Your first week with LiftSignals
Day 1 — Connect and sync
The most important thing on day 1 is getting your store connected and the initial sync started. Everything else depends on this.
- Connect your Shopify or WooCommerce store (or import a CSV)
- Connect Klaviyo — you'll want this ready before models finish so you can export your first audience immediately
- Invite your team members if you have a marketing analyst or retention specialist
Day 2–3 — Explore your data
Once sync and model training complete (you'll get an email), spend time in Explore to understand your customer base:
- Open Explore → Churn Detection — look at the score distribution. How many customers are in each band?
- Check Explore → RFM Segmentation — how many Champions do you have? How many At-Risk former Champions?
- Review Explore → CLV Forecast — what's the predicted CLV distribution across your base?
The Today screen summarises the most urgent actions. Check this every morning — it surfaces the highest-priority tasks based on your live model scores.
Day 4 — Your first audience export
Create and export your first at-risk audience to Klaviyo:
- Go to Protect
- Click Export all Critical (score ≥ 81) — this is your highest-priority group
- In Klaviyo, build a win-back sequence for this audience. Our recommended email cadence: Day 0 (personal tone), Day 5 (social proof), Day 12 (offer)
Day 5–7 — Set up automation
Now that you've seen your data and done a manual export, set up recurring automation:
- Go to Audiences and create a "Critical churn risk" segment using the template
- Set up a daily scheduled export of this segment to Klaviyo
- Create a "Win-back window open" audience and schedule it to export daily to Klaviyo or Attentive
- Set up a Weekly Performance report on a Monday morning schedule
Benchmarks to watch
| Metric | Healthy range | Where to find it |
|---|---|---|
| % customers in Critical band | < 3% | Protect → top of screen |
| Win-back rate from win-back campaigns | 15–25% | Grow → win-back section |
| Churn model accuracy | > 85% | Explore → Churn Detection |
| Data health score | > 70 | Settings → Data → Health |
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