Sales.

Challenges

Why data matters

Prioritising the right accounts, forecasting revenue and giving sales teams reliable information: sales data translates directly into revenue.

What data brings

What data changes

Sales management

Dashboards by team, region and product, shared between sales and finance.

Sales forecasting

Revenue forecasts based on pipeline and history.

Account prioritisation

Prospect and customer scoring, identifying upsell and cross-sell opportunities.

Pricing

Discount and margin analysis, price recommendations.

Customer portals

Dashboards made available to customers to track their volumes and spend.

Generative AI

First generative AI use cases

• Meeting preparation from customer data
• Assisted writing of commercial proposals
• Summarising conversations and updating the CRM

Method

The Visian approach

1. Framing with the department concerned: decisions to inform, indicators, priorities.
2. Data : source inventory, quality measurement, corrections at source.
3. Tool : dashboard, model or AI assistant delivered in short iterations.
4. Adoption : team training, usage tracking, skills transfer.

References

Visian achievements

• Société Générale: commitment-tracking dashboards for more than 10,000 client users
• Edenred: product management and AI
• Accor: direct sales channel management

All references