Market Research Final Havrilla

Quantivative research

Descriptive and Causal Research

Descriptive

Surveys

casual

Experiments

Quantitative Primary Research

Original research that gathers numerical data from a representative sample to describe a target market

Why choose a survey?

Projectable results

Descriptive results

4 functions of survey

1. Use specific questions to address the research objective

2. Standardize questions and response categories

3. Motivate respondents

4. Reduce response error

When doing a survey what must you ask yourself

- Am I being clear/motivational in instructions

- Right questions to address for objective

- Easy to read and answer

- As brief as possible

Best practices for a survey

- No more than 5-7 minutes

- Mostly close ended Qs

- Cluster related Content

- Optimize ability to analyze and report

2 Common universal survey components

1. Overall measurement= gauging sentiment

2. Demographic Question= describe sample representation

3 Basic Measurement concepts

1. Attributes

2. Definitions

3. Measurement

3 Question Response types?

1. Open ended

2. Categorical

3. Continuous

Categorical questions

Nominal- no natural order

Ordinal- can place in order

continuous (metric)

Ratio- number to attribute to something

Interval- Scales

NPS

Net Promoter Score; measures customer loyalty. (0-6 Detractors, 7-8 Passives, 9-10 Promotors)

Balanced scales

Do you have the same number of positive and negative options

*remember neutral is not zero (midpoint)

Likert Scales

Measures intensity- range of options from one extreme to another

Best practices for demographic questions

- Dont necessarly help RO

- Necessary to inducle to describe the sample represenations

- Respondent profiles (sample compared to target popualatuon to assess representativness

Common survey questions

1. Satisfaction

2. New Product Development

3. Brand Perception

4. Advertising concept

Satisfaction Questions

To gauge feedback on current products and services

- understand levels of engagement

Comparing Customer Satisfaction Results

-Trending monitors data over time

- Benchmarking compares data to peer organizations

New Product Development Questions

To gain feedback from a sample of target market about new product direction

Brand Perception Questions

Gather unbiased perceptions; almost always blind

Advertising Concept

To test advertising concepts prior to full development and production

Distribution Method 6 Factors to Consider

1. Topic Sensitivity

2. Time Requirements- when needed

3. How invested respondents are

4. Survey Length

5. Survey Complexity

6. Cost

Survey invitation components

1. Research Credentials

2. Purpose of the survey

3. Reason the respondent is being asked to participate

4. How responses will be used and if confidential

5. Survey Due date

6. Incentive

Survey Software

Qualtrics, Survey Monkey, and Google Forms

Why do satisfaction surveys have much higher response rates

People can say what they think good or bad

softening the list

alerting potential respondents ahead of invitation to participate

How to increase response rates

-soften the list

- create compelling invitation

- reminders

-Deploy soon after event

- incentives

Types of errors in surveys

sampling and non-sampling errors

Non-sampling errors (response)

Response- when someone answers a question in a way that misrepresents the truth

EX- 1- Deliberate falsification

2. Lazy respondents

3. Extremely bias

Non-sampling errors (Non-response)

- Failure to take part or answer specific questions on survey

Ex- Non-contacts, refusal to participate, Refusal to answer specific questions, Break off

Sampling calculation apply only to _1._______ not _2.________

1. Final obtained sample, 2. initial sample

Sources for sample names

-Company lists

-List brokers

-Research Panels

margin of error

the range of percentage points in which the sample accurately reflects the population

"How precise do I want to be?"

confidence level

the estimated probability that a population parameter lies within a given confidence interval

- Reliability

Data Cleaning

Process of correcting or removing inaccurate data.

Data Analysis

The process of compiling, analyzing, and interpreting the results of primary and secondary data collection.

- Making the raw data meaningful

Data Analysis- managerial skills

-Know who to pick good consultants/tools

-Healthy Skepticism

-Ability to spot data patterns

Common types of Data Analysis

-Summarizing Single Variables

-Differences and Relationships between variables

Summarizing Single Variables

-Looking at variables tested and summarizing frequency, average, % response

Ex : What % of shoppers using coupons

Differences and relationships between variables

Looking a differences and focusing on those that are significant

Responsibility's as a manager in Data analysis

1. Identify most significant learnings and differences

2. Support differences with statistical analysis

Written Reports

Title Page

Table of contents

Exec summary

Research design

Key learning and findings

Recommendations

Executive summary

Overview of research results and actionable recommendations

-Highlight vital inforamtion

Written report (Research design)

Business problem

key questions

Objectives

How research was conducted

Key learnings

Detailed portion highlighting critical observations and learnings

Data Visualization

Percentages

Line chart for data over time

Mean scores

Open ended comments

Word clouds

Verbatims

Market Research Process

Plan

1.State Business problem

2.State Research Objective

3.List Key Questions

4. Design the study

Execute

5. Collect Data

6. Analyze Results

7. Report and Recommend

Types of Research

exploratory, descriptive, causal

Qualitative Research

Exploratory

Tools

IDI

Ethnography

Stake Holder advisory board

Focus groups