Sales Analyst

Roles and responsibilities

As a Sales Analyst, you will use analytical and problem-solving skills to provide analyses and solutions that satisfy business needs and inform strategy development. Leverages data tools to develop revenue and expense benchmarks and performance trends. Assists with creating sales presentations, proposals and internal business case development. Works collaboratively across various internal teams to support a variety of business initiatives

What you’ll need

To be available to work Full-time between 26th May/2nd June 2025 to 8th August or late June to late August 2025

To be a Penultimate Masters/Undergraduate Student, due to graduate no earlier than 2026

Innovative thinking and thoughtful risk-taking.

Ability to partner across the organization.

Sound communication skills.

Expert PC skills including proficiency in Microsoft Excel, Word, PowerPoint, and Access

• Excel or Google Sheets: For data analysis, reporting, and visualization.
• SQL: For querying and extracting data from databases.
• Tableau or Power BI: For creating interactive dashboards and visualizations.
• CRM Tools: Salesforce, HubSpot, or similar tools for tracking customer interactions and sales activities.
• Google Analytics or Marketing Automation Tools: For tracking sales and marketing efforts, particularly in digital sales.

Additional Skills That Could Be Helpful:

• Python or R: If you need to handle large datasets or perform advanced data analysis, programming languages like Python or R can be beneficial, especially for automating reports or implementing statistical models.
• Machine Learning: If your organization is moving toward more data-driven predictive sales models, having a basic understanding of machine learning (e.g., regression analysis, clustering) can be advantageous.
• Financial Acumen: Understanding financial reports and key financial metrics, such as operating income and return on investment (ROI), can provide more in-depth insights when analyzing sales performance.

Example of Daily Responsibilities:

• Analyze Sales Trends: Reviewing past sales data to identify trends, such as seasonality, customer preferences, and sales team performance.
• Generate Reports: Creating daily, weekly, or monthly reports for senior management to evaluate performance against KPIs.
• Provide Actionable Insights: Offering recommendations for sales strategies based on your findings (e.g., targeting specific customer segments or adjusting pricing).
• Collaborate with Sales & Marketing: Helping to identify sales opportunities and gaps in the market by providing data-driven insights.

Key Metrics a Sales Analyst May Track:

• Sales Revenue: Total sales generated during a specific period.
• Average Deal Size: The average value of deals closed by the sales team.
• Sales Pipeline Health: Understanding the number of prospects at each stage of the sales funnel.
• Conversion Rates: The percentage of leads that turn into paying customers.

Desired candidate profile

. Analytical Skills

• Data Analysis: Analyzing sales data to identify trends, patterns, and areas for improvement. This includes breaking down large datasets into actionable insights.
• Data Visualization: Presenting data clearly using visual tools like charts, graphs, or dashboards to make insights easier for stakeholders to understand.

2. Excel/Spreadsheet Proficiency

• Advanced Excel Skills: A Sales Analyst must be comfortable with advanced Excel functions like VLOOKUP, pivot tables, SUMIFs, and conditional formatting.
• Data Modeling: Building models to forecast sales trends, revenue, or other performance metrics.

3. SQL/Database Skills

• SQL: Being able to query and extract data from databases to analyze sales performance, customer behavior, and other key metrics. SQL is a valuable tool when working with large datasets that are stored in relational databases.
• Database Management: Understanding how to manage and query data in platforms like MySQL, PostgreSQL, or cloud-based solutions like Google BigQuery or AWS Redshift.

4. Sales Forecasting & Reporting

• Forecasting: Using historical data and analytical techniques to predict future sales, revenue, or market trends. Familiarity with time series analysis or predictive modeling techniques is beneficial.
• Reporting: Generating regular sales reports for leadership, including key performance indicators (KPIs) such as sales growth, conversion rates, and customer acquisition costs.

5. CRM Tools

• Familiarity with customer relationship management (CRM) tools like Salesforce, HubSpot, or Zoho CRM is often important, as they are used to track sales activities, customer interactions, and lead generation.

6. Understanding of Key Sales Metrics

• Revenue & Profit Margins: Analyzing revenue growth, profit margins, and sales conversion rates.
• Customer Acquisition Cost (CAC): Calculating how much it costs to acquire a customer, which helps in assessing the efficiency of marketing and sales efforts.
• Lead Conversion Rates: Understanding how well sales teams are converting prospects into customers.
• Sales Cycle: Evaluating the length of the sales cycle and identifying ways to improve efficiency.