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Summer internship project report
To carry out the data handling, cleaning and analysis
processes employed for a study on changing purchasing
patterns of Low Unit Packs and a toothbrush visibility survey
(A Project Study Submitted In Partial Fulfilment for The Requirement Of
The Two-Year Post Graduate Diploma In Management 2009-2011)
Industry Guide Faculty guideAnkur Sinha Dr Amarnath Bose
Manager, Operations BIMTECH
The Nielsen Company. Greater Noida,
Submitted By
Swarandeep Singh Chopra
Undertaken at: The Nielsen Company, Vododara
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DECLARATION
I hereby declare that this Project Report titled To carry out the data handling,
cleaning and analysis processes employed for a study on changing purchasing
patterns of Low Unit Packs and a toothbrush visibility survey is a genuine project
undertaken by me under the guidance of Mr. Ankur Sinha, Industry guide, Manager,
operations, Vadodara and Prof. Amarnath Bose, Associate Professor BIMTECH Greater
Noida. All the findings and analysis in this project report are true, authentic and impartial.
I promise that the data gathered for the purpose of this report will not be made public and
will be kept confidential, except for academic purpose.
Swarandeep Singh Chopra
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CERTIFICATE OF APPROVAL- FACULTY GUIDE
Birla Institute of Management Technology
Summer Project Certificate
This is to certify that Mr. Swarandeep Singh chopra , Roll
No.174 ,a student of Post Graduate Diploma in Management has
worked on Summer Project titled To carry out the data
handling, cleaning and analysis processes employed for a study
on changing purchasing patterns of Low Unit Packs and a
toothbrush visibility survey in the FMCG sector after trimesterIII in partial fulfilment of the requirement for the programme. This
is his original work to the best of my knowledge.
Date: Signature
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TABLE OF CONTENTS
Page no
Acknowledgement2
Declaration...3
Certificate by college mentor...4
Certificate by company.....5
EXECUTIVE SUMMARY..10
CHAPTER 1: INTRODUCTION
1.1 Market Research industry12
1.2 Company profile .......14
1.3 Nielsens Products & Services ........15
1.4 Census department........18
1.5 Retail Store Census.......19
CHAPTER 2: DATA PROCESSING
2.1 Data handling and cleaning methodology21
CHAPTER 3: TOOTHBRUSH VISIBILITY STUDY
3.1 Important aspects of the study..........26
3.2 Questionnaire...27
3.3 Data processing steps......31
3.4Analysis tables and their interpretations..,..................34
3.5 Recommendations...38
CHAPTER 4: A study on LUPs
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4.1 Low Unit Packs- Introduction.40
4.2 Objective of the study..41
4.3 Coverage....41
4.4 Questionnaire.....42
4.5 Data processing steps....43
4.6 Analysis tables and their interpretations.46
4.7 Recommendations..57
CHAPTER 5: LEARNING EXPERIENCE
BIBLOGRAPHY......58
APPENDIX... .59
Questionnaire 1..
..59
Questionnaire 2.
...61
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LIST OF TABLES AND CHARTS
Page No.
Figure 1: ...21
Figure 3.1: ....28
Figure 3.2...29
Figure 3.3...29
Figure 3.4...31
Table 3.1.34
Table 3.2.....35
Table 3.3.35
Table 3.4.....36
Table 3.5.36Table 3.6.37
Table 3.7.....37
Table 3.8.38
Table 4.1.46
Table 4.2.....47
Table 4.3.....47
Table 4.4.....48
Table 4.5.48
Table 4.6.49
Table 4.7.49
Table 4.8.50
Table 4.9.....50
Table 4.10...51
Table 4.11...51
Table 4.12...52
Table 4.13...52
Table 4.14...52
Table 4.15...53
Table 4.16...53
Table 4.17...54
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Table 4.18..54
Table 4.19..55
Table 4.20......55
Table 4.21..56
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Executive summary:
The three main pillars of any market research are data acquisition, data processing
and data analysis. The first objective of this study was to understand the whole
process that begins when raw data comes in the form of filled questionnaires till the
time it is finally ready for analysis. Data is acquired by the field teams, then comes
data processing which includes keeping track of questionnaires coming in, studying
them and providing feedback to operation executives on the data quality, coding and
scrutinizing the data, coordinating with the field people, making screen for data entry
operators, defining the hygiene checks for the questionnaires and writing programs
for the same. Then came the data analysis part where each projects final data was
converted into an excel sheet and analysis tables were formed by using pivots. The
understanding of these processes was then employed in two live projects. First was a
study to understand the purchasing pattern of the retailer and analyzing its impact on
documentation of purchase records for Low Unit Packs (LUPs) of various brands of a
leading FMCG company and the second was a toothbrush visibility survey for an
FMCG company to understand what kind of displays and POS materials are used for
toothbrushes. Some of the important aspects were:
Business relatedness of the internship:
- Resolution to queries of the client
- Provide client with additional insight on his market
Skills developed:
- Coordination
- Reading the data
- Working in a team
- Defining checks for cleaning the data
- Analyzing the data
Sources and materials used:
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- Market research basics
- Microsoft excel: Basic and pivots
Based on above analysis key data tables were made for the client in such a way which
gave the best possible answers to their queries.
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CHAPTER 1
INTRODUCTION
1.1 Market Research
Market research is any organized effort to gather information about markets or
customers. It is a very important component ofbusiness strategy. Market research
consists of testing the market to determine the acceptance of a particular product or
service, especially amongst different demographics. It is used to establish which portion
of the population will or does purchase a product, based on age, gender, location, income
level and many other variables. Market research allows companies to learn more about
past, current and potential customers, including their specific likes and dislikes. Based on
market research data, businesses can develop a "target audience." A target audience is a
specific group of customers that has a distinct need or desire for a product or service.
Market research is used to determine how often the target audience will buy a particular
item, how much they are willing to pay for it, and their overall satisfaction with it. By
analyzing market research information,manufacturers and service providers learn where
to focus their resources most effectively.
Market research also helps companies develop information regarding new products or
product lines and learn how well new items will be received. It can also help businesses
learn how the public responds to a comparable product already on the market. In this way,
business can stay in the loop, keeping in touch with the wants and needs of consumers.
They can halt production of a product that the public shows little or no interest in, or
change it, improve it, or lower the price as necessary based on market research
information. The largest national market research market is the USA, followed by the
UK, Germany, France and Japan. After the USA, China is the strongest-growing country
of the ten largest national market research markets
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Market research process:
To conduct market research, organizations may decide to undertake the project
themselves (some through a marketing research department) or they might choose to
commission it via a market research agency or consultancy. Whichever, before
undertaking any research project, it is crucial to define the research objectives i.e. what
are you trying to achieve from potential the research? and what do you need to know?
After considering the objectives, Market Researchers can utilise many types of research
techniques and methodologies to capture the data that they require. All of the available
methodologies either collect quantitative or qualitative information. The use of each very
much depends on the research objectives but many believe that results are most useful
when the two methods are combined.
Quantitative Research
Quantitative research is numerically oriented, requires significant attention to the
measurement of market phenomena and often involves statistical analysis. For example, a
bank might ask its customers to rate its overall service as either excellent, good, poor or
very poor. This will provide quantitative information that can be analysed statistically.
The main rule with quantitative research is that every respondent is asked the same series
of questions. The approach is very structured and normally involves large numbers of
interviews/questionnaires.
Perhaps the most common quantitative technique is the market research survey. These
are basically projects that involve the collection of data from multiple cases such as
consumers or a set of products. Quantitative surveys can be conducted by using post (self-
completion), face-to-face (in-street or in-home), telephone, email or web techniques. The
questionnaire is one of the more common tools for collecting data from a survey, but it is
only one of a wide ranging set of data collection aids.
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Qualitative Research
Qualitative research provides an understanding of how or why things are as they are. For
example, a Market Researcher may stop a consumer who has purchased a particular type
of bread and ask him or her why that type of bread was chosen. Unlike quantitative
research there are no fixed set of questions but, instead, a topic guide (or discussion
guide) is used to explore various issues in-depth. The discussion between the interviewer
(or moderator) and the respondent is largely determined by the respondents' own thoughts
and feelings.
As with quantitative techniques, there are also various types of qualitative methodologies.
Research of this sort is mostly done face-to-face. One of the best-known techniques is
market research group discussions (or focus groups). These are usually made up of 6 to 8
targeted respondents, a research moderator whose role is to ask the required questions,
draw out answers, and encourage discussion, and an observation area usually behind one
way mirrors, and video and/or audio taping facilities.
1.2 Company profile
The Nielsen Company is a multi disciplinary research organisation, engaged in the fields
of Retail Measurement Services, Customised Research, Media Research and other such
researches. ACNielsen operations span more than 100 countries. Its regional business
centers are located was established in the United States in 1923 by Arthur C. Nielsen, Sr.,
one of the founders of the modern marketing research industry. Headquartered in New
York, USA and Haarlem, The Netherlands, Nielsen operates in more than 100 countrieswith a global team dedicated to helping clients compete more effectively and discover
opportunity with more clarity than ever before.
In 2001, ACNielsen became part of VNU, a world leader in marketing information,
media measurement and information and business media.In 2003, VNU announced a new
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organizational structure for VNU Marketing Information (MI), its largest business group,
to address evolving client needs and to create an enhanced platform for accelerated
growth.
In 2007, VNU changed its name to The Nielsen Company. This new identity emphasizes
its best known brand name and underscores its commitment to create an integrated,
streamlined global organization.
Among many innovations in consumer-focused marketing and media research, Mr.
Nielsen was responsible for creating a unique retail-measurement technique that gave
clients the first reliable, objective information about competitive performance and the
impact of their marketing and sales programs on revenues and profits.
Clients work with Nielsens services to:
Measure their market performance
Analyze market dynamics
Diagnose and solve marketing and sales problems, and
Identify and capture growth opportunities
For years, the name ORG has been synonymous with Retail Store Audits of any kind in
India similar to ACN in the world, be it on Consumer products or Pharmaceutical products.
Drawing on the wealth of experience gained over the past few decades, ORG also started
Retail Audits for categories such as Durables and Sanitaryware.
1.3 Nielsens Products & Services
Nielsen markets a wealth of information products, together with services and tools that
help clients use information correctly to address specific business issues and decisions.
Retail Measurement
Our Retail Measurement Services (RMS) provide continuous tracking of product sales to
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consumers, based on information gathered at the retail point-of-sale. Clients receive
detailed information on sales, market shares, distribution, pricing and merchandising and
promotional activities. RMS information is available in more than 80 countries.
Consumer Panel
Consumer Panel research tracks the purchasing behaviour of consumers in over 125,000
households in 24 countries worldwide, primarily through the use of in-home scanners.
Panel information reveals consumers purchasing from all outlets they visit and provides
insights into who is buying, methods of payment, use of coupons and participation in
frequent shopper programs.
Assortment and In-Store Space
A team of experts work with retailers and manufacturers around the world to deliver
business-driven, easy-to-implement solutions that provide a measurable return on their
investment in managing assortment and in-store space. We help them make key decisions
on issues such as shelf inventories, shelf space, category growth opportunities, product
listings and how best to distribute merchandising information.
Consumer Research
A diverse and powerful suite of Consumer Research services help clients obtain
qualitative and quantitative measures of consumers attitudes and purchasing behaviour,
customer satisfaction, brand awareness and equity, advertising effectiveness and other
marketing issues.
Retailer Services
The services for retailers are designed to help them understand what attracts consumers to
their stores. Retailers work with us to evaluate competitive performance, increase traffic
and sales, leverage their frequent-shopper data and build consumer loyalty, improve
performance of their private label products and understand their results across all product
classes and categories they carry.
Modelling & Analytics
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Our advanced Modelling & Analytical Services help clients address such key business
issues as pricing, promotion, marketing mix, assortment and product rationalisation,
category placement, category structure and in-store, in-market auditing and testing.
Nielsen Online
Nielsen's Internet audience measurement services, syndicated and proprietary tools and
custom analytics provide actionable insights to help you measure your audience, evaluate
and differentiate your site, track the competition and develop measurably-effective site
content.
Decision Support
We provide clients with a wide range of software tools and delivery methods designed to
put the right information on the desks of decision-makers at the moment they need it.
These tools range from advanced analytical and data-management systems for
sophisticated users to standard reports for end-users that are automatically refreshed
when our databases are updated.
Global Services
Nielsen Global Services coordinates with local Nielsen offices throughout the world to
deliver clear, consistent information across markets. This helps manufacturers effectively
understand emerging marketing opportunities for global brands. Utilizing consistent and
comparable cross-country data, combined with local country information, Nielsen Global
Services provides information-based solutions to worldwide marketers with a broad
international scope.
Business Consulting Services
Nielsen Business Consulting Services address your CEO agenda, bringing decades of
data management, advanced analytics and strategic management expertise to bear on the
high-level issues facing your business. Proven, prescriptive roadmaps are offered to
success that help your team answer the all-important where to play and how to win
questions.
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1.4 Census department:
Census department is a part of Global Operations at The Nielsen Company. This is the
department where all the data handling and data cleaning processes take place for analysis
.During my internship I got to work in this department where the basis of market research
starts. The census department conducts regular census surveys to keep track of the present
stocking patterns of dealers and also handles some client specific surveys, to solve their
problem or give them better insights. All stores that stock and sell any product category of
our interest (all product categories listed across all product forms) are enumerated.
Canteens in school, college, university should be enumerated if they stock and sell anyproduct category of our interest or serve tea/ coffee. Canteens in airport, areas like military/
air force stations, ports are enumerated if entry permitted and the outlet stocks any product
of our interest. However, canteens located in office and factory are outside the purview of
census. The work of this department is very critical as the actual physical data from field
firstly comes here which has to be checked, cleaned, filtered before it goes into the soft
form to be used for analysis or to be used by other departments of our company for any
purposes. Some other departments like management science department also get their
data cleaned and handled by this department for their projects. The work of this
department starts with the finalization of questionnaires, then field briefings are done to
field people so that the survey is carried out in the way it is desired, then the
questionnaires for particular projects or some regular census surveys to track the retail
space, come here after getting filled from the field. The questionnaires are manually
checked, inwarded, queries are sent to field, data entry takes place, data scrutiny is done
and several hygiene tests are done before it becomes useful without any errors. I will be
explaining these processes in detail later. After the data is cleaned it is interpreted in the
required form and then used. There are various surveys like panel surveys which reveals
consumers purchasing from all outlets they visit and provides insights into who is
buying, methods of payment, use of coupons and participation in frequent shopper
programs. Then regular census to find out the stocking pattern of the stores is done
regularly and there are also some small projects to answer client related queries or if the
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client wants further insights into its market through fresh surveys, the projects that I
handled comes under this category.
1.5 Retail Store Census
A census of shops means a complete listing of shops that deal in one or more product groups of our
interest. The basic steps that are involved in a census are
a) Identifying the towns in which retail measurement is to be conducted
b) Visiting these areas, listing and collecting information from all shops that fall in that area which
stock any product of our interest.
The need for Census:
Census information forms the foundation of the Retail Store Audit (RSA).
A census provides us with the following information
a) The total number of shops stocking a particular product within a town, which is defined as
the UNIVERSE OF OUTLETS.
b) Specific information on the retail outlet
Whether he is a big or a small retailer
The locality of the shop
Products stocked by the retail outlet
Companies whose brands the retail outlet stocks
Any other information of our interest
All the information listed above provides input to setup retail audit for any product, besides serving
as a useful database for other studies.
A Note on Turnover
Retail Store Audit for any product category requires the selection of a sample of retailers from
whom purchase and stock information can be collected at regular intervals. This sample of retailers
is selected so as to be representative of the universe. For this, we first have to break the universe into
smaller homogenous groups, meaning that the retailers belonging to each group should display
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similar characteristics/ patterns. This breaking or stratification as it is called is done on the basis of
certain criteria, the most crucial of them being the Outlet Turnover in Rupees.
Turnover of the outlet is an indication of the volume of business transacted from that outlet. In other
words, it is an indicator of the size of business of the retailer. Hence in every census exercise, the
turnover of the outlet assumes great significance.
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Chapter 2
DATA PROCESSING
2.1 Data handling and cleaning methodology:
Defi
Co
(Cens
Planning & Implementation
Chart 1 (Data process flow)
The first step to carry out any kind of research or survey is to define what the coverage of
the towns is going to be. The coverage is defined by census or management science
department and it depends on the scale of the study being conducted and based on various
factors a sample size is known on which the study is conducted and different statistical
tools are used to define it. Then the questionnaire is finalized and field briefings are held
for different zones so that the field people get to know how the questionnaires are to be
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filled and any ambiguities are resolved. Then after filling of questionnaires, they come to
the census department. Now, the data handling part starts and this was the main part
which I understood while working in this department.The various data handling and
cleaning processes are explained below:
1. Inwarding:
This is the first step of data handling, when the questionnaires come from the field
after getting filled the first task is to record which questionnaire has come out of
the sample size. Census department already has a dealer code for its dealers and
has a huge database of retailers which are known by these numbers. There is a
database of the entire sample size from where we are expecting filled
questionnaires to come. This database contains the dealer code and town code to
identify a particular dealer from whom we are expecting the filled questionnaire to
come. When the questionnaires arrive, their dealer numbers are recorded and they
are also given separate serial numbers to identify them during batch making. If the
study is for say 1 month, then questionnaires keep on arriving everyday from
different parts of the country and data entry for them is only possible if they arefirstly inwarded.
2. Manual Coding:
After the questionnaires are inwarded and serial numbers are given to them,
manual coding of the questionnaires start. This is the first step where cleaning of
the data starts. In what is known as coding, the questionnaires are manually
checked by operations executives to find out different mistakes which may be
done by the field people. These can unfilled questions, out of range answers of
some questions, there may also be cases where the answer of any one question is
not consistent with the answer of any other questions and other such errors may be
there depending on different questionnaires. All the questionnaires which contain
these errors are sent back to the field with an excel sheet mailed to them giving
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descriptions of the different problems which are there. The queries are then
resolved by the field people and then questionnaires sent back. There are also
cases where the error is solved by the coder only if the answer is obvious but that
rarely happens. Coding is a very important part of the whole process as in this step
we come to now what are the potential errors which can be there in the answers
which helps us to make better quality checks in the later steps and here we find
out what are the questions confusing the field people and therefore better
instructions can be given to the data entry operators so that they dont get
confused.
3. Batch preparation:
After the coding of the questionnaires is done, they are clubbed together in a
batch and sent for data entry. Batches are used as all the questionnaires dont
come from the field the same day, so as and when few questions come, they are
inwarded, coded and their batch is formed and this is issued to the vendor (data
entry operator) who has pre installed program for data entry. Sometimes batches
are formed according to towns or zones also, so that it is easy to carry out town
specific studies. A survey may consist of many batches depending on the speed of
questionnaires coming in and also on the speed of query resolution. Thesebatches have to be merged in the end when final data is prepared.
4. Data entry:
Data entry work is outsourced. There are some data entry operators who are
known as vendors who regularly do this work. They are called when needed and
they have to deliver the data the next day. After batch making is done it is time
for data entry. Now, different questionnaires require different screens and
structures to be made so that their entry can be done. Screen preparation is done
on Fox, there are 88 columns and 22 rows in one screen , so depending on the
question requirement adequate spacing is given and format is made. The space
left after each questions should consist of exactly those many spaces which are
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required to be filled and there should be adequate spacing between questions to
avoid any confusion. This screen is then given to the vendor and instructions are
given to him as to how to fill and what kind of mistakes are possible so that they
can be avoided. Along with screen preparation, a structure is also prepared
which has all the questions in the columns and the required space for the answers
in the rows, this is used to see the data after it comes from data entry and carry
out any changes or checks required. The vendor can do the data entry for only
those questionnaires which are inwarded in the batch and after the data entry, the
entered batch is submitted back.
5. Pre scrutiny:
After the receipt of the data from the vendors, it is now checked for any errors.
There are different checks employed. Pre and main scrutiny is done mainly for
census forms and for small projects direct hygiene checks are employed to clean
the data. When the data is received from the data entry operator, there are some
preliminary checks which are employed which are checking whether data for all
the questionnaires which were there in the batch is filled and nothing left which is
done by cross checking with inwarded data, then it is checked whether any extra
entry is done which was not in inwarded list. Then it is checked to see if there is
any duplicate entry which is done by the vendor. All these checks are done and
any irregularities if found are then resolved. Now in pre-scrutiny the fields like
dealer code, town code, date of filling etc fields which are not related to questions
are checked using a program which when run catches any mis-match from the
required data and then these errors can be resolved. This is done to be sure of
what data is coming from which source, when was the survey done and this data
can be used in the analysis.
6. Main-scrutiny:
This is the step where the data is cleaned using different checks employed to filter
out the errors. The questionnaire follows a flow and different questions are
dependent on one another for another for consistency. The different checks which
are employed include range checks which check whether a given answer is
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within the desired limit, for ex it should not be there that percentage is asked and
answer is more than hundred, which means that there is some error as this is not
possible, so the questionnaire which shows this error is taken out and seen what is
the mistake done by data entry operator and this mistake is then resolved. Then
there are consistency checks which are employed to see whether answer of one
question is consistent with another question, say it is marked that a retailer is not
stocking soft drinks in the first question but in the second question he is showing
10 percent sales due to soft drinks which is inconsistent and should be checked.
So, such errors are removed. There are also some other checks which are
employed like the sum of percentages should be 100 if percentage contribution is
required etc. So, data scrutiny is done to remove all the errors which may have
crept in the data at different stages of the data handling process. The checks are
put according to questionnaire and these are very critical, so a lot of thought is
given to employ right checks and not leave out any room for error as this step is
the final step before the batches are merged together and put as a single data final
data of the project to be used for analysis.
7. Data analysis:
The final data is used for analysis depending on what analysis is to be done, thedata which is on Fox is converted to excel worksheet and then using pivots or
other such tools as per the requirements final data tables are made and the results
of the study are found out.
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CHAPTER 3
Toothbrush Visibility Study
3.1 Important aspects of the study
1. Visibility tracking The Concept
Visibility tracking means observing each and every POS (Point of sale) material and
SKUs(Stock keeping units) placed for public display in a shop. These displays are
primarily used to draw attention and also increase in-store sales. Te more the visibility,
the more the expected sales and this is true for both visibility in terms of POS and
SKUs.
2. Objective
The client* wants to understand what kind of displays and POS materials are used for
toothbrushes. With this information, they could possibly identify if they need to design
more or different types of displays. It will also help them to understand what their
primary competitor is doing to drive toothbrush sales. The project was titled as I
think I saw a toothbrush
The scope of this project is to
Find out if the shop has some kind of display specifically for toothbrushes
Find out if the shop uses any POS material (danglers, streamers, posters etc.) to advertise
toothbrushes
Count how many SKUs of 4 brands of Brand A and 4 brands of Brand B are on display
*The name of the client cannot be disclosed as the data is sensitive and the company doesnot allow to put the actual brand name. So I have used some generic dummy names in place
of actual brand names.
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3. Coverage
The coverage for this study will be in approximately 1600 outlets spread across 4
metros and 3 class 1 towns. These outlets are all panel stores for Nielsen.
4. POS material Captured
Posters (any wall in the shop)
Danglers (anywhere inside the shop or just outside the entrance to the shop
Buntings/streamers
Shop-front banners
Leaflets
Any display that holds toothbrush SKUs is considered a toothbrush display. Any
display that only advertises toothbrush but does not hold any SKUs is considered a
POS material.
3.2 Questionnaire:
The actual questionnaire is attached in Appendix at the end. The overview of the
questionnaire is as follows:
1. What is the outlet nature of business?
Please encircle only one option from the given options
a) Groceries/Consumer/Food Products
b) General Store
c) Chemist
d) Cosmetics Store
e) Paan Plus (Selling Cigarette/Tobacco etc)
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2. Observe if toothbrush displays or POS materials are present in the shop.
This observation will determine if we should continue with the survey for this shop. If
the shops has POS material, or toothbrush display, we need to continue with the
questionnaire. If both are not present, we need to stop here after making a note that
both are not present. If POS material is visible then Q3 and 4 should be answered and
similarly if SKU displays are there then Q5 and 6 should be answered.
SECTION 1 POS MATERIAL
3. Please circle brand/s for which POS material is visible.
If the shop has any POS material for Brand Aor Brand B, circle the number before the
name. If any other brand toothbrush POS material is visible, write the name of the
brand after Others Pls. Specify.
The following pictures explain what different POS materials mentioned in this
questionnaire look like
Posters:
Figure 3.1
Danglers:
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Figure 3.2
Leaflets:
Figure 3.3
Buntings:
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Figure 3.4
4. For brands where POS material is visible, please circle type/s of POS
visible.
Circle 1, 2, 3 or 4 for the type of POS material for the brand selected in Q3. E.g. If a
poster for Brand Ais seen, circle 1 in Q3, and 1 in Q4.
SECTION 2 - LOCATION AND SKUs ON DISPLAY
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5. Please circle brand/s for which SKUs are visible when standing in
front of counter and looking in all 4 directions:
Observer the store entrance and all around when standing in front of the counter andmake a note if any toothbrushes are on display. The brushes could be in a hanging
container, basket/cup/mug display, in a display rack, or under the glass counter top.
Client primary requirement is to check if the 8 listed brands are visible. For any other
brands of Brand B or Brand Aon display, circle 5 or 10 (Brand A others or Brand B
Others).
6. For brands where SKUs are visible, please enter count of each brand
at each location:
Take a stock count of any of the 8 brands listed earlier if they are on display. If any other
Brand B or Brand A brand is on display, take a stock count and indicate the number of
SKUs against the Brand A Others or Brand B Others brand in the table.
3.3 Data processing steps:
This was a live project in which a study was conducted to find out toothbrush visibility
of a leading FMCG company vis--vis its main competitor. Due to the rules of company
the names of the companies cannot be mentioned. The experience of working in a real
project gave me a lot of exposure. It involved dealing with questionnaires, coordinating
with field people, vendors and other operations executives. The main processes that were
followed in this project are given below:
1) Inwarding:
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The inwarding process was similar to the one discussed earlier. The
questionnaires coming in from the field were inwarded by putting their dealer
code and town code and serial numbers were given to them as explained earlier.
2) Manual coding:
Coding was done to find out any visible mistakes. The things to watch out for
included things like, in question 2 if POS and SKU both are marked not visible
then the rest of the questionnaire should be empty and vice versa. If POS present
then Q3 and 4 must be marked and vice versa, and if SKU is visible then Q5 and 6
should be marked. Such things were checked out besies unfilled questions and
they were sent back to field.
3) Queries sent to field:
The questionnaires which had some queries related to some questions as found out
during coding were sent back to field along with a description of the the queries
and I also had to talk to field people on phone to explain to them any ambiguities
that they had. After resolving the queries the questionnaires were sent back to us.
4) Batch preparation:
As the coding got completed for as many questionnaires as used to come in a day
or two, their batches were made and sent for data entry.
5) Screen and structure preparation:
Screen was prepared for data entry according to the questionnaire, this was done
on Fox pro. The screen gave as much space required for each question as required
by a question. Then a structure was also prepared where the final data would be
kept and changes will be made there. This was also done on Fox Pro and final data
was kept in this structure only.
6) Data entry:
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Data entry was done by the vendor on the batches which were issued to him from
time to time during the project using the screen made above and batches were
received from him after data entry.
7) Preliminary checks:
After the data came back after data entry, then 3 preliminary checks were
employed, firstly it was checked whether data entry was done for every
questionnaire which was inwarded. Then it was checked if any extra
questionnaires data entry was done even when it was not inwarded. The third
check was the duplicacy check which was employed to find out whether there
were any duplicate entries. These checks helped to sort out these problems. These
checks were done by writing a small program on Fox and then using it.
8) Main Scrutiny:
Now checks like range and consistency checks were employed to clean out any
errors which may still be there in the data. The range checks include checks like
values of Q1 should be from 1 and 5, for Q2 it should be 1 or 2, for Q3 it should
be from 0 to 3, for Q4 from 0 to 5. Then there were consistency checks which
were employed. In question 2 if POS and SKU both are marked not visible then
the rest of the questionnaire should be empty and vice versa. If POS present then
Q3 and 4 must be marked and vice versa, and if SKU is visible then Q5 and 6
should be marked. If Q3 is marked then 4 should also be marked and similarly for
Q5 and 6. All these checks were made in Fox Pro and changes were made in the
data as a result of these checks in the structure we had made earlier. After all the
batches were checked, they were merged together and final data was ready for
analysis.
9) Data analysis:
The final data available was converted in excel sheet. After this data filters were
put for any kind of sorting required. Then pivot tables were made of the available
data. These pivots are helpful for making different cross tabulations. The sample
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size included 4 metros and 3 FLPs(Five lakh plus) towns. So analysis based on
kind of cities was also possible.Using pivot tables different analysis tables were
made which I thought will be helpful for our client. These tables are shown. Bases
on these tables we got some important findings about this visibility study.
3.4 Analysis tables and their interpretations:
The nature of outlets where maximum no of POS materials were visible were grocers
followed by general stores and chemists and 95 % of the total POS materials present were
in the metros.
Table 3.1
The nature of outlets where toothbrushes were visible the most were grocers
followed by general stores and chemists and here as well approx. 92 % of the
outlets where the toothbrushes were visible were in metro cities.
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Table 3.2
Out of the total stores visited 66% of the stores did not have POS material visible
or toothbrush visible. Another important point is that in Dehradun there was not
even a single outlet where POS or toothbrush were visible.
Table 3.3
Out of the total POS materials visible, the share of Brand A i.e our client was nearly 50%
of its main rival i.e brand B while others contributed very little
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Table 3.4
Buntings was the most preferred POS material which was present in about 45% of the
stores followed by danglers and posters for Brand A
Table 3.5
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For brand B as well the most common POS material used was buntings and almost 90%
of them were present in Delhi alone.
Table 3.6
For brands other than Brand A and Brand B, the most common POS material was other
than the ones we had specified which means buntings is the preferred POS material
mainly for Brand A and Brand B
Table 3.7
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This shows that the different brand variants of our client i.e Brand As
toothbrushes were visible only50 % of those visible for Brand B and Brand As
toothbrushes had no visibility at all in Trivendrum along with Dehradun. Delhi
had maximum visibility for Brand A toothbrushes while it was Bangalore for
Brand B. The overall distribution of both the umbrella brands were similar in
FLPs and metros.
Table 3.8
3.5 Recommendations:
As only 5% and 8% of the total POS materials and toothbrushes respectively were
visib;e in FLPs, so there is a huge scope there, the company should try and put
more emphasis on towns like Dehradun to increase its visibility in these towns.
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More emphasis should be given on increasing the visibility in chemist shops and
cosmetic stores.
Two third of the stores still does not have any kind of visibility, so it should be
tried to make them visible in these stores
It should be tried to put POS materials and make toothbrushes visible in those
stores as well where competitors visibility is there while targeting new stores as
well we are lagging far behind the competitor.
It should be tried to push more buntings as the preferred POS in Mumbai and
Kolkata as it is the most preferred POS in other metros.
FLP towns prefer some other POS material which is not in our present study, so it
should be found out what that is and it should then be tries to make available in
more stores across FLPs.
Overall visibility of toothbrushes of all the brands of Brand A is half that of Brand
B so a conscious effort should be made to increase the visibility by insentivising
the retailers and by making attractive toothbrush holders and racks, so that
retailers put them where the customers can see them
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CHAPTER 4
A study on Low Unit Packs (LUPs)
4.1 Low Unit Packs- Introduction:
You order a cup of tea and look around for a quick snack but the tea stall has only large
take-home packs of biscuits. They look daunting; you dont want to munch through 15
biscuits, nor do you want to lug those you cant eat. You would be happy with a handful
of biscuits. That is where Low Unit Packs come in and are beneficial for both the
company as well as the consumer. The LUP market forms 35% of the total Indian FMCG
market. The market size for LUPs is different for different categories. For example, in
shampoos, close to 80% of sales come from sachets. The LUP market for balms is around
Rs100 crores, it is currently contributing about 20%-25% of the total sales of balms. In
current times of inflation, low-unit packs have started playing a bigger role. Mass brands
are likely to suffer more due to inflation as consumers of premium brands are not price-
elastic Since it is a low unit price pack, the consumers soak out less amount of money.
Even daily wage laborers can buy the best of brands. This is working in favor of many
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companies. Also the small size packs have the ability to reach the remotest part of the
country.
In a low per capita income country such as India, low-unit packs have been a key
strategic tool used to increase penetration across several categories. Shampoos were one
of the first few categories to successfully employ this concept in India, such that sachets
today account for over 50 per cent of total shampoo volumes. Across several other
categories, where high price is believed to be a purchase barrier, from teas to soaps,
companies are focusing on low-unit packs to increase penetration and hence sales.
Chocolates are a good example, where we have seen the launch of unit packs in the price
range of Rs 5 to Rs 6 per 15-18 gm packs. Clearly a low-unit pack at Rs 5 places the
product in the consideration set of several target consumers who might have earlier found
the regular product too expensive. But more importantly, it also opens up new and more
frequent occasions for consumption. From a manufacturers point of view, however, there
is another important element to this situation - cost of producing and distributing a low
unit pack. Every marketer who wants to harvest the wind has to adopt a little-drops
strategy. This means going the way of small packs. The low unit packs strategy can be
adopted by everyone. Products have done this first and services will follow. Our client is
a leading FMCG company and does not have much insight into the changing purchasing
and documentation patterns of its LUPs, so this study will bring out zone wise and all
India pattern of purchase for 2 shampoo brands, one toilet soap brand, 2 personal care, 3
tea brands and 3 coffee brands under its umbrella which are offering Low Unit Packs.
The name of the company and ots brands cannot be disclosed due to company policy.
4.2 Objective of the study:
The objective is to study to understand the purchasing pattern of the retailer and
analyzing its impact on documentation of purchase records for Low Unit Packs (LUPs) of
various brands of the client. Our client is a leading FMCG company* of the world and
has a very stong presence in India. The client has a huge product portfolio and wants to
have proper understanding of the purchasing patterns but it does not have much insight
into the changing purchasing and documentation patterns of its LUPs. So this study will
bring out zone wise and all India pattern of purchase for 2 shampoo brands, one toilet
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soap brand, 2 personal care, 3 tea brands and 3 coffee brands under its umbrella which are
offering Low Unit Packs. The name of the company and its brands cannot be disclosed
due to company policy.
*The name of the client cannot be disclosed as the data is sensitive and the company does not allow to put the actual
brand name. So I have used some generic dummy names in place of actual brand names.
4.3 Coverage
The coverage for this study will be in approximately 6600 outlets spread across the 4
zones of India. This was decided by the management science department. The stores
covered under this study are our panel stores which are recruited by us for continuous
tracking of products in the retail space. Panel stores are useful in this study as they give
us the true picture about documentation details which other dealers may be apprehensive
about sharing.
4.4 Questionnaire
The actual questionnaire is attached in Appendix at the end. The overview of the
questionnaire is as follows:
Q1: It was required to mention whether the given products were stocked or not and if they
were stocked then what was the frequency of purchasing them, if a particular product it
was marked as not stocked, then throughout the questionnaire entries corresponding to
that product had to be blank and vice-versa. If it was stocked, then its purchase frequency
had to be mentioned i.e whether the products are bought more than once a week, weekly,
fortnightly ,monthly.
Q2. For the products which were stocked as per the first question, now it was required to
mention whether the purchase frequency has increased, decreased or remained same over
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last year, this question was aimed at analyzing the changing purchasing patterns over the
last year.
Q3: Current proportion billing record of this year (2010) was available to us in our data
base. This question helped us to probe if the proportion mentioned has changed over last
year and enter % proportion of billing record for corresponding period of last year. If the
respondent was not able to share actual percentage after probing using the current
percentages, indicate increase or decrease or no change using codes mentioned in the
table. Increase/ decrease or no change was to be entered with respect to current year
(2010) over corresponding period in 2009. Comparison of period: start of 2010 year
(CURRENT) compared to same period previous year (i.e. 2009).
Q4. If percentage of NO DOCUMENTS AT ALL has increased, the reason behind the
same was asked. This was an open ended question. This was included to have a database
of the potential reasons why oral method of documentation has increased if any such
query is raised by the client.
4.5 Data processing steps:
This was a very interesting study as it was done to gain further insights into the LUP
segment which is gaining strength in our country. The data handling process was quite
similar to the one followed for the toothbrush visibility study, but the checks were
different and due to its huge sample size, more batches were made and better care of the
data had to be taken. I have tried to explain the main differences in the processes below
while the main points remain the same. One of the main differences while handling the
data of these two projects came in handling of the queries with the field people and
coordinating them as in this project there was some ambiguity regarding percentages to
be filled in Q3, so there were many cases where it was left unfilled or there were some
errors. So, a lot of queries were sent and I had to explain to field people again at times
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what the errors were and so it consumed a lot of time for the questionnaires to again
come back from the field which left you waiting for them and similarly the data entry
operators had to be explained thoroughly so that they did not commit any mistakes, in
the end the deadline was just met. But, in the end the whole process was a great learning
experience and gave me better insights into what are the potential points of confusion for
field people and how to coordinate better with them in the future. The different steps of
data handling and cleaning are as follows:
1. Inwarding: This process was similar to the one explained earlier. In this only the
dealer code and date of filling had to be inward.
2. Manual coding: The points for this questionnaire which were to be checked
manually included checking for unfilled responses in Q1, then if a product was
mentioned as stocked in Q1 then its corresponding entries should be marked in Q2
and Q3 and vice-versa. If percentages were mentioned in Q3 then its sum should be
100 across different documentation methods. If it was marked that the percentage of
aparticular method of documentation has increased ,then it could not have been 0
currently (we had current percentages database with us), as how can it increase to 0.
So, such checks were done manually and the queries were sent to the field for
resolution.
3. Queries sent to the field:
The different queries as explained in the coding part were sent to the field for
resolution. There were some instances in this project when the questionnaires came
back frm the fiels without the queries being resolved and they had to be sent again,
which put a lot of time pressure for the project to get completed within the deadline.
4. Batch making: Questionnaires Kept coming in for about a fortnight due to the
sample size, so around 21 batches were made at different times and sent for the data
entry.
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5. Screen and structure preparation:
Screen and structure was made as per the questionnaire as was explained earlier.
6. Data entry:
Data entry was done by the vendor on the batches which were issued to him from
time to time during the project using the screen made above and batches were
received from him after data entry.
7. Preliminary checks:
After the data came back after data entry, some preliminary checks were employed,
similar to the ones employed for the toothbrush visibility study, firstly it was
checked whether data entry was done for every questionnaire which was inwarded.
Then it was checked if any extra questionnaires data entry was done even when it
was not inwarded. The third check was the duplicacy check which was employed to
find out whether there were any duplicate entries. These checks helped to sort out
these problems. These checks were done by writing a small program on Fox and then
using it.
8. Main scrutiny:
The checks employed here were different from the ones used earlier. The range
checks included check in Q1 that the responses should be between 1 and 5. In Q2
between 0 and 3 and in Q3 between 0 and 100. There were some problems with
regard to Q1 because there were a lot of questionnaires which marked 0 as the
response confusing it with 1, which was the correct response for not stocked items.
So that had to be corrected many a times. Then came the consistency checks in which
the checks included checking if the response was other than 1 i.e stocker for a
particular product, then the responses for that product in Q2 and Q3 should be
marked and vice versa. If the product is marked as not stocked in Q1, then its
purchase frequency cant change nor can its documentation be there, so Q2 and Q4
should be left blank in such cases and vice versa. Then there was a check to see
whether the sum of percentages across different documentation methods of a
particular product was 100 or not. The last check was to check whether the open
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ended question given at the end was answered if the percentage of no documents
documentation method increased over last year or not. These checks were made in
Fox Pro by writing small programs. When a batch came back from data entry, it was
put through each check which was in the form of small programs one by one, and if it
showed any errors, the serial no and town code of the error containing questionnaire
was shown which could then be resolved by taking the questionnaire out and finding
what was the mistake done by data entry operator, which is then rectified and next
check is run an so on.
9. Data analysis:
The final data available was converted in excel sheet. After this data filters were put
for any kind of sorting required which was similar to what we did in the toothbrush
survey. Then pivot tables were made of the available data. These pivots are helpful
for making different cross tabulations. The processes for the two projects seem
similar but there were a lot of differences in how they wre carried out and the
analysis part was completely different. In this survey the analysis tables were made
for different zones and also for all India analysis which are shown.
4.6 Analysis tables and their interpretations:
For the LUP study carried out across key states we observed that almost
13 % cases were not successful
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Table 4.1
Stocking Pattern Observed for LUP indicated that for Coffee LUP were being
stocked mostly in South and Shampoo1 does not have as good penetration levels in
North zone as compared to other zones.
Table 4.2
Penetration levels are maximum in West and South zones across brands and its quite
uniform across brands other than tea and coffee for north zone
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Table 4.3
Across brands we observe that the Purchase frequency is between 2 to 4 weeks. With
only 17 % stores having frequency less than 2 weeks. However for West and South
Frequency of Purchases is higher, with 54 % of stores having purchasing of less
than a fortnight for West and 58 % for South.
Table 4.4
For Shampoos maximum stores are purchasing once a month followed by once
a fortnight frequency. Similar pattern is emerging for Cream 1 as well as Soap. For
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coffee no of stores stocking is very low also the frequency of purchase is to the tune
of once month
Table 4.5
For East we observe that for most of the brands the purchase frequency is in the
range of once a month.
Table 4.6
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For West across most brands frequency of purchase is once in a fortnight or lower
indicating a faster rotation of stocks present in the outlet.
Table 4.7
For South too we observe that the frequency of purchase is on higher side with
most of the stores are purchasing once in fortnight or more.
Table 4.8
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Highest increase in purchasing frequency is observed in once a week and once a
fortnight period indicating that regular purchases are increasing for Shampoo 1
Table 4.9
For Sampoo 2 the Increase in shift towards purchasing frequency of once a
fortnight is seen
Table 4.10
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For Soap 1 the Increase in shift towards purchasing frequency of once a fortnight
is seen
Table 4.11
For creams also the shift towards purchasing frequency of once a
fortnight is seen.
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Table 4.12 and Table 4.13
Coffee 1 which is dominant in south we observe a huge shift towards higher purchase
frequencies as compared to last year, which means purchases are increasing.
Table 4.14
For 3 roses which is predominantly south brand, the Shift in purchasing pattern is
primarily seen for Re 1 pack and the shift is towards increased frequency of
purchases
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Table 4.15
The most common method for documentation was invoicing, but was decreasing.
Table 4.16
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The oral method of documentation was decreasing very fast and PRB method was on th uprise.
Table 4.17
Purchase frequency for 60-65% of stores has remained same across brands whereas around 7
% stores have reported decline in purchase frequency. However for Shampoo 1 - 37%
increase in purchase frequency was reported.
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Table 4.18
For East approx 10 % of stores have reported Decline in purchase frequency where as 55-
60 % of stores has maintained their purchase frequency
Table 4.19
For West 55 to 60 % stores have maintained their purchase frequency as compared to last
year
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Table 4.20
Increase in purchase frequency was reported by around 40 % of dealers for Coffee 1,
Coffee 2 and Shampoo 1 LUPs
Table 4.21
4.7 Recommendations
Shampoo 1 should be promoted in the North zone through sales promotion or better
communication as it is less stocked in this zone.
The 3 tea brands should be made more available in zones other than the south zone.
The purchase frequency of tea 2 and tea 3 is quite stagnant so they should be tried in
other zones as well.
Purchase frequency of Shampoo 2 was decreasing across the country, so attention
should be paid on this to increase sales.
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Maximum sales are coming from Shampoo 1 and its purchase frequency is increasing
towards weekly and fortnightly sales, so this brand should be made available at all
times.
CHAPTER 5
LEARNING EXPERIENCE:
The internship at The Nielsen Company was a great learning experience. The culture,
structure, processes and functions at Nielsen provide a different dimension to Business
growth and development. I am very fortunate to undertake my interns at Nielsen which
could expose me to two parallel aspects Organization: The Technology aspect and
Business aspect. The internship helped me to liberally apply all the business aspects
studied for the past one year. Nielsen work principle gave me an opportunity to work on
many confidential aspects of the company. The policies restricted me to depict many
important aspects of the company and data. I had apprehensions about my performance
before joining as I was going into highly process oriented Multinational Company
without any prior work experience. Initially I was required to understand the Organization
Structure, Process, various departments, Teams and their functions. As Nielsen is worldsleader in Market Research in FMCG products I could directly co-relate various concepts
of Marketing Research, Marketing & Organization Behavior read in my curriculum. The
internship period exposed me to various formalities and protocols in an organization.
My internship here helped me to develop better team skills, coordination and required me
to do two activities at one time i.e. to get the work done and to do work. This involved
persuading the operations executives for giving me time to discuss the projects and their
process. I had to convince the operations executives that the task which I am performing
is of vital importance to them and organization. I understood the overall process of
market research right from questionnaire fillings to giving the final data to the clients. It
taught me how to work with time constraints and how to coordinate with people from
different backgrounds with different skill sets. In the end I would like to conclude by
saying that the 2 months I spent with The Nielsen Company were the most fruitful in
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terms of learning and it has opened up my mind and given several new dimensions to my
personality.
Bibliography:
[1] http://www.fundinguniverse.com/company-histories/ACNielsen Corporation-
Company
[2] http://www.nextbillion.net/news/why-small-packs-make-sense-for-fmcg-cos
[3] http://www.hindustantimes.com/Focus-on-pushing-low-unit-packs/Article1-
320847.aspx
[4] http://www.neytri.com/how-small-packs-pay-off-big
[5] en.wikipedia.org/wiki/Market_research
[6] managementhelp.org/mrktng/mk_rsrch/mk_rsrch.htm
[7] http://www.infibeam.com/Books/info/naresh-k-malhotra/marketing-research-5-e-
applied-orientation/9788131723173.html
59
http://www.fundinguniverse.com/company-histories/ACNielsen%20Corporation-http://www.nextbillion.net/news/why-small-packs-make-sense-for-fmcg-coshttp://www.hindustantimes.com/Focus-on-pushing-low-unit-packs/Article1-320847.aspxhttp://www.hindustantimes.com/Focus-on-pushing-low-unit-packs/Article1-320847.aspxhttp://www.infibeam.com/Books/info/naresh-k-malhotra/marketing-research-5-e-applied-orientation/9788131723173.htmlhttp://www.infibeam.com/Books/info/naresh-k-malhotra/marketing-research-5-e-applied-orientation/9788131723173.htmlhttp://www.fundinguniverse.com/company-histories/ACNielsen%20Corporation-http://www.nextbillion.net/news/why-small-packs-make-sense-for-fmcg-coshttp://www.hindustantimes.com/Focus-on-pushing-low-unit-packs/Article1-320847.aspxhttp://www.hindustantimes.com/Focus-on-pushing-low-unit-packs/Article1-320847.aspxhttp://www.infibeam.com/Books/info/naresh-k-malhotra/marketing-research-5-e-applied-orientation/9788131723173.htmlhttp://www.infibeam.com/Books/info/naresh-k-malhotra/marketing-research-5-e-applied-orientation/9788131723173.html8/7/2019 Garry Project final
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Appendix:
Questionnaire 1 - LUP capture
Dealer Code: 1310101001 1-11 Date of audit:
Q.1. HOW MANY TIMES IN A MONTH DO YOU PURCHASE THE FOLLOWING?
NOT
STOCKED
MORE THAN
ONCE A WEEK
ONCE A
WEEK
ONCE IN
15 DAYS
ONCE IN A
MONTH
Shampoo 1 1 2 3 4 530
Shampoo 2 1 3 3 4 531
Soap 1 1 3 3 4 532
Cream 1 1 3 3 4 533
Cream 2 1 3 3 4 534
Coffee 1 1 3 3 4 535
Coffee 2 1 3 3 4 536
Coffee 3 1 3 3 4 537
Tea 1 1 3 3 4 538
Tea 2 1 3 3 4 539
Tea 3 1 3 3 4 540
Q.2. HAS THE NUMBER OF TIMES YOU PURCHASE THE PRODUCT CHANGED OVER LAST YEAR?
INCREASED DECREASEDSAME AS
LASTYEAR
Shampoo 1 1 2 3 41
Shampoo 2 1 3 3 42
Soap 1 1 3 3 43
Cream 1 1 3 3 44
Cream 2 1 3 3 45
Coffee 1 1 3 3 46
Coffee 2 1 3 3 47
Coffee 3 1 3 3 48
D D M M Y Y
60
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Tea 1 1 3 3 49
Tea 2 1 3 3 50
Tea 3 1 3 3 51
Q3. HAS THE PROPORTION OF PURCHASE RECORD METHOD CHANGED OVER LAST YEAR?
INVOICE/KUCCHA
BILLSPRB
NO DOCUMENTSAT ALL
TOTAL
Shampoo 1CURRENT - - - 100%
CHANGE OVER LAST YEAR 52-54
Shampoo 2
CURRENT - - - 100%
CHANGE OVER LAST YEAR 55-57
Soap 1CURRENT - - - 100%
CHANGE OVER LAST YEAR 70-78
Cream 1CURRENT - 0% - 100%
CHANGE OVER LAST YEAR 79-87
Cream 2CURRENT 0% 0% 100% 100%
CHANGE OVER LAST YEAR 88-96
Coffee 1CURRENT - - - 100%
CHANGE OVER LAST YEAR 97-105
Coffee 2CURRENT - - - 100%
CHANGE OVER LAST YEAR 106-114
Coffee 3CURRENT - - - 100%
CHANGE OVER LAST YEAR 115-123
Tea 1CURRENT - - - 100%
CHANGE OVER LAST YEAR 124-132
Tea 2CURRENT - - - 100%
CHANGE OVER LAST YEAR 133-141
Tea 3CURRENT - - - 100%
CHANGE OVER LAST YEAR 142-150
PLEASE USE FOLLOWING CODES FOR CHANGE OVER LAST YEAR
INCREASED 1DECREASED 2
SAME AS LAST YEAR 3
61
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62
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G T L 1-7PROJECT I THINK I SAW A
TOOTHBRUSH
DEALER NUMBER
8-1213-14 15-18
19-20
TOWN CODE MSISDN NUMBER (10 Digit)
1. What is the outlets nature of business?(Single response)
Products
Groceries/Consumer/FoodProducts/
1
General Store 2
Chemist 3
Cosmetics Store 4
Paan Plus / Others 5 33
2. Please Observe and record if any POS or Tooth brush is visible
Yes No
1 POS materialVisible
1 234
2 Toothbrushvisible
1 235
Section 1: POS MATERIAL
3. Please circle brand/s for which POS material is visible.FOR ALL THE BRANDS CODED IN Q3 ADMINISTER Q44. For brands where POS material is visible, please circle type/s of POS visible
Q3
Brand
Q4 Type of POS material
PosterDangle
r
Buntings/Streamers
Other
1 Brand A 1 2 3 4 36-402 Brand B 1 2 3 4 41-453 Others Pls. Specify 1 2 3 4 46-50
63
Supervisor Name: ________________Status SC /NAReasons if NA: ____________________Back Check _Date
IF CODED 1 FOR POS ORTOOTHBRUSH GOTO Q3IF 2 CODED FOR BOTH TERMINATE
SURVEY
Questionnaire 2-Toothbrush visibility survey
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SECTION 2: LOCATION AND SKUs ON DISPLAY
5. Please circle brand/s for which SKUs are visible when standing in front ofcounter and looking in all 4 directions.
6. For brands where SKUs are visible, please enter count of each brand ateach location.
Q5
Q6DoorDispl
ay
GlassCounter
Display Rack Hanging Display
FacingCustomer
NotFacingCustomer
WallBehind
Counter
Wallsto
Sideof
Retailer
WallBehindConsumer
01
BrandA(1)
51-
6602
BrandA (2)
67-82
03
BrandA (3)
83-98
04
BrandA (4)
99-114
05
BrandAOther
s
115-130
06
BrandB (1)
131-146
07
BrandB (2)
147-162
08
BrandB (3)
163-178
09
BrandB
179-194
10
BrandB -Others
195-210