.5


Business Loan

Actual TA time (Mean) 3.6 5.4 5.9 3.8 4.5


Car LoanActual TA time (Mean) 5.2 4.5 8 6.9 5


Customer Complaint

Actual TA time (Mean) 1.6 1.3 3.1 3.2 2.5


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SPEED OF DELIVERY - Savings Account

Bank Name

Excellent

Extremely poor

10 9 8 7 6 5 4 3 2 1

ING Vysya

37 6 22 5 30

Mean - 6.9

Bank 137 6 22 5 30

Mean - 6.9

Bank 237 6 22 5 30

Mean - 6.9

Bank 337 6 22 5 30

Mean - 6.9

Bank 437 6 22 5 30

Mean - 6.9

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SPEED OF DELIVERY - Current Account

Bank Name

Excellent

Extremely poor

10 9 8 7 6 5 4 3 2 1

ING Vysya

37 6 22 5 30

Mean - 6.9

Bank 137 6 22 5 30

Mean - 6.9

Bank 237 6 22 5 30

Mean - 6.9

Bank 337 6 22 5 30

Mean - 6.9

Bank 437 6 22 5 30

Mean - 6.9

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SPEED OF DELIVERY - Business Loan

Bank Name

Excellent

Extremely poor

10 9 8 7 6 5 4 3 2 1

ING Vysya

37 6 22 5 30

Mean - 6.9

Bank 137 6 22 5 30

Mean - 6.9

Bank 237 6 22 5 30

Mean - 6.9

Bank 337 6 22 5 30

Mean - 6.9

Bank 437 6 22 5 30

Mean - 6.9

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SPEED OF DELIVERY - Car Loan

Bank Name

Excellent

Extremely poor

10 9 8 7 6 5 4 3 2 1

ING37 6 22 5 30

Mean - 6.9

Bank 137 6 22 5 30

Mean - 6.9

Bank 237 6 22 5 30

Mean - 6.9

Bank 337 6 22 5 30

Mean - 6.9

Bank 437 6 22 5 30

Mean - 6.9

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SPEED OF SOLVING - Customer Complaint

Bank Name

Excellent

Extremely poor

10 9 8 7 6 5 4 3 2 1

ING Vysya

37 6 22 5 30

Mean - 6.9

Bank 137 6 22 5 30

Mean - 6.9

Bank 237 6 22 5 30

Mean - 6.9

Bank 337 6 22 5 30

Mean - 6.9

Bank 437 6 22 5 30

Mean - 6.9

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Managing Quality

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• Hansa Research meets or exceeds industry standards for quality control in data collection and data processing. The following steps would be taken to ensure quality control:

– Fieldwork would be carried out by teams of interviewers trained by Hansa researchers and senior field staff.

– A centralized briefing of our full data collection team would be organized on the goals and specifications of a project before data collection.

– Daily contact with researchers during the fieldwork process.– 25% of all interviewed would be back checked– 10% of all interviews would be accompanied – 100% of all questionnaires would be scrutinized

Quality Control

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Required Investments

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Time

Option 1 - City wise Option 2 - Zone wise

Questionnaire Design 1 week 1 week

Field Material Preparation and Briefing 1 week 1 week

Field Work 2 weeks 1 ½ weeks

Tabulation and Analysis 1 week 1 week

Report Preparation 1 week 1 week

TOTAL Time 6 weeks 5 ½ weeks

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Cost

• The costs given above do not include the mandatory service tax component of 10.36% payable to the Government of India

• Payment terms and conditions– 50% advance at the stage of project commissioning– 50% balance on presentation of findings

Option 1 - City wise Option 2 - Zone wise

SMB 10,92,000 5,20,000

Individual 7,51,000 3,60,000

TOTAL 18,43,000 8,80,000

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Hansa Research’s Customer Satisfaction Experience

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• Objective: To capture customer feedback for the services offered at branches.

• Methodology: Information is captured using a self-administered feedback form.

• Scope: Services are monitored at around 390 branches spread across 188 cities of

India

• Frequency: Continuous track (initiated in Dec 2003) where each branch is monitored

twice in a month and the data is reported on fortnightly basis.

• Reporting: The data is reported by branch, city, cluster, region, zone and also by

different service parameters ( for instance, soft skills, waiting time etc)

– Data reported on fifth day from fieldwork

Customer Satisfaction Survey: Branch (Liability)

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• Objective: To capture customer feedback for the services offered at Phone Banking

Channel.

• Methodology: Online survey where after seeking customer’s approval, the call is

transferred to the Research Officer who then captures customer’s feedback on

today’s experience. The data is captured on a website and gets automatically saved

on HRG’s server.

• Frequency: Continuous track where the data is captured on daily basis. The data is

analyzed and reported on weekly basis.

• Reporting: The data is reported by location (Mumbai, Hyderabad), skill (for instance,

credit card, loans etc), team leaders, etc and also by different service parameters ( for

instance, soft skills, waiting time etc)

Customer Satisfaction Survey: Phone Banking

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• Objective: To capture customer feedback on his experience on query resolution via

Email Channel.

• Methodology: A customer may raise a query to the client via Email. The query then

gets transferred to different teams depending on the product or which the query has

been raised. Along with the resolution, goes a link where customer is requested to

submit his responses regarding his experiences on the query resolution process. The

data then gets automatically saved on HRG’s server.

• Frequency: Continuous track where the data is captured on daily basis. The data is

analyzed and reported on weekly basis

• Reporting: The data is reported separately for each product (for instance, credit card,

private banking, loans, FDs etc)

Customer Satisfaction Survey: Email

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• Objective: To capture customer feedback on his experience on the initial interaction

with the bank

• Methodology: During the initial interaction with the bank, a customer gets a

welcome kit (across all the products and services). The kit along with other

documents, also contains a Business Reply Envelope (BRE) asking the customer to

submit his responses with respect to his experiences on the initial interaction with

the bank.

• Frequency: Continuous track

• Reporting: The data is analyzed and reported separately for each product (for

instance, credit card, savings account, loans, etc)

Service Quality Survey: Initial Interaction Experience

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• Objective: To assess satisfaction using Hansa’s proprietary ACT model

– Factoring in criticality of individual dimensions across all interaction points

– Assessed against customers’ expectation

– Benchmarked across competition

• Methodology :Respondents selected from database provided by client following

systematic random sampling, sorting by size of relationship. For benchmarking

competition customers selected purposively.

• Sample size: 9000 covered across 32 cities

• Products and Services covered in the study:

– Savings Account, Salary Account, Current Account

– Credit Cards

– Home Loan, Car Loan, Personal Loan, Commercial Vehicle Loan and Two Wheeler Loan

Customer Satisfaction Survey

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Engagement Team Profile(Quantitative Research)

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Anuradha Roy ChowdhurySenior Vice President and Head of Hansa TechHansa Research Group, Bangalore

Anuradha Roy Chowdhury heads Hansa Tech, the Technology research business of Hansa Research.

She has about 20 years of experience in all areas of Market Research including Customer Satisfaction Research, Brand Health Measurement and monitoring, Advertising Research, Concept and Product Tests, Corporate Image Measurement. Post launch evaluation, Pricing research, Baseline market studies, Demand estimations, Industry/Category studies and Database building. This experience spans diverse categories and verticals … including Technology, FMCG, Durables and Retail.

Anuradha has considerable experience in different data collection methodologies, including face to face, telephone and Online. She has worked on data from a range of countries, including both developed markets such as the US and UK, and developing ones such as India, Malaysia, China and Turkey.

Anuradha has a Masters degree in Research and Evaluation Methodology from Utah State University. She was with ACNielsen ORG-Marg for 15 years prior to joining Hansa Research, where she help positions such as Head - Branded Products, Head – Claritas Micromarketing and Head – Tobacco Business

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Sonakshi SinghAssociate Research DirectorHansa Research Group, Bangalore

Sonakshi Singh has around 4 years of research experience in Quantitative research. During this period, she has executed and managed projects of varying sizes across a number of categories. She has handled projects across a wide stream of verticals such as FMCG, beverages, finance and IT

Also, she has experience in conducting and managing an array of customised and syndicated research studies … to name a few Product tests, Catchment area profiling, Advertisement concept tests, Pricing research, Satisfaction measurement, Market sizing and Syndicated research.

Sonakshi has considerable experience in different data collection methodologies, including face to face, telephone and Online. She has worked on data from a range of countries, including both developed markets such as the US and UK, and developing ones such as India, Malaysia, China and Turkey.

Sonakshi has a post graduate degree in business administration

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Gurpreet Singh AulakhSenior Research ExecutiveHansa Research Group, Bangalore

Gurpreet Singh has around 3 years of research experience in Quantitative research. During this period, he has executed and managed projects of varying sizes across a number of categories. This experience spans diverse categories and verticals such as Technology, FMCG, Alcoholic beverages, Retail, and Durables.

Also, he has experience in conducting and managing an array of customised and syndicated research studies … to name a few Product tests, Catchment area profiling, Advertisement concept tests, Pricing research, Satisfaction measurement, Market sizing and Syndicated research.

Gurpreet has considerable experience in different data collection methodologies, including face to face, telephone and Online. He has worked on data from a range of countries, including both developed markets such as the US and UK, and developing ones such as India, Malaysia, China and Turkey.

Gurpreet has a bachelors degree in electronics and communication engineering and a post graduate degree in business administration.

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CH JagadishSenior Research ExecutiveHansa Research Group, Bangalore

Jagadish currently works with Hansa Tech, the Technology research business of Hansa Research.

He has 2 years of research experience in Quantitative research. During this period, he has executed and managed projects of varying sizes across a number of categories. This experience spans diverse categories and verticals such as Technology, Alcoholic beverages, Retail, and Durables.

Also, he has experience in conducting and managing an array of customised and syndicated research studies … to name a few Product tests, Catchment area profiling, Advertisement concept tests, Satisfaction measurement and Syndicated research.

Jagadish has considerable experience in different data collection methodologies, including face to face, telephone and Online. He has worked on data from a range of countries, including both developed markets such as the US and UK, and developing ones such as India, Malaysia, China and Turkey.

Jagadish has a Master’s degree in Business Administration from ICFAI Business School, Chennai and a Bachelor’s degree in Pharmacy from JNTU, Hyderabad.

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Swati D. SatamAnalysis ManagerHansa Research Group, Mumbai

Swati Satam heads the Analysis Dept. of Hansa Research, Mumbai.

She is involved in several aspects of analysis engagements including setting up the analysis of projects, using software’s like Quantum/SPSS, Job allocation & Monitoring, Recruitment & Training, and delivery of Quality outputs within given time .

In the span of 12 years in Analysis, she has garnered considerable experience in projects from all industries, including Media, Pharma, Financial Services, and Telecom & Industrial Products. She has honed the skills of handling large volume of data & analysed data for any type of interview including Pen & Paper, online / web based, CATI and CAPI.

She has hands on studies like syndicated studies, Brand Scan, product testing, Readership survey, Outdoor. In addition, she has exposure to an array of statistical tools like Cluster, Factor, Regression, Correlation, Conjoint, Correspondence, MDPref, BPTO, Jaccard and CHAID

Swati has a Masters degree in Statistics from Mumbai University & a Diploma in Computer programming & systems analysis. She has worked with IMRB, Ugam Solutions & ACNielsen ORG-Marg for about 6 years prior to joining Hansa Research

ANALYSIS