Verified against ChatGPT · 2026-08-14
Design a referral campaign brief that tells paid social exactly which incentive and creative to amplify
Specifies the referral incentive structure, the exact organic-to-paid handoff moment, and which advocate content is worth boosting, instead of a vague "promote our best referrals" instruction that leaves the media buyer guessing.
The prompt
Ready to copy — highlighted parts are example details you can swap.
Design a referral campaign for the offer below, ending specifically in a brief the paid social team can act on directly — which piece of advocate content to boost, with what budget logic, and when to stop. OFFER AND REFERRAL INCENTIVE Referrer gets a $50 account credit, referee gets 20% off their first order. WHO REFERS AND WHO THEY REFER TO Existing customers of 6+ months referring friends in similar income brackets, usually via direct message rather than public post. CURRENT ORGANIC REFERRAL SIGNAL Top 5% of referral posts get roughly 4x the engagement of a typical customer post within the first 48 hours. PAID SOCIAL BUDGET AVAILABLE FOR AMPLIFICATION $3,000/month set aside specifically for boosting top-performing referral posts. Start from the incentive structure and check it for a specific failure mode before anything else: an incentive that rewards the referrer richly but gives the referee a weak reason to act creates lopsided sharing (people post links for their own benefit) with poor conversion on the receiving end — if offer_and_incentive looks like this, flag it and propose a rebalance before building the rest of the campaign around an incentive likely to underperform. Identify the specific handoff moment where an organic referral becomes a paid-amplification candidate — not "boost popular posts" in the abstract, but the concrete signal (a referral link crossing a share count, a specific advocate's post outperforming baseline engagement) that should trigger a media buyer to actually spend against it, using organic_referral_signal as the basis for that threshold rather than an arbitrary round number. Specify what content format is worth boosting versus what should stay purely organic — a heartfelt personal testimonial post might convert well organically because it reads as authentic, but the same post reformatted and pushed through paid social distribution can read as inauthentic once an audience recognizes it as an ad, which is a real risk specific to amplifying referral/advocate content rather than brand-made ads. Budget the amplification spend against amplification_budget with a stated stopping condition — a signal that would tell the team to cut spend on this amplification before the whole budget is used, not just a plan for how to spend all of it. OUTPUT FORMAT 1. Incentive structure check — flagged rebalance if lopsided, or confirmation it's reasonably balanced. 2. The specific organic-to-paid handoff trigger. 3. Content-format guidance — what to amplify as-is, what to reformat first, what should never be paid-boosted. 4. Budget plan with an explicit stopping condition.
Customize
Optional — swap in your own details for the highlighted parts above.
Why this works
Asked generally to design a referral campaign, GPT-5.1 tends to produce a plausible-sounding incentive structure and a generic "boost your best content" instruction for the paid team, because that's the shape most referral-marketing writeups take, without checking whether the incentive is actually balanced between both sides of the referral — a real and common design flaw where a generous referrer reward with a weak referee incentive produces lots of low-quality link-sharing and poor conversion on the receiving end, a failure mode that's invisible unless something explicitly prompts a check for it. Requiring a concrete handoff trigger tied to the organic_referral_signal data, rather than an instruction to "boost popular posts," is what actually makes the brief executable by a media buyer who wasn't part of the strategy conversation — "popular" is not a number a person can act on, while "a post crossing 4x baseline engagement in 48 hours" is a rule they can operationalize without further clarification. The content-format warning about reformatting advocate testimonials for paid distribution addresses a failure specific to referral marketing that doesn't apply to brand-made ads: authenticity is often the entire reason a referral post converts, and audiences are good at recognizing when organic-feeling content has been pushed through paid distribution, at which point the same words that worked organically can read as manipulative rather than genuine — a risk a generic "amplify what works" instruction has no mechanism to catch. Requiring an explicit stopping condition rather than a plan to fully spend the budget counters the default assumption, common in AI-generated media plans, that a budget exists to be spent in full regardless of whether performance holds up throughout the period.
What you get back
Incentive check: referrer gets $50 credit, referee gets 20% off — reasonably balanced, referee incentive is substantial enough to expect real conversion, not just link-sharing for the referrer's benefit. Handoff trigger: boost a referral post once it crosses 4x baseline engagement within 48 hours of posting, matching the organic top-5% pattern already observed. Content guidance: boost the post as-is if it's under 100 words and reads as a direct personal statement; do not reformat it into branded ad creative, since testimonial authenticity is the actual conversion driver here. Stopping condition: pause amplification spend on a given post if cost-per-referral-conversion exceeds 1.5x the organic average for two consecutive weeks.
Verified against
ChatGPT GPT-5.1 · 2026-08-14
Changelog
- 2026-08-14 — Initial publish, verified against ChatGPT GPT-5.1.
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