3. Strategic Planning, Objectives and Economics

Introduction: From Business Intent to Measurable Action

Digital advertising is often described through platforms, formats and targeting technologies. Yet effective performance marketing begins before a campaign is created. It begins with a strategic decision about what the organisation is trying to achieve, for whom, through which value proposition, and at what economic cost. Without this foundation, a campaign may generate impressions, clicks or conversions while still failing to create sustainable business value.

Strategic planning connects business ambition with communication and performance activity. A firm may seek market entry, profitable growth, customer retention, premium positioning, increased lifetime value or stronger brand salience. These are business outcomes, not advertising metrics. The planner’s task is to translate them into a coherent chain of objectives, audiences, messages, channels, measures and financial assumptions.

This chapter presents an integrated approach based on segmentation, targeting and positioning (STP), SMART objectives, KPI trees, unit economics and the relationship between acquisition, retention, revenue, profitability and brand outcomes. It treats performance marketing not as an isolated media function but as a managerial system in which media investment, customer behaviour and financial results are connected.

Learning Objectives

By the end of this chapter, students should be able to:

1. Distinguish business goals, marketing objectives, communication objectives and media or performance objectives.

2. Apply STP to define strategically valuable audiences and positioning choices.

3. Formulate objectives that are specific, measurable, achievable, relevant and time-bound.

4. Construct KPI trees linking business outcomes to controllable campaign metrics.

5. Calculate and interpret CAC, conversion rate, contribution margin, LTV, ROAS and related measures.

6. Evaluate trade-offs between acquisition, retention, revenue growth, profitability and brand building.

7. Design measurement and optimisation approaches that support managerial decision-making.

8. Identify ethical, technical and organisational risks in performance planning.

1. The Strategic Logic of Digital Advertising

A useful strategic plan answers five connected questions. First, what organisational result is required? Second, which customer or stakeholder group can contribute to that result? Third, what change in knowledge, attitude or behaviour is required? Fourth, what economic conditions make the activity viable? Fifth, how will progress and causality be assessed?

These questions prevent a common error: beginning with a platform rather than a problem. Selecting a social network, search engine or programmatic marketplace before defining the business objective encourages channel-led thinking. A channel is a means of reaching an audience; it is not a strategy in itself.

A hierarchy of objectives is helpful. A business goal may be profitable growth. A marketing objective may be to increase profitable subscriptions in a defined market. A communication objective may be to establish the service as a credible solution for a particular need. A performance objective may be to generate qualified trials at an allowable acquisition cost. A media objective may specify reach, frequency or efficient delivery among the priority audience. Each lower level should support, but not substitute for, the level above it.

The hierarchy also clarifies accountability. Senior management may own revenue and profit; marketing may influence demand, preference and customer value; media teams may optimise delivery, response and cost. No single metric can fairly evaluate every level.

2. STP as the Starting Point for Strategic Choice

Segmentation

Segmentation divides a broad market into groups with meaningful differences in needs, behaviour, value or response to marketing. Traditional bases include demographic, geographic, psychographic and behavioural characteristics. In digital environments, behavioural and contextual data can add dimensions such as purchase frequency, product usage, content engagement, device pattern and stage in the customer journey.

Effective segmentation is not simply the production of many audience labels. A segment should be identifiable, substantial or strategically important, reachable, differentiable and actionable. A small segment may still be valuable if it has high margins, strong referral potential or strategic importance. Conversely, a large segment may be unattractive if it is expensive to serve or weakly aligned with the brand.

Segmentation should also recognise the difference between observed behaviour and inferred identity. A user who visits a product page has demonstrated an action, but the action does not prove intent, income, attitude or personal characteristics. Strategic plans should therefore distinguish reliable first-party observations from probabilistic platform classifications.

Targeting

Targeting involves selecting the segments the organisation will prioritise and deciding how resources will be allocated among them. It requires a comparison of customer potential, competitive intensity, accessibility, expected response and economics. A target audience is not necessarily the same as the total audience exposed to an advertisement. Broad reach may be appropriate for a brand-building objective, while a narrower audience may be justified for a high-value conversion objective.

Targeting choices can be exclusive, prioritised or sequential. A firm may target early adopters first, then expand after evidence of product-market fit. It may use prospecting to create demand, retargeting to support evaluation and customer programmes to encourage repeat purchase. These activities should not be treated as independent campaigns when they address the same customer relationship.

Positioning

Positioning is the intended place of the brand or offering in the target customer’s mental and behavioural frame of reference. It explains why the offering is relevant, distinctive and credible. A positioning statement generally identifies the target, the category or need, the distinctive benefit and the reason to believe.

Positioning affects economics. A clear and differentiated value proposition can improve response rates, reduce dependence on discounts and support retention. A weak or undifferentiated proposition may force the firm to buy attention repeatedly or compete mainly on price. Thus, creative strategy and financial performance are not separate concerns.

3. From Goals to SMART Objectives

A goal expresses direction; an objective expresses a defined result. “Increase awareness” is a goal-like intention. “Increase aided awareness among prospective urban subscribers by eight percentage points within two quarters, while maintaining a defined reach and frequency, measured through a comparable brand study” is an objective with operational meaning.

The SMART framework requires objectives to be:

• Specific: focused on a defined outcome, audience, product or market.
• Measurable: associated with an observable indicator and credible method of measurement.
• Achievable: demanding but consistent with resources, market conditions and capability.
• Relevant: connected to the organisation’s strategic priorities.
• Time-bound: constrained by a stated period or milestone.

SMART does not mean that every objective must be short-term or purely numerical. Brand preference, trust and perceived relevance may be measured through research rather than immediate sales. Nor does a numerical target become strategic merely because it is precise. A target for low cost per click can be harmful if it attracts low-quality traffic.

A strong objective identifies the unit of change. The unit may be people reached, qualified leads, completed orders, active users, retained accounts, revenue, contribution profit or a brand-attitude score. It should also identify the baseline, target, period, audience and owner. For example: “Increase the proportion of first-time purchasers who make a second purchase within 90 days from 22% to 28% among customers acquired in the first half of the year.”

Objectives should be separated into leading and lagging indicators. Leading indicators, such as qualified visits, product engagement or trial activation, provide early signals. Lagging indicators, such as retained revenue or contribution profit, confirm whether value was ultimately created. Optimising only leading indicators can produce attractive dashboards without business improvement.

4. Building a KPI Tree

A KPI tree decomposes a high-level outcome into the drivers that influence it. It helps teams move from measurement abundance to measurement logic. Consider the following simplified revenue model:

Revenue = Traffic × Conversion Rate × Average Order Value.

If traffic itself is the result of impressions and click-through rate, then:

Revenue = Impressions × Click-through Rate × Conversion Rate × Average Order Value.

This decomposition permits diagnosis. If revenue falls, the cause may be reduced delivery, weaker engagement, lower landing-page conversion, lower basket value or a combination of factors. Each branch suggests different managerial actions.

For a subscription business, a more appropriate tree may be:

Customers acquired × activation rate × retention rate × average revenue per customer.

For profitability, revenue is insufficient. A simplified contribution-profit tree is:

Contribution profit = Revenue − variable product and service costs − variable fulfilment costs − marketing cost.

A KPI tree should distinguish outcome KPIs from diagnostic and activity metrics. Profit, retained revenue or customer lifetime value may be outcome measures. Conversion rate, cost per qualified lead and repeat-purchase rate are drivers. Impressions, bids, audience size and creative variants are activity or delivery measures. The fact that an activity is measurable does not make it important.

A practical KPI tree normally contains:

1. A north-star business outcome.

2. Two or more major value drivers.

3. Metrics that diagnose each driver.

4. Definitions, data sources, frequency and ownership.

5. Decision rules specifying what action follows a change.

For example, a team might define a rule that prospecting is scaled only when incremental customer acquisition cost remains below the contribution-based threshold for two consecutive measurement periods. Such rules reduce arbitrary optimisation.

5. The Economics of Acquisition and Retention

Customer acquisition cost

Customer acquisition cost (CAC) is commonly calculated as:

CAC = Attributable acquisition spend ÷ Number of new customers acquired.

The word “attributable” requires care. If total marketing expenditure is divided only by directly tracked conversions, CAC may be overstated or understated depending on the allocation method. Costs may include media, creative production, agency fees, technology, incentives and sales effort. Organisations should state which costs are included and use a consistent definition.

Cost per lead or cost per conversion is not automatically CAC. A lead becomes economically meaningful only when its quality and progression are understood. Similarly, a platform-reported purchase may not represent an incremental purchase caused by advertising.

Contribution margin and allowable acquisition cost

Contribution margin is the amount remaining after variable costs are deducted from revenue. If a product sells for $100 and variable costs are $60, the contribution is $40 before acquisition cost. If the organisation expects to recover acquisition investment from the first purchase, allowable CAC cannot exceed $40, subject to overhead and risk assumptions.

A firm may rationally accept a higher first-order CAC when repeat purchases are probable. However, this decision should be based on contribution, not revenue alone. Discount-heavy campaigns can produce high revenue and negative contribution.

Lifetime value

Customer lifetime value (LTV) estimates the economic value of a customer over a defined relationship period. A basic contribution-based model is:

LTV = Average contribution per purchase × Expected purchase frequency × Expected relationship duration.

For a subscription, an approximate model may use:

LTV = Average contribution per period × Expected number of active periods.

These models are simplifications. They should account, where possible, for churn, retention cohorts, refunds, service costs, discounting and differences among customer segments. LTV is not a universal fact about a customer; it is a forecast under specified assumptions.

The LTV:CAC ratio can support comparison, but it should not be used mechanically. A high ratio may reflect underinvestment and missed growth, while a low ratio may be acceptable during a controlled market-entry phase. Payback period—the time required for contribution from a customer to recover CAC—is often more useful for cash-constrained businesses.

ROAS and its limitations

Return on advertising spend is:

ROAS = Attributed revenue ÷ Advertising spend.

ROAS is useful for comparing campaigns under a consistent attribution and revenue definition. It does not reveal profit unless margins are stable and other variable costs are excluded or separately considered. A campaign selling high-margin products may justify a lower revenue ROAS than one selling low-margin products. Profit-based measures such as contribution return on ad spend can therefore be more decision-relevant.

6. Aligning the Customer Lifecycle

Strategic planning should connect acquisition, activation, retention, expansion and advocacy. Acquisition creates the opportunity for a relationship; it does not complete it. A campaign that delivers inexpensive first orders but attracts customers who never return may destroy value. Conversely, retention activity cannot compensate indefinitely for a poor product or a misleading acquisition promise.

The customer journey is not always linear, but lifecycle planning remains useful. At the awareness and consideration stages, objectives may concern reach, attention, understanding and qualified engagement. At conversion, they may concern completed purchase, trial or application. After conversion, activation, repeat purchase, renewal, cross-sell, referral and reduced churn become important.

The strategic issue is coordination. Prospecting messages should not promise benefits that onboarding fails to deliver. Retargeting should respect exclusions for existing customers when acquisition messages are irrelevant. Frequency management is necessary because repeated exposure can support recall but also create irritation and waste. Retention investment should be evaluated against the incremental value of preventing churn, not against the cost of a single message.

Brand outcomes and performance outcomes are interdependent. Brand familiarity and trust can improve future response, reduce friction and support pricing power. Short-term conversion activity can generate sales but may weaken the brand if it relies on deceptive urgency, excessive discounting or inconsistent positioning. A balanced plan therefore uses both immediate response measures and longer-horizon indicators such as consideration, preference, distinctive associations and customer advocacy.

7. Measurement, Attribution and Experimentation

Digital platforms provide detailed reporting, but reporting is not the same as causal measurement. Attribution assigns credit according to a rule; incrementality asks what additional outcome occurred because of the activity. Last-click attribution may be simple and useful for operational reporting, yet it can undervalue earlier exposures, organic demand and offline influences.

Common approaches include platform attribution, rule-based multi-touch attribution, media mix modelling, geo-experiments, holdout tests and controlled lift studies. Each has assumptions and data requirements. No method eliminates uncertainty. A responsible planner uses triangulation: platform data for optimisation, experiments for causal confidence and financial analysis for business relevance.

A measurement plan should specify the conversion event, data owner, source of truth, attribution window, exclusions, identity rules, reporting cadence and quality checks. Events should be defined consistently across website, application, CRM and advertising platforms. Data discrepancies should be investigated rather than silently averaged.

Experimentation is especially important when teams face competing claims. A/B tests can compare creative, landing pages or offers, provided randomisation, sample size and success criteria are appropriate. Holdout designs can estimate incremental conversions or retention. Tests should avoid changing multiple major variables without a reason, and results should be interpreted with uncertainty rather than as permanent truths.

8. An Applied Illustrative Case: Northstar Meal Kits

Background

Northstar Meal Kits is an illustrative direct-to-consumer subscription service operating in three metropolitan markets. It offers weekly ingredient boxes and recipe instructions. The firm has grown through paid social and search advertising but reports rising acquisition costs and a high cancellation rate after the first box.

Situation and problem

Management has been using first-order revenue and platform-reported ROAS as its primary measures. The media team receives a target of 4.0 ROAS, while the retention team is measured separately on cancellation. Discounted first orders produce attractive revenue but low contribution. The company wants growth, yet it cannot determine whether additional advertising will create profitable customers.

Analysis

The planning team begins with STP. It identifies three segments: convenience-seeking professionals, price-sensitive family shoppers and food enthusiasts seeking variety. Cohort analysis shows that convenience-seeking professionals have a higher average order value and stronger three-month retention, although they cost more to acquire. The team therefore prioritises this segment rather than selecting the cheapest available audience.

The business objective is defined as profitable subscriber growth. The marketing objective is to increase active subscribers while maintaining a positive contribution after acquisition cost. Communication objectives focus on communicating reliable convenience, flexible menu choice and predictable delivery. Performance objectives include qualified trial starts, activation after the first delivery and 90-day retention.

The team constructs a KPI tree. Active subscribers depend on new activated subscribers, retained subscribers and churn. Contribution profit depends on subscriber revenue, food and fulfilment costs, discounts and acquisition expenditure. Diagnostic metrics include landing-page conversion, trial-to-first-delivery completion, first-to-second-box retention and contribution CAC.

Historical data indicates an average first-box contribution of $18, an average second-box contribution of $24 and an average third-box contribution of $25. The firm estimates that a typical retained customer contributes $92 during the first six months, after variable service costs and discounts. It sets a provisional six-month CAC ceiling below $92, with a stricter target based on cash-flow requirements.

Strategy and solution

Northstar changes its campaign structure in four ways. First, prospecting creative focuses on the convenience problem rather than a generic discount. Second, the landing page presents delivery flexibility and menu choice before the promotional offer. Third, onboarding messages help customers select meals and modify deliveries, addressing avoidable early churn. Fourth, reporting separates new-customer acquisition from retention and uses cohort contribution rather than first-order revenue alone.

The firm tests two prospecting audiences and two value propositions through controlled experiments. It uses a holdout group in one market to estimate incremental subscription starts and monitors 90-day retention by acquisition source. Existing customers are excluded from prospecting campaigns where appropriate, while a separate programme tests referral and add-on offers.

Outcome

The case is illustrative rather than a report of a real company, so no external performance claim is implied. The strategic outcome is that management can now distinguish cheap acquisition from valuable acquisition. The media team is allowed to scale only when contribution CAC and retention meet agreed thresholds. A campaign with lower platform ROAS may be preferred if it produces stronger six-month contribution and lower churn.

Learning points

The case demonstrates five principles. STP determines whose value matters. SMART objectives make the desired change explicit. KPI trees connect operational signals to business outcomes. Unit economics prevent revenue metrics from disguising loss. Finally, acquisition and retention must be planned as one economic system.

9. Strategic Risks, Governance and Professional Judgement

Several risks undermine objective-led planning. Vanity metrics can reward visible activity without value. Overly narrow attribution can shift credit rather than create demand. Forecasts may treat LTV as certain, ignore churn or use averages that conceal unprofitable segments. Teams may also optimise towards a target that is easy to measure rather than one that matters.

Data quality is a central governance issue. Duplicate conversions, consent gaps, broken event tags, changing attribution windows and inconsistent revenue definitions can materially distort decisions. Organisations should document metric definitions, maintain access controls, respect consent requirements and avoid using sensitive personal information in ways that create unfair exclusion or unlawful profiling.

Ethical planning requires more than legal compliance. Advertising should not exploit vulnerability, conceal material conditions or use manipulative interface design. Audience exclusion can produce discriminatory outcomes even when automated systems are used. Frequency, personalisation and retargeting should be proportionate and transparent. Performance pressure does not justify misleading claims or the use of dark patterns.

Managerial judgement remains essential. A dashboard cannot decide whether to sacrifice short-term efficiency for strategic entry, whether a brand investment is premature, or whether a high-value segment is being overexposed. Such decisions require assumptions, scenario analysis and explicit risk appetite.

10. Technology, Automation and Emerging Practice

Modern advertising systems automate bidding, audience selection, creative variation and budget allocation. Machine learning can identify patterns that are difficult to manage manually, but it optimises the signals supplied to it. If the conversion event is low-quality, automation may scale low-quality outcomes efficiently. The quality of inputs, objectives, exclusions and feedback loops is therefore decisive.

Server-side measurement, clean rooms, consent-aware identity solutions and first-party data strategies are increasingly important as third-party identifiers become less dependable. These technologies can improve measurement, but they do not remove the need for governance or causal testing. Artificial intelligence can support forecasting, segmentation, copy development and anomaly detection; human review remains necessary for accuracy, bias, brand suitability, privacy and compliance.

Emerging practice is moving from platform-specific optimisation towards portfolio management. Budgets are evaluated across the customer lifecycle, with attention to marginal returns, payback, incrementality and resilience. Scenario planning is also becoming more important: managers ask what happens if acquisition costs rise, retention falls, a channel becomes unavailable or a privacy rule changes.

Best Practices for Strategic Performance Planning

A disciplined planning process should:

• Begin with a business outcome rather than a media format.
• Use STP to make explicit choices about priority customers.
• Define objectives with baselines, targets, time periods and owners.
• Build KPI trees that distinguish outcomes, drivers and activities.
• Use contribution economics rather than revenue alone.
• Separate new-customer, retained-customer and brand measures.
• Document attribution, measurement and data-quality assumptions.
• Combine platform reporting with experiments and financial analysis.
• Review forecasts by cohort and segment instead of relying only on averages.
• Set decision rules before results are observed where feasible.
• Protect privacy, fairness, transparency and brand trust.
• Revisit assumptions as markets, products and customer behaviour change.

Chapter Summary

Strategic digital advertising translates organisational ambition into measurable, economically defensible action. STP identifies valuable audiences and clarifies the positioning that should guide communication. SMART objectives convert broad intentions into defined outcomes with baselines, measures and time limits. KPI trees connect business results to their operational drivers, preventing teams from confusing activity metrics with value.

Unit economics provide the financial discipline required for performance marketing. CAC, contribution margin, LTV, payback and ROAS must be defined carefully and interpreted in relation to product margins, retention and cash-flow requirements. Acquisition should be integrated with activation, retention, expansion and advocacy, while brand and performance outcomes should be managed as complementary rather than opposing systems.

Measurement requires more than platform attribution. Sound planning combines consistent data definitions, experimentation, incrementality thinking and managerial judgement. Automation and AI can improve execution, but they amplify the quality of the objectives and data provided to them. Ethical governance, privacy, transparency and fairness are therefore strategic requirements, not peripheral concerns.

Key Terms

Business goal: A broad organisational result the firm seeks to achieve.

Marketing objective: A defined market or customer outcome supporting a business goal.

Communication objective: A desired change in audience awareness, understanding, attitude or behaviour.

Performance objective: A measurable response or commercial outcome used to manage marketing activity.

Segmentation: Division of a market into groups with meaningful differences.

Targeting: Selection and prioritisation of segments for investment.

Positioning: The intended distinctive place of an offering in the customer’s perception.

SMART objective: An objective that is specific, measurable, achievable, relevant and time-bound.

KPI tree: A hierarchical model linking a business outcome to its causal or diagnostic drivers.

Leading indicator: An early signal that may predict a later business result.

Lagging indicator: A measure of an outcome after it has occurred.

Customer acquisition cost (CAC): Attributable acquisition expenditure divided by new customers acquired.

Contribution margin: Revenue remaining after specified variable costs are deducted.

Customer lifetime value (LTV): Estimated contribution or value generated by a customer over a defined relationship period.

ROAS: Attributed revenue divided by advertising expenditure.

Payback period: Time required for customer contribution to recover acquisition cost.

Attribution: A rule for assigning credit for an outcome to marketing contacts or channels.

Incrementality: The additional outcome caused by an intervention compared with what would have happened without it.

Cohort: A group of customers sharing a defined acquisition or behavioural characteristic and observed over time.

Unit economics: Financial analysis of revenue, cost and contribution at the level of a customer, order or transaction.

Review Questions

Short Answer Questions

1. Distinguish a business goal from a performance objective.

2. What makes a market segment strategically actionable?

3. Why should a KPI tree separate outcome measures from activity metrics?

4. Define customer acquisition cost and identify one cost-definition issue.

5. Why can ROAS be misleading as a measure of profitability?

Long Answer Questions

1. Explain how STP informs digital advertising strategy, using an example of a multi-segment market.

2. Discuss the role of SMART objectives in aligning management, marketing and media teams.

3. Explain how acquisition, retention and brand outcomes can be integrated in one planning system.

4. Compare attribution and incrementality as approaches to evaluating advertising effectiveness.

5. Analyse the importance of contribution margin, LTV and payback period in performance marketing decisions.

Analytical / Application Questions

1. A campaign generates $120,000 in attributed revenue from $30,000 in advertising spend. Variable product and fulfilment costs equal 65% of revenue. Calculate ROAS and contribution before advertising cost, then explain why the two measures lead to different interpretations.

2. Construct a KPI tree for an online education subscription whose business goal is profitable growth. Include at least one outcome KPI, three driver KPIs and relevant activity metrics.

3. A firm can choose between Segment A, with CAC of $45 and six-month contribution of $60, and Segment B, with CAC of $70 and six-month contribution of $120. Evaluate the choice using contribution, payback considerations and strategic assumptions that would require further investigation.

22. Multiple Choice Questions with Answers

Question 1

Which statement best represents the correct hierarchy of strategic objectives?

A. Media format → platform metric → communication objective → business goal

B. Business goal → marketing objective → communication or performance objective → operational measures

C. Performance metric → business goal → audience segment → positioning

D. Audience size → creative execution → revenue forecast → business goal

Correct Answer: B. Business goal → marketing objective → communication or performance objective → operational measures

Question 2

A segment is most strategically useful when it is primarily distinguished by which combination?

A. Its size alone

B. Its availability on a single advertising platform

C. Meaningful need or behaviour, reachability and actionability

D. The number of demographic variables attached to it

Correct Answer: C. Meaningful need or behaviour, reachability and actionability

Question 3

Which objective is most clearly SMART?

A. Improve brand performance soon

B. Get more clicks from social media

C. Increase second-purchase rate among first-half customers from 22% to 28% within 90 days

D. Become the most popular service in the market

Correct Answer: C. Increase second-purchase rate among first-half customers from 22% to 28% within 90 days

Question 4

If Revenue = Impressions × Click-through Rate × Conversion Rate × Average Order Value, which metric should be examined first when impressions remain stable but revenue declines?

A. Only the number of employees

B. Click-through rate, conversion rate and average order value

C. The brand’s legal structure

D. The total market population alone

Correct Answer: B. Click-through rate, conversion rate and average order value

Question 5

A product generates $100 in revenue and has $60 in variable costs before advertising. What is its contribution before advertising cost?

A. $40

B. $60

C. $100

D. $160

Correct Answer: A. $40

Question 6

Why might a campaign with a lower ROAS be preferred to one with a higher ROAS?

A. It always has more impressions

B. It may generate higher contribution because of better margins or retention

C. ROAS is never useful

D. Lower ROAS always indicates stronger branding

Correct Answer: B. It may generate higher contribution because of better margins or retention

Question 7

Which measure most directly addresses whether advertising caused additional conversions rather than merely receiving credit for them?

A. Incrementality

B. Frequency

C. Reach

D. Creative length

Correct Answer: A. Incrementality

Question 8

In a KPI tree, profit is best classified as which type of measure?

A. Business outcome KPI

B. Creative activity metric

C. Audience descriptor

D. Delivery setting

Correct Answer: A. Business outcome KPI

Question 9

What is a major danger of optimising only for low cost per lead?

A. It may increase the quality of retained customers automatically

B. It can reward inexpensive but low-quality leads that do not create value

C. It eliminates the need for segmentation

D. It guarantees positive contribution margin

Correct Answer: B. It can reward inexpensive but low-quality leads that do not create value

Question 10

Which practice best supports responsible use of automated advertising systems?

A. Allowing the system to optimise an undefined conversion event

B. Using platform-reported revenue without checking data quality

C. Providing clear objectives, reliable conversion signals, exclusions and governance

D. Removing human review from targeting and creative decisions

Correct Answer: C. Providing clear objectives, reliable conversion signals, exclusions and governance