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Optimizing the quality of your marketing strategy:
CMM (Consumer Mix Modeling) Analysis Platform
COMPASS
This is a unique CMM analysis platform that mathematically elucidates consumers' "brand choice structure."
We analyze the impact of the 4Ps of marketing, competition, and external factors on purchasing behavior.
Deepen your understanding of consumers and optimize the quality of your company's strategies.
*Part of the COMPASS technology is currently under patent application.
ISSUE We are listening to the "voice of the consumer."
Still, why aren't there any results?
Many marketing managers, despite having large amounts of survey data and reports, are unable to answer questions such as "Why did it sell (or not sell)?" and "Which factors most contribute to consumer purchasing behavior?"
Customers' "true feelings" and "purchasing motivations"
from Japan.
They are unable to grasp the "unconscious" purchasing motives that customers themselves cannot put into words, such as "There is a contradiction between what they say in the interview and their actions" or "Survey scores are high but sales are not increasing."
Supporting strategic certainty
There is a lack of evidence
It is not possible to formulate a highly reliable strategy, as "the direction is determined by rules of thumb and subjective interpretations" and "there are hypotheses, but there is no objective evidence to prove whether they are really the 'best move'".
The "criteria" for the measures are vague,
精度が落ちる
The strategy is poorly supported, instructions to the company and agencies are abstract, and there is no common understanding among the parties involved. Judgments about the quality of the output become unclear, leading to a decline in the quality of execution.
SOLUTION We will use statistics to explain "why it was chosen."
Quantifying customers' true feelings and identifying the next step to increase sales
COMPASS is an analytical consulting firm that uses its proprietary CMM (Consumer Mix Modeling) analytical platform to unravel the mechanisms of consumer brand choice. We analyze the impact of the 4Ps of marketing, CX, and brand assets on consumer purchasing behavior. Rather than simply compiling data, we use statistical analysis to calculate the probability of switching from competitors and increasing loyalty.
Visualizing customers' unconscious purchasing motives
High scores do not necessarily lead to purchases. COMPASS quantifies which factors have the greatest impact on brand selection (purchase).
Identify the "who, what, and where" of your strategy
We derive winning patterns by combining target attributes (Who), the message to be conveyed (What), and the optimal touchpoint (Where).
From "intuitive discussions" to "data-driven agreements"
Objective evidence based on statistical models becomes the "common language" in internal meetings and agent briefings, enabling quick decision-making and reliable execution.
*Part of the COMPASS technology is currently under patent application.
RELATED WHITEPAPER
At the forefront of marketing strategy formulation
- CMM reveals the mechanism of brand selection
In this white paper, we explain the analysis method "CMM", which statistically analyzes the mechanism of consumer brand selection and enables effective strategy design. How can CMM be used to dig deeper into consumer insights that could not be fully captured by conventional questionnaire surveys and incorporate them into concrete marketing strategies? We will explain in detail using examples from a restaurant chain.
right now
materials
Read More
FEATURES Two analytical approaches to choose from depending on the issue
"Why we are chosen" and "Why we continue to be chosen" -- we support strategy formulation using two approaches depending on your objectives.
Analysis of the mechanism of "brand choice" among competitors:
Brand Switch Analysis
Identify the key factors that will persuade customers to switch from your competitors' products to your brand.
Analysis Perspective
Analyze which elements of each competitor need to be strengthened to maximize the likelihood of switching to your company
Suggestions gained
It is possible to perform simulations such as "If the score is increased by one point, the market share will increase by a certain percentage," and to derive specific measures to seize market share.
Analysis of your company's "loyalty" mechanism:
Loyalty Driver Analysis
We will develop "light users" into "medium/heavy users" and clarify the loyalty factors to prevent them from leaving.
Analysis Perspective
Analyze not only behavior but also what forms the psychological loyalty behind it
Suggestions gained
It is possible to conduct simulations such as "What percentage of customers will become loyal if the score is increased by one point?", and to design measures to improve LTV.
DIFFERENCE WITH TRADITIONAL SURVEYS Common pitfalls with traditional surveys
In general surveys, a higher score than the average or competitors is considered a good score, but this does not necessarily mean that the brand will be chosen more often.
Although it provides an understanding of the current situation for each item's score, it is often difficult to translate it into actionable information, such as the impact of improvement or predictions based on that information.
Even if the degree of impact is considered using a statistical approach, it is difficult to take into account the heterogeneity of respondents, and the results tend to be weak as suggestions for specific actions.
HOW IT WORKS CMM Consulting Process and Analysis Flow
From hypothesis design to simulation, data scientists and consultants will accompany you and guide you to success in sure steps.
STEP 1: Strategy organization and hypothesis discussion
We clarify the target audience and segments and decide which demographic to approach. We analyze and design after sorting out your company's current marketing situation and issues, such as your competitors' market share and your company's loyalty status.
STEP 2: Data collection and analysis
We design surveys to structurally and numerically grasp the driver elements for increasing "switches" and "loyalty," collect asking data, and then perform analysis.
STEP 3: Model construction and simulation
Finally, we develop a consumer behavior model and perform a switching rate simulation to quantitatively evaluate the extent to which each factor affects consumers' brand choice.
ANALYSIS OUTPUTs An example of CMM analysis output
Patent pending
We convert complex consumer psychology into "numbers" and "structures" that can be used for decision-making and present them to you.
Identify numerically what you need to focus on to win
We visualize in a ranking format which elements (4P, CX, brand image) are most effective in switching customers from competitors/converting them into loyal customers.
This is the point
- Calculating the "switch rate*" makes priorities clear
- Identify the differences in effective "attack methods" against competitors A and B (Brand Switch Analysis)
*Switch rate: The percentage of people who switch/loyal when their survey response score increases by 1 point
Organizing "strengths to maintain" and "opportunities to exploit"
Plot elements on two axes: "your company's evaluation score" and "difference with competitors." This clarifies the "maintenance elements (critical success factors)" where you are already winning, and the "growth elements" where you are competing closely.
This is the point
- At a glance, you can see where you should focus your investment resources
- Avoid inefficient investments (which have already won or have little impact)
Clarifying the structure of brand choice
We identify not only the direct impact on consumer behavior, but also the "indirect effect" via a specific brand image, and structurally clarify which measures contribute to building brand assets.
This is the point
- Identify the specific experiences and messages needed to increase brand loyalty and trust
- The entire mechanism of measures → change in attitude → purchasing behavior can be quantified.
RELATED WHITEPAPER
Identify your selling points to beat your competitors
- Data-driven strategy that connects analysis to the next step
This white paper addresses the issue of "competitive analysis not leading to action" by explaining a methodology for identifying winning "selling points" based on data. How do you calculate the probability that consumers will switch from a competitor (switching rate) and develop a strategy to maximize your return on investment? We introduce a practical framework using examples from a consumer goods manufacturer.
right now
materials
right now
materials
MMM × CMM SYNERGY CMM × MMM Synergy
By combining this with analysis using our unique MMM (Marketing Mix Modeling) analysis platform, "MAGELLAN," we can aim to optimize both the "quality" and "quantity" of marketing, thereby realizing a growth cycle.
CMM clarifies who should be approached and how, while MMM clarifies the optimal budget allocation (where and how much) to maximize ROI. This synergy strengthens data-driven decision-making and dramatically improves the success rate of a company's marketing strategy.
