Explain the campaign decision with evidence
Return to the re-engagement question and explain both the groups to activate and the work to hold.
Question for this chapter
Which customers should you re-engage, and what should not happen yet?
Complete the solution
| Initial problem | Applied solution | Evidence left behind | What changed |
|---|---|---|---|
| Source orders contained missing values. | Removed seven missing amounts and five missing customer IDs, then replaced two unknown products. | 88 clean rows, 2 PRD-UNKNOWN rows | Valid purchases and unknown products are distinct. |
| Customer state was too vague. | Classified with recency, frequency, and monetary questions. | 22 customer rows | Each label has an explainable rule. |
| All four groups were assumed to exist. | Counted the actual 7, 11, 4, and 0 distribution. | Zero at_risk customers | The empty campaign is on hold. |
| Product-level personalization was desired. | Materialized the purchase graph and isolated unknown products in one node. | 22 customers, 88 orders, 9 products | Only known products become relationship evidence. |
State the final decision
JaffleMart will prepare recognition and retention for seven
championcustomers, repeat-purchase suggestions for elevenloyalcustomers, and second-purchase onboarding for fournewcustomers. It will not send anat_riskcampaign because that group is empty. Known-product purchase paths can support personalization, whilePRD-UNKNOWNrelations remain excluded until resolved.
Completion check
- Reduced 100 source orders to 88 cleaned rows.
- Can explain when to remove a missing value and when to replace it with
PRD-UNKNOWN. - Can explain recency, frequency, and monetary value in plain language.
- Confirmed the 7, 11, 4, and 0 segment distribution.
- Drafted actions for the three groups that exist.
- Confirmed seven purchase paths for CUST-017.
- Excluded unknown-product relations from product personalization.
Apply next
A real campaign also needs customer consent, reachable channels, recent-contact frequency, margin, and experiment groups. When that data is unavailable, record it as a prerequisite for the next decision instead of filling the gap with an estimate.