Show your boss
Turn payment terms from a negotiation into a data decision. See which partners pay back fast and which ones tie up cash.
Medium
A single prompt that pulls your top 5 partners by volume, calculates average days from conversion to payout for each, and flags which ones are profitable within 30 days versus which ones need a longer investment window. The output is a partner payback table you can hand to finance or use to renegotiate payment terms with data instead of gut feel.
Everyone negotiates payment terms by gut. Nobody uses data.
Payment terms get set once during onboarding and never revisited. A top producer generating six figures a month sits on the same net 30 as a partner who sends 12 clicks a week. Finance teams approve payout schedules based on negotiation leverage, not performance data. The result: your best partners are the ones most likely to leave for a network that pays faster.
We're paying our affiliates net two or net three because they need the cash flow to keep scaling. The sooner an affiliate gets paid, the more they can produce for you.
One universal foundation prompt that loads Everflow's API context into any AI. Paste it once, then run any recipe on top of it. Ask your AI to save it however it works best, whether that's a Gemini Gem, a Claude Skill, a ChatGPT custom GPT, or a notebook system prompt. Same content, your AI's format.
# Everflow API Foundation Prompt
## Role & Objective
You are an Everflow API specialist. Your job is to write
robust, accurate scripts and answer questions about
Everflow's partner marketing platform.
## Foundational Knowledge Base
Before writing any code, ingest the official LLM docs:
https://developers.everflow.io/llms.txtSame prompt across Claude, ChatGPT, Gemini. The prompt pulls conversion timing data and payment terms, then builds a payback analysis per partner.
v1.0 · tag
Paste this prompt into Claude. Replace {API_KEY}, {NETWORK_ID}, and {TOP_N} with your values.
# role
You are an Everflow financial analyst.
# inputs
api_key = {API_KEY}
network_id = {NETWORK_ID}
top_n = {TOP_N} # default 5
window_days = 90 # last 90 days for stable signal
currency = USD
# task
1. Compute date range:
to = today (YYYY-MM-DD)
from = today - {window_days} days
2. GET /v1/networks/affiliates
Pull the full affiliate list. For each affiliate, capture:
- affiliate_id, affiliate_name
- billing_frequency (payment terms: net 7 / net 14 / net 30 / net 60 / custom)
- status (active only)
3. POST /v1/networks/reporting/entity
body: {
from: "{from}", to: "{to}",
columns: [{ column: "affiliate" }],
query: { filters: [], exclusions: [] },
sort_columns: [{ column: "total_conversions", direction: "desc" }],
timezone_id: 80,
currency_id: "{currency}"
}
Take the top {top_n} rows by conversion volume.
4. For each top partner, POST /v1/networks/reporting/conversions
Pull conversion detail with timestamps and payout amounts.
For each conversion, capture:
- conversion_unix_timestamp
- payout
- sale_amount
5. Calculate per partner:
a. Total conversions, total payout, total revenue, net margin
b. Average days from conversion to scheduled payout (use billing_frequency)
c. Profitable within 30 days? = YES if cumulative revenue at day 30 > cumulative payout at day 30
d. Estimated break-even day
6. Build a partner payback table sorted by break-even day (fastest first):
Columns: Rank | Partner | Conversions | Revenue | Payout | Margin | Payment Terms | Est. Break-Even | 30-Day Profitable? | Recommended Action
Recommended Action logic:
- Break-even < 14d: "Strong candidate for accelerated terms (net 7 / weekly)"
- Break-even 14-30d: "Profitable inside net 30. Current terms appropriate."
- Break-even 31-60d: "Review: volume may justify faster terms despite longer payback"
- Break-even > 60d: "Evaluate: high-value but slow payback. Confirm quality before adjusting."
7. Summary: how many profitable inside 30d, total cash tied up in >30d partners, one-line recommendation.
# guardrails
- Exclude test partners (affiliate_id = 1 or flagged as internal/test)
- Round currency to whole dollars
- If fewer than 10 conversions in window, flag "insufficient data"
- For subscription/recurring models: add footnote if average sale_amount suggests recurring billing
- If billing_frequency missing, default to net 30 and flag it
- Use 90-day window minimum for stable signalPaste this prompt into ChatGPT. Replace {API_KEY}, {NETWORK_ID}, and {TOP_N} with your values.
You are an Everflow financial analyst. I need you to analyze partner payback periods.
Here are my credentials:
- API Key: {API_KEY}
- Network ID: {NETWORK_ID}
- Number of top partners to analyze: {TOP_N} (default 5)
- Window: last 90 days
- Currency: USD
Please do the following:
1. Calculate the date range (today minus 90 days).
2. Call GET /v1/networks/affiliates to get each partner's billing_frequency (their payment terms like net 7, net 14, net 30, net 60).
3. Call POST /v1/networks/reporting/entity to rank partners by total_conversions descending. Take the top {TOP_N}.
4. For each top partner, call POST /v1/networks/reporting/conversions to get conversion timestamps and payout amounts.
5. For each partner calculate:
- Total conversions, revenue, payout, and margin
- Estimated break-even day (when cumulative revenue exceeds cumulative payout)
- Whether they are profitable within 30 days
6. Build a table sorted by break-even day (fastest first) with columns: Rank, Partner, Conversions, Revenue, Payout, Margin, Payment Terms, Est. Break-Even, 30-Day Profitable?, Recommended Action.
Action rules:
- Break-even under 14 days: suggest accelerated terms
- Break-even 14-30 days: current terms appropriate
- Break-even 31-60 days: review, volume may justify faster terms
- Break-even over 60 days: evaluate quality before adjusting
7. Add a summary: how many are profitable inside 30 days, total cash tied up in slower partners, and a one-line recommendation.
Guardrails: skip test partners, round to whole dollars, flag partners with fewer than 10 conversions as insufficient data, note if subscription/recurring revenue complicates the 30-day window.Paste this prompt into Gemini. Replace {API_KEY}, {NETWORK_ID}, and {TOP_N} with your values.
Act as an Everflow financial analyst. Analyze partner payback periods for my network.
Credentials:
- API Key: {API_KEY}
- Network ID: {NETWORK_ID}
- Top N partners: {TOP_N} (default 5)
- Analysis window: 90 days
- Currency: USD
Steps:
1. Date range: today minus 90 days to today.
2. GET /v1/networks/affiliates for billing_frequency (payment terms) per partner.
3. POST /v1/networks/reporting/entity, group by affiliate, sort by total_conversions desc. Take top {TOP_N}.
4. POST /v1/networks/reporting/conversions per partner for conversion timestamps + payout + sale_amount.
5. Per partner, calculate: total conversions, revenue, payout, net margin, estimated break-even day, profitable within 30 days (yes/no).
6. Output a Markdown table sorted by break-even day:
| Rank | Partner | Conv. | Revenue | Payout | Margin | Terms | Break-Even | 30d Profit? | Action |
Action logic:
- Under 14d break-even: "Accelerate to net 7 / weekly"
- 14-30d: "Terms appropriate"
- 31-60d: "Review: volume may justify faster terms"
- Over 60d: "Evaluate quality before changing terms"
7. Summary paragraph: count profitable inside 30d, total cash in over-30d partners, recommendation.
Rules: exclude test partners (id=1), round to whole dollars, flag under 10 conversions as insufficient data, add footnote for subscription/recurring revenue models, default to net 30 if billing_frequency is missing.Generate an API key
Core Platform → Control Center → Security → API Keys → click the + API key button. Read-only on Reporting plus read access to Affiliates.
Choose your metric and window
The default ranks your top 5 partners by conversion volume over the last 90 days. Swap total_conversions for payout or gross_sales to rank by spend instead of volume.
Paste your keys into the prompt
Replace {API_KEY}, {NETWORK_ID}, and {TOP_N} (default 5) in the prompt block below.
Run it in Claude, ChatGPT, or Gemini
The prompt pulls conversion timing data and payment terms per partner, then calculates break-even day, 30-day profitability, and a recommended action for each. Takes 1-2 minutes.
Share the table with finance
Partners profitable inside 30 days are candidates for accelerated terms (net 14 or weekly). Partners requiring 45+ days may need a volume conversation first. Use the table as the data foundation for any payment term renegotiation.
A Markdown table you can paste into Slack, email, or a finance review doc:
Partner Payback Analysis - Top 5 by Volume - Feb 25 to May 26, 2026
| Rank | Partner | Conv. | Revenue | Payout | Margin | Terms | Break-Even | 30d Profit? | Action |
|------|------------------|-------|-----------|-----------|-----------|--------|------------|-------------|-------------------------------------------------|
| 1 | Partner Alpha | 4,218 | $312,400 | $189,200 | $123,200 | Net 7 | ~5 days | YES | Strong candidate for weekly payouts |
| 2 | Partner Beta | 2,891 | $201,300 | $142,800 | $58,500 | Net 30 | ~22 days | YES | Current terms appropriate |
| 3 | Partner Gamma | 2,104 | $178,600 | $121,400 | $57,200 | Net 14 | ~11 days | YES | Strong candidate for accelerated terms (net 7) |
| 4 | Partner Delta | 1,830 | $94,200 | $79,600 | $14,600 | Net 30 | ~41 days | NO | Review: volume may justify faster terms |
| 5 | Partner Epsilon | 1,204 | $52,800 | $48,100 | $4,700 | Net 60 | ~58 days | NO | Evaluate quality before adjusting terms |
Summary:
- 3 of 5 top partners are profitable inside 30 days.
- $127,700 in payouts tied up in the 2 partners with over 30-day payback.
- Recommendation: your top 3 pay back fast. Consider accelerating their
terms to increase their production. For Delta and Epsilon, schedule a
quality review before changing anything.Recipe 04 answers "who hasn't been paid yet?" That is a payment operations question. Recipe 22 answers "what percentage of my total payout goes to my top 10?" That is a concentration risk question. This recipe answers "how fast does each partner pay back?" That is a cash flow timing question. All three use payout data from the same API, but the lens is different: operations vs. risk vs. speed. Run all three together for a complete financial picture.
If your partners drive subscription sign-ups, the "profit within 30 days" framing gets complicated. A $20/month subscription might cost $50 in payout but generate $240 over 12 months. The prompt flags this scenario with a footnote when average sale amounts suggest recurring billing. For recurring models, extend the window to 180 or 365 days to capture LTV, or pair this recipe with a cohort analysis that tracks revenue per partner over time.
No. Longer payment terms serve as a quality buffer. If a partner sends traffic that generates chargebacks, refunds, or fraud, 30 to 60 days of delay gives you time to detect the problem before money leaves your account. The recommended action column in the output is intentionally conservative: it only suggests faster terms for partners with strong margins and fast break-even. For newer or lower-margin partners, the data might justify keeping terms longer, not shorter.
Not all partners should be paid faster. The recipe assumes faster payment equals a better outcome. But for low-quality or unproven partners, longer payment terms serve as a risk buffer, giving you time to detect fraud, chargebacks, or quality issues before money leaves your account. The recommended action column is deliberately conservative.
Subscription revenue extends the payback window. For SaaS or subscription-model advertisers, the "profit within 30 days" framing may not apply. Lifetime value extends over months. Extend the analysis window to 180 or 365 days for recurring revenue models.
"Payback period" is your language, not theirs. Customers say "net 30," "cash flow," and "payment terms." Almost nobody uses the phrase "payback period" in conversation. If you share this analysis with partners, frame it as "payment term optimization" or "cash flow analysis," not "payback period review."
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