ROI Methodology Whitepaper

1. The Problem with Traditional Income Tracking

Most freelancers track income in one of two ways: a spreadsheet summing gross revenue, or an accounting tool (Wave, QuickBooks) that records transactions but provides no time-adjusted analysis. Both approaches share the same fundamental flaw: they confuse revenue with value.

A freelancer with four income streams might see this in their accounting tool:

Now add time data:

The digital products stream — generating the least absolute revenue — has by far the highest ROI per hour. Without time-adjusted analysis, this freelancer might deprioritize their highest-value activity. GigAnalytics is built to surface this inversion systematically.

2. Core Definitions and Data Model

GigAnalytics operates on three first-class entities:

All calculations are performed over a configurable date range window (default: 90 days). Transactions and time entries outside the window are excluded. The window is applied independently to each stream.

3. Net Revenue Calculation

Gross revenue is what platforms report. Net revenue is what you actually keep. GigAnalytics uses net revenue — not gross — as the basis for all ROI calculations. This matters: Upwork charges a 10–20% service fee; Stripe charges 2.9% + $0.30; PayPal varies.

net_amount = gross_amount - fee_amount

Where fee_amount is:
  - Stripe: gross_amount × 0.029 + 0.30 (if not already in export)
  - PayPal: gross_amount × 0.0299 + 0.49 (if not in export)
  - Upwork: gross_amount × fee_rate (10-20% per contract tier)
  - CSV: use fee_amount column if present, else 0

stream_net_revenue(stream, from, to) =
  SUM(t.net_amount)
  FOR t IN transactions
  WHERE t.stream_id = stream.id
    AND t.transaction_date BETWEEN from AND to

4. True Hourly Rate

The true hourly rate is the central metric of GigAnalytics. It answers: "Given everything I earned and everything I spent on this stream, what did I actually make per hour of work?"

true_hourly_rate(stream, from, to) =
  (stream_net_revenue(stream, from, to) - acquisition_costs(stream, from, to))
  ÷ total_hours_worked(stream, from, to)

Where:
  acquisition_costs = SUM of ad spend, platform subscription fees,
                      tools, and other costs attributed to the stream
  total_hours_worked = SUM(time_entry.duration_minutes) / 60
                       FOR time entries in the date window

portfolio_hourly_rate(from, to) =
  SUM(stream_net_revenue(s, from, to) - acquisition_costs(s, from, to))
  ÷ SUM(total_hours_worked(s, from, to))
  FOR s IN active_streams

5. Acquisition ROI

Acquisition ROI measures the return on money spent to generate income from a stream. This includes ad spend, platform fees, tools subscriptions, and any other costs you explicitly attribute to a stream.

acquisition_roi(stream, from, to) =
  (stream_net_revenue(stream, from, to) - acquisition_costs(stream, from, to))
  ÷ acquisition_costs(stream, from, to) × 100

Result is a percentage.
A value > 0% means the stream is net-positive after acquisition costs.
A value of 400% means you earned $5 for every $1 spent on acquisition.

cost_per_dollar_earned(stream, from, to) =
  acquisition_costs(stream, from, to)
  ÷ stream_net_revenue(stream, from, to)

Lower is better. 0.0 = no acquisition cost. 1.0 = break-even.

6. Cross-Stream Comparison Index

Comparing streams by raw hourly rate alone ignores risk, effort variance, and income reliability. GigAnalytics computes a composite comparison index that weights four dimensions:

score(stream) =
  0.50 × normalize(true_hourly_rate)
  + 0.25 × reliability_score
  + 0.15 × normalize(acquisition_roi)
  + 0.10 × normalize(revenue_growth_rate)

Where normalize(x) maps x to [0, 1] across all active streams using min-max scaling.
reliability_score = months_with_income / total_months_in_window

7. Income Goal Projection

The pricing wizard answers: "Given my income goal, how should I price each stream?" The calculation works backwards from a target monthly net income.

For a stream you want to grow:

required_rate(stream, monthly_goal, target_hours) =
  monthly_goal / target_hours

Adjusted for acquisition costs:
required_gross_rate =
  (monthly_goal + projected_acquisition_costs) / target_hours

Where projected_acquisition_costs is extrapolated from
the stream's historical cost-per-revenue ratio.

8. Statistical Significance in Pricing Experiments

When you run an A/B pricing experiment (e.g., "$80/hr vs $100/hr for 30 days each"), GigAnalytics determines whether the observed revenue difference is statistically meaningful or likely due to random variation.

For two pricing variants A and B:

p_A = conversions_A / impressions_A
p_B = conversions_B / impressions_B
p_pool = (conversions_A + conversions_B) / (impressions_A + impressions_B)

z = (p_A - p_B) / sqrt(p_pool × (1 - p_pool) × (1/n_A + 1/n_B))

significance_level = two-tailed p-value from standard normal distribution

We report: "significant at 95% confidence" if |z| > 1.96

9. Design Decisions and Tradeoffs

10. Limitations and Known Edge Cases

• ⚠️

  Passive income attribution

  Royalties, affiliate income, and ad revenue are difficult to attribute to specific work hours. GigAnalytics excludes time-entry-less transactions from hourly rate calculations, which may cause passive income streams to appear artificially low or show "no hourly rate available."

• ⚠️

  Retainer contracts

  A $5,000/month retainer with variable deliverables will have accurate revenue tracking but potentially misleading hourly rates if the time logged doesn't reflect the full scope of work. We recommend logging all client-related time, including async communication.

• ⚠️

  Expenses beyond acquisition costs

  GigAnalytics currently models only acquisition costs as an expense category. General business expenses (equipment, software, insurance) are not subtracted from stream revenue — doing so would require a full bookkeeping model outside our scope.

• ⚠️

  Currency conversion lag

  Exchange rates are fetched at transaction_date. For multi-currency freelancers, actual received amounts may differ if payment processors apply their own exchange rates. The variance is typically < 2%.

• ⚠️

  Long-running projects

  A project billed in Month 3 for work done in Months 1–3 will be attributed to the transaction_date (Month 3). The ROI calculation for Month 3 will appear elevated, while Months 1–2 will appear lower. Use the 90-day window to smooth this out.