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Ch4: Market Research - Coggle Diagram
Ch4: Market Research
6 Step Market Research Approach
Step 1 - Def the Problem/Issue/Opportunity
Set R objectives
ID possible marketing actions
Identify Possible Marketing Actions
Measures of success
Criteria or standards used in evaluating proposed solutions to prob
Diff R outcomes, based on measure of success, lead to diff marketing actions
First step in market R process is to clearly def prob, issue, opp, & to clarify R objectives. Often posed as a question that needs to be answered
If objectives too broad, prob is not tangible, if objectives are too narrow, value of research questionable
Objectives
Specific measurable, achievable goals that decision maker seeks to achieve
Common R objectives are to discover consumer needs & wants & determine why product not selling
Step 2 - Develop the Research Plan
Specify constraints
ID data needed for marketing actions
Determine how to collect data
Information Requirements
Collect data that is relevant to the task. Makes it time efficient, avoids confusion, and is cost effective
Collection Methods
Methodology, cost, efficiency, accuracy of results are important considerations
Need data collection plan (mathematical considerations & operational issues Rer must consider)
To get accurate answers - Rers select R methods that encourage honesty
CA market Rers rely on training, expertise, judgement to make appropriate methodology decisions & utilize professional association (Marketing Research & Intelligence Association) for resources and training
Sampling
IDs who to be sampled, sample size, how sample selected
[Process of gathering data from subset of total pop. rather than from all members of that particular group]
Sampling errors - Increasing sample size decreases error but increases cost
Other factors that impact R design - Timeline for completion & budget
2 Basic Sampling Techniques
Probability Sampling
Precise rules to select sample so each element of pop. has specific known chance of being selected
Non-Probability Sampling
Use arbitrary judgement to select sample so chance of selecting particular element of pop either unknown or zero
Intros bias
But can be done if have time & budget limitations or for exploratory R when conclusions mostly directional & need more R
ID which approach taken to complete project includes IDing what info needed, how to collect, whether sampling plan needed
Step 3 - Collect Relevant Info
Obtain secondary data
Obtain primary data
See Figure 4.2 Sources of info
Secondary Data
Facts & figures that have already been recorded prior to project at hand
Internal Data
Exists within company & can include data derived from data analysis, or simpler approaches that review basic sales reports, profitability data, and costing info
Marketing Inputs Data
Relates to effort expended to make sales
Range from marketing budget reports (ads spent, salesppl's call reports, # of sales call per day, who was visited, what was discussed)
Marketing Outcomes
Relates to results of marketing efforts
Accounting records on shipments, sales & repeat sales (sale reps, industry, geo), includes emails, phone calls, letters from customers can reveal both complaints & what is working well
External Data
Comes from published sources outside org
Example - StatsCan - Best known for 2016 Census
Use to ID characteristics & trends of ultimate consumers
Includes the following info
Economic indicators
International trade
Culture & leisure
Agriculture
Tourism & travel
Manufacturing
Government
Environment
Justice & crime
Health
Syndicated Panel
Several marketing R companies pay households & businesses to record all their purchases in a diary
Data economically answer questions that require consistent data collection over time
Primary Data
Facts & figures newly collected for the project
General rule - Get secondary data 1st then detailed proprietary primary data
Cost efficient & easier to obtain secondary data
Secondary can illuminate further data requirements
Weigh against secondary data disadvantages (data might be out of date, def or categories might not be right for project, data may not be accurate or specific enough)
Focus Groups
Informal interview session of 6-10 ppl in a room with a moderator to discuss topics surrounding market R prob
Popular qualitative R technique
In-Depth Interviews
Detailed individual interviews where Rer discusses topics with individual at length in free-flowing conversation to discover info that may help solve marketing prob
Online Research Communities
Use consumer groups, brought together privately in online environ, to answer questions, respond to ideas, collaborate with Rers in real time
New qualitative R tool
High-involvement categories - Areas where consumers are passionate about products.
Consumers provide feedback to Rers in private online enviro where only marketers, Rers, and respondents privy to convo
Invites consumers to join online community on specific topic
Managed by R company to ensure community engaged and continues to be interested in topic
Involves regular 2-way communication visible to all in community, managed by Rer, involves 200-300 ppl
Online Research Bulletin Boards
[Private online forums where respondents can post their responses to questions]
New R tool
Static website locations where Qs posted online, respondents asked to comment on ideas, only those with access to bulletin board privy to posted Q&A
Easy to manage & administer but not that much depth of info
Social Listening
Exploratory R technique
Metrics measure positive & negative sentiments, popularity scores, message reach, lvls of convo, buzz & crisis monitoring
Can be qualitative or quantitative
Pros of quantitative R - Designed to be statistically accurate & less open to interpretation
Cons of quantitative R - Costly & time consuming
Primary quantitative techniques - Observational R, surveys/questionnaires, experiements
Observational R
Obtained by watching how ppl behave (in person or using machine to record events)
Eg. Social listening, web tracking, in person
Useful & flexible but can be costly & unreliable (bias/subjective)
Surveys
To gather quantitative info
Questionnaires - standardized forms asked to large rep sample to obtain accurate data
Balance cost against expected quality of info
See Figure 4.5 for Advantages & disadvantages of survey techniques
Types
Personal interviews - Can ask probing Q & get reactions to visual materials but very costly
Mail - Less costly but low response rates & bias cause responders most likely have positive or negative exp
Telephone - Hard because of call-display & reluctance to participate
Internet - Limited to respondents who have tech but becoming more popular to gather info
Online Survey
Pros - Minimal cost & turnaround time from data collection to report prezi is very quick
Cons - Emails marked as junk/spam/unsubscribe, deleted, pop-up blocker, survey completed multiple times (result bias)
Qs must get clear, unambiguous answers from respondents
Syndicated studies
Hybrid of primary & secondary R conducted by R company, spreading cost across many clients to reduce price. Routinely conducted with extensive panels of consumers to determine trends
Survey Panel
Large sample of respondents that voluntarily complete questionnaires on regular basis so Rers can assess changes in behaviour & attitudes
Omnibus survey
Voluntary participation of respondents in routine surveys, allowing individual marketers to add small number of questions to existing survey to receive cost-effective data in response to Q
Mistakes to avoid in Q
Leading or loaded Qs - Qs designed to make person think specific way
Non-specific Qs - Qs that can't be clearly understood
Missing options - Potential answers missing
Asking 2 Qs at one time - Qs that ask two things but respondent can only provide one answer
Confusing wording - Qs that include acronyms, industry jargon, or other language that may be unfamiliar to respondent
Experiments
Quantitative R
Measures changes in consumer beaviour over time to determine reactions to new product intro or new promotional offers
Marketing experiment
Involves changing a variable involved in purchase to find out what happens. Rer changes just one element (e.g. marketing mix) & keeps other variables constant
Contrived Environment
Mimic real life situations
[simulated test markets]
Use comp simulations to predict consumer beh
Marketers input marketing mix variables & rely on complex forecasting programs to determine potential success levels
In-market
Real-time in-field tests where product/promotion is actually sold in limited location & monitored for success during specific time period
Test market - in-market localized approach, or short-term online destination, used to test success of promotional offers, new services, or new product launches
Test Market
Provides more realistic eval of product/promotional success than other R options
Time-consuming, costly, visible to competition
Internet marketers routinely test pay-per-click ad campaigns, alt online consumer offers, design of various website landing pages
New products - Large orgs use this to determine whether consumer will buy new products etc.
Test markets in CA - Edmonton, Alberta, Barrier, Ontario
Data
Facts & figures related to project
Step 4 - Develop Findings
Analyze the data
Present the findings
Metrics
KPI (Key performance indicators)
Type of metric used to eval performance
Rules of marketing metrics
Should be easy to understand
Should be available on a regular basis
Should be actionable and impact business
Brand health
2 drivers
Market Share
% of sales volume for product, relative to entire sales volume of category in which it competes
Brand Development Index (BDI)
How well a brand's sales are developed in a region relative to region's population size
% of total brand sales in particular region relative to % of country's population in that region
Analyze Data
Big Data, Data Analytics, & AI
See figure 4.9 - Use of Intel enterprise to create action
Big Data
Broad term used to describe large amounts of data collected from a variety of sources and analyzed with increasingly sophisticated set of technologies
4Vs of big data
Volume - Amount of Data
Variety - Different Types of Data
Velocity - Speed fo Data
Veracity - Certainty of Data
Types of Data
Structured - Easily tagged, stored, searched in database using consistently identifiable terms that can be systematically organized
Unstructured - Comes from word-processed docs, prezi, audio files, images
Semi-structured - Hybrid of un/structured
Information Technology
Includes all computing resources that collect, store, analyze data
Growth of the Internet of Things (IoT) allows data collection from almost any device consumer uses
Intelligent Enterprise
Companies that combo data, tech, analytics to convert data to useful info that answers marketing Qs and lead to effective marketing actions
Data mining & predictive modelling
Data mining
Practice of examining large databases to find statistical rela between consumer purchasing patterns
Predictive modelling
Statistical models use data mining & probability analysis to foretell outcomes.
Analytics
Predictive Analytics
Combo data from varied sources to reveal patterns that are modelled to predict what might happen in future
Data mining - Processing large amounts of data using software to find insightful correlations & patterns that lead to better business decisions
Descriptive Analytics
Focus on what has happened
Simplest & most common form of analytics
E.g. Web analytics, social analytics, RFM (recency, frequency, monetary value) analysis
Web Analytics
Measurement & analysis of website data, looking at elements
E.g. Google Analytics
Social Analytics
Gains insights from SM interaction & social listening
Can measure SM campaign performance, assess message resonation & amplification, determine brand's buzz level, gauge sentiment toward brand through words or images
Can ID influencers, brand advocates, opinion leaders, interact real-time with consumers
Social listening
Pays attention to real-time public conversations on social networks to discover trends & common themes, attitudes, topics, areas of interest
RFM Analysis
Uses automated software to classify customers on basis of how recently products were purchased (recency), how often products purchased (frequency), and dollar value of transactions (monetary value)
Common in NPO to target donors
Can be descriptive - Captures data then categrozies customers based on data
Can be predictive - Determines factors that drive purchases & link factors to future beh = Make offers based on past beh
Types of Analytics
Descriptive - Focus on what has happened
Predictive - Focus on what might happen
Types of Market R
Exploratory
Preliminary R that clarifies scope & nature of marketing problem or oppo
Descriptive
Describe basic characteristics of a given pop. or to clarify its usage and attitudes
Causal
Designed to ID cause-&-effect relas among variables
Step 5 - Take Marketing Actions
Make action recommendations
Implement action recommendations
Evaluate results
Evaluate the Results
2 aspects of the process
Evaluating the decision itself
Involves monitoring marketplace to determine if action is necessary in future
Evaluating decision process used
Was marketing R & analysis used to dev recommendations effective? Was it flawed? Could it be improved for similar situations in future?
Marketing data & info have little value unless translated into findings & recommendations that lead to marketing actions
Actually there is 6 steps
1) Def prob/issue/opp
2) Design R plan
3) Conduct exploratory & qualitative R (secondary & primary data)
4) Collect quantitative primary R
5) Compile, analyze, interpret data
6) Generate reports & recommendations
The Future of Market Research
Continued growth in online market R & increased use of analytics platforms to help manage big data & obtain insights
Org expected to increasingly invest in tech & training programs that will help marketers focus on meaningful, actionable data
Privacy laws in CA require businesses to comply with PIPEDA (Personal Info Protection & Electronic Documents Act) & CASL (Canada's Anti-Spam Legislation)
Places to check latest
CMA (Canadian Marketing Association)
Office of Privacy Commissioner of Canada
MRIA (Marketing R & Intel Association of Canada) - Rep all aspects of market intel & survey R industries
The Role of Marketing Research
What is Marketing Research
Process of defining a marketing problem & opp, systematically collecting and analyzing info & recommending actions
Can reduce risk
Provides managers with insights - Add vision, knowledge, & experience
Marketing Information System (MIS)
Set of procedures & processes for collecting, sorting, analyzing, and summarizing marketing info on an ongoing basis to help manage the data
Competitive advantage
Helps marketers understand how elements impact its business, anticipate competitive moves, predict consumer behaviour & preferences
Challenges in Doing Good Marketing Research
How can marketing R determine if consumers will buy a product they have never seen & never thought about before?
How can marketing research obtain answers that people know but are reluctant to reveal?
How can marketing research help ppl accurately remember & report their interests, intentions, & purchases?