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Marketing risk assessment

Growth Marketing and Conversion Optimization Risk Assessment: Attribution, Fraud, Claims and Account Controls

A worked example of how a small growth marketing team finds, scores and controls the risks that waste budget, mislead customers and weaken trust in conversion work, from attribution errors and fake leads to privacy gaps and platform dependency.

Updated November 2026 8 hazards assessed Review every 3 months Highest risk: Critical to Medium
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Executive summary

This assessment shows how a small growth marketing team can find, rate and control the risks that matter most to its budget, its measurement and the trust customers place in its messages. Eight risks were chosen because they are plausible in everyday paid acquisition and conversion work. Misleading claims and privacy failures carry the highest inherent scores because their consequences reach regulators and customers. Budget overspend and attribution errors are likely but easier to correct. Each risk is scored before controls and again after existing and added controls. Most risks fall to Medium or Low once added controls are in place, but claims risk stays Medium because the impact remains serious. The first actions are daily spend limits, a claims register, multi-factor sign in and a written test plan. The business is a teaching example, so every score illustrates method, not a real organization.

Focus area
Growth marketing, paid acquisition and conversion rate optimization
Setting
In-house growth team of a mid-sized online retailer running paid social, search, email and landing page tests
Method
Five by five likelihood and impact risk register with inherent and residual scoring

Scope

This assessment covers the planning, launch and monitoring of paid acquisition campaigns, landing page and checkout experiments, email and influencer promotion, and the reporting used to judge them. It looks at risks to budget, measurement, customer trust, legal duties and platform access. Jurisdiction, product type, advertising platforms and team size are not specified, so they are treated as assumptions for teaching. It does not give legal advice on advertising claims or review a live campaign.

Context

The team has a growth lead, two marketing executives, a data analyst and a freelance designer. Campaigns run on several advertising platforms, supported by an analytics tool, a tag manager, a customer relationship system and a testing tool. Influencers and a creative agency are engaged on fixed term contracts. Each risk is scored before controls to show its natural level, then again after existing controls and the additional controls proposed here.

Objectives, assets and stakeholders

The objective is to grow profitable customer acquisition and conversion while keeping spend under control, measuring results honestly, respecting customer consent and staying within advertising rules. The assets in scope are the advertising and analytics accounts, the audience and customer data, the testing results, the brand and its public voice, and the budget. Stakeholders include the growth team, the budget holder, the data protection lead, customers, influencers, agencies, platform partners and regulators. Clear roles matter: every risk has one owner role, and the growth lead reviews the register with the head of marketing each month.

Risk matrix: before and after controls

Each cell shows hazard numbers placed by likelihood and impact. Compare the two grids to see how controls move each hazard.

Before controls

Inherent risk

Risk before controls: rows are likelihood from almost certain to rare, columns are impact from insignificant to catastrophic. Cells list hazard numbers.
1
Insignificant		 2
Minor		 3
Moderate		 4
Major		 5
Catastrophic
5 Almost certain
4 Likely Likelihood 4, impact 3, score 12, high: H02 H07 Likelihood 4, impact 4, score 16, high: H01 H05 Likelihood 4, impact 5, score 20, critical: H04
3 Possible Likelihood 3, impact 3, score 9, medium: H08 Likelihood 3, impact 4, score 12, high: H03 H06
2 Unlikely
1 Rare

After controls

Residual risk

Risk after controls: rows are likelihood from almost certain to rare, columns are impact from insignificant to catastrophic. Cells list hazard numbers.
1
Insignificant		 2
Minor		 3
Moderate		 4
Major		 5
Catastrophic
5 Almost certain
4 Likely
3 Possible Likelihood 3, impact 2, score 6, medium: H07
2 Unlikely Likelihood 2, impact 2, score 4, low: H03 H08 Likelihood 2, impact 3, score 6, medium: H01 H02 H05 H06 Likelihood 2, impact 4, score 8, medium: H04
1 Rare
  • Low 1 to 4
  • Medium 5 to 9
  • High 10 to 16
  • Critical 17 to 25

Hazard register

A summary first, then the detail for each hazard.

Summary of hazards with scores before and after controls
No.HazardBeforeAfterOwner
H01 Budget overspend and wasted acquisition spend 16 High 6 Medium Growth lead
H02 Attribution errors and misleading test results 12 High 6 Medium Marketing data analyst
H03 Fraudulent traffic and fake leads 12 High 4 Low Paid media manager
H04 Misleading claims and advertising law breach 20 Critical 8 Medium Head of marketing
H05 Privacy, consent and targeting failures 16 High 6 Medium Data protection lead
H06 Account compromise and platform lockout 12 High 6 Medium IT manager
H07 Brand and reputational harm from influencer or agency failure 12 High 6 Medium Brand manager
H08 Platform and vendor dependency 9 Medium 4 Low Marketing operations manager
H01

Budget overspend and wasted acquisition spend

Financial Before 16 After 6

Campaign budgets are raised, left running or allocated to poor performing audiences without review, so spend exceeds plan and returns fall well below what the business expects from paid acquisition.

Who or what is affected: Growth team, budget holder and finance function

Causes

Automated bidding left unchecked, pressure to hit volume targets and budget moved without a record.

Consequences

Cash lost to poor campaigns, distorted cost per acquisition and a cut in future budgets.

Existing controls

  • Monthly budget caps are set in each ad account.
  • Spend is reviewed in a weekly marketing meeting.

Control gaps

Caps are set monthly, so a campaign can overspend within days before anyone notices.

Additional controls

  • Prevent: Set hard daily spend limits and an approval threshold for any budget increase.
  • Detect: Compare spend with plan each day and flag any campaign running ahead of its pacing curve.
Likelihood 4 x impact 4 before; 2 x 3 after Owner: Growth lead Target: Within 30 days Early warning: Daily spend above 110 percent of planned pacing on any single campaign.
H02

Attribution errors and misleading test results

Operational Before 12 After 6

Tracking tags, cookies and platform reports double count or misassign conversions, and tests are stopped early or run without enough traffic, so the team scales the wrong campaigns and pages.

Who or what is affected: Marketing leadership, data analysts and finance reviewers

Causes

Mixed attribution models, duplicate tags and peeking at results before a test ends.

Consequences

Wrong budget decisions, failed launches and a false sense of what works.

Existing controls

  • Conversions are checked against order totals each week.
  • Tests use a fixed sample size set before launch.

Control gaps

Platform dashboards are trusted over order data, and early stopping is not recorded.

Additional controls

  • Prevent: Set a minimum sample size and run length in a written test plan before any launch.
  • Detect: Reconcile platform conversions with order records and investigate gaps above an agreed tolerance.
Likelihood 4 x impact 3 before; 2 x 3 after Owner: Marketing data analyst Target: Within 45 days Early warning: Platform conversions differ from order records by more than 10 percent in a single week.
H03

Fraudulent traffic and fake leads

Financial Before 12 After 4

Bots, click farms and fake sign ups inflate traffic and lead numbers, so the team pays for visits and leads that never convert and reports a growth picture that does not exist.

Who or what is affected: Growth team, sales staff and budget holder

Causes

Automated traffic sources, low cost placements and weak checks on form input.

Consequences

Wasted spend, sales time lost on fake leads and distorted growth reporting.

Existing controls

  • Ad platform invalid traffic filters are switched on.
  • Lead forms require email verification.

Control gaps

Filters are platform defaults that are never tuned to the business.

Additional controls

  • Prevent: Block known bot sources and suspicious placements, and limit lead form submissions per address.
  • Detect: Review lead quality each week and flag clusters of identical or disposable email addresses.
Likelihood 3 x impact 4 before; 2 x 2 after Owner: Paid media manager Target: Within 30 days Early warning: Lead form submissions rising sharply while engagement and repeat visits stay flat.
H04

Misleading claims and advertising law breach

Legal and compliance Before 20 After 8

Ads, landing pages and influencer posts make product claims, discounts or testimonials that cannot be supported by evidence, or hide the commercial nature of content, which can breach advertising rules.

Who or what is affected: Customers, the business, platforms and regulators

Causes

Pressure for strong headlines, untested superlatives and content created without legal review.

Consequences

Takedown, complaints, fines or orders from regulators, and lasting loss of customer trust.

Existing controls

  • Ad copy is reviewed by a second person before launch.
  • Product claims must cite a source held on file.

Control gaps

Evidence files are not checked for currency and influencer disclosures are not audited after posting.

Additional controls

  • Prevent: Keep a claims register listing the evidence behind each product claim and its approving owner.
  • Respond: Pull and correct any ad or page within one working day of a complaint or review finding.
Likelihood 4 x impact 5 before; 2 x 4 after Owner: Head of marketing Target: Within 30 days Early warning: A complaint, platform rejection or reviewer note that questions a product claim.
H05

Privacy, consent and targeting failures

Technology and data Before 16 After 6

Tags, pixels and customer lists are used before consent is recorded, or sensitive audiences are targeted, so personal data is collected or shared in ways customers did not agree to.

Who or what is affected: Customers, data protection lead and marketing team

Causes

Many third party tags, lookalike audiences built from weak data and consent rules not understood by the team.

Consequences

Complaints, regulator scrutiny, forced deletion of data and a loss of customer goodwill.

Existing controls

  • A cookie consent banner is shown on the website.
  • Customer lists are uploaded only where sign up consent is recorded.

Control gaps

Tags are added by campaign teams without a central list, so new pixels go unchecked.

Additional controls

  • Prevent: Collect only the data each campaign needs and exclude sensitive audiences from targeting.
  • Detect: Audit tags and pixels each month to confirm they fire only after consent is given.
Likelihood 4 x impact 4 before; 2 x 3 after Owner: Data protection lead Target: Within 45 days Early warning: A tag that fires before consent is recorded in a test or routine audit.
H06

Account compromise and platform lockout

Technology and data Before 12 After 6

Advertising, analytics or email accounts are taken over through phishing or shared passwords, so campaigns are altered, budgets are spent or the business loses access to its own data.

Who or what is affected: Growth team, finance, customers whose data is held and platform partners

Causes

Phishing emails, reused passwords and accounts shared with agencies and freelancers.

Consequences

Unauthorized spend, deleted audiences, leaked data and a campaign blackout.

Existing controls

  • Ad accounts use named user access.
  • Passwords are stored in a managed password vault.

Control gaps

Agency logins are not reviewed when contracts end.

Additional controls

  • Prevent: Require multi-factor sign in and remove access for leavers within one working day.
  • Recover: Keep a documented recovery route and a second administrator on every ad and analytics account.
Likelihood 3 x impact 4 before; 2 x 3 after Owner: IT manager Target: Within 30 days Early warning: Unexpected sign in alerts or payment method changes on any advertising account.
H07

Brand and reputational harm from influencer or agency failure

Reputational Before 12 After 6

An influencer post, agency creative or community reply is offensive, misleading or off brand, and it spreads quickly through paid amplification before the business can respond.

Who or what is affected: Brand, customers, influencers and agency staff

Causes

Fast creative cycles, influencers with weak oversight and comments that go unmoderated.

Consequences

Public complaints, removed content, lost partners and a dip in conversion.

Existing controls

  • Influencer contracts include disclosure and approval duties.
  • Agency work is reviewed before publication.

Control gaps

Approval covers the main post only, not later edits, replies or stories.

Additional controls

  • Prevent: Approve each influencer brief and disclosure wording before any content is posted.
  • Respond: Pause paid amplification and publish a correction if a post misleads or offends.
Likelihood 4 x impact 3 before; 3 x 2 after Owner: Brand manager Target: Within 30 days Early warning: Complaint volume or negative comment rate rising well above the usual weekly level for a post.
H08

Platform and vendor dependency

Supplier Before 9 After 4

The business relies on one advertising platform, testing tool or agency for most traffic and data, so a policy change, outage or contract end stops growth and makes past results hard to reuse.

Who or what is affected: Growth team, leadership and key vendors

Causes

Concentration of spend, lock in to proprietary tools and policy rules that change without notice.

Consequences

Lost traffic, lost audiences, rising costs and weak negotiating power.

Existing controls

  • Key vendors are listed in a supplier register.
  • Budgets are spread across two advertising platforms.

Control gaps

Exports exist only for some tools and the fallback plan has never been tested.

Additional controls

  • Prevent: Export customer lists and test results each month to a store the business controls.
  • Recover: Keep a fallback channel plan and a tested transfer route to another testing tool.
Likelihood 3 x impact 3 before; 2 x 2 after Owner: Marketing operations manager Target: Within 60 days Early warning: A platform policy change or outage affecting more than 20 percent of conversions.

Rating method and evaluation

Each risk is rated on two five-point scales. Likelihood runs from rare to almost certain, and impact runs from minor to severe. Multiplying the two gives a score from 1 to 25, which falls into one of four bands: Low from 1 to 4, Medium from 5 to 9, High from 10 to 16 and Critical from 17 to 25. The score guides the order of work and is not a precise measurement. Inherent risk is the score before any controls. Residual risk is the score after existing and added controls, and it can never be higher than the inherent score. Impact is judged on money lost, customer harm, legal exposure, time to correct and damage to trust. A risk is never rated down only because it has not happened yet. Anything still High needs senior attention and a dated plan, anything Medium needs routine controls with a named owner, and anything Low is accepted and watched. Team members who run campaigns should challenge the ratings, and each rating is reviewed whenever a warning indicator reaches its threshold or a campaign changes materially.

Likelihood, impact and rating bands

Likelihood

  • 5 Almost certain: Expected to happen in most circumstances.
  • 4 Likely: Will probably happen in many circumstances.
  • 3 Possible: Could happen at some time.
  • 2 Unlikely: Not expected, but it could happen.
  • 1 Rare: Only in exceptional circumstances.

Impact

  • 1 Insignificant: No lasting effect. Handled within routine work.
  • 2 Minor: Small effect that is quickly corrected.
  • 3 Moderate: Noticeable effect that needs managed effort to correct.
  • 4 Major: Serious effect on people, delivery or reputation.
  • 5 Catastrophic: Severe or lasting effect that threatens the whole activity.

Bands (likelihood x impact)

  • Low (1 to 4): Accept and monitor.
  • Medium (5 to 9): Manage with routine controls.
  • High (10 to 16): Senior attention and a treatment plan.
  • Critical (17 to 25): Act first. Do not proceed until reduced.

Monitoring, escalation and review

Review this assessment every 3 months, and sooner when an indicator below reaches its threshold.

Early-warning indicators and escalation thresholds
Indicator to watchEscalate when
Daily spend above 110 percent of planned pacing on any single campaign.Escalate to the growth lead the same day, and to the budget holder if spend stays above plan for two days.
Platform conversions differing from order records by more than 10 percent in a week.Escalate to the marketing data analyst for review within two working days, and to the head of marketing if the gap persists.
A product claim questioned by a complaint, platform rejection or reviewer note.Escalate to the head of marketing at once, pause the asset, and refer to specialist legal review within one working day.
A tag or pixel that fires before consent is recorded, or unexpected sign in alerts on an ad account.Escalate to the data protection lead or IT manager at once, and suspend the tag or lock the account until cleared.
Negative comment rate or complaint volume rising well above the usual weekly level for a post.Escalate to the brand manager the same day, and to the head of marketing if the rise continues for 48 hours.

Contingency arrangements

If a serious event occurs, such as a claims complaint from a regulator, a confirmed account takeover or a viral negative post, the head of marketing pauses the affected campaigns and preserves records. The IT manager locks compromised accounts and restores audiences from the latest exported copy. The data protection lead decides whether data must be deleted or reported as the rules that apply require. Legal review is sought through the company secretary, and customers and partners are told what they need to know early and plainly.

Prioritized action plan

  1. Set hard daily spend limits and a written approval threshold for budget increases, owner growth lead, within 30 days.
  2. Start a claims register and require legal review of every product claim and disclosure, owner head of marketing, within 30 days.
  3. Enable multi-factor sign in and remove agency access when contracts end, owner IT manager, within 30 days.
  4. Audit tags and pixels against consent records each month, owner data protection lead, within 45 days.
  5. Write test plans with sample sizes and reconcile platform conversions with orders, owner marketing data analyst, within 45 days.

Conclusion

Reliable growth depends on a few steady habits: capped budgets, written test plans, honest claims backed by evidence, consent checks on every tag and tested access recovery. The highest scores sit with claims and privacy risks, and each has actions that bring residual scores down. Treat the register as a living record, review it every quarter or after any major change, and seek qualified legal and data protection advice for any real advertising, privacy or contract question.

Assumptions and limitations

Assumptions

  • The business sells consumer goods online and collects customer data through its website and email sign up forms.
  • Marketing spend is approved by a budget holder each month and paid through company cards or invoices.
  • Jurisdiction is not specified, so advertising, consent and privacy duties are described in general terms only.

Limitations

  • The scores are examples for learning and do not describe any real campaign, platform or business.
  • Advertising, privacy and consumer rules vary by place and change over time, so specialist legal review is needed.
  • This is educational content and is not legal, financial or professional marketing advice.

Related frameworks to study

  • Risk register with likelihood and impact scoring
  • Three lines model of risk ownership
  • Hierarchy of controls
  • Consent and data minimization principles for marketing data

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For Learning Reference Only: This assessment demonstrates how risk assessment principles are applied in a practical setting, providing a useful reference for learning and understanding. Actual assessments may be adapted to suit specific site conditions and circumstances.

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