Ch. 4 - Market Research

Marketing Research

The process of defining a marketing problem and opportunity, systematically collecting and analyzing information, and recommending actions.

Although imperfect, marketers conduct marketing research to reduce the risk inherent in and thereby improve, marketing decisions.

Decision

A conscious choice from among two or more alternatives.

Five Step Market Research Approach

• Step 1: Define the problem / issue / opportunity

  • Setting the objectives, and identifying possible marketing actions.

• Step 2: Develop the research plan

  • Specify the constraints

  • Identify the data needed

  • Determine how to collect the data (concepts and methods)

• Step 3: Collect relevant information

  • Obtain secondary data.

  • Obtain primary data.

• Step 4: Develop findings

  • Analyze the data

  • Present the findings

• Step 5: Take marketing actions.

  • Make action recommendations.

  • Implement action recommendations.

  • Evaluate results.

Methods

(Sampling and Statistical Inference)

The approaches that can be used to collect data to solve all or part of a problem. Methods that are important in marketing include:

• Sampling: The process of gathering data from a subset of the total population, rather than from all members of that particular group.

• Statistical inference: The theory, methods, and practice of forming judgements about the parameters of a population and the reliability of statistical relationships, typically on the basis of random sampling.

Two Basic Sampling Techniques

1. Probability sampling

2. Nonprobability sampling

• Probability sampling: Selecting a sample so that each element of a population has a specific known chance of being selected.

• Nonprobability sampling: Selecting a sample so that the chance of selecting a particular element of a population is either unknown or zero.

  • These samples are used with caution by researchers as they can be biased.

Data

(Primary and Secondary)

Data: The facts and figures related to the project that are divided into two main parts: secondary data and primary data.

• Secondary data: Are facts and figures that have already been recorded prior to the project at hand.

• Primary data: Are facts and figures that are newly collected for the project. Secondary research may be followed up by primary research such as focus groups, or research with online communities.

Secondary Data

Internal and External

Secondary data: Are facts and figures that have already been recorded prior to the project at hand. This data is usually obtained first, then the primary data is.

• Internal data: Exist within a company and can include data derived from data analytics, or simpler approaches that review basic sales reports, profitability data, and costing information.

• External data: Come from published sources outside the organization (e.g. Statistics Canada).

Primary Data Collection Types

1. Observational data: Obtained by watching how people actually behave, either in person or by using mechanical, personal or neuromarketing methods.

2. Mechanical methods: Tracking who is looking at and watching certain things.

3. Personal methods: watching consumers, mystery shoppers, customer service efforts, subtle behavior and emotional reactions.

4.   Neuromarketing: A relatively new field of study that merges technologies used to study the brain with marketing’s interest in understanding consumers.

5. Questionnaire data: Facts and figures obtained by asking people about their attitudes, awareness, intentions, and behaviours.

6. In depth interviews

7. Focus groups: Informal group of six to ten past, present, or prospective customers.

8. Social media

Disadvantages of Primary Data

The main disadvantages are that primary data are usually far more costly and time-consuming to collect than secondary data.

1. A general rule among marketing researchers is to obtain secondary data first and then collect primary data. This is because

   1. Time savings because the data have already been collected and published or exist internally

   2. The low cost, such as free or inexpensive Census reports.

Step 1: Define the problem / issue / opportunity

The first step in the market research process is to clearly define the problem, issue, or opportunity, and to clarify the research objectives. This is often posed as a question that needs to be answered.

The two key elements in defining a problem are setting the research objectives and identifying possible marketing actions.

Step 2: Develop the Research Plan

The second step in the marketing research process requires that the researcher

(1) specify the constraints on the marketing research activity,

(2) identify the data needed for marketing actions, and

(3) determine how to collect the data.

This includes concepts, methods, probability and nonprobability samples.

Step 3: Collect Relevant Information

Collecting enough relevant information to make a rational, informed marketing decision sometimes simply means using your knowledge to decide immediately. At other times it entails collecting an enormous amount of information at great expense.

This includes gathering primary and secondary data.

Step 4: Develop the Findings

Analyzing marketing data today often involves very sophisticated and complex methods.

Examples of this include big data, data analytics, artificial intelligence, data mining, and predictive modelling.

Step 5: Marketing Actions

Effective marketing research doesn’t stop with findings and recommendations, someone has to identify the marketing actions, put them into effect, and monitor how the decisions turn out, which is the essence of Step 5.

• Make action recommendations

• Implement the action recommendations

Big Data

A broad term generally used to describe large amounts of data collected from a variety of sources and analyzed with an increasingly sophisticated set of technologies.

Information Technology

Includes all of the computing resources that collect, store, and analyze the data. 

Data mining

The practice of examining large databases to find statistical relationships between consumer purchasing patterns.

Refinements in data mining and data analytics now permit marketers to actually foresee consumer behaviour using predictive modelling, statistical models that use data mining and probability analysis to foretell outcomes.

Analytics

Refers to the process of taking metrics data and applying smart thinking and technology to gain actionable insights that can help make better business decisions.

• Two main categories: Predictive and descriptive analytics.

• Descriptive analytics includes web and social analytics and social listening.

Metrics

Refers to numeric data that is collected and grouped to track performance.

• Metrics are often presented in spreadsheets and dashboards to make the data easy to understand and interpret.

Dashboard

Visualize data and key performance indicators (KPIs), using graphs, charts, and numbers, so numerical information tells a story that is insightful, easy to use, and understand.

Descriptive analytics

Focus on what has happened. It is the simplest and most common form of analytics. Web analytics, social analytics, and RFM (recency, frequency, and monetary value) analysis are descriptive.

Web analytics

The measurement and analysis of website data, looking at elements such as visits, unique visitors, page views, time on site, traffic sources, referrals, and bounce rate.

Google Analytics is an example of an excellent, free web analytics tool.

Social Analytics

Gains insights from social media interaction and social listening.

• Social media interactions, such as followers, views, comments, likes/unlikes, reach, shares, engagement, sentiment, conversion rates, and churn rate, are analyzed to determine the level of interaction with customers and the success of marketing programs on social platforms.

Social Listening

Pays attention to real-time public conversations on social networks to discover trends as well as common themes, attitudes, topics, and areas of interest.

• Social analytics can measure social media campaign performance, assess message resonation and amplification, determine a brand’s buzz level, and gauge sentiment toward a brand through words or images.

• It can identify key influencers, brand advocates, and opinion leaders, and it can interact in real time with consumers.

Predictive Analytics

Combines data from varied sources to reveal patterns that are modelled to predict what might happen in the future.

• For example, data can be combined from CRM databases, social media analytics, marketing program metrics, customer service databases, and purchased data to reveal groupings of customers with common attitudes and purchase patterns.

• This information can then be used to predict future consumer behaviour and to customize offers for specific groupings.

Sales Forecast

The total number of a product that a firm expects to sell during a specified time period under specified environmental conditions and its own marketing efforts. There are three main forecasting techniques often used:

• 1. Judgments of the decision maker (this includes direct forecast and lost-horse forecast).

• 2. Surveys of knowledgeable groups (this includes a survey of buyers intentions forecast, and a salesforce survey forecast)

• 3. Statistical methods: This includes trend extrapolation, and linear trend extrapolation.

Direct forecast

Judgments of Decision Maker

Involves estimating the value to be forecast without any intervening steps.

• Examples appear daily: How many litres of milk should I buy? How much money should I withdraw at the ATM?

Lost-horse Forecast

Judgments of the Decision Maker

Involves starting with the last known value of the item being forecast, listing the factors that could affect the forecast, assessing whether they have a positive or negative impact, and making the final forecast.

• The technique gets its name from how you’d find a lost horse: Go to where it was last seen, put yourself in its shoes, consider those factors that could affect where you might go (to the pond if you’re thirsty, the hayfield if you’re hungry, and so on), and go there.

Survey of buyers intentions forecast

Surveys of Knowledgeable Groups

Asks prospective customers if they are likely to buy the product during some future time period.

• For industrial products with few prospective buyers, this can be effective.

• There are only a few hundred customers in the entire world for Boeing’s large airplanes, so Boeing surveys them to develop its sales forecasts and production schedules.

Salesforce Survey Forecast

Surveys of Knowledgeable Groups

Involves asking the firm’s salespeople to estimate sales during a forthcoming period.

Because these people are in contact with customers and are likely to know what customers like and dislike, there is logic to this approach.

Trend Extrapolation

Statistical Methods

Which involves extending a pattern observed in past data into the future.

Linear Trend Extrapolation

Statistical Methods

The best-known statistical method of forecasting is trend extrapolation, which involves extending a pattern observed in past data into the future. When the pattern is described with a straight line, it is linear trend extrapolation.

Brand Development Index (BDI)

An index that shows how well a brand’s sales are developed in a region relative to the region’s population size.

Key Performance Indicators (KPIs)

Types of metric that are used to evaluate performance.