What counts as a CRM or loyalty campaign?

A CRM or loyalty campaign reaches a brand's owned audience — people who have opted into an email list, downloaded a loyalty app, or joined an SMS program — as opposed to anonymous social media followers or a retailer's own trade loyalty scheme. This skill plans that owned-channel campaign end to end: segments, messaging, send sequence, offer mechanics, and KPIs.

How is this different from the Shopper Activation Planner skill?

The Shopper Activation Planner builds retailer-specific activation programs — in-store, retail media, trade promotions — for shoppers at a specific retailer, often working alongside that retailer's own loyalty mechanics. This skill is scoped to the brand's own owned-audience channels — its email list, its loyalty app, its SMS program — where the brand holds first-party data and messages members directly, independent of any single retailer.

What AI models does this prompt work in?

Any capable chat model — ChatGPT, Claude, or Google Gemini. It is model-agnostic, and lifecycle and CRM marketers often save it as a Custom GPT or a reusable Claude Skill so every campaign — launch, seasonal, or win-back — gets segmented and sequenced the same structured way.

What data should I have ready before using it?

At minimum, how your members are currently segmented (or that they are not segmented at all) and roughly what share of your base falls into each group. Real purchase-frequency or tenure data sharpens the segments considerably. The skill will not invent member counts or redemption-rate figures — bring your own numbers, or it will flag lift and behavior claims as assumptions your team needs to confirm.

Brand

Loyalty & CRM Campaign Brief

Plan a CRM or loyalty-app campaign for your owned audience.

What is the Loyalty & CRM Campaign Brief?

The Loyalty & CRM Campaign Brief is a free AI skill that plans a campaign for a food or beverage brand's owned audience — email, loyalty app, or SMS — distinct from retailer trade loyalty programs or social media content. You give it the campaign objective, audience segments, and the offer or content under consideration; it returns segment-specific messaging, a send sequence mapped to the campaign window, offer and reward logic that protects margin, a re-engagement angle for lapsing members, and KPIs that separate a healthy program from one running on vanity opens. It is built for brand and loyalty managers who own a CRM list or app membership and need a structured brief instead of one-off blasts. Because it segments before it messages, it stops every member from getting the same email regardless of their relationship to the brand. Layering live food and beverage demand data into the segment offers confirms members are getting the flavor or benefit they are actually craving this season.

Who it's for

Brand managers running an owned email or app loyalty program
CRM or lifecycle marketing managers planning a campaign sequence
Loyalty program managers designing an offer or rewards push
Marketing directors building a retention plan for existing customers

What you get

Audience segments defined by relationship to the brand, not just demographics
Segment-specific messaging and subject-line or push-notification directions
A send sequence mapped across the campaign window
Offer and reward logic that protects margin
A re-engagement plan for lapsing or inactive members
KPIs that separate real engagement from vanity opens

How to use it

1Open ChatGPT, Claude or Gemini and paste the prompt.
2Fill the bracketed inputs (objective, segments, offer, campaign window).
3Answer its clarifying questions about what data you actually have on members.
4Iterate: ask it to build a lapsed-member win-back variant of the same campaign.

See it in action

Example input

Brand: fictional 'Fernglen' kombucha. We have a loyalty app with about 40,000 members, three tiers based on purchase frequency. Objective: drive trial of a new ginger-turmeric flavor over a 6-week window using a mix of app push and email, with a bounce-back reward for members who buy it twice.

Example output

CRM Campaign Brief — Fernglen Ginger-Turmeric Launch (excerpt)

Objective: Drive trial of ginger-turmeric among existing members over 6 weeks, converting trial into a second purchase via a bounce-back reward.

Segments:
1. Top-tier frequent buyers (~15% of base): already trust the brand's flavor calls. Job: early trial and social proof — ask them to review or share, not just buy.
2. Mid-tier regular buyers (~45%): the volume opportunity. Job: straightforward trial-driving offer, no extra convincing needed.
3. Low-tier infrequent buyers (~40%): buy occasionally, may be price- or habit-driven lapsers in disguise. Job: a stronger incentive, since a weak offer likely gets ignored by this segment.

Messaging by segment:
- Top tier: 'You find our flavors first — ginger-turmeric just landed.' Push notification plus a short email; no discount needed, framed as early access.
- Mid tier: 'New: Ginger-Turmeric. Buy two, get $2 back.' Straightforward, offer-forward.
- Low tier: 'Come back for this one: Ginger-Turmeric, $3 off your next two.' Larger incentive; also functions as a re-engagement message for this segment regardless of the new flavor.

Send sequence (6 weeks):
Week 1: Launch push + email to all segments, tier-specific copy.
Week 2: No send — let the app-browse and purchase data populate before the next message.
Week 3: Reminder to anyone who has not yet purchased, segment-specific.
Week 4: Bounce-back reward triggers automatically for anyone on their first ginger-turmeric purchase.
Week 5: Reward reminder to anyone who redeemed purchase one but not two.
Week 6: Wrap message to everyone who completed the bounce-back, inviting them to a future early-access list.

Offer and reward logic: the bounce-back reward (small credit on a second purchase) is structured to pay for itself in repeat purchase, not just redemption — model the cost against expected repeat-rate lift before finalizing the dollar amount (assumption to validate with your finance partner).

Re-engagement note: the low-tier segment's messaging doubles as a lapsed-member play; if a meaningful share of that segment has not purchased anything in 90+ days, consider pulling them into a separate win-back flow instead of folding them into the launch send.

KPIs beyond opens: purchase-through rate per segment (not just push/email open rate), second-purchase (bounce-back) redemption rate, and net-new versus existing-member trial split, since a flavor launch that only sells to existing top-tier buyers is not actually growing the program.

Segment note: if the low-tier segment's redemption rate on this campaign comes in meaningfully higher than its typical purchase rate, treat that as evidence the segment was under-incentivized in past campaigns, not just responsive to this one flavor.

Want me to build the lapsed-member win-back flow as its own campaign?

The prompt

Here's the start of the prompt. Download the free bundle for the full, ready-to-paste version — plus the installable Claude Skill and Custom-GPT instructions.

# Role
You are a senior CRM and loyalty marketing strategist for food and beverage brands. You treat owned-audience channels — email, app, SMS — as their own discipline, not a smaller version of social media, and refuse to send every member the same message regardless of their relationship to the brand.

# Context I'll provide
- Brand and program: [BRAND / LOYALTY OR CRM PROGRAM]
- Campaign objective: [OBJECTIVE e.g. trial a product, drive repeat purchase, re-engage lapsed members]
- Audience segments or tiers, if defined: [SEGMENTS — how grouped today, or "none yet"]
- Offer or content under consideration: [OFFER / CONTENT]
- Campaign window: [TIMEFRAME]
- Channels: [e.g. email, app push, SMS] (optional)

# Your task

Frequently asked questions

What counts as a CRM or loyalty campaign?: A CRM or loyalty campaign reaches a brand's owned audience — people who have opted into an email list, downloaded a loyalty app, or joined an SMS program — as opposed to anonymous social media followers or a retailer's own trade loyalty scheme. This skill plans that owned-channel campaign end to end: segments, messaging, send sequence, offer mechanics, and KPIs.
How is this different from the Shopper Activation Planner skill?: The Shopper Activation Planner builds retailer-specific activation programs — in-store, retail media, trade promotions — for shoppers at a specific retailer, often working alongside that retailer's own loyalty mechanics. This skill is scoped to the brand's own owned-audience channels — its email list, its loyalty app, its SMS program — where the brand holds first-party data and messages members directly, independent of any single retailer.
What AI models does this prompt work in?: Any capable chat model — ChatGPT, Claude, or Google Gemini. It is model-agnostic, and lifecycle and CRM marketers often save it as a Custom GPT or a reusable Claude Skill so every campaign — launch, seasonal, or win-back — gets segmented and sequenced the same structured way.
What data should I have ready before using it?: At minimum, how your members are currently segmented (or that they are not segmented at all) and roughly what share of your base falls into each group. Real purchase-frequency or tenure data sharpens the segments considerably. The skill will not invent member counts or redemption-rate figures — bring your own numbers, or it will flag lift and behavior claims as assumptions your team needs to confirm.

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