Software-Then-Service Offer
Upgrade existing product users into expert engagements at the exact point their configuration outgrows self-serve.
What it adds
The AI builder uses your product usage patterns, service catalog, and account documentation to build an in-product offer surfaced by the customer's own configuration complexity. It converts because the pitch arrives as a solution to a state the customer is already in, evidenced by their own account. The goal is expansion revenue from the installed base without generic upsell messaging.
What your builder is told to do
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The actual instructions, in order.
What your builder is told to do
8The actual instructions, in order.
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Read the supplied usage and support files and define the specific account-state signals that indicate outgrown self-serve: configuration depth, integration count, seat growth, recurring support themes, or manual workaround volume.
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Build the offer surface so it appears only for accounts matching those signals. Presenting it universally converts it into ordinary upsell noise and reduces its effect on the accounts that matter.
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Open the offer by naming the observed state in the customer's own terms — what their account looks like now — before proposing anything, using only data the account actually contains.
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Map each service in the catalog to the signal it resolves, so the customer sees a targeted match rather than a menu.
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State scope, duration, and what the customer must contribute for each service, taken from the service catalog documentation.
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Provide a dismiss-and-defer control with a documented re-surface rule so the offer does not become persistent noise.
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Define breakpoints: on mobile the offer is a full-screen interstitial reachable from an account-health entry point, never an interrupting modal mid-task; on tablet it renders as a side panel over the account view; on desktop it appears as an inline card within the account or settings area where the complexity signal is visible.
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Preserve continuity of account context into the inquiry so the customer does not re-describe their setup.
Edge cases it handles
5
The things an agent skips when you only say "build a software-then-service offer".
Edge cases it handles
5The things an agent skips when you only say "build a software-then-service offer".
- The signal is present but the account is in a support escalation; suppress the offer until the issue resolves.
- The customer's complexity is caused by a product defect; route to support rather than selling services.
- Multiple signals fire at once; present the highest-impact service rather than every match.
- The account contacted is not the decision maker; include a forward-to-stakeholder path with the context attached.
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Signal thresholds are undocumented; use
[VERIFY: threshold]placeholders rather than choosing values arbitrarily.
Definition of done
7
Your builder is required to check every one of these before reporting the work finished.
Definition of done
7Your builder is required to check every one of these before reporting the work finished.
- Offer visibility is gated on documented account-state signals, not shown universally.
- The offer opens by describing the observed account state using real account data.
- Each service maps to the specific signal it resolves.
- Scope, duration, and customer contribution are stated from the service catalog.
- A dismiss control with a documented re-surface rule exists.
- Mobile, tablet, and desktop each place the offer without interrupting active work.
- The builder reports which usage and catalog files it used and which signal thresholds remain unverified.
Related offer files
Special Offer Structures
Internal Champion Offer
Arm the person selling you inside their own company with the exact materials their approval process demands.
Build This Offer: Internal Champion OfferSpecial Offer Structures
Partner Enablement Offer
Equip resellers and implementers with everything they need to sell and deliver your work without your team.
Build This Offer: Partner Enablement OfferSpecial Offer Structures
Case-Study-Led Offer
Retell one engagement in enough operational detail that the reader recognizes their own situation in it.
Build This Offer: Case-Study-Led OfferHow it works
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Copy the link
Grab the Markdown blueprint URL for this offer type.
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Give it to your builder
Paste it into Claude Code, Cursor, Codex, or whatever AI builder is already working in your app.
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It maps, then builds
Your agent reads the blueprint first, then builds the offer into your app around the product, audience, and stack.
Works with your stack
These blueprints are written to adapt. They tell the agent to detect your framework, match your existing design system, and use your source files instead of guessing the offer.
Need it tighter than that? Customize the offer file and tell it exactly which source docs and stack to use.