DONT STUDY Chapter 10- Marketing, Research, Analytics

Factors managers consider before embarking on market research project

• Will the research be useful

• is top management committed to project

• should project be small or large

Market Research Process

1 - Define Objectives and research needs

2 - Designing the research

3 - Collecting the data

4 - Analyzing the data and developing insights

5 - Developing and implementing action plan

Step One - Defining Objectives and research needs

Defining clear objectives for market research project

Step Two -Designing the Research

researchers determine the type of data and research necessary to confirm it

Step Three: Collecting the Data

Based on the design of the project, data can be collected from 2 sources

Secondary Data Source

Pieces of information that have already been collected from other sources and usually are readily available.

Primary Data Source

Data collected to address specific research needs.

Step 4: Analyzing Data and Developing Insights

Researchers analyze and make use of data

Step 5 - Developing and Implementing Action Plan

Analyst defines results and prepares them to present to decision makers. Report is made up of executive summary (research, objectives, methodology used) and conclusions, limitations, appropriate supplemental tables, figures, and appendixes.

What is the difference between data and information?

Data is numbers, information is meaning derived from those numbers

Syndicated Data

Data available for a fee from commercial research firms such as Information Resources Inc. (IRI), NDP Group, and Nielsen.

Scanner Data

A type of syndicated external secondary data used in quantitative research that is obtained from scanner readings of UPC codes at checkout counters.

Panel Data

Contain information collected from a group of consumers.

Qualitative Data

Informal research methods, including observation, following social media sites, in-depth interviews, and focus groups.

Quantitative research

Structured responses that can be statistically tested to confirm insights and hypotheses generated via qualitative research or secondary data.Co

Components of Qualitative research

• observation

• in depth interviews

• focus groups

Quantitative Research

• Survey

• Panel

• Scanner

• Experiments

Observation

An exploratory research method that entails examining purchase and consumption behaviors through personal or video camera scrutiny.I

In Depth Interview

An exploratory research technique in which trained researchers ask questions, listen to and record the answers, and then pose additional questions to clarify or expand on a particular issue.

Focus Group Interviews

A research technique in which a small group of persons (usually 8 to 12) comes together for an intensive discussion about a particular topic, with the conversation guided by a trained moderator using an unstructured method of inquiry.

Survey Research

A systematic means of collecting information from people that generally uses a questionnaire.

Experimental Research

A type of conclusive and quantitative research that systematically manipulates one or more variables to determine which variables have a causal effect on another variable. Also called experiment.

Dis/Advantages of primary research

• specific to immediate needs

• behavioral insights generally unavailable from secondary

• costly

• time consuming

• sophisticated training

Dis/Advantages of Secondary research

• saves time

• free/cheap

• not precise

• not timely

• un original sources

Big Data

Data sets that are too large and complex to analyze with conventional data management and data mining software.

Data Warehouse

A large computer file containing data including sales transactions, customer relationship management (CRM) systems, websites, social media, blogs, locational devices, wearables, and so forth.

Data Mining

Statistical tools used to uncover previously unknown patterns or relationships among variables stored in the big data databases.

What are the 5 Vs for Big Data

Volume

Variety

Velocity

Varacity

Value

Volume

An inherent quality of big data that infers that big data contain a large amount of data.

Variety

An inherent quality of big data that infers that big data contain both numeric and textual data and are obtained from different media formats.

Velocity

An inherent quality of big data that infers that data are collected and can be analyzed and accessed quickly.

Veracity

An inherent aspect of big data that infers that big data users must evaluate the accuracy and reliability of the collected data.

Marketing Analytics

Techniques that use advanced technologies and models to gather data so that marketers can improve their decision making, optimize their returns, and make appropriate customer-related decisions.

Marketing Mix Decisions

• Determine Which segments to target

• Understand Managing Consumer Segments

• Create Micro Segmentation Strategies at a Local Level

Descriptive Analytics Tool

Methods that help firms organize, tabulate, and depict their available data, usually in easy-to-understand reports, tables, and charts.

Predictive Analytics Tool

Methods that rely on historically available data to forecast the future.

Churn Rate

The number of consumers who stop using a product or service, divided by the average number of consumers of that product or service.

Prescriptive Analytics Tool

Analyses that use simulations, which ask a series of what if–type questions, and optimization techniques, which find the most effective or best result, to help firms better understand what they should do.

Active Analytics Tool

Artificial intelligence algorithms that are used to analyze input gathered by the Internet of Things (IoT).