Sales

The volume of accounts worked on is multiplied without sacrificing personalization. Prospect research goes from twenty minutes to two, and the sequence adapts to each target.

lemlist or equivalent with AI, enrichment (Clay, Dropcontact), LinkedIn Sales Navigator, Claude for approach angles.

1. Build a precise ICP and document it in the tool to frame targeting. 2. Automatically enrich each account, generate a personalized angle per prospect, review before sending. 3. Analyze responses each week and iterate messages with AI based on this.

A generic message sent to a thousand people destroys the brand. Personalize genuinely or do not send.

The pipeline scores and cleans itself, forecasts improve, at-risk deals are flagged before it's too late.

CRM with native AI (HubSpot AI, Salesforce Einstein), forecasting tools, automations (n8n, Zapier).

1. Automate CRM hygiene: enrichment, deduplication, update reminders. 2. Implement lead and deal scoring, calibrate it based on actual history. 3. Build a weekly alert for drifting deals: inactivity, date slippage, silence.

A score is not a truth: regularly check what the model misses.

Competitive pricing monitoring runs continuously, elasticity is measured on actual data, pricing scenarios are simulated in minutes.

Pricing monitoring tools, Excel/BI + AI, Claude for scenario analyses.

1. Automate the collection of competitor prices in the key scope. 2. Analyze sales-price history to estimate elasticities by segment. 3. Simulate each price change before decision: volume, margin, competitive risk.

The optimal model price must remain explainable to the client and defensible by the sellers.

Each meeting is prepared in depth in ten minutes: account context, news, probable issues, anticipated objections. Proposals come out in hours, not days.

CRM with AI, Claude (project per key account), call analysis (Gong, Modjo), proposal generator.

1. Before each meeting, have the preparation sheet produced: company, contacts, angle, questions. 2. Record calls, extract issues, objections, and next steps in the CRM. 3. Generate the proposal from the call, then personalize it based on expressed issues.

AI prepares the sale; it does not make it. Listening during meetings remains the core of the job.

Monitoring of strategic accounts becomes continuous: news, movements, buying or risk signals. Account reviews are prepared in hours.

AI monitoring by account, CRM, Claude (project by strategic account with history).

1. Create an AI project for each key account: history, contracts, org chart, reports. 2. Set up monitoring alerts: appointments, results, projects, competitors at the client. 3. Prepare each account review: achievements, risks, opportunities, proposed plan.

The relationship cannot be outsourced: AI enriches the conversation, it does not replace it.

One hundred percent of calls are analyzed instead of a sample. The real reasons for wins and losses become visible, coaching is based on facts.

Gong, Modjo or equivalent, Claude for cross-summaries, pipeline dashboard.

1. Deploy the recording and systematic analysis of calls with team consent. 2. Extract patterns each month: rising objections, converting arguments, risk signals. 3. Transform patterns into actions: targeted coaching, updating playbooks, deal alerts.

Analysis serves to advance, not to monitor. The usage framework is established with the teams, not against them.

Playbooks become dynamic: continuously updated from actual calls. Training is personalized for each salesperson based on observed weaknesses.

Enablement platform, call analysis, Claude to produce content, LMS.

1. Produce and maintain playbooks based on actual winning calls. 2. Build short modules by situation: price objection, competitor X, negotiation. 3. Target each person's training based on their observed patterns in their own calls.

A playbook that the field does not use is a dead document: co-create with the best sellers.

The identification of potential partners accelerates, network performance is continuously monitored, partner reporting is generated.

Partner CRM (PRM), AI monitoring, Claude for network analyses.

1. Map the target network with AI: profiles, complementarities, interest signals. 2. Automate reporting by partner: pipeline brought, conversion, activity. 3. Prepare each partner review: assessment, gaps, proposed action plan.

A partnership lives by the relationship and shared value: data drives, humans animate.