Pricing Concepts for Capturing Value

Step 1 of Marketing Research Process

Defining the objectives and research need. The first sign of a problem is a departure from normal or expected results. To determine whether to conduct research, two questions must be addressed: what information is needed to answer specific research questions? How should that information be obtained?

Step 2 of Marketing Research Process

Designing the research. Hypothesis (an informed guess or assumption about a certain problem or set of circumstances - accepted or rejected hypotheses act as conclusions for the research effort). Identify type of data needed. Success depends on identifying the correct type of data needed

Step 3 of Marketing Research Process

Collecting the data; primary and secondary data

Secondary Data

Inexpensive and fast access. Collected prior to the start of the research project. External data - includes government sources, trad associations and shows, periodicals, corporate information. Internal sources - organization’s own database. Saves time in collecting data because they are readily available.

Primary Data

Tailored + relevant. Collected to address specific research needs. Examples: focus groups, in-depth interviews, surveys. Sample - choose a group of customers who represent the customers of interest and generalize their opinions to the market segment. Specific to immediate data needs and topic at hand. Offers behavioral insights generally not available in secondary research

Step 4 of Marketing Research Process

Analyzing the data and developing insights. Converting data into useful information that is useful in making more effective marketing decisions. Data require careful interpretation. Managers must understand the research results and relate them to a context that permits effective decision making. Sample group —> analysis —> market segment

Step 5 of Marketing Research Process

Developing and implementing an action plan. Executive summary, body of the report, conclusions, limitations, supplements including tables, figures, and appendices

Inexpensive Secondary Data

Can be quickly accessed at a relatively low cost. For example, US Bureau of the Census

Syndicated Data

Data generally more detailed but can be very costly: Nielsen, IRI, JD Power and Associates, NDP Group, NOP World, Research and Markets, Roper Center for Public Opinion Research

Scanner Data

Data from scanner reading of UPC labels at checkout. Information helps firm assess what is happening in the marketplace

Panel Data

Information collected from a group of consumers, organized into panels, over time. Data collected from panelists often include records of purchases and responses to survey questions.

Qualitative

Yields descriptive non-numerical information. Observation entails examining purchase and consumption behaviors. Examples: scrutiny (personal/video camera observation), tracking (tracking movements electronically), interaction (Microsoft Kinect and heat maps)

In-Depth Interviews

Trained researchers ask questions one-on-one with a customer. Expensive and time consuming

Focus Groups

Small group of 8 to 12 people with a trained moderator. Now often take place online. Unstructured; about new or existing products or services

Quantitative

Yields empirical information that can be communicated through numbers. Survey (most popular type), questionnaires (a document that features a set of questions designed to gather information from respondents that will lead to more effective marketing decisions

Structured vs. Unstructured Response

Rate the importance of the following shampoo attributes vs. what are the most important characteristics for choosing a brand of shampoo?

Panel and Scanner Based Research

Can be either secondary or primary data. Example: New Balance encourages people to join its panel known as the “New Balance Tester Community” to help in the process of designing new sneakers

Experimental Research

An experiment is a type of quantitative research that systematically manipulates one or more variables to determine which variables have a causal effect on other variables. Can also be used on social media

Big Data

Enormous changes in recent years; driver is the vast increase in digital data. Data sets that are too large and complex to analyze with conventional data management and data mining software. Accesses from numerous sources: sales transactions, Customer Relationship Management systems, social media and blogs, wearables, blogs, locational devices, websites. Stored in a large computer file known as a data warehouse

Data Mining

A variety of statistical tools used to analyze big data to uncover previously unknown patterns or relationships among variables stored in the data warehouse

5 V’s of Big Data

Volume (large quantities), variety (many forms), velocity (moving quickly), veracity (in doubt), value (into money)

Marketing Analytics

Used to make sense out of big data and can be used to make marketing decision that span all the elements of a firm’s current or planned marketing strategy, including the following: how to make marketing mix (4Ps) decisions, how to determine which segments to target, how to understand and manage those customer segments, how to create micro-segmentation strategies at a local level

Descriptive Analytics

Helps firms organize, tabulate, and depict their available data, usually in easy to understand reports, tables, and charts

Predictive Analytics Tools

Rely on historically available data to forecast the future, such as what is predicted to happen to a firm’s product sales in the next month, next quarter, next year, and so on

Company objectives

Different firms embrace very different goals

Profit Orientation

Example - institute a companywide policy that all products must provide for at least an 18% profit margin to reach a particular profit goal for the firm. Does not take into consideration the value customers have for the product

Sales Orientation

Focusing on increasing sales, more concerned with overall market share

Competitor Orientation

Particularly common among smaller firms

Competitive Parity

Prices similar to competitorsS

Status Quo Pricing

Only change prices to meet competitors’ prices. Value is not directly a part of this pricing strategy

Customer Orientation

Based on how the firm can add value to its products/services. Match prices to customer expectations

Customer

How many units will a customer demand during a specific period at different prices? Inverse relationship between price and demand

The 5 Cs of Pricing

Company objectives, customer, costs, competition, channel members

The Demand Curve

For most products, there is an inverse relationship between price and demand. A graph of the quantity of products expected to be sold at various prices, if other factors remain constant