Fictional examples, clearly labelled

See how different FMCG teams could use Satuangka.

Each scenario shows the data, decision, possible value, and setup work involved. Every number is an assumption for planning—not a customer claim.

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Illustrative scenario—not a customer claim

Beauty and skincare

Starting problem

Marketplace reports disagree with finance, hero-SKU margin is unclear, and campaigns can exhaust stock.

Data sources involved

  • Shopee and TikTok Shop exports
  • Meta and TikTok advertising reports
  • SKU master and landed COGS
  • Inventory snapshots
  • Discount and refund reports

Implementation requirements

SKU master, effective-dated COGS, six months of marketplace and advertising history, fee definitions, and weekly inventory snapshots.

Decision Satuangka enables

Satuangka maps every SKU, fee, deduction, and campaign period so the team can protect stock and scale only contribution-positive demand.

Illustrative impact assumptions

  • 32 reporting hours × Rp125.000 = Rp4,0 jt capacity/month
  • Rp12 jt assumed monthly margin leakage identified
  • Rp18 jt forecast revenue exposure protected before a campaign
Illustrative scenario—not a customer claim

Food and beverage

Starting problem

Promotions drive volume, but low-margin bundles and channel fees make profitability hard to compare.

Data sources involved

  • Marketplace and distributor sales files
  • Bundle and promotion definitions
  • COGS and fulfilment costs
  • Refund and expiry adjustments
  • Inventory by lot or SKU

Implementation requirements

Product and bundle master, promotion calendar, landed cost, channel deductions, fulfilment rates, and expiry rules.

Decision Satuangka enables

Satuangka separates base product economics from promotion mechanics and compares contribution by bundle and channel.

Illustrative impact assumptions

  • 24 reporting hours × Rp125.000 = Rp3,0 jt capacity/month
  • Rp9 jt assumed promotion leakage avoided
  • 14 days of excess cover removed from one slow bundle
Illustrative scenario—not a customer claim

Personal care

Starting problem

Ad costs rise while repeat-purchase visibility and profitable hero-product selection remain weak.

Data sources involved

  • Meta and marketplace ad reports
  • Website and marketplace orders
  • Customer identifiers or cohorts
  • SKU contribution model
  • Campaign taxonomy

Implementation requirements

Campaign naming standards, order history, privacy-approved customer keys, SKU costs, refund data, and an agreed attribution window.

Decision Satuangka enables

Satuangka links spend to new customers, repeat behavior, revenue, and contribution so budgets follow durable unit economics.

Illustrative impact assumptions

  • 28 reporting hours × Rp125.000 = Rp3,5 jt capacity/month
  • Rp8 jt assumed weak campaign spend stopped
  • 4 contribution points recovered through discount review
Illustrative ROI model

Test the value case with your own assumptions.

Adjust the assumptions

Illustrative values only—not achieved customer results.

Illustrative monthly valueRp44 jt

Time capacity releasedRp5 jt

Margin + spend + stock impactRp39 jt

Compare this with the subscription and setup fee. Your actual value will depend on data quality, execution, and business conditions.

Let’s untangle the first question together

Bring one messy report. Leave with a clearer next move.

We’ll spend 45 minutes on your sources, metric gaps, priority decision, and the safest next step. No generic sales presentation.

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