When defining marketing research, it is important to make the distinction between marketing research and market research. These disciplines have different focuses in order to address a unique set of business needs.
Marketing research is the analysis of customer behavior with the intent to develop or implement a marketing plan. Marketing research typically addresses some of the following research objectives:
A business can reduce its risk of product failure by conducting marketing research because it allows them to predict how customers will respond to a change in their marketing strategy.
Market research, on the other hand, is an industry analysis of a specific business in order to gather data on the size, growth, trends, and new entrants. It is based on statistics, SWOT, trends, and players. Market research relies on various sources of data: secondary research such as government data and trade association data, as well as primary research. This discipline is devoted to the metrics and statistics of the market itself rather than how customers behave within that market.
Marketing Research Process
A primary marketing research study is custom research, defined by the client to collect data that cannot be found with secondary research (using existing sources), and encompasses three distinct phases: research design, data collection, and data analysis.
RESEARCH DESIGN: Objectives - TMTG V1 Outline
The first step in any study is to define the research objectives (i.e., the question(s) that the study seeks to address). A few examples of objectives are listed above in the definition of marketing research. Once the research objectives are defined, the researcher must determine whether the study will be quantitative (quant) or qualitative (qual). This choice is primarily informed by the objectives. In their simplest terms, quant is the “what” and qual is the “why”.
Quantitative studies are typically hypothesis-driven research, where potential answers to the research questions are known, but data is needed to confirm the hypothesis. On the other hand, qualitative studies are typically more exploratory in nature, and provide insight into how people think, how they react, and what drives their choices. Although, it is possible to address some of the “why” in quantitative research as well.
Now that the researcher has determined whether the study will be quantitative, qualitative, or a mixture of both, the next step is to select the methodology (or methodologies) that will be employed to address the research objectives.
Quantitative methodology selection, at a high level, is determined by the research objectives (e.g., Pricing, Segmentation, KAP, Concept testing, Message / Ad testing, etc.). To the right is a list of quantitative design options examples from simplest to most complex.
For example, when a pricing assessment is included in the research objectives, a number of design options should be considered based on the existing market conditions, such as: competitive alternatives, maturity of the market, accuracy in share projections, and client budget. Some design options involve a direct self-explicated question on price while others are based on a derived measurement of preference.
- Self-explicated questioning:
- Monadic concept testing: The most straightforward; it presents a concept to the respondent and asks their purchase likelihood at a specific price.
- Price to value analysis: Maps the relationship between perceived value (i.e., satisfaction) and price for each offering tested.
- Cascading price: Similar to monadic concept testing, cascading price presents a concept to the respondent and asks their purchase likelihood at a series of price points from highest to lowest.
- Van Westendorp: Asks respondents to define four price points (too cheap, bargain, expensive, too expensive) for an offering, which can be supplemented by additional questions (Newton/Miller/Smith Extension) to test purchase likelihood at respondents’ bargain and expensive prices.
- Derived measurement of preference:
- MaxDiff: Respondents are shown three or four items at a time and asked to select the top and bottom items. This pairwise technique takes advantage of people’s ability to distinguish the top and bottom (e.g., most and least important) in order to effectively rank a large quantity of items based on their selections, although it necessitates a longer survey duration than a declarative approach.
- Conjoint analysis: Defines a set of products using attributes relevant to decision making (e.g., color) and attribute levels (e.g., blue) and simulates a real-life purchasing scenario by asking respondents to choose between products defined by random permutations of the attribute levels, including a penalty attribute (e.g., price). Respondents’ collective trade-off decisions inform the utility and importance scores of each attribute via derived measurement, which can then be used in a simulation tool for further analysis.
Qualitative studies are more limited in terms of methodologies that may be used to question the respondent, which can be broadly classified in two approaches on the right.
- Declarative approaches are structured around a moderation guide, which the moderator uses to direct the discussion flow to address a specified set of open-ended questions.
- Projective approaches invite the respondents to imagine themselves in the role of another person or object, and to respond on behalf of this projection. This technique may be used to bypass common hurdles that people face to speak the truth, such as taboos, lack of confidence, perceptions of a socially acceptable answer, or a desire to have the “correct” answer or to “win.”
DATA COLLECTION: Survey efficiency and optimization - TMTG V2
Data collection is predicated on the final design of the instrument (qual or quant) to maximize respondent engagement and experience while optimizing efficiency and quality of the expected responses. There are three major aspects of data collection methods:
FINAL QUESTION DEVELOPMENT, including phrasing and scales for optimal quality and efficiency
- Asking respondents a question with a set of predefined response items to choose from. In the simplest cases, respondents may be limited to one response item for a given question (single select) or multiple response items (multiple select). Slightly more complex question types include point allocation and ranking.
- Scales should contain an odd number of response items (i.e., 5, 7, or 11) to maintain a neutral center value and should be anchored with statements to define the meaning of each value (i.e., 1 is “strongly disagree”).
FIELDING TECHNIQUES are dependent on the type of study and research objectives, which can be classified into quantitative and qualitative techniques, as follows:
CATI/CAWI (Computer Assisted Telephone/Web Interviewing) can be used for win/loss studies, customer satisfaction studies, point of sales/service studies, and are applicable when surveys are short (<10 min)
Online/web-based surveys are mandatory for any trade-off techniques (derived measurement of preference) and when surveys are longer (>10 min)
IDIs (In-depth interviews) are administered as a one-on-one interview between a respondent and a moderator. As the name suggests, this is the most in-depth way to get inside of a customer’s mind and extract key insights.
Dyads involve two respondents and a moderator. Dyads may be used to get a reaction and/or discussion between respondents when presenting a concept. Dyads facilitate consensus, dialogue, and confrontation between respondents. This tends to be a better approach with high-level executives or two different types of stakeholders, as disagreement is typically a source of rich information. On the other hand, “groupthink” may arise, where respondents’ innate desire to be well perceived by their peers dissuades them from expressing their true opinion.
Triads (three respondents) & Focus Groups drastically reduce the talking time of each respondent, so these are best used for product or concept testing. Face-to-face focus groups are particularly useful when there is a prototype or mock-up of the concept to provide a hands-on experience and see the respondents’ reactions to the product. Similar to dyads, “groupthink” can arise in triads and focus groups, which requires strong moderation capabilities to elicit the individual’s beliefs on a topic.
THE ART OF SAMPLING is to avoid biases and maximize response rate (RR)
Who to sample?
The first thing a researcher must do when collecting data is to find the right respondents to participate in the study. This again depends on the research objectives and scope. For example, in an ergonomics study the sample should be composed of the user, while a pricing study in B2B research should sample the relevant decision-makers.
How to avoid sample bias?
Sample bias is the biggest concern in data collection and is driven by screener requirements. If there is no screener, such that anyone is qualified to participate, then there is no bias. However, marketing research studies typically have a screener to ensure that the data collected is only from relevant targets. A quality screener balances these factors by restricting the study to relevant targets while not introducing more bias than necessary. From there, sampling bias can be mitigated by ensuring randomization of the targets on relevant demographic elements. In healthcare research for example, some of these demographics include: geography, type of institution, institution size, and years of experience. In B2C research, relevant demographics may include: income, ethnicity, origins, marital status, etc.
How many people to sample?
The simple answer is that more is always better. That said, more respondents come with greater fielding costs (recruitment and incentive) as well as increased duration of fieldwork. Therefore, the main consideration for sample size is budget. Fielding costs are highly variable depending on the targets. For example, in B2B research there tends to be a lack of available sample, simply because there are less qualified targets, and per-target costs are greater because high-level targets require more incentive. Alternatively, B2C research has relatively low fielding costs because there are many qualified targets and incentives are much lower.
DATA ANALYSIS: From data to actionable information
The final step in a marketing research study is to analyze the data that has been collected to extract key insights and address the research objectives. The type of analysis is dependent on the methodology that was employed. For example, in a conjoint study, the researcher may use a simulation tool to identify the preference share of a product within the competitive environment. For qualitative research, the analytical capabilities are much more limited, and may include identifying themes or key words that were brought up in multiple sessions. Quantitative data analysis can be considered as a three-step process, as follows:
- Data processing, identifying missing data, and verifying data quality
- First level analysis with means and frequencies
- Second level of analysis may include the following techniques:
- ANOVA (Analysis of Variance): Used to analyze the differences among means to determine statistical significance.
- Segmentation analysis: Seeks to identify natural groupings (i.e., segments) that have distinct behaviors, sets of beliefs, or characteristics. Segmentation may be achieved with one of the following methodologies: CHAID, CART, and cluster analysis.
- Discriminant analysis / Perceptual mapping: Weighs the interaction of measured characteristics to reveal key differences in customers’ perception of the tested offerings or concepts.
- Modeling and projection: Time-series analysis, repeated measures, market demand modeling (includes additional variables and calibration to sales data, etc.)
Marketing Research Trends
The marketing research industry has grown significantly in the past few decades as more businesses have found value in conducting research tailored to their needs. Voice of customer (VoC) research has become the standard, best practice approach to address business questions. The growth of marketing research has impacted the industry in several ways:
- It is increasingly difficult to recruit people to participate in research. This is particularly prevalent in healthcare, where many institutions have instated policies to prevent their employees from participating in research.
- Honoraria, that is, the monetary incentive to participate in research, has increased over the years. On the other hand, some respondents are forbidden to accept payment for participating or may not accept payment above a threshold amount. Payment restrictions are prevalent in healthcare research as a result of regulations such as the Sunshine Act in the USA and GDPR in the EU.
- Usage of online platforms has increased and tends to be the most convenient and cost-effective way of conducting research today.
As the industry continue to grow and adapt to meet demand, there are a few expected future trends:
- There will be new ways to get information such as advanced data analytics as well as language analysis via AI allowing for more efficient qualitative and secondary research analysis.
- Social media will allow for asynchronous research using tools such as online chat. This is a more intimate type of research, but it has yet to take a stronghold in the industry today.
- A continued need for a journalistic approach to marketing research, by conveying the key findings as a cohesive story in order to facilitate better comprehension and information retention.
Tips for a Successful Marketing Researcher
How TMTG can help you
Since 1995, The MarkeTech Group has been a leader in providing global marketing research for the healthcare IT, medical device, and pharmaceutical industries. Our passion for excellence is not restricted to revealing the voice of the customer. We go one step further to address your unique business challenges and goals by delivering highly actionable, strategic recommendations.
We deliver precise and innovative solutions to meet your marketing research needs throughout a product’s life cycle. In addition to our consulting excellence, we provide a suite of proprietary marketing research software including: simPRO™ (preference simulator), vwPRO™ (pricing simulator), Reactor ™ (demand simulator), PROfiler™ (segmentation tool), and chatPRO™ (social media, message board experience to directly interact with customers. We also provide a suite of tools to provide instantaneous access to imagePRO™ panel – the leading panel of imaging directors in the United States. This array of software will help you truly interact with your customized voice of customer data and shape your long-term marketing strategy.