CDMRE MCQ cheat sheet

SMART objectives: Specific, Measurable, Achievable, Relevant, Time-bound; each objective maps to a KPI.

AIDA funnel stages: Awareness, Interest, Desire, Action; budget allocation should reflect stage-specific goals.

Customer lifetime value (CLV) = average purchase value × purchase frequency × customer lifespan.

CLV:CAC ratio of 3:1 is a common benchmark; below 1:1 means acquisition spend exceeds customer value.

PESTLE analyzes Political, Economic, Social, Technological, Legal, Environmental macro factors.

SWOT: Strengths and Weaknesses are internal; Opportunities and Threats are external.

Marketing mix (4Ps): Product, Price, Place, Promotion; digital adds People, Process, Physical evidence (7Ps).

A channel mix decision rule: fund channels with lowest CAC at or above target ROAS before scaling new channels.

Primary data is collected firsthand (surveys, interviews); secondary data is pre-existing (reports, databases).

Probability sampling: simple random, systematic, stratified, cluster; every unit has a known selection probability.

Non-probability sampling: convenience, purposive, quota, snowball; results cannot be generalized with confidence intervals.

Margin of error for a proportion ≈ z × √(p(1−p)/n); at 95% confidence z = 1.96.

Sample size n = z²p(1−p)/e²; for p=0.5, e=0.05, 95% confidence yields n ≈ 384.

Likert scales are ordinal; report median or mode rather than mean unless treated as interval data.

Leading or double-barreled questions bias responses; pretest instruments to detect wording problems.

Response rate = completed responses ÷ eligible sample contacted; low rates raise non-response bias risk.

Five-stage purchase process: need recognition, information search, evaluation of alternatives, purchase, post-purchase behavior.

Maslow hierarchy: physiological, safety, social, esteem, self-actualization; lower needs dominate until satisfied.

Cognitive dissonance is post-purchase discomfort; brands reduce it with reassurance, warranties, and follow-up content.

Reference groups and opinion leaders shape norms; social proof (reviews, ratings) leverages conformity.

Loss aversion: losses loom larger than equivalent gains, so framing offers as avoided loss can increase uptake.

Anchoring: the first number presented biases subsequent judgments of price or value.

Segmentation criteria: measurable, accessible, substantial, differentiable, actionable (MASDA).

Persona = fictional archetype built from research data; it should cite behavioral and demographic evidence, not assumptions.

On-page factors: title tag, meta description, heading hierarchy, internal links, keyword placement in body.

Technical SEO: crawlability (robots.txt), indexability (noindex), canonical tags, XML sitemap, page speed (Core Web Vitals).

Off-page authority is driven mainly by backlinks; relevance and quality of linking domains matter more than raw count.

Keyword intent types: informational, navigational, commercial investigation, transactional; match content format to intent.

Search ad rank = bid × quality score (plus expected impact of extensions); higher quality score lowers CPC.

Quality score components: expected CTR, ad relevance, landing page experience.

ROAS = revenue ÷ ad spend; a ROAS of 4 means $4 revenue per $1 spent.

Negative keywords prevent ads from matching irrelevant queries and reduce wasted spend.

Content funnel mapping: awareness (blogs, videos), consideration (case studies, webinars), conversion (demos, offers).

Editorial calendar defines cadence, owner, channel, and format for each content asset.

Engagement rate = (likes + comments + shares) ÷ reach (or impressions); state the denominator used.

Reach is unique users who saw content; impressions count total displays; frequency = impressions ÷ reach.

UGC (user-generated content) increases trust; disclose paid partnerships per FTC endorsement guides.

Evergreen content retains search value over time; newsjacking content decays quickly.

A/B testing content: change one variable per test and use sufficient sample size before declaring a winner.

Social listening tracks brand mentions and sentiment; sentiment scoring must be validated against a human-coded sample.

CPM = (cost ÷ impressions) × 1000; CPC = cost ÷ clicks; CPA = cost ÷ conversions.

CTR = clicks ÷ impressions; conversion rate = conversions ÷ clicks.

ROAS = revenue ÷ ad spend; ROI = (revenue − cost) ÷ cost. ROAS ignores margin; ROI does not.

Programmatic buying uses real-time bidding (RTB) auctions; DSP buys inventory, SSP sells it.

Frequency capping limits exposures per user per period to reduce ad fatigue and wasted impressions.

Attribution models: last-click, first-click, linear, time-decay, position-based, data-driven; each redistributes credit differently.

Viewability standards: display ads ≥50% pixels in view for ≥1 second; video ≥50% for ≥2 seconds (MRC/IAB).

Campaign flighting: continuous, pulsing, or burst scheduling; choose based on seasonality and budget constraints.

Bounce rate = single-page sessions ÷ all sessions; a bounce is a session with no interaction hit.

Conversion rate = conversions ÷ sessions (or users); always state the denominator.

A/B test significance: use a two-proportion z-test; p < 0.05 is the conventional threshold.

Statistical power of 0.80 means an 80% chance of detecting a true effect of the specified size.

UTM parameters: source, medium, campaign, term, content; they attribute traffic in analytics tools.

Last-click attribution overstates lower-funnel channels; use incrementality tests to measure true lift.

Cohort analysis groups users by acquisition date to compare retention curves over time.

KPI vs metric: a KPI is a metric tied directly to a strategic objective; not every metric is a KPI.

Mean is sensitive to outliers; median is robust; mode is the most frequent value.

Standard deviation measures spread around the mean; variance is its square.

Correlation does not imply causation; establish causality with experiments or quasi-experimental designs.

Simpson's paradox: an aggregate trend can reverse when data is segmented by a confounding variable.

Confidence interval = estimate ± (critical value × standard error); 95% CI excludes the null if p < 0.05.

Data visualization rule: match chart type to data (bar for categories, line for time series, scatter for correlation).

Dashboard design: lead with the decision-relevant KPI, then supporting context; avoid decorative chart junk.

Segmentation analysis should report segment size, behavior, and statistical difference from the overall population.

GDPR lawful bases include consent, contract, legal obligation, vital interests, public task, legitimate interests.

GDPR data subject rights: access, rectification, erasure, restriction, portability, objection.

Consent must be freely given, specific, informed, and unambiguous; pre-ticked boxes are invalid under GDPR.

CCPA/CPRA grants California consumers rights to know, delete, opt out of sale/sharing, and correct personal information.

CAN-SPAM requires accurate header info, non-deceptive subject lines, an opt-out mechanism, and a physical address in commercial email.

FTC endorsement guides require clear disclosure of material connections between advertisers and endorsers.

Dark patterns (e.g., confirmshaming, hidden costs, roach motel) are deceptive design tactics and may violate consumer protection law.

Data minimization: collect only personal data necessary for the stated purpose; retain only as long as needed.