Marketing Engineering, Conjoint Analysis, CLV, and Marketing Metrics

0.0(0)
Studied by 0 people
call kaiCall Kai
learnLearn
examPractice Test
spaced repetitionSpaced Repetition
heart puzzleMatch
flashcardsFlashcards
GameKnowt Play
Card Sorting

1/36

flashcard set

Earn XP

Description and Tags

Comprehensive vocabulary flashcards covering the core concepts, quantitative formulas, psychological models, and strategic tools of Marketing Engineering, Conjoint Analysis, Customer Lifetime Value, Customer Satisfaction, and Brand Positioning Metrics.

Last updated 11:40 PM on 10/15/26
Name
Mastery
Learn
Test
Matching
Spaced
Call with Kai
Chat

No analytics yet

Send a link to your students to track their progress

37 Terms

1
New cards

Marketing Engineering

The practice of using data (the 'physics') and mathematical or statistical models (the 'math') to design marketing strategies that are efficient, robust, and deliver measurable return on investment.

2
New cards

Click-Through Rate (CTR)

The percentage of individuals who clicked on an advertisement out of the total impressions it received, computed as CTR=(ClicksImpressions)×100\text{CTR} = \left(\frac{\text{Clicks}}{\text{Impressions}}\right) \times 100.

3
New cards

Average Order Value (AOV)

A sales metric tracking the average amount of money spent by customers per transaction, calculated as AOV=Total RevenueNumber of Orders\text{AOV} = \frac{\text{Total Revenue}}{\text{Number of Orders}}.

4
New cards

Cost-Per-Click (CPC)

A digital marketing advertising efficiency metric calculated by dividing the total advertising spend by the number of clicks generated (CPC=Ad SpendClicks\text{CPC} = \frac{\text{Ad Spend}}{\text{Clicks}}).

5
New cards

Cart Abandonment Rate

The percentage of potential purchasers who add items to an online cart but exit without completing a purchase, calculated as (Cart Adds−PurchasesCart Adds)×100\left(\frac{\text{Cart Adds} - \text{Purchases}}{\text{Cart Adds}}\right) \times 100.

6
New cards

RFM Analysis

A database segmentation tool that evaluates customer value based on three behavioral dimensions: Recency (how recently they purchased), Frequency (how often they buy), and Monetary value (how much they spend).

7
New cards

Marketing Mix Modeling (MMM)

An analytical modeling technique that quantifies the impact of various marketing activities (such as TV, social media, and digital promotions) to optimize the allocation of marketing budgets for maximum return.

8
New cards

Conjoint Analysis

A decompositional market research method that models consumer preferences by asking respondents to evaluate multi-attribute alternatives, statistically inferring the underlying utility of each attribute level.

9
New cards

Decompositional Preference Model

An approach in preference modeling where consumers evaluate a product bundle as a whole, and statistical methods deconstruct this overall evaluation into discrete utilities for each individual component or attribute.

10
New cards

Part-Worth Utility

An interval-scaled numerical score indicating the subjective value or preference a consumer assigns to a specific level of a product attribute, centered around zero within each attribute.

11
New cards

Attribute Importance Weight

A percentage representing the relative impact of an attribute on consumer choice, calculated as ImportanceA=(Utility RangeA∑Utility Ranges of All Attributes)×100\text{Importance}_A = \left(\frac{\text{Utility Range}_A}{\sum \text{Utility Ranges of All Attributes}}\right) \times 100.

12
New cards

Choice-Based Conjoint (CBC)

A conjoint methodology where respondents select their single preferred offering from a set of competing product profiles (or choose 'none'), closely simulating real marketplace purchase behavior.

13
New cards

Orthogonal Array

A statistical experimental design framework used to select an efficient fractional subset of product profiles to test, allowing unconfounded estimation of main attribute utilities without surveying every combination.

14
New cards

Market Simulator

A decision support model that utilizes calculated conjoint utilities to predict market shares, test product configurations, and conduct 'what-if' competitive simulations.

15
New cards

Logit Model (Conjoint Simulation)

A probabilistic simulation model using Euler's number (e≈2.71828e \approx 2.71828) that converts total product utility into non-negative choice probabilities and simulated market share values.

16
New cards

Customer Lifetime Value (CLV)

The present value of all future net profits expected to be generated from a customer across their entire relationship with a business, viewed as an ongoing stream of cash flows rather than a single transaction.

17
New cards

Customer Acquisition Cost (CAC)

The total sales and marketing expenditure required to win a new customer, calculated as CAC=Total Acquisition CostsNumber of New Customers Acquired\text{CAC} = \frac{\text{Total Acquisition Costs}}{\text{Number of New Customers Acquired}}.

18
New cards

CLV:CAC Ratio

A vital health metric comparing the lifetime profit of a customer to the cost of acquiring them, with a ratio of 3:13:1 or higher recognized as the standard benchmark for a sustainable business.

19
New cards

Customer Retention Rate (CRR)

The percentage of customers maintained over a defined period, calculated using the formula CRR=(E−NS)×100\text{CRR} = \left(\frac{E - N}{S}\right) \times 100, where EE is ending customers, NN is newly acquired customers, and SS is starting customers.

20
New cards

Customer Equity

The total financial asset value of a company's customer base, represented conceptually as the aggregated lifetime values of all current and potential future customers.

21
New cards

Customer Pyramid

A value-based customer segmentation model categorizing accounts into four distinct tiers based on profitability and loyalty: Platinum (top tier/advocates), Gold, Iron (mass market), and Lead (costly/drain on resources).

22
New cards

Customer Satisfaction

A psychological state resulting from a customer's cognitive comparison between pre-purchase expectations and post-consumption perceived performance (Perception≥Expectation\text{Perception} \ge \text{Expectation}).

23
New cards

Expectancy Confirmation Theory

A psychological theory stating that customer satisfaction is determined by whether product performance confirms, positively disconfirms (exceeds), or negatively disconfirms (falls short of) pre-purchase expectations.

24
New cards

Positive Disconfirmation

An outcome within Expectancy Confirmation Theory where actual product or service performance exceeds customer expectations (Performance>Expectations\text{Performance} > \text{Expectations}), producing high satisfaction or delight.

25
New cards

Cognitive Dissonance

The psychological discomfort or post-purchase doubt experienced by a consumer holding conflicting thoughts or beliefs after making a significant purchase decision.

26
New cards

Customer Satisfaction Score (CSAT)

A transactional satisfaction metric calculated as CSAT (%)=(Number of Satisfied Customers [Ratings 4 and 5]Total Number of Respondents)×100\text{CSAT (\%)} = \left(\frac{\text{Number of Satisfied Customers [Ratings 4 and 5]}}{\text{Total Number of Respondents}}\right) \times 100.

27
New cards

Net Promoter Score (NPS)

A customer loyalty and brand advocacy index derived from a 0–10 recommendation scale, calculated as NPS=% Promoters (9–10)−% Detractors (0–6)\text{NPS} = \%\,\text{Promoters (9--10)} - \%\,\text{Detractors (0--6)}.

28
New cards

Customer Effort Score (CES)

A service-process metric tracking the ease of interaction or issue resolution for a customer, built on the philosophy that minimizing customer friction increases loyalty.

29
New cards

Product Positioning

The strategic act of designing a company's offering and brand identity to occupy a distinct, valued, and competitive position in the mind of the target consumer.

30
New cards

Point of Difference (POD)

A core attribute, feature, or benefit of a brand's offering that convincingly sets it apart from and makes it superior to existing competitive alternatives in the market.

31
New cards

Reason to Believe (RTB)

The credible evidence, proof points, or factual support provided by a brand to substantiate its positioning claims and customer promises.

32
New cards

Unaided Awareness

A top-of-mind brand visibility metric measuring the percentage of target consumers who mention a brand spontaneously without any prompt when asked about a product category.

33
New cards

Aided Awareness

A brand familiarity metric measuring the percentage of survey respondents who recognize a brand when presented with its name alongside other competitors.

34
New cards

Market Share

A behavioral indicator of competitive strength representing the portion of total industry sales captured by an individual brand: Market Share=(Company Sales RevenueTotal Market Sales Revenue)×100\text{Market Share} = \left(\frac{\text{Company Sales Revenue}}{\text{Total Market Sales Revenue}}\right) \times 100.

35
New cards

Sales Growth Rate

A primary financial metric measuring the trajectory of sales revenue changes over time, calculated as (Current Period Sales−Previous Period SalesPrevious Period Sales)×100\left(\frac{\text{Current Period Sales} - \text{Previous Period Sales}}{\text{Previous Period Sales}}\right) \times 100.

36
New cards

Return on Marketing Investment (ROMI)

A marketing efficiency metric quantifying profitability from marketing activities, calculated as ROMI=(Incremental Revenue×Contribution Margin)−Marketing CostMarketing Cost\text{ROMI} = \frac{(\text{Incremental Revenue} \times \text{Contribution Margin}) - \text{Marketing Cost}}{\text{Marketing Cost}}.

37
New cards

Repeat Rate

A behavioral retention metric measuring the percentage of unique buyers who return to complete more than one purchase within a given time period: (Repeat CustomersTotal Unique Customers)×100\left(\frac{\text{Repeat Customers}}{\text{Total Unique Customers}}\right) \times 100.