ForgeSDLC
Navigate
Home
Discover ForgeSDLC (101)
Practice (201)
Master (301)

This page is part of the ForgeSDLC knowledge base — an AI-assisted, human-directed methodology for taking product work from concept to production. For the core operating model and vocabulary, see Forge SDLC overview and What is ForgeSDLC?.

Paid Advertising & Social Media Marketing

Overview: Paid advertising buys reach and intent capture on platforms where your ICP already spends attention. Social media marketing blends organic presence, community, and paid boosts so creative, targeting, and landing experience stay aligned. For digital products, both must connect to measurement, attribution, and product onboarding — not vanity reach alone.

CPC ranges are illustrative; they vary wildly by industry, geo, and auction dynamics. Use them for relative planning only.

Platform Audience & formats Targeting highlights Typical CPC (indicative) Best for
Google Ads — Search, Display, Shopping, YouTube High-intent search; visual/video reach Keywords, audiences, in-market, custom intent, PMax Search: mid–high; Display: lower B2B/B2C; dev tools (search + YouTube tutorials)
Meta — Facebook, Instagram Broad consumer; visual storytelling Interests, lookalikes, retargeting, Advantage+ Mid (varies by vertical) B2C; prosumer; creative-heavy categories
LinkedIn Ads Professional, job-title granular Company, title, seniority, Matched Audiences, ABM lists High B2B; enterprise; hiring/HR adjacencies
Twitter / X Ads Newsy, tech, creator-adjacent Keyword, follower lookalikes, engagement retargeting Mid–high (volatile) Launch moments; dev/tech audiences (validate current policy/tools)
TikTok Ads Younger skew; short video Interest, behavior, Spark Ads (organic-style) Mid B2C; viral creative testing
Reddit Ads Community-niche Subreddit, interest, keyword Low–mid Niche B2C/B2B; authentic tone required
flowchart LR I[Impression] --> CL[Click] CL --> LP[Landing page] LP --> CV[Conversion] CV --> AT[Attribution & modeling] AT --> I

Campaign structure

Level Role Best practices
Account Billing, access, global settings Separate brands or regions; shared libraries where appropriate
Campaign Objective, budget, geo, schedule One primary goal per campaign; align naming to funnel stage
Ad group / ad set Audience + creative theme + placements Tight themes; avoid mixing unrelated intents
Ad Copy, creative, extensions 3–5 variants per set; refresh on fatigue signals

Naming and tracking: Use a consistent convention (region_objective_audience_vN) and UTM parameters (or platform click IDs) so web analytics, CRM, and warehouse models agree on source/medium/campaign. Document parameter ownership so product and marketing do not fork conventions.

Creative testing checklist

Check Question
Hook Does the first 1–2 seconds state the problem or outcome?
Proof Is there a concrete stat, logo, or demo frame?
CTA Is the next step obvious and consistent with the landing page?
Format Static, carousel, short video — matched to platform norms?
Fatigue When did this creative last beat a challenger on CPA or CTR?

Targeting strategies

Strategy When it shines
Keyword targeting Search: capture existing demand; use negatives aggressively
Audience targeting Demographics, interests, custom segments from first-party data
Lookalike / similar Scale after a seed list of converters
Retargeting / remarketing Recover consideration-stage users; cap frequency
Contextual Brand-safe placements; topic alignment
Account-based (LinkedIn) Named accounts; sales + marketing alignment

Bidding strategies

Model Meaning When to use
CPC Pay per click Learning phases; tight keyword control
CPM Pay per thousand impressions Awareness with strong creative testing
CPA / cost per conversion Optimize toward conversions Stable pixel/SDK and volume
ROAS target Revenue per ad spend E-com and clear LTV signals
Maximize conversions Platform-driven volume After baseline tracking is trusted

Landing page optimization

  • Message match: Headline and hero mirror the ad promise and keyword intent.
  • Single primary CTA: Reduce competing actions above the fold.
  • Social proof: Logos, quotes, usage stats — truthful and specific.
  • Form optimization: Fewer fields, smart defaults, progressive profiling post-signup.
  • A/B testing: Tie experiments to hypothesis and pre-registered success metrics.

Social media strategy

Dimension Organic Paid
Goal Community, trust, retention signals Scale reach, retargeting, conversions
Cadence Sustainable publishing + engagement Flight-based with creative rotation
Risk Algorithm shifts Cost inflation, policy changes

Platform selection (simple frame): For each candidate platform, score audience fit × content you can ship consistently × business model (PLG vs sales-led). Drop platforms where two of three are weak.

  • Content calendar: Mix education, proof, behind-the-scenes, and community highlights; align peaks with product launches.
  • Community management: Response SLAs, escalation paths, and moderation standards belong in ops docs — not only marketing.

Social media metrics

Metric Definition / use
Reach Unique users who saw content
Engagement rate Interactions ÷ reach or followers (define denominator consistently)
Share of voice Brand mentions vs competitors (sampled)
Follower growth Net new; quality > raw count
Social traffic Sessions and assisted conversions from social referrers
Social conversions Signups/purchases attributed to social touchpoints
flowchart TB C[Publish content] --> E[Engagement] E --> R[Reach & saves] R --> A[Awareness & follows] A --> CV[Conversion paths] CV --> INS[Insights: creative & topics] INS --> C

Attribution models

Model Logic Strength / weakness
Last click 100% credit to final touch Simple; undervalues upper funnel
First click Credit to discovery Highlights acquisition; ignores nurture
Linear Equal credit across touches Fairer blend; can dilute signal
Time decay More credit to recent touches Balances recency and path
Position-based Heavy first + last, light middle Hybrid; still somewhat arbitrary
Data-driven ML allocation (where data volume allows) Powerful when models are trusted and audited

Budget allocation

  • Testing budget: Fixed slice for new channels, audiences, and creative formats before scale decisions.
  • Scaling rules: Many teams increase spend 20–30% when ROAS or CPA holds above target for a defined window — avoid sudden 2× jumps that reset learning.
  • Seasonality: Retail peaks, fiscal-year enterprise cycles, and conference seasons should pre-allocate creative and landing updates.
  • Incrementality: Where possible, run geo or audience holdouts and platform lift studies — last-click dashboards often over-credit paid social and under-credit organic + brand.

Compliance and brand safety

Ad platforms and regions impose privacy, targeting, and copy rules (cookies, sensitive categories, political ads, financial services). Maintain a short policy sheet per channel: prohibited claims, required disclaimers, and approval workflows so launches are not blocked at the last mile.

Anti-patterns

Anti-pattern Why it hurts
Broad targeting without learning data Burned spend, no insight
No negative keywords (search) Irrelevant clicks and polluted learning
Creative fatigue ignored Rising CPA, declining CTR
Vanity metrics as north stars Reach without pipeline or retention
No attribution / conversion tracking False confidence in channel mix

External references

  • Google Ads Help — policies, bidding, measurement
  • Meta Business Help Center — Ads Manager, pixels, catalogs
  • Donald Miller, Marketing Made Simple — clarifying message and funnel alignment (book)

Index: channels/README.md · Marketing map: ../MARKETING.md


Keep project-specific marketing plans in docs/product/marketing/ and GTM documents in docs/product/, not in this file.