Upsell Engine
Introduce timely, relevant offers that feel helpful—not pushy.
Outcome at a Glance
Who it’s for: Creators, teams, and stores with 2–10 clear offers. What you’ll achieve: Context-aware product cards, follow-ups, and alerts that surface the right offer at the right moment — automatically. Time to first win: 60–90 minutes (initial setup), then weekly 20-minute tune-ups.
Why it Matters
Right time, right product: Offers appear when users show intent — no hunting, no hard sell.
Trust-preserving: Frequency limits and smart Alerts keep promotions contextual, not pushy.
Compounding results: Weekly keyword and Alert tuning turn small optimizations into steady gains.
The Upsell Engine works because Delphi doesn’t sell — it listens, interprets, and offers exactly what fits.
What You’ll Set Up
Products: We’ll feature 3–5 key items with short descriptions, images, and links that surface naturally during conversations — shown only once per chat.
Tags: Smart tags will track lead states such as Interested, Buyer, and Not Yet Ready to guide follow-ups and segmentation.
Alerts: Intelligent triggers will detect signals of purchase intent or curiosity in real time to identify engaged prospects.
Actions: Automated responses will activate based on alerts — sending follow-ups, showing product cards, or initiating nurture sequences.
Broadcasts: Monthly “What’s New” updates will keep your Interested audience informed and ready to take the next step.
Build → Launch → Operate
Build (45–60 min)
Products:
Add 3–5 products manually, via Shopify, or CSV import.
Keep each description ≤ 2 sentences: outcome first, details second.
Include 3–5 conversational keywords per product (e.g., “pricing,” “framework,” “next step”).
Set frequency = once per conversation to avoid oversaturation.
Tags:
Create tags for each stage of the buyer journey. For example:
Interested: For when users clicked the product or asked further questions.
Buyer: When a user has purchased.
Not Yet Ready: For when users are not interested.
Alerts: Write alerts in plain language to watch for upsell signals. Delphi will interpret them contextually to fire precise actions.
Examples:
“If user asks for deeper training or advanced examples, tag as Upsell Candidate and show ‘Pro Course.’”
“When someone mentions wanting templates, guides, or starter kits, tag as Interested and recommend the Starter Pack.”
“If user references previous purchase or interest in upgrades, tag as Repeat Buyer and share Premium Tier.”
Actions:
Action A: Product Recommended → Send Message (User) — acknowledge, give one benefit, link, invite one question.
Action B: Alert Triggered (Interested) → Send Message (User) — personalized offer tied to detected interest.
Action C: Inactivity 1d (Tagged Interested) → Send Message (User) — gentle check-in (Fixed Delay).
Launch (10–15 min)
Enable Actions A–C in your workspace.
Create your monthly Broadcast for the Interested tag: “New resources and updates you asked about.”
Verify that Alerts fire correctly (Testing → Actions Log).
The best upsell moments aren’t scripted — they’re recognized. Alerts find them.
Operate (Weekly, 20 min)
Review Product Mentions → note which items drive clicks by using UTM links.
Refine Alerts: check if your alerts are triggering at the right times, and try updating or creating new ones to improve accuracy.
Adjust Keywords: align with how users naturally ask (avoid internal jargon).
Audit Actions: confirm triggers fire and feel conversational.
Recipes to Follow
Action A — Follow-Up After Recommendation
Trigger: Product Recommended Action: Send Message (User) (Immediate) Instruction: “Acknowledge context; state one benefit; share link; invite a question.”
Example: “That’s a great question about pricing. My Pricing Playbook walks you through it step-by-step — here’s the link. Want a quick 2-minute overview?”
Action B — Alert-Triggered Upsell
Trigger: Alert “If user shows interest in advanced training…” Action: Send Message (User) (Immediate) Instruction: “Recognize their interest; introduce relevant offer; keep tone helpful.”
Example: “Since you mentioned scaling your audience, you might like my Growth Accelerator. It covers exactly that — want me to send details?”
Action C — Gentle Check-In
Trigger: Inactivity 1d Filter: User Tag = Interested Action: Send Message (User) (Fixed Delay) Instruction: “Check if timing was the issue; offer one-sentence summary + link; invite a question.”
Broadcast — Monthly ‘What’s New’
Subject: “New resources you asked for” Body: Hi {name}, here are the resources people asked about most this month: [Product A] — one-liner outcome [Product B] — one-liner outcome [Product C] — one-liner outcome Reply with your goal and I’ll point you to the best next step.
Metrics to Watch
Mentions → CTR (per product)
Conversions after recommendation
Alert → Action conversion rate (triggered upsells)
Return rate (7-day) for Interested users
Unanswered product questions → revised trend
Troubleshooting
Feels spammy: Drop frequency to once per user; refine benefit copy; review alert precision.
Low clicks: Lead with outcomes; move link earlier; verify tone isn’t too generic.
Alerts not firing: Check phrasing and scope; confirm correct tag or action mapping.
Too many false positives: Add conditions (“if mentions pricing AND readiness”).
Pre-Flight Checklist
3–5 products added with keywords and
frequency = once per conversation.Tags (Interested, Buyer, Not Yet Ready) created and active.
Alerts configured to detect upsell cues and tag accordingly.
Actions A–C tested in workspace.
Monthly Broadcast drafted.
Weekly product review and Alert-tuning block scheduled.
In Practice
Your Delphi becomes a silent salesperson — one that never pushes, only offers. Alerts read the room; Actions deliver relevance. Each conversation teaches your Delphi when to suggest, when to wait, and when to follow up.
“If a user asks about templates or scaling, tag as Interested and recommend the Starter Pack.” That’s not a campaign — that’s an intelligent upsell in real time.
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