AI in sales management

Implementation

1. Day 1

   Audit

   We discussed with the sales team and management what was slowing them down. It turned out that the CRM they used was inconvenient and unstable for managing sales and client relationships, and it offered very little analytics.
2. Day 2

   Decision

   Based on the audit, we decided to build a new CRM from scratch with multi-factor analytics on sales and managers. We also decided to give every manager a voice AI assistant to make working with the CRM easier.
3. Day 6

   CRM development

   We built the core modules: companies and contacts, deals, proposals and contracts, client tasks, sales targets and per-manager analytics — with access rights and duplicate checks.
4. Day 8

   Data integration

   We analysed all email correspondence with clients in depth and built a database from it. That database, along with data from the old CRM and client files on Google Drive, was imported into the new CRM.
5. Day 10

   AI assistant

   Each sales manager got a personal AI assistant. Managers share meeting outcomes by voice or text, and the assistant updates the CRM, reviews tasks, prepares and files documents, and sends emails to clients.
6. Day 12

   Analytics

   We set up dashboards for sales managers and the head of sales: targets vs. actuals, deals and cash flow, receivables, and risk alerts that flag what needs attention right now.
7. Day 14

   Training

   We walked the team through the solution and trained them to work with the AI assistant and the CRM — from entering data to reading the analytics.
8. Day 15

   Handover

   We handed the CRM and the business process over to the client to run on their own.