Software Sales

The role of a sales representative for data and AI-driven software involves selling complex platforms to businesses looking to leverage their data and integrate AI solutions. Responsibilities include understanding customer needs, demonstrating the value of solutions, managing complex sales cycles, and collaborating with technical teams to meet customer requirements.

Core Responsibilities

a. Prospecting and Customer Needs Analysis

• Prospect Identification
  • Use CRM tools (Salesforce, HubSpot) and market data to target companies with needs in data science, machine learning, and data management.
• Needs Analysis
  • Understand the business challenges of customers (e.g., digital transformation, process optimization, predictive analytics) and align them with the features of the proposed software.

b. Technical Demonstration and Argumentation

• Technical Presentations
  • Ability to explain software features (e.g., data pipelines, machine learning models, API integrations) and demonstrate their added value through concrete use cases.
• Customized Demonstrations
  • Prepare and deliver tailored demonstrations to meet specific customer needs, in collaboration with technical teams (e.g., data scientists, engineers).

c. Sales Cycle Management

• Opportunity Tracking
  • Manage the stages of the sales cycle (lead qualification, commercial proposals, negotiations, closing) with a focus on complex and long-cycle sales.
• Internal Collaboration
  • Work closely with product, support, and marketing teams to address objections and tailor offers to customer needs.

d. Competitive and Market Intelligence

• Competitive Analysis
  • Monitor competitive offerings (e.g., Alteryx, Snowflake, Palantir) and market trends to adjust sales arguments.
• Technological Watch
  • Stay updated on innovations in data and AI to anticipate future customer needs.

Concrete Project Examples

• Selling a Dataiku Platform
  • Assisted a bank in adopting Dataiku to automate its credit scoring processes and reduce fraud risks, demonstrating a 25% ROI.
• Deploying Databricks
  • Helped a retail company migrate its data to Databricks and optimize real-time analytics, reducing infrastructure costs by 20%.
• Integrating an MLOps Solution
  • Collaborated with an industrial company to integrate an MLOps solution and accelerate the deployment of predictive maintenance models.