Sage Turns Copilot Into a Trusted AI Assistant, Cutting Time-to-Payment by Over a Week

Immediate pain: A live Copilot product needed to be fast AND trusted — right away. Customers demanded speed plus control and reliable outcomes, but the team had no real-time evidence of what users would actually trust, use and pay for.

We empathise: launching quickly to secure market advantage left product, commercial and brand teams under intense pressure to act without guessing. The client (Sage; industry confidential) triggered urgent research after the Copilot launch to resolve this exact gap.

The core question to answer was clear: how can the team gather real-time customer evidence — including MRS and other signals — to prioritise fixes, protect adoption and safeguard revenue, UX and brand reputation?

Key differentiator: a live research programme that put customers inside product development — enabling engineer-led, structured co-creation with real users.

Process (what we did, in sequence):

1. First we designed and launched a live research programme to embed customer input directly into the product cycle.
2. Then engineers ran structured co-creation sessions with real users to pressure-test use cases and surface points of friction.
3. Next rapid-turn quantitative testing sized demand, prioritised features and refined the proposition.
4. Finally we iterated product decisions using this hybrid, in-market approach (live customer intelligence + co-creation + fast quantitative validation).

Methodologies & keywords: live research, co-creation, in-market testing, quantitative validation, demand sizing, feature prioritisation, product iteration, user research, friction discovery.

Client vs. our involvement: Basis Global designed and ran the live research programme and quantitative testing; engineers conducted the structured co-creation sessions as part of the programme.

Speed of implementation: The hybrid approach enabled product decisions to be made and iterated in weeks rather than quarters.

Saved customers up to 30 minutes per day.

1. Up to 30 minutes/day saved on core workflows
2. Time-to-payment reduced by over a week via payment workflows

Business impact: these efficiency gains reduced manual effort, accelerated cash collection and increased product-market fit by refocusing the roadmap on commercially viable use cases (profitability, payments, decision support). That matters to decision-makers because it improves operational productivity, shortens payment cycles and strengthens competitive positioning.

Credibility: the project positioned Copilot as a halo product for the Sage brand and won industry recognition — the MRS B2B award (the second consecutive MRS B2B award for Basis and Sage).

The work also supports broader goals such as shopper insights savings and improved mobile survey turnaround time and underpins Sage’s AI roadmap, enabling scale, faster iterations and greater ROI.

1. Was the method scalable or replicable? Yes — outcomes informed the wider product roadmap and underpin Sage’s AI strategy, indicating replicability within the organization.