Data collection over view - BR final

8/14/2019 Data collection over view - BR final

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Business Research

Presentation on Data collection


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Good After noon Friends

Our team members are..


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Market research

The process of collecting, recording andanalyzing the data available, in order to help

the company understand and analyze itsmarket and prospective customers.

It includes the monitoring of marketingobjectives, targets and goals and alsoanalyzes the strategies of the competitors.With the help of market research, a companycan understand the needs of its customersand can satisfy their needs and demand and

try to deliver them the best possible productand services that matches their style andtaste.


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Consumermarket research is a form ofapplied sociology that concentrates onunderstanding the behaviors, whims and

preferences, of consumers in a market-basedeconomy, and aims to understand the effectsand comparative success of marketingcampaigns.

Thus marketing research is the systematicand objective identification, collection,analysis, and dissemination of information forthe purpose of assisting management in

decision making related to the identificationand solution of problems and opportunities inmarketing. The goal of marketing research isto identify and assess how changing

elements of the marketing mix impacts


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Data collectiondata collection includes the

collection of all the relevant information about

the consumers, their taste, needs andpreferences. This is the initial step before

moving further with the market research. The

market relies on the data gathered.

The collected data is first divided into primary

and secondary categories.

The primary data is collected in the field itself.

The secondary data is collected from thealready available material on the subject and

by rule is always referred to first while doing

desk research.


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Data collection

The Backbone of Market Research Data collection is an important step in the market research

process. It involves Gathering information about customers, competitors, and the

market to help companies improve existing products and servicesand launch new products or services, expand into new markets,and create marketing plans. This process can be performed on alarge or small scale and can involve both qualitative andquantitative data. By utilizing the Internet, data collection allowsfor a broad range of consumer feedback on behaviors,perceptions, needs, attitudes, and opinions. Data collectionprojects range from simple habits and attitudes questionnaires,which gather data from a large number of consumers, to complexin-home product testing, which gather in-depth consumer insight.

Though data collection by means of the Internet provides a cost-effective approach to market research, at times traditionalmethods such as focus groups and in-home interviewing canprove to be effective as well.


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Desk researchdesk research includes the

collection of secondary data (already

collected data), be it published orunpublished. It can be collected from the

companys production, sales marketing and

finance records. Besides this you can even

get secondary data from governmentpublications on the Internet such as

governments expenditure and food survey,

which shows how much amount the

households spend along with the changingsocial trends of the country. Mintel, a

commercial research organization and other

similar organizations provide market research

reports, which are accessible on the Internet.


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Sampling/sample surveysMarket researchcompanies commonly use this method to collect fileddata. Convenience sampling involves gathering

information from a focus group, which is easy toaccess. For example you can interview peoplewalking on the road or traveling in buses. Apart fromconvenience sampling, judgment sampling and quotasampling are also commonly used sampling

methods. QuestionnairesThis is one of the commonly

used methods for collecting information whilecarrying out the market research. Surveys

carried out by this method, can be conductedover the telephone or through personalinterviews or even via Internet. Answering thequestionnaires is not a difficult task. It can

provide you with detailed and requisiteinformation.


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Telephone interviewsthis method is best suited

when the company urgently requires the information.

It has been noted that in the present day context,consumers prefer to answer questionnaires; framed

by the market research companies, online rather than

giving a personal interview

Personal interviewsin this method the person beinginterviewed, has to answer all the questions in

personal to the interviewer. In the case of semi-

structured interviews, all the order and wording of the

question is mentioned in the questionnaire and the

response is open ended and the person being

interview is free to answer the questions in his words.

Unstructured interviews include questions that have

to be covered in a relaxed fashion.


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Other Technologies In addition to the Internet, marketing research has benefited from other

technological improvements including:

Virtual Reality and Simulations - Marketers can use computerdeveloped virtual worlds to simulate real world customer activity suchas store shopping. While this type of research is mostly performed in acontrolled laboratory setting, there are emerging virtual worlds on theInternet where marketers can test concepts and communicate withcustomers.

Global Positioning Systems GPS enables marketers to trackinventory and even track mobile sales and service personnel. SoonGPS will be a common feature of customers communication devices,such as cell phones, offering marketers the potential to locate andtrack customers.

Data Analysis Software As we will see in the Planning for MarketResearch Tutorial, research includes gathering information and it alsoinvolves analyzing what is collected. A number of software andstatistical programs have been refined to give marketers greaterinsight into what the data really means.


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Affordable Research

For many years formal research projects were

considered something that only the largestmarketers could afford due to the expense ofcarrying out relevant research. However, thetechnologies discussed above make itaffordable for companies of all sizes toengage in research that were financiallyprohibitive just few years ago. For instance,surveying customers is quick and easy usingone of the many online survey services which

charge low fees to create, distribute andanalyze results.


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What is Primary Research?

When research is conducted to unearth

original data, it is called primary research.To do this, an original research plan must

be devised which will encompass, data

collection, data input and then theproduction and analysis of the subsequent

results. Due to the sometimes lengthy

duration of this research it can often be

expensive to conduct. However, because

the research is original, the results gathered

will be more relevant to the needs of the

client.


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Types of Primary ResearchIn general there are two basic types of primary research

quantitative data collection and qualitative data collection. Quantitative Data Collection

Quantitative data collection involves the use of numbersto assess information. This information can then beevaluated using statistical analysis which offersresearchers the opportunity to dig deeper into thedata and look for greater meaning. (we will look in

step 6)Certain information is by nature numerical. For

example, asking a person their actual age or yearlyincome will result in a number. But under the rightcircumstances numbers can also be used to

represent certain characteristics which are not on thesurface considered numerical. This most oftenoccurs with data collected within a structured andwell-controlled scientific research design. Forinstance, research of customers attitude toward acompanys products may include the following:


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Place an "X" on the line that best indicates yourimpression of the overall quality of our companysproducts:

Poor _ _ _ _ _ _ _ Excellent In this example each line, which represents a

potential customer response, could be assigned anumber. For example, checking the left-most linecould result in the researcher entering a 1, the nextline a 2, the next line a 3 and so on. Onceresearch is completed this question can undergostatistical analysis.

While quantitative analysis is potentially used for all

types of research purposes (Step 1) it is most criticalfor hypothesis testing. As discussed below in Step 6:Analyze Data, such analysis may prove very relevantby allowing the researcher to draw conclusions.


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Types of Quantitative Data Collection

Quantitative data collection comes in many forms butthe most popular forms are surveys, tracking and

experiments. Surveys - This method captures information throughthe input of responses to a research instrumentcontaining questions (i.e., such as a questionnaire)..Information can be input either by the respondents

themselves (e.g., complete online survey) or theresearcher can input the data (e.g. phone survey,mall intercept). The main methods for distributingsurveys are via postal mail, phone, website or inperson. However, newer technologies are creating

additional delivery options including through wirelessdevices, such as smart phones.


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Tracking - With tracking research marketers are ableto monitor the behavior of customers as they engagein regular purchase or information gathering

activities. Possibly the most well-known example oftracking research is used by websites as they trackcustomer visits. But tracking research also hasoffline applications, especially when point-of-purchase scanners are employed, such as trackingproduct purchases at grocery stores and automated

collections on toll roads. This method of research isexpected to grow significantly as more devices areintroduced that provide means for tracking. However,as we discussed in the Marketing Research Tutorial,some customers may see tracking devices as

intrusive and many privacy advocates have raisedconcerns about certain tracking methods especially ifthese are not disclosed to customers.


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Experiments - Marketers often undertakeexperiments to gauge how the manipulation of onemarketing variable affects another (i.e., causal

research). The use of experiments has applicationsfor many marketing decision areas including producttesting, advertising design, setting price points andcreating packaging. For example, a marketresearcher for a retail chain may want to study the

effect on sales if a product display is moved todifferent locations in a store. Unfortunately,performing highly controlled experiments can be quitecostly. Some researchers have found the use ofcomputer simulations can work nearly as well as

experiments and may be less expensive, though thenumber of simulation applications for marketingdecisions is still fairly limited.


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What is Qualitative Research

Qualitative research is used to help us

understand how people feel and why they

feel as they do. It is concerned with

collecting in-depth information asking

questions such as why do you say that?.Samples tend to be smaller compared with

quantitative projects that include much larger

samples. Depth interviews or groupdiscussions are two common methods used

for collecting qualitative information.


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Qualitative Data Collection Sometimes referred to as touchy-feely research,

qualitative data collection requires researchers tointerpret the information gathered, most often withoutthe benefit of statistical support. If the researcher iswell trained in interpreting respondents commentsand activities, this form of research can offer verygood information. However, it may not hold the samelevel of relevancy as quantitative research due to the

lack of scientific controls with this data collectionmethod. For example, a researcher may want toknow more about how customers make purchasedecisions. One way to do this is to sit and talk withcustomers using one-on-one interviews. However, ifthe interview process allows the researcher to varywhat questions are asked (i.e., not all respondentsare asked the same questions), then this type ofresearch may lack controls needed to follow ascientific approach.


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An additional drawback of qualitative research is thatit can be time consuming and expensive and,

consequently, only a very small portion of themarketers desired market can participate inqualitative research. Due to the lack of strongcontrols in the research design (i.e., not as wellstructured, fewer participants), using results to

estimate characteristics of a larger group is moredifficult. Thus, qualitative data collection is generallynot used for hypothesis testing. This is not to sayqualitative research is not useful, it is very useful if itslimitations are understood.It is widely employed for

marketing research especially for research for thepurpose of discovery, and to a lesser extent,explanation.


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Types of Qualitative Data Collection Qualitative data collection options

include personal interviews, focus groups and

observational research. Personal Interviews - Talking to someone

one-on-one allows a researcher to covermore ground than may be covered if a

respondent was completing a survey. Thereason lies with the researchers ability to digdeeper into a respondents comments to findout additional details that might not emergefrom initial responses. Unfortunately,

individual interviewing can be quite expensiveand may be intimidating to some who are notcomfortable sharing details with a researcher.


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Focus Groups - To overcome the drawbacksassociated with personal interviews, marketers can turnto focus groups. Under this research format, a group ofrespondents (generally numbering 8-12) are guided

through discussion by a moderator. The power of focusgroups as a research tool rests with the environmentcreated by the interaction of the participants. In well-run sessions, members of the group are stimulated torespond by the comments and the support of others in

the group. In this way, the depth of information offeredby a respondent may be much greater than thatobtained through individual interviews. However, focusgroups can be costly to conduct especially ifparticipants must be paid. To help reduce costs, onlineoptions for focus groups have emerged. While there

are many positive aspects to online focus groups, thefact that respondents are not physically presentdiminishes the benefits gained by group dynamics.However, as technology improves, in particular videoconferencing, the online focus group could become a

major research option.


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Observational Research - Watching

customers as they perform activities can be avery useful research method, especially when

customers are observed in a natural setting

(e.g., shopping in a retail store, using

products at home). In fact, an emergingresearch technique called ethnographic

research has researchers following

customers as they shop, work, and relax at

home in order to see how they makedecisions, use products and more.


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Evaluate Data

The researchers next task is to make sense of the collected data.Before the researcher can gain understanding from the collected data,he/she must first examine the raw information (i.e., what was actuallycollected) to make sure the information exists as required. There are

many reasons why data may not be presented in the form needed forfurther analysis. Some of reasons include:

Incomplete Responses This most likely occurs when the method ofdata collection (e.g., survey) is not fully completed, such as when theperson taking part in the research fails to provide all information (e.g.,skips questions).

Data Entry Error This exists when the information is not recordedproperly which can occur due to the wrong entry being made (e.g., entryshould be choice B but is entered as choice C) or failure of data entrytechnology (e.g., online connection is disrupted before full completion ofsurvey).

Questionable Entry This occurs when there are apparent

inconsistencies in responses such as when a respondent does notappear to be answering honestly.


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To address these issues the researcher

will take steps to cleanse the data

which may include dropping problematicdata either in part (e.g., exclude a single

question) or in full (e.g., drop an entire

survey). Alternatively, the research

may be able to salvage some problem

data with certain coding methods,

though a discussion of these is beyond

the scope of this class presentation butstill lets see we will cover in cleaning

data.


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Analyze Data

With the data in a form that is now useful, the

researcher can begin the process ofanalyzing the data to determine what hasbeen learned. The method used to analyzedata depends on the approach used to collectthe information (secondary research, primaryquantitative research or primary qualitativeresearch). For primary research the selectionof method of analysis also depends on thetype of research instrument used to collect

the information. Essentially there are twotypes of methods of analysis descriptiveand inferential


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1. Descriptive Data Analysis : Not to be confused withdescriptive research, descriptive analysis, as thename implies, is used to describe the results

obtained. In most cases the results are merely usedto provide a summary of what has been gathered(e.g., how many liked or dislike a product) withoutmaking a statement of whether the results hold up tostatistical evaluation. For quantitative data collection

the most common methods used for this basic levelof analysis are visual representations, such as chartsand tables, and measures of central tendencyincluding averages (i.e., mean value). For qualitativedata collection, where analysis may consist of the

researchers own interpretation of what was learned,the information may be coded or summarized intogrouping categories.


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Inferential Data Analysis While descriptive data analysis can present a picture of the results,

to really be useful the results of research should allow theresearcher to accomplish other goals such as:

Using information obtained from a small group (i.e., sample ofcustomers) to make judgments about a larger group (i.e., allcustomers)

Comparing groups to see if there is a difference in how theyrespond to an issue

Forecasting what may happen based on collected information

To move beyond simply describing results requires the use ofinferential data analysis where advanced statistical techniques areused to make judgments (i.e., inferences) about some issue (e.g., isone type of customer different from another type of customer).Using inferential data analysis requires a well-structured researchplan that follows the scientific method. Also, most (but not all)inferential data analysis techniques require the use of quantitativedata collection.


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As an example of the use of inferential dataanalysis, a marketer may wish to know ifNorth American, European and Asian

customers differ in how they rate certainissues. The marketer uses a survey thatincludes a number of questions askingcustomers from all three regions to rate

issues on a scale of 1 to 5. If a survey isconstructed properly the marketer cancompare each group using statistical softwarethat tests whether differences exists. This

analysis offers much more insight than simplyshowing how many customers from eachregion responded to each question.


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Communicate Results : The final stage inthe marketing research process is to reportthe findings. For marketers doing small-scale

research for their own purposes,communication may be quite informal. Themarketer may simply draw conclusions fromwhat he or she gleans from the data

analysis. For more serious marketingresearch projects, those conducting theresearch will prepare a written report outliningwhat was researched and offer results.

Additionally, an oral presentation may berequired in which the research is explainedwithin a slide presentation.


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Other Methods

Exploratory data analysis (EDA) is an

approach to analyzing data for the purpose of

formulating hypotheses worth testing,

complementing the tools of conventional

statistics for testing hypotheses. It was so

named by John Turkey to contrast withConfirmatory Data Analysis, the term used for

the set of ideas about hypothesis testing, p-

values, confidence intervals etc. which

formed the key tools in the arsenal ofpracticing statisticians at the time.


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Dimensional analysis is a conceptual tooloften applied in physics, chemistry, andengineering to understand physical situations

involving certain physical quantities. It isroutinely used by mathematicians,statisticians, physical scientists and engineersto check the plausibility of derived equationsand computations. It is also used to form

reasonable hypotheses about complexphysical situations that can be tested byexperiment or by more developed theories ofthe phenomena, and to categories types ofphysical quantities and units based on theirrelations to or dependence on other units, ortheir "dimensions", or their lack thereof.


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Dimensional analysis was developed by the 19thcentury French mathematician Joseph Fourier, basedon the idea that the physical laws like F = ma shouldbe independent of the units employed to measure thephysical variables. This led to one to the conclusionthat meaningful laws must be homogeneousequations in their various units of measurement.Furthermore, and, most important, it provides amethod for computing these dimensionless

parameters from their variables. A dimensional equation can have the dimensionsreduced or eliminated through nondimensionalization,which begins with dimensional analysis, and involvesscaling quantities by characteristic units of a system

or natural units of nature. This gives insight into thefundamental properties of the system, as illustrated inthe examples below.


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Multivariate analysis (MVA) is based on the statistical principleof multivariate statistics, which involves observation andanalysis of more than one statistical variable at a time. In designand analysis, the technique is used to perform trade studiesacross multiple dimensions while taking into account the effectsof all variables on the responses of interest.

Uses for multivariate analysis include: Design for capability (also known as capability-based design) Inverse design, where any variable can be treated as an

independent variable

Analysis of alternatives, the selection of concepts to fulfill acustomer need Analysis of concepts with respect to changing scenarios Identification of critical design drivers and correlations across

hierarchical levels


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Multivariate analysis can be complicated by thedesire to include physics-based analysis to calculatethe effects of variables for a hierarchical "system-of-systems." Often, studies that wish to use multivariateanalysis are stalled by the dimensionality of theproblem. These concerns are often eased throughthe use of surrogate models, highly accurateapproximations of the physics-based code. Since

surrogate models take the form of an equation, theycan be evaluated very quickly. This becomes anenabler for large-scale MVA studies: while a MonteCarlo simulation across the design space is difficultwith physics-based codes, it becomes trivial when

evaluating surrogate models, which often take theform of response surface equations.


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Statistics is a mathematical science pertaining to the collection,analysis, interpretation or explanation, and presentation of data.It also provides tools for prediction and forecasting based ondata. It is applicable to a wide variety of academic disciplines,from the natural and social sciences to the humanities,

government and business. Statistical methods can be used to summarize or describe a

collection of data; this is called descriptive statistics. In addition,patterns in the data may be modeled in a way that accounts forrandomness and uncertainty in the observations, and are thenused to draw inferences about the process or population being

studied; this is called inferential statistics. Descriptive statisticsand inferential statistics (a.k.a., predictive statistics) togethercomprise applied statistics.

There is also a discipline called mathematical statistics, which isconcerned with the theoretical basis of the subject.


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The word statistics can either be

singular or plural. In its singular form,

statistics refers to the mathematicalscience discussed in this article. In its

plural form, statistics is the plural of the

word statistic, which refers to a quantity

(such as a mean) calculated from a set

of data.

Th k Y Li t


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Thank You Listeners

Data collection over view - BR final

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