Start with the old day
Identify calls, emails, WhatsApp messages, spreadsheets, price checks and order corrections before launch.
Compare case studies by buyer adoption, order desk workload, account pricing, correction work and invoice-ready next step.
Manual channels mapped
Buyer adoption separated
Staff cleanup measured
Invoice next step reviewed
Real Porosi product screens. Customers can order on iOS, Android or the web, and submitted orders appear in the supplier dashboard for review.
The strongest proof shows the current ordering mess, the rollout path, who adopted, what staff still handle and what becomes cleaner before finance.
Identify calls, emails, WhatsApp messages, spreadsheets, price checks and order corrections before launch.
Check whether the case study separates app users, web users and staff-assisted accounts.
See how staff review products, prices, notes, delivery details and exceptions after orders are submitted.
Look for cleaner data before warehouse, delivery and invoice preparation rely on the order.
A buyer builds the order from the products, prices and history available to their account. When they press submit, before-and-after manual order channels, buyer adoption, order desk workload and account pricing stay with the order, so the supplier can check it without retyping a call, email or message.
The supplier team receives one order record with before-and-after manual order channels, buyer adoption, order desk workload and account pricing. Staff can check exceptions before picking, delivery or invoice preparation begins.
The starting point can be too vague to compare.
List the actual order routes and the work each created.
A launch story can hide weak customer usage.
Separate first orders, repeat orders, web fallback and support-heavy accounts.
A screenshot may not prove cleaner operations.
Follow reviewed orders into fulfilment, delivery and finance context.
Build a scorecard from your own order channels before accepting a provider's proof at face value.
Document order sources, retyping work, corrections and invoice cleanup in the current workflow.
Use real customer types, products, prices and notes in the demo.
Decide which adoption and workload signals would make the case study believable for your team.
The strongest proof shows the current ordering mess, the rollout path, who adopted, what staff still handle and what becomes cleaner before finance.
That customers used a better ordering route after launch. That account prices, usual products and order history made adoption easier.
How much manual interpretation still remained after rollout. Whether corrections fell because orders arrived with better context.
Build a scorecard from your own order channels before accepting a provider's proof at face value.
Bring current manual channels, customer groups, account pricing examples and staff cleanup work so the proof can be tested directly.