Marketingo tyrimai

Seminaras Nr.1 – Marketingo tyrimai

1 užduotis:
Pateikti 3-4 autorių požiūrius į marketingo tyrimų sampratą.

1. Antanas Poviliūnas: “Marketingo tyrimai – sistemingas duomenų būtinų dėl iskylančių firmai marketingo situacijų, nustatymas, rinkimas, analizė ir rezultatų ataskaita” [1, 13].
2. Vytautas Pranulis: “Marketingo tyrimai – tai marketingo sprendimams reikalingos informacijos paieška, rinkimas, apdorojimas ir interpretavimas” [3, 99].
3. Джоель Эванс, Берман Барри: “Маркетинговое исследование – это систематический сбор, отражение и анализ данных о проблемах, связанных с маркетингом товаров н услуг; кроме того, это комплексное понятие, которое включает все виды исследовательской деятельности, связанные с управлением маркетингом” [5, 58].

Mano nuomone, geriausiai marketingo tyrimų sampratą aprasė V.Pranulis, kurio manymu, būtina rinkti reikiamą informaciją, ją apdoroti, tinkamai suprasti bei įvertinti, norint priimti tinkamus marketingo sprendimus. Tačiau viena aišku, marketingo tyrimai yra būtini, norint sėkmingai vystyti savo veiklą.

2 užduotis:
Pateikti 3 autorių nuomonę apie marketingo tyrimų rūšis: nurodyti kriterijus (pagal ką klasifikuojama) ir kokios rūšys.

1. Vytautas Pranulis:
Marketingo tyrimų rūšys ir metodai
Marketingo tyrimo rūšį nusako tyrimo pobūdis, jo kryptingumas, tikslai bei tyrimo objektas. Remiantis šiais požymiais galima būtų apibūdinti gana daug marketingo tyrimo rūšių:
1) Pagal tyrimo kryptingumą trys marketingo tyrimų rūšys: žvalgybiniai tyrimai, išvadų tyrimai ir veiklos vertinimo (grįžtamojo ryšio) tyrimai.
2) Pagal tiriamą objektą skiriami: išorinės marketingo aplinkos tyrimai, vidinės marketingo aplinkos tyrimai, vartotojų tyrimai.
3) Pagal teorinį lygį bei praktinį pritaikomumą skiriami fundamentalieji ir taikomieji marketingo tyyrimai.

Žvalgybinis tyrimas. Išaiškina ir apibrėžia marketingo tikslus, prasmę, problemas, galimybes. Atliekamas pradinėse tyrimo stadijose. Žvalgybinio tyrimo metu gali paaiškėti, kokie tyrimo rezultatų iškraipymo pavojai kyla (ar ne) dėl senėjimo ar kitų reiškinių, nustatyti tyrimui ir projekto įgyvendinimui turinčius reikšmės vietinius di

ialektus ir žargonus, išsiaiškinti tyrimo atlikimo sunkumus, taip pat antrinių ir pirminių duomenų šaltinius, galimybes pasitelkti vietinius ekspertus.
Išvadų tyrimas. Įvertina veiksmų kryptį. Padeda įvertinti pasirinktą veiklos būdą ir duoda pagrindą padaryti išvadas dėl šio būdo tinkamumo arba tobulinimo krypčių. Tyrime privalo būti aiškiai apibrėžtas jo tikslas, aiškus ir suformuotas jo vykdymo planas, numatytos imčių atrinkimo procedūros, duomenų rinkimo ir jų apdorojimo metodai.
Veiklos vertinimo ( grįžtamojo ryšio) tyrimai. Padedantis kontroliuoti, kaip vykdomi marketingo planai, kaip ir kiek sutampa numatyti ir realiai gaunami veiklos rezultatai. Apima ne vien marketingo komplekso elementus, bet ir kitus rodiklius, pavyzdžiui, pardavimų apimtis, rinkos dalies dydį, pelną, investuotam kapitalui tenkančias įplaukas.
Kiekybiniai ir kokybiniai marketingo tyrimai.
Kokybiniai:
Nėra iki galo išbaigti, dinamiški ir lankstūs.
Gilinamasi į suvokimo problemą.
Išsiaiškinami vartotojų kūrybiškumas, jausmai, emocijos, poožiūriai.
Didesnė duomenų bazės įvairovė.
Pateikiami racionalūs pavyzdžiai ar pavieniai atsakymai.
Didesni marketingo veiklos ir kūrybinių idėjų ištekliai.
Kiekybiniai:
Matuojama statistiškai ir skaitmenimis.
Grupių, imčių palyginimai.
Tyrimas gali būti pakartotas ateityje ir lyginami rezultatai.
Dominuoja individų atsakymo ir elgesio pavyzdžių srautai.
Mažiau priklauso nuo tyrimo vykdytojų meistriškumo ir orientacijos.
Vartotojų tyrimai. Žinoti vartotojų norus, reikmes ir kiek įmanoma geriau šiuos norus ir reikmes tenkinti. Labai svarbu turėti nuolatinį ryšį su vartotojais ir gauti informaciją iš jų ir apie juos.
Taikomieji ir fundamentalieji marketingo tyrimai. Fundamentalieji tyrimai atliekami siekiant praplėsti žinojimo ribas. Ne
esiekia specifinių pragmatinių tikslų. Dažniausiai dirba akademinės pakraipos mokslininkai. Taikomieji tyrimai vykdomi specifinių pragmatinių problemų sprendimo tikslais siekiant geriau pažinti realią rinką, išsiaiškinti kur yra netinkama taktika ar strategija, šalinti vadybos sprendimų neapibrėžtumą. Konsultavimas yra specifinių marketingo ir kitų vadybos žinių perteikimas ir panaudojimas, padedantis pasiekti užsibrėžtus verslo tikslus ir rezultatus.
Išorinės marketingo aplinkos tyrimas. Marketingo kompleksą tenka keisti, nes keičiasi aplinka, kurioje veikia įmonė, gyvena, dirba ir apsprendžia pirkėjai. Aplinkos pažinimas padeda įmonėms keisti ne tik dabartinį jų marketingo kompleksą, bet ir išsiaiškinti naujas galimybes.
Vidinės marketingo aplinkos tyrimas. Galima atlikti įmonės vidinio marketingo tyrimą ir gauti svarbios informacijos apie įmonės veiklos, jos personalo tobulinimo poreikius, kryptis ir galimybes.
[2, 30-33]

2. Regina Virvilaitė:
Marketingo tyrimų tipai:
• Pažintiniai
• Aprašomieji
• Priežastiniai

Jie skiriasi tyrimų tikslais, tiriamais klausimais, hipotezių patikimumu ir duomenų rinkos metodais.
Pažintiniai tyrimai pasitelkiami tada, kai reikia bendro supratimo apie problemą, galimus alternatyvius sprendimus ir veiksnius, kuriuos reikia įvertinti.
Hipotezės yra netikslios arba visai neegzistuoja. Jie naudingi, kai siekiama nustatyti tiriamųjų klausimų prioritetus bei išsiaiškinti praktines tyrimų eigos problemas.
Aprašomieji tyrimai sudaro didžiausią rinkos tyrimų dalį. Jų tikslas – pateikti tikslią informaciją apie tam tikrus marketingo aplinkos aspektus. Hipotezės egzistuoja, bet dažnai būna netikslios. Tiriamųjų ryšių kilmė nėra priežastinė. Tačiau tyrimų rezultatai yra naudingi, nuodugniau nagrinėjant iškilusią problemą.
Priežastiniai tyrimai praverčia tada, kai re

eikia parodyti, kad vienas kintamasis yra kito priežastis arba nulemia pastarojo reikšmes.
Jie parodo, kad du kintamieji yra susiję. Tai svarbu atliekant priežastinius tyrimus, nes kitaip negalima teigti, kad egzistuoja prižastinis ryšys.
Marketingo tyrimams svarbus respondentų parinkimas. Respondentų parinkimo plane turi būti numatytas jų parinkimo metodas.
Vienas iš būdų yra tikimybinis parinkimas. Čia yra tikimybė visiems gyventojams patekti į apklaustųjų tarpą. Šis metodas tinka, kai reikia parodyti, kaip parinktoji grupė atstovauja visiems gyventojams.
Jei renkama nedidelė respondentų grupė arba informacijos tikslumui nekeliami aukšti reikalavimai, remiamasi netikimybiniais respondentų parinkimo metodais.
Taip pat labai svarbu nustatyti respondentų grupių dydį, nes tai daro įtaką tyrimų biudžetui ir rezultatų patikimumui.
Esama nemažai duomenų rinkimo tipų. Pagal duomenų šaltinius jie skirstomi į grupes:

• Antriniai duomenys;
• Pirminiai duomenys

Antrinius duomenis nesunku gauti, nes jie jau yra surinkti kokiems nors tikslams. Paprastai išskiriami šie antriniai duomenų šaltiniai:
• Įmonės marketingo informacinė sistema (MIS);
• Kitų organizacijų ir valstybiniai duomenų bankai;
• Informacinių organizacijų duomenų šaltiniai.

Pirminiai duomenys renkami, problemos sprendimui prireikus specifinės informacijos arba susiklosčius nestandartinei situacijai. Jie renkami tokiais pirminių duomenų rinkimo metodais:

• Kokybiniai metodai; tai bendro pobūdžio interviu, padedantys iškelti hipotezes (pavyzdžiui, ekspertų nuomonė);
• Tiriamieji metodai; tai konkrečios informacijos rinkimas iš specialiai parinktų respondentų (pavyzdžiui, asmeniniai, pašto ir telefoniniai interviu);
• Eksperimentiniai metodai; nustato vieno kintamojo įtaką kitam (pavyzdžiui, laboratoriniai eksperimentai).
[4, 120-121]

3. http://www.smenet.com.vn/counsel/marketresearch.htm

Marketing research can involve an in

nvestigation of any of the elements of the marketer’s task. In particular it could involve looking at competitors, marketing channel members such as distributors and suppliers and the components of the marketing mix as well as the narrowly defined market research of consumers. Types of marketing research:
Desk Research & Field Research
Desk research Field research

Seeks existing (published) data
Provides original data

Uses internet or libraries
Uses “live” interviews or discussions

Often not exactly what is needed
Can be tailored to your exact needs

Sometimes incomplete or out of date
Expensive to collect

Cheap and relatively quick to collect
Quite time-consuming to collect

Best conducted internally
Often best delegated to specialists
Qualitative Research & Quantitative Research
Qualitative research Quantitative research

Why respondents do?
How many respondents do?

explaining and understanding
describing and measuring

interpretative/impressionistic
precise/definitive/scientific

taps consumer creativity, dynamic, flexible
standardized, repeatable

depth/richness of understanding
subgroup sampling or comparisons

intensive
structured

quota sampling of individuals/groups covering a range of opinions probabilistic sampling to represent a segment of the market

topic guide, open ended questions
pre-coded questions on structured questionnaire

interpretation
numerical analysis/statistic

provides ideas, insights and hypotheses
provides conclusions

Mano manymu, geriausia ir išsamiausia informacija apie marketingo tyrimų rūšis yra apibūdinama V.Pranulio užrašuose. Kitose publikacijose yra pateikiamos ne visos arba ne pagrindinės marketingo tyrimų rūšys. Mano nuomone, svarbiausios tyrimų sritys turėtų būti vidinė ir išorinė marketingo aplinkos, nes čia atrandama dauguma visų įmonės problemų. Jas numačius galima būtų sėkmingiau konkuruoti rinkoje.

3 užduotis:
Schematiškai pateikti 3-4 autorių požiūrį į marketingo tyrimų procesą (etapus): etapų pateikimas ir jų apibūdinimas.

1. Vytautas Pranulis, Arvydas Pajuodis, Sigitas Urbonavičius, Regina Virvilaitė:
Marketingo tyrimų proceso etapai:

1. Problemos išsiaiškinimas

2. Žvalgybinis tyrimas

3. Tyrimo tikslų nustatymas

4. Tyrimo reikalingumo pagrindimas

5. Tyrimo plano parengimas

6. Duomenų rinkimo metodo parinkimas

7. Imčių atrinkimas

8. Duomenų rinkimas

9. Duomenų analizavimas

10. Tyrimo ataskaitos parengimas ir pateikimas

11. Tyrimo rezultatų įvertinimas ir naudojimas

1. Problemos išsiaiškinimas yra pats svarbiausias marketingo tyrimų etapas. Neteisingai suprasta ar blogai apibrėžta problema visą tyrimą gali padaryti bevertį. Būtina surasti tą svarbiausiąjį klausimą, atsakymas į kurį lemia, ar bus pasiekti verslo strateginiai tikslai. Jau išsiaiškinimo stadijoje pageidautina atsakyti į šiuos klausimus:
1. Kokios informacijos reikės jai spręsti?
2. Ar bus galima pasinaudoti antrine informacija, ar teks rinkti pirminę?
3. Ar marketingo tyrimas leis pakankamai atsakyti į svarbiausius problemos klausimus?
Problemos išsiaiškinimo stadijoje reikia nustatyti, ar problema iš tikrųjų reali ir aktuali, o ne tariama ar išgalvota ir ar lėšos, darbas, laikas nebus eikvojami mažareikšmiams antreiliams dalykams.
2. Žvalgybinis tyrimas atliekamas siekiant geriau suprasti problemos turinį, kilmę ir aplinką, kurioje ji iškilo ir egzistuoja. Dažniausiai remiasi antrine informacija. Tačiau kartais gali vykti ir laisvos formos apklausos, laisvi pokalbiai, stebėjimai.
3. Tyrimo tikslų nustatymas. Reikia apibrėžti svarbiausiąjį ir šalutinius tyrimo tikslus, aiškiai pasakant, ko tyrimu norima pasiekti. Marketingo tyrimų tikslai dažniausiai būna susiję su informacijos, reikalingos ir tinkamos aiškiai žinomai valdymo problemai spręsti, rinkimu, apdorojimu, interpretavimu ir panaudojimu. Geriausias būdas užtikrinti tyrimo veiksmingumą – numatyti tyrimo rezultatų įdiegimo programą.
4. Tyrimo reikalingumo pagrindimas. Tyrimo reikalingumas iš esmės nustatomas griežtai ir aiškiai suformuluojant problemą ir parūpinant jos sprendimui reikalingų lėšų.
5. Tyrimo plano parengimas. Numatymas to, kaip bus atsakoma į tiriamosios problemos klausimus
6. Duomenų rinkimo metodo parinkimas. Nusprendžiama, kokiu būdu bus gaunami tyrimo duomenys, kurie iš žinomų metodų – apklausa, stebėjimas, eksperimentas, fokusuota grupė – bus naudojami kaip pagrindiniai ir kurie kaip pagalbiniai.
7. Imčių atrinkimas. Reikia nuspręsti, kokiu būdu – tikimybiniu ar netikimybiniu ir kaip konkrečiai – bus atrenkamos imtys, koks bus jų dydis.
8. Duomenų rinkimas. Parengiami klausimynai, stebėjimo informacijos užrašymo formos, kokybinio tyrimo instrukcijos.
9. Duomenų analizavimas. Analizės tikslas yra sugrupuoti, susisteminti, išnagrinėti surinktus duomenis ir tuo remiantis parengti išvadas bei siūlymus. Dažniausiai pasitelkiama skaičiavimo technika ir speciali programinė įranga.
10. Tyrimo ataskaitos parengimas ir pateikimas. Reikia parengti tokią ataskaitą, kuri įtikintų užsakovus, jog gauti rezultatai yra teisingi, patikimi ir pagrįsti surinktais duomenimis. Ataskaita pateikiama rašytinė arba žodinė.
11. Tyrimo rezultatų įvertinimas ir naudojimas. Kiekvieno tyrimo rezultatus tikslinga įvertinti. Visų pirma , tai padeda suprasti, ar tyrimo rezultatas atitiko numatytus tyrimo tikslus. Antra, atsiranda galimybė nekartoti šio tyrimo klaidų ateityje.Vienas iš pagrindinių būdų pasiekti, kad tyrimų rezultatai būtų naudojami praktikoje, yra pastangos didinti tyrėjų ir vadovų tarpusavio supratimą vengiant įtampos ir konfliktų. Tyrėjo darbas yra užsiimti tyrimais ir parengti sprendimams reikalingą informaciją; vadovo darbas – naudojant šią informaciją priimti sprendimus.
[3, 113-115]

2. Philip Kotler, Gary Armstrong, Peggy H.Cunningham, Robert Warren:
The Marketing Research Process

Defining the problem and research objectives

Developing the research plan for collecting information

Implementing the research plan collecting and analysing the data

Interpreting and reporting the findings

Defining the problem and research objectives

The marketing manager and the researcher must work closely to define the problem carefully, and they must agree on the research objectives. The manager best understands the decision for which information is needed; the researcher best understands marketing research and how to obtain the information.
Managers must know enough about marketing research to help in planning and interpreting research results. If they know little about marketing research, they may obtain the wrong information, accept wrong conclusions, or ask for information that costs too much. Experienced marketing researchers who understand the manager’s problem also should be involved at this stage. The researcher must be able to help the manager define the problem and suggest ways that research can help the manager make better decisions.
Defining the problem and research objectives is often the hardest step in the research process. The manager may know that something is wrong, without knowing the specific causes.
After the problem has been defined carefully, the manager and researcher must set research objectives. A marketing research project might have one of three types of objectives. The objective of exploratory research is to gather preliminary information that will help define the problem and suggest hypotheses. The objective of descriptive research is to describe things such as the market potential for a product or the demographics and attitudes of consumers who buy the product. The objective of causal research is to test hypotheses about cause-and-effect relationships.

Developing the research plan

The second step of the marketing research process calls for determining the information needed, developing a plan for gathering it efficiently, and presenting the plan to marketing management. The plan outlines sources of existing data and spells out the specific research approaches, contact methods, sampling plans, and instruments that researchers will use to gather new data.
Determining specific information needs
Research objectives must be translated into specific information needs.
Gathering secondary information
To meet the manager’s information needs, the researcher can gather secondary data, primary data, or both. Secondary data consist of information that already exists somewhere, having been collected for another purpose. Primary data consist of information collected for the specific purpose at hand.
Researchers usually start by gathering secondary data. Secondary data usually can be obtained more quickly and at a lower cost than primary data. Also, secondary sources sometimes can provide data an individualcompany cannot collect on its own-information that either is not directly available or would be too expensiveto collect.
Secondary data can also present problems. The needed informationmay not exist-researchers can rarely obtain all the data they need from secondary sources. Even when data can be found, they might not be very usable. The researcher must evaluate secondary information carefully to ensure that it is relevant, accurate, and impartial.
Secondary data provide a good starting point for research and often help to define problems and research objectives. In most cases, however, the company must also collect primary data.
Sources of secondary data:
• Internal sources
• Government publications
• Periodicals and books
• Commercial data
• On-line data
• International data

Planning primary data collection
Good decisions require good data. Justas researchers must carefully evaluate the quality of secondary information, they also must take great care when collecting primary data to assure that it will be relevant, accurate, current, and unbiased information. Designing a plan for primary data collection calls for a number of decisions on research approaches, contact methods, sampling plan, and research instruments.
Research approaches:
Observational research is the gathering of primary data by observing relevant people, actions, and situations.
Survey research is the gathering of primary data by asking people questions about their knowledge, attitudes, preferences, and buying behaviour.
Experimental research is the gathering of primary data by selecting matched groups of subjects, giving them different treatments, controlling related factors, and checking for differences in group responses.
Contact methods. Information can be collected by mail, telephone, or personal interview. Mail questionnaires can be used to collect large amounts of information at a low cost per respondent. Telephone interviewing is the best method for gathering information quickly, and it provides greater flexibility than mail questionnaires. Personal interviewing takes two forms-individual and group interviewing. Individual interviewing involves talking with people in their homes or offices, on the street, or in shopping malls. Such interviewing is flexible. Group interviewing consists of inviting six to ten people to gather for a few hours with a trained moderator to discuss a product, service, or organization. The participants typically are paid a small sum for attending.
Sampling plans. Marketing researchers usually draw conclusions about large groups of consumers by studying a small sample of the total consumer population. Designing the sample requires three decisions. First, who is to be surveyed (what sampling unit)? The answer to this question is not always obvious. Second, how many people should be surveyed (what sample size)? Large samples give more reliable results than small samples. Third, how should the people in the sample be chosen (what sampling procedure)?
Research instruments. In collecting primary data, marketing researchers have a choice of two main research instruments-the questionnaire and mechanical devices. The questionnaire is very flexible-there are many ways to ask questions. Questionnaires must be developed carefully and tested before they can be used on a large scale. Mechanical research instruments subjects’ physical responses.

Implementing the research plan

The researcher next puts the marketing research plan into action. This involves collecting, processing, and analysing the information. Data collection can be carried out by the company’s marketing research staff or by outside firms. The company keeps more control over the collection process and data quality by using its own staff. However, outside firms that specialize in data collection often can do the job more quickly and at lower cost.
The data-collection phase of the marketing research process is generally the most expensive and the most subject to error. The researcher should watch field work closely to ensure that the plan is implemented correctly and to guard against problems with contacting respondents, with respondents who refuse to cooperate or who give biased or dishonest answers, and with interviewers who make mistakes or take shortcuts.
Researchers must process and analyse the collected data to isolate important information and findings. They need to check data from questionnaires for accuracy and completeness and code it for computer analysis. The researchers then tabulate the results and averages and other statistical measures.

Interpreting and reporting the findings

The researcher must now interpret the findings, draw conclusions, and report them to management. The researcher should not try to overwhelm managers with numbers and fancy statistical techniques. Rather, the researcher should present important findings that are useful in the major decisions faced by management. Interpretation is an important phase of the marketing process.
[6, 121-135]

3. Quick MBA http://www.quickmba.com/marketing/research/

The Marketing Research Process
Once the need for marketing research has been established, most marketing research projects involve these steps:
1. Define the problem
2. Determine research design
3. Identify data types and sources
4. Design data collection forms and questionnaires
5. Determine sample plan and size
6. Collect the data
7. Analyze and interpret the data
8. Prepare the research report

Problem Definition
The decision problem faced by management must be translated into a market research problem in the form of questions that define the information that is required to make the decision and how this information can be obtained. Thus, the decision problem is translated into a research problem. For example, a decision problem may be whether to launch a new product. The corresponding research problem might be to assess whether the market would accept the new product.

The objective of the research should be defined clearly. To ensure that the true decision problem is addressed, it is useful for the researcher to outline possible scenarios of the research results and then for the decision maker to formulate plans of action under each scenario. The use of such scenarios can ensure that the purpose of the research is agreed upon before it commences.

Research Design
Marketing research can classified in one of three categories:
• Exploratory research
• Descriptive research
• Causal research
These classifications are made according to the objective of the research. In some cases the research will fall into one of these categories, but in other cases different phases of the same research project will fall into different categories.
• Exploratory research has the goal of formulating problems more precisely, clarifying concepts, gathering explanations, gaining insight, eliminating impractical ideas, and forming hypotheses. Exploratory research can be performed using a literature search, surveying certain people about their experiences, focus groups, and case studies. When surveying people, exploratory research studies would not try to acquire a representative sample, but rather, seek to interview those who are knowledgeable and who might be able to provide insight concerning the relationship among variables. Case studies can include contrasting situations or benchmarking against an organization known for its excellence. Exploratory research may develop hypotheses, but it does not seek to test them. Exploratory research is characterized by its flexibility.
• Descriptive research is more rigid than exploratory research and seeks to describe users of a product, determine the proportion of the population that uses a product, or predict future demand for a product. As opposed to exploratory research, descriptive research should define questions, people surveyed, and the method of analysis prior to beginning data collection. In other words, the who, what, where, when, why, and how aspects of the research should be defined. Such preparation allows one the opportunity to make any required changes before the costly process of data collection has begun. There are two basic types of descriptive research: longitudinal studies and cross-sectional studies. Longitudinal studies are time series analyses that make repeated measurements of the same individuals, thus allowing one to monitor behavior such as brand-switching. However, longitudinal studies are not necessarily representative since many people may refuse to participate because of the commitment required. Cross-sectional studies sample the population to make measurements at a specific point in time. A special type of cross-sectional analysis is a cohort analysis, which tracks an aggregate of individuals who experience the same event within the same time interval over time. Cohort analyses are useful for long-term forecasting of product demand.
• Causal research seeks to find cause and effect relationships between variables. It accomplishes this goal through laboratory and field experiments.

Data Types and Sources
Secondary Data
Before going through the time and expense of collecting primary data, one should check for secondary data that previously may have been collected for other purposes but that can be used in the immediate study. Secondary data may be internal to the firm, such as sales invoices and warranty cards, or may be external to the firm such as published data or commercially available data. The government census is a valuable source of secondary data.

Secondary data has the advantage of saving time and reducing data gathering costs. The disadvantages are that the data may not fit the problem perfectly and that the accuracy may be more difficult to verify for secondary data than for primary data.

Some secondary data is republished by organizations other than the original source. Because errors can occur and important explanations may be missing in republished data, one should obtain secondary data directly from its source. One also should consider who the source is and whether the results may be biased.

Primary Data
Often, secondary data must be supplemented by primary data originated specifically for the study at hand. Some common types of primary data are:
• demographic and socioeconomic characteristics
• psychological and lifestyle characteristics
• attitudes and opinions
• awareness and knowledge – for example, brand awareness
• intentions – for example, purchase intentions. While useful, intentions are not a reliable indication of actual future behavior.
• motivation – a person’s motives are more stable than his/her behavior, so motive is a better predictor of future behavior than is past behavior.
• behavior

Primary data can be obtained by communication or by observation. Communication involves questioning respondents either verbally or in writing. This method is versatile, since one needs only to ask for the information; however, the response may not be accurate. Communication usually is quicker and cheaper than observation. Observation involves the recording of actions and is performed by either a person or some mechanical or electronic device. Observation is less versatile than communication since some attributes of a person may not be readily observable, such as attitudes, awareness, knowledge, intentions, and motivation. Observation also might take longer since observers may have to wait for appropriate events to occur, though observation using scanner data might be quicker and more cost effective. Observation typically is more accurate than communication.

Personal interviews have an interviewer bias that mail-in questionnaires do not have. For example, in a personal interview the respondent’s perception of the interviewer may affect the responses.

Questionnaire Design
The questionnaire is an important tool for gathering primary data.

Validity and Reliability
The validity of a test is the extent to which differences in scores reflect differences in the measured characteristic. Predictive validity is a measure of the usefulness of a measuring instrument as a predictor. Proof of predictive validity is determined by the correlation between results and actual behavior. Construct validity is the extent to which a measuring instrument measures what it intends to measure.

Reliability is the extent to which a measurement is repeatable with the same results. A measurement may be reliable and not valid. However, if a measurement is valid, then it also is reliable and if it is not reliable, then it cannot be valid. One way to show reliability is to show stability by repeating the test with the same results.

Attitude Measurement
Customer attitude is an important factor to measure for the following reasons:
• Attitude helps to explain how ready one is to do something.
• Attitudes do not change much over time.
• Attitudes produce consistency in behavior.
• Attitudes can be related to preferences.

Attitudes can be measured using the following procedures:
• Self-reporting – subjects are asked directly about their attitudes. Self-reporting is the most common technique used to measure attitude.
• Observation of behavior – assuming that one’s behavior is a result of one’s attitudes, attitudes can be inferred by observing behavior.
• Indirect techniques – use unstructured stimuli such as word association tests.
• Performance of objective tasks – assumes that one’s performance depends on attitude.
• Physiological reactions – subject’s response to a stimuli is measured using electronic or mechanical means. While the intensity can be measured, it is difficult to know if the attitude is positive or negative.
• Multiple measures – a mixture of techniques can be used to validate the findings, especially worthwhile when self-reporting is used.

Sampling Plan
The sampling frame is the pool from which the interviewees are chosen. The telephone book often is used as a sampling frame, but have some shortcomings. Telephone books exclude those households that do not have telephones and those households with unlisted numbers. Since a certain percentage of the numbers listed in a phone book are out of service, there are many people who have just moved who are not sampled. Such sampling biases can be overcome by using random digit dialing. Mall intercepts represent another sampling frame, though there are many people who do not shop at malls and those who shop more often will be over-represented unless their answers are weighted in inverse proportion to their frequency of mall shopping.
In designing the research study, one should consider the potential errors. Two sources of errors are random sampling error and non-sampling error. Sampling errors are those due to the fact that there is a non-zero confidence interval of the results because of the sample size being less than the population being studied. Non-sampling errors are those caused by faulty coding, untruthful responses, respondent fatigue, etc.
There is a tradeoff between sample size and cost. The larger the sample size, the smaller the sampling error but the higher the cost. After a certain point the smaller sampling error cannot be justified by the additional cost.
While a larger sample size may reduce sampling error, it actually may increase the total error. There are two reasons for this effect. First, a larger sample size may reduce the ability to follow up on non-responses. Second, even if there is a sufficient number of interviewers for follow-ups, a larger number of interviewers may result in a less uniform interview process.

Data Collection
In addition to the intrinsic sampling error, the actual data collection process will introduce additional errors. These errors are called non-sampling errors. Some non-sampling errors may be intentional on the part of the interviewer, who may introduce a bias by leading the respondent to provide a certain response. The interviewer also may introduce unintentional errors, for example, due to not having a clear understanding of the interview process or due to fatigue.
Respondents also may introduce errors. A respondent may introduce intentional errors by lying or simply by not responding to a question. A respondent may introduce unintentional errors by not understanding the question, guessing, not paying close attention, and being fatigued or distracted.
Such non-sampling errors can be reduced through quality control techniques.

Data Analysis – Preliminary Steps

Before analysis can be performed, raw data must be transformed into the right format. First, it must be edited so that errors can be corrected or omitted. The data must then be coded; this procedure converts the edited raw data into numbers or symbols. A codebook is created to document how the data was coded. Finally, the data is tabulated to count the number of samples falling into various categories. Simple tabulations count the occurrences of each variable independently of the other variables. Cross tabulations, also known as contingency tables or cross tabs, treats two or more variables simultaneously. However, since the variables are in a two-dimensional table, cross tabbing more than two variables is difficult to visualize since more than two dimensions would be required. Cross tabulation can be performed for nominal and ordinal variables.

Cross tabulation is the most commonly utilized data analysis method in marketing research. Many studies take the analysis no further than cross tabulation. This technique divides the sample into sub-groups to show how the dependent variable varies from one subgroup to another. A third variable can be introduced to uncover a relationship that initially was not evident.

Conjoint Analysis

If asked to do so outright, consumers may not be able to determine the relative importance and preferred combinations of product attributes. Conjoint analysis is a tool that allows a subset of the possible combinations of product features to be used to determine the relative importance of each feature in the purchasing decision. Conjoint analysis is based on the fact that the relative values of attributes considered jointly can better be measured than when considered in isolation.

In a conjoint analysis, the respondent may be asked to arrange a list of combinations of product attributes in decreasing order of preference. Once this ranking is obtained, a computer is used to find the utilities of different values of each attribute that would result in the respondent’s order of preference. This method is efficient in the sense that one does not need to conduct the survey using every possible combination of attributes in order to find the utilities and be able to predict the desirability of attribute combinations that were not tested.

Hypothesis Testing

A basic fact about testing hypotheses is that a hypothesis may be rejected but that the hypothesis never can be unconditionally accepted until all possible evidence is evaluated. In the case of sampled data, the information set cannot be complete. So if a test using such data does not reject a hypothesis, the conclusion is not necessarily that the hypothesis should be accepted.

The null hypothesis in an experiment is the hypothesis that the independent variable has no effect on the dependent variable. The null hypothesis is expressed as H0. This hypothesis is assumed to be true unless proven otherwise. The alternative to the null hypothesis is the hypothesis that the independent variable does have an effect on the dependent variable. This hypothesis is known as the alternative, research, or experimental hypothesis and is expressed as H1. This alternative hypothesis states that the relationship observed between the variables cannot be explained by chance alone.

In order to analyze whether research results are statistically significant or simply by chance, a test of statistical significance can be run.

Tests of Statistical Significance

The chi-square ( c2 ) goodness-of-fit test is used to determine whether a set of proportions have specified numerical values. It often is used to analyze bivariate cross-tabulated data. The chi-square test is performed by defining k categories and observing the number of cases falling into each category. Knowing the expected number of cases falling in each category, one can define chi-squared as:
c2 = å ( Oi – Ei )2 / Ei

where

Oi = the number of observed cases in category i,

Ei = the number of observed cases in category i,

k = the number of categories,

the summation runs from i = 1 to i = k.

ANOVA
Another test of significance is the Analysis of Variance (ANOVA) test. The primary purpose of ANOVA is to test for differences between multiple means. Whereas the t-test can be used to compare two means, ANOVA is needed to compare three or more means. If multiple t-tests were applied, the probability of a TYPE I error (rejecting a true null hypothesis) increases as the number of comparisons increases.

One-way ANOVA examines whether multiple means differ. The test is called an F-test. ANOVA calculates the ratio of the variation between groups to the variation within groups (the F ratio). While ANOVA was designed for comparing several means, it also can be used to compare two means. Two-way ANOVA allows for a second independent variable and addresses interaction.

This F-test assumes that the group variances are approximately equal and that the observations are independent. It also assumes normally distributed data; however, since this is a test on means the Central Limit Theorem holds as long as the sample size is not too small.

ANOVA is efficient for analyzing data using relatively few observations and can be used with categorical variables. Note that regression can perform a similar analysis to that of ANOVA.

Discriminant Analysis

Analysis of the difference in means between groups provides information about individual variables, it is not useful for determine their individual impacts when the variables are used in combination. Since some variables will not be independent from one another, one needs a test that can consider them simultaneously in order to take into account their interrelationship. One such test is to construct a linear combination, essentially a weighted sum of the variables. To determine which variables discriminate between two or more naturally occurring groups, discriminant analysis is used. Discriminant analysis can determine which variables are the best predictors of group membership. It determines which groups differ with respect to the mean of a variable, and then uses that variable to predict new cases of group membership. Essentially, the discriminant function problem is a one-way ANOVA problem in that one can determine whether multiple groups are significantly different from one another with respect to the mean of a particular variable.

Discriminant analysis analyzes the dependency relationship, whereas factor analysis and cluster analysis address the interdependency among variables.

Factor Analysis

Factor analysis is a very popular technique to analyze interdependence. Factor analysis studies the entire set of interrelationships without defining variables to be dependent or independent. Factor analysis combines variables to create a smaller set of factors. Mathematically, a factor is a linear combination of variables. A factor is not directly observable; it is inferred from the variables. The technique identifies underlying structure among the variables, reducing the number of variables to a more manageable set. Factor analysis groups variables according to their correlation.

Cluster Analysis

Market segmentation usually is based not on one factor but on multiple factors. Initially, each variable represents its own cluster. The challenge is to find a way to combine variables so that relatively homogenous clusters can be formed. Such clusters should be internally homogenous and externally heterogeneous. Cluster analysis is one way to accomplish this goal. Rather than being a statistical test, it is more of a collection of algorithms for grouping objects, or in the case of marketing research, grouping people. Cluster analysis is useful in the exploratory phase of research when there are no a-priori hypotheses.

Marketing Research Report
The format of the marketing research report varies with the needs of the organization. The report often contains the following sections:
• Authorization letter for the research
• Table of Contents
• List of illustrations
• Executive summary
• Research objectives
• Methodology
• Results
• Limitations
• Conclusions and recommendations
• Appendices containing copies of the questionnaires, etc.

Concluding Thoughts
Marketing research by itself does not arrive at marketing decisions, nor does it guarantee that the organization will be successful in marketing its products. However, when conducted in a systematic, analytical, and objective manner, marketing research can reduce the uncertainty in the decision-making process and increase the probability and magnitude of success.

Rengiant šios užduoties medžiagą, man labiausiai patiko P.Kotler išsamiai, aiškiai ir teisingai aprašyta tema. Sakyčiau bent kiek suprantantis anglų kalbos vadybos pagrindinę terminiją, čia būtinai ras naudingų žinių. Ruošiantis marketingo tyrimų seminarui, siūlyčiau pasiskaityti V.Pranulio, A.Pajuodžio, S.Urbonavičiaus bei R.Virvilaitės bendrą knygą “Marketingas”(2000); taip pat P.Kotler, G.Armstrong, P.H.Cunningham, R.Warren “Principles of Marketing”.

Naudota literatūra:
1. Antanas Poviliūnas “Marketingo pradmenys”- Vilnius: Vilniaus universiteto leidykla, 1993 – 99p.
2. Vytautas Pranulis “Marketingo tyrimai”- Vilnius: Kronta, 1998, -166p.
3. Vytautas Pranulis, Arvydas Pajuodis, Sigitas Urbonavičius, Regina Virvilaitė “Marketingas”- Vilnius: The Baltic Press, 2000 – 470p.
4. Regina Virvilaitė “Marketingas”- Kaunas: Technologija, 1997, – 145p.
5. Эванс Джоель, Берман Барри “Маркетинг”- Москва: Экономика, 1993, – 335c.
6. Philip Kotler, Gary Armstrong, Peggy H.Cunningham, Robert Warren “Principles of Marketing”- Scarborough, Ontario: Prentice-Hall Canada Inc., 1996, – 840p.
7. Quick MBA http://www.quickmba.com/marketing/research/
8. http://www.smenet.com.vn/counsel/marketresearch.htm

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