Lifecycle Marketing Automation

Lifecycle Marketing Automation

Overview

Lifecycle marketing treats each customer as being at a defined stage in their relationship with your brand — from anonymous visitor to loyal advocate — and delivers stage-appropriate messaging automatically. Unlike broadcast campaigns, lifecycle automation is triggered by behavior and stage transitions, ensuring every message is relevant. Klaviyo's predictive analytics and flow builder cover most lifecycle automation needs without custom code.

When to Use This Skill

• When moving from batch-and-blast campaigns to behavior-triggered messaging
• When different customer segments are receiving identical generic emails
• When onboarding new customers and needing a structured first-30-day nurture plan
• When LTV and repeat purchase rate are flat despite healthy acquisition numbers
• When building a holistic view of the customer journey across email, SMS, and push

Core Instructions

Step 1: Define your lifecycle stages

Step 2: Set up lifecycle automation per stage

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Shopify with Klaviyo

Klaviyo computes expected repurchase dates and churn risk automatically based on your order history — you do not need to calculate lifecycle stages manually.

Subscriber stage — Welcome Series: 1. Go to Klaviyo → Flows → Create Flow → Welcome Series (use template) 2. The flow fires when someone joins your email list 3. Configure 3 emails over 7 days:

• Email 1 (immediate): Welcome + brand story + first-order discount
• Email 2 (day 2): Bestsellers or "Start here" product guide
• Email 3 (day 7): Social proof (reviews, customer photos, media mentions)

4. Add a flow filter: "Has NOT placed an order" — exits the flow if they purchase before completing it

First-time buyer stage — Post-Purchase Onboarding: 1. Create a new flow: trigger = Placed Order, filter = "First order ever" (Klaviyo's "First order" conditional) 2. Configure 3 emails:

• Email 1 (day 2): Product usage tips or setup guide
• Email 2 (day 7): Cross-sell recommendations based on purchased product
• Email 3 (day 21): Review request

3. This flow is separate from the standard post-purchase flow to give first-timers extra attention

Loyal stage — VIP Recognition: 1. Create a segment: Total Customer Value > $500 OR Total Order Count >= 4 2. Create a flow triggered by Segment Entry for this segment 3. Send a single "You've unlocked VIP status" email with exclusive benefits (early access, free shipping, loyalty points bonus) 4. Add these customers to a Klaviyo List called "VIP" and use it as a segment for early access campaigns

At-risk stage — Retention Nudge: 1. Create a segment using Klaviyo's predictive analytics: Predicted Churn Risk = High OR Mid 2. Create a flow triggered by Segment Entry:

• Email 1 (immediate): Personalized "We miss you" with product recommendations based on past purchases
• Wait 5 days → Email 2: New arrivals or "What's changed since your last visit"
• Wait 5 days → Email 3 (only for customers with > $200 LTV): 15% off exclusive offer

Lapsed stage → Win-Back:

• See @win-back-reactivation for the full win-back campaign setup

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WooCommerce with AutomateWoo

1. Install AutomateWoo ($99/yr) from the WooCommerce marketplace 2. Build individual workflows for each stage transition:

Welcome Series:

• Trigger: Subscribe → Newsletter (with your email plugin) or Customer → Created (new account)
• Add 3 email actions with timing delays

Post-purchase onboarding:

• Trigger: Order → Status Changed to Completed
• Add condition: Customer order count equals 1 (first-time buyer)
• Configure email sequence with delays

At-risk re-engagement:

• Trigger: Customer → Win Back (built-in AutomateWoo trigger)
• Set "No order in last" to 1.5x your average repurchase cycle
• Create escalating emails: reminder → offer

AutomateWoo's built-in RFM Analysis (go to AutomateWoo → Reports → RFM Analysis) shows your customers on an RFM grid — use this to identify which customers to target with each lifecycle stage campaign.

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BigCommerce

1. Install Klaviyo from the BigCommerce App Marketplace 2. Klaviyo syncs all BigCommerce order history automatically 3. Follow the same Klaviyo flow setup as the Shopify section above

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Custom / Headless

Send lifecycle events to Klaviyo's API:

// Update customer's lifecycle stage as a Klaviyo profile property
async function updateLifecycleStage(email: string, stage: string) {
  await fetch('https://a.klaviyo.com/api/profile-import/', {
    method: 'POST',
    headers: {
      'Authorization': `Klaviyo-API-Key ${process.env.KLAVIYO_PRIVATE_KEY}`,
      'Content-Type': 'application/json',
      'revision': '2024-10-15',
    },
    body: JSON.stringify({
      data: {
        type: 'profile',
        attributes: {
          email,
          properties: {
            lifecycle_stage: stage,
            lifecycle_stage_updated_at: new Date().toISOString(),
          },
        },
      },
    }),
  });
}

// Call this on key events:
// After first purchase: updateLifecycleStage(email, 'first-time-buyer')
// After 4th purchase or $500 LTV: updateLifecycleStage(email, 'loyal')
// When churn risk detected: updateLifecycleStage(email, 'at-risk')

Then in Klaviyo, create flows triggered by Profile Property Changed → lifecycle_stage equals [stage].

Step 3: Configure stage-appropriate messaging

Step 4: Measure lifecycle health

Track these in Klaviyo or your analytics dashboard:

Best Practices

• Cancel competing flows on conversion — in Klaviyo, add a flow filter to every win-back and retention flow: "Has placed order since starting flow → exit"; prevents irrelevant messages after purchase
• Always cancel retention flows when a customer purchases — set up a Klaviyo flow that triggers on "Placed Order" and uses a Trigger Split to exit the person from any active retention flows
• Use Klaviyo's predictive analytics — do not manually calculate lifecycle stages; Klaviyo's expected next purchase date and churn risk are more accurate than manual rules
• Personalize with dynamic product blocks — every retention and win-back email should show products based on what the customer has bought before, not generic bestsellers
• Keep stage definitions simple — 5–7 stages is enough; adding more stages creates messaging overlap and complexity without proportional benefit

Common Pitfalls

Related Skills

• @customer-retention-engine
• @email-marketing-automation
• @win-back-reactivation
• @loyalty-program-optimization
• @email-list-segmentation

Lifecycle Campaign Layer and Analytics

Problem Description

Nourish & Co. is a health food e-commerce company that has just deployed a customer lifecycle stage engine. Now they need to build the campaign management layer on top of it, plus an analytics dashboard so the marketing team can monitor health of the funnel.

The engineering team has two immediate needs:

Campaign configuration: Different lifecycle stages need different treatment — the channel used to reach customers, how often they receive messages, what the messaging focuses on, and whether incentives like discounts are offered. Anonymous visitors (those who haven't yet shared their email) are harder to reach through traditional channels; lapsed customers are the hardest to win back and may need a meaningful incentive; loyal customers should get exclusive content and typically don't need financial incentives to engage. The team wants a central config object that encodes these rules so campaign workers can look up the right parameters without hard-coding decisions. A critical concern: the marketing ops team has seen campaigns fire with stale stage data — a customer who made a purchase yesterday might still get a "we miss you" email if the campaign worker uses the stage from when the job was enqueued rather than the current stage.

Real-time event hooks: The lifecycle engine runs nightly, but two events need to update a customer's stage immediately without waiting for the batch: (a) when a customer submits a product review, reaching a threshold of reviews should move them into the advocate tier; (b) webhook handlers for other real-time purchase events should also feed into stage re-evaluation.

Analytics dashboard: The team wants visibility into funnel health — how customers are distributed across stages, which transitions are happening (and at what rates), how long customers spend in each stage, and the average LTV by stage.

Output Specification

Produce a TypeScript file campaign-layer.ts containing: 1. A STAGE_CAMPAIGN_CONFIG object (or equivalent) mapping every lifecycle stage to its campaign parameters 2. A sendCampaignToCustomer(customerId, campaignType) function (or equivalent) that guards against stale stage data at send time 3. An onReviewSubmitted(customerId) event handler 4. A getLifecycleDashboard() function

Also write campaign-design.md explaining how the campaign config decisions were made for each stage, particularly around channel selection and incentive levels.

Customer Lifecycle Stage Engine

Problem Description

Growthwave is a mid-sized DTC apparel brand that has been running a single broadcast newsletter to its entire customer base. The marketing team has noticed declining open rates and repeat purchase rates, and the VP of Growth suspects that customers are receiving completely irrelevant emails — loyal customers get the same acquisition-focused messages as someone who signed up yesterday but never bought anything.

The engineering team has been tasked with building a core customer lifecycle classification module in TypeScript. This module will form the foundation of a new behavior-triggered automation platform. The goals are: (1) classify every customer into the right lifecycle bucket based on their purchase history and engagement signals, and (2) keep the stage model simple enough for non-technical marketers to understand and act on.

The system should be designed to run reliably at scale — Growthwave has roughly 400,000 customers, so the nightly re-evaluation job needs to be written with performance in mind to avoid timeouts.

Output Specification

Produce a TypeScript module (one or more .ts files) that implements:

1. The lifecycle stage taxonomy as TypeScript types and interfaces 2. A function assignLifecycleStage(customerId) that classifies a customer 3. A batch update function updateLifecycleStages() that nightly re-evaluates all customers — make sure it handles large tables without timing out 4. A mechanism to prevent a customer from bouncing back and forth between stages on consecutive nightly runs

Write the output to a file named lifecycle-engine.ts.

Additionally, write a brief design-notes.md describing:

• The stage taxonomy you chose and why
• How the at-risk and lapsed thresholds work
• Any performance optimizations in the batch job
• How you handle the stage-stability problem

Automated Marketing Workflow Triggers

Problem Description

Brewsmith, an online specialty coffee subscription service, has a customer lifecycle system that classifies customers into stages. Now they need to wire up the automation layer: whenever a customer moves from one stage to another, the right marketing workflow should fire automatically. The current system does nothing when customers transition — loyal customers receive no recognition, and at-risk customers churn silently without any intervention.

The growth team has documented the workflows they want triggered at each stage transition. The key requirements are:

• New subscribers should enter a short welcome sequence
• When someone makes their first purchase, they should exit the welcome sequence immediately (they've already converted) and enter a product onboarding flow
• When someone makes a second purchase, acknowledge the milestone
• Loyal customers deserve meaningful recognition — both an acknowledgment and some tangible benefit
• Customers who are slipping away need a gentle nudge — but the team does NOT want to immediately offer discounts to everyone who goes at-risk; discounts erode margins and should only be used as a last resort
• If a customer continues to lapse after already receiving a retention nudge, then a stronger win-back offer is appropriate
• Advocates who refer friends or leave reviews deserve exclusive perks

Additionally, the team wants to handle real-time purchase events properly: when a customer buys something, any active win-back or re-engagement flows should be cancelled immediately — there's nothing worse than receiving a "we miss you" email an hour after placing an order.

The system needs to be documented. Produce a transition matrix document that maps every possible stage transition to the workflow it triggers.

Output Specification

Write a TypeScript file workflow-triggers.ts containing the triggerStageTransitionWorkflow function and any supporting handlers (e.g. an onOrderPaid handler for real-time purchase events).

Also write a transition-matrix.md that documents: for each destination stage, which workflows fire and under what conditions (include the from-stage where it matters).