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⚡ Source: ReedRef: 56644116

Sales Analyst

Dennis and Robinson T/A Paula Rosa Manhattan·Lancing Business Park·Posted 1 months ago
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Job description

Original text imported from Reed

We are seeking a Sales Analyst to support data-driven decision-making across our sales function. The role combines detailed analysis with the ability to communicate findings clearly and persuasively. Working closely with Sales, Design, Commercial, Finance, and Operations, the Sales Analyst will present insight that helps guide sales strategy and improve pipeline quality.

A key element of the role is the ability to create a coherent story from data and influence sales teams to act on the insights provided.

Key Responsibilities

Sales & Pipeline Analysis

  • Analyse performance across regional sales managers, national accounts, major projects, and design
  • Maintain Salesforce reporting across pipeline health, conversions, quoting activity, and win/loss trends
  • Use Glenigan to identify opportunities and track competitor activity
  • Produce weekly, monthly, and quarterly reporting for stakeholders

Insight, Storytelling & Influence

  • Translate complex data into clear, actionable narratives
  • Present findings in a structured, persuasive way that gains buy-in from sales teams
  • Support the Sales Director in embedding data-led decision-making
  • Build strong relationships with sales managers to help them understand and trust analytical insight

Market & Customer Insight

  • Analyse customer buying patterns, repeat business, and profitability
  • Highlight at-risk accounts and emerging opportunities
  • Produce market and competitor intelligence to support sales planning

Reporting & Forecasting

  • Develop accurate sales forecasts using CRM data and market indicators
  • Support annual budgets and quarterly reforecasting
  • Maintain KPI dashboards across revenue, margin, design throughput, and opportunity stages

Data Quality & Collaboration

  • Improve Salesforce data accuracy and consistency
  • Standardise reporting processes within the sales team
  • Work with Design (UK & Bangkok), Commercial, Operations, and Finance on cross-functional data needs

About You

  • Experience as a Sales Analyst, Commercial Analyst, or similar
  • Strong Excel skills including modelling and advanced formulas
  • Experience with Salesforce CRM
  • Familiarity with Glenigan, Barbour ABI, or similar platforms
  • Excellent communication skills with the ability to present data clearly
  • Confidence to challenge assumptions and influence senior stakeholders
  • Strong attention to detail and ability to work independently

Desirable: A degree in Data Analytics, Economics, Business, Marketing, or related discipline.

Benefits

  • Hybrid working - work from home one day per week
  • 25 days’ holiday, rising with length of service (plus 8 bank holidays)
  • SMART Pension Scheme
  • Health Cash Plan to claim back every day healthcare costs
  • Employee Assistance Programme – wellbeing, legal and emotional support
  • Life Assurance - 2× basic salary
  • Holiday purchase scheme (up to 6 weeks total leave)
  • Bike2Work Scheme
  • EV Salary Sacrifice Scheme (after 6 months)
  • Employee discount scheme for kitchens, appliances and staff sales


SpeedCV AI

Key skills

AI-extracted from the job advert

Must-have skills
Sales Analyst experienceAdvanced ExcelSalesforce CRMGlenigan platformData modellingSales forecastingPipeline analysis
Nice-to-have
Barbour ABIData Analytics degreeEconomics degreeBusiness degreeMarketing degree
Soft skills
CommunicationStakeholder influenceAttention to detailIndependent workingAnalytical thinkingPresentation skillsRelationship building
SpeedCV AI

Application advice

5 AI-generated recommendations to maximise your chances.

1

⭐ Highlight your Salesforce CRM expertise prominently as this is specifically mentioned as essential for pipeline reporting and data accuracy

2

📊 Quantify your analytical impact: 'Improved forecast accuracy by 15% through enhanced CRM data modelling'

3

🎯 Emphasise your storytelling abilities - the role specifically values translating complex data into actionable narratives

4

🤝 Showcase experience influencing senior stakeholders and sales teams, as challenging assumptions is key to this role

5

🌐 Mention any experience with construction industry platforms like Glenigan or Barbour ABI to demonstrate sector knowledge

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Suggested CV bullets

3 bullets our AI drafted for this specific advert, mirroring its ATS keywords.

How to tailor your CV

Add these 3 bullets under your most recent experience:

  • Improved Salesforce data accuracy by 25% through standardised reporting processes, enabling more reliable pipeline forecasting for 12 regional sales managers
  • Developed Excel-based sales forecast model incorporating CRM data and market indicators, achieving 18% improvement in quarterly prediction accuracy
  • Analysed customer buying patterns across 200+ accounts using advanced Excel formulas, identifying £1.2M in at-risk revenue and 15 emerging opportunities

Free to copy — tailoring requires a 30-sec CV upload.

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Letter preview — tailored to Dennis and Robinson T/A Paula Rosa Manhattan

Dear Hiring Manager,

Dennis & Robinson's focus on data-driven sales strategy aligns perfectly with my analytical background, which is why I am applying for the Sales Analyst position. My experience with Salesforce CRM and advanced Excel modelling, combined with my ability to translate complex data into actionable narratives, makes me well-suited to support your sales function's decision-making process.

My background in commercial analysis has equipped me with the skills to maintain pipeline reporting, develop accurate forecasts, and influence senior stakeholders through clear data presentation. I have successfully worked with cross-functional teams including Sales, Finance, and Operations to improve data quality and embed analytical insights into strategic planning.

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SpeedCV AI

Interview questions

10 questions generated from this advert.

Technical

  • How would you approach cleaning and standardising Salesforce data to improve reporting accuracy?
  • Walk me through how you would build a sales forecast model using CRM data and market indicators
  • How do you use Glenigan or similar platforms to identify sales opportunities?
  • Describe your approach to creating KPI dashboards for revenue and pipeline metrics
  • How would you analyse win/loss trends to improve sales performance?

Behavioural

  • Tell me about a time you had to influence a sales team to change their approach based on your analysis
  • Describe a situation where you had to present complex data findings to senior stakeholders
  • Give an example of when you challenged assumptions in a sales forecast or strategy
  • Tell me about a time you identified an at-risk account through data analysis
  • Describe how you've built trust with sales managers who were initially sceptical of data insights
SpeedCV AINEW

STAR answer examples

Model answers using the Situation-Task-Action-Result framework. Adapt to your own experience.

1Question

Tell me about a time you had to influence a sales team to change their approach based on your analysis

Situation: Our regional sales team was consistently missing quarterly targets despite high activity levels. Task: I needed to analyse their approach and convince them to change their prospecting strategy. Action: I analysed 6 months of Salesforce data and discovered they were focusing on low-value prospects with 12% conversion rates, while ignoring mid-tier accounts with 34% conversion potential. I presented this finding to the 8-person sales team using clear visualisations showing the revenue impact. I also created territory maps highlighting the untapped mid-tier opportunities worth £2.1M annually. Result: The team adopted the new targeting strategy, and within 3 months, their conversion rate improved from 12% to 28%, generating an additional £480K in quarterly revenue.
2Question

Describe a situation where you had to present complex data findings to senior stakeholders

Situation: Our sales forecast was consistently 15% off target, causing budget planning issues for the executive team. Task: I needed to identify the root cause and present a solution to the Sales Director and CFO. Action: I conducted a deep-dive analysis of 18 months of pipeline data, comparing forecast vs actual across different deal stages and sales managers. I discovered that deals in the 'proposal submitted' stage were being weighted at 70% probability, but actually converted at only 45%. I created a presentation showing the financial impact of this discrepancy - £850K in overestimated quarterly revenue. I recommended adjusting stage probabilities and implementing weekly pipeline reviews. Result: The executive team approved my recommendations immediately. After implementing the changes, our forecast accuracy improved from 85% to 96% over the following 6 months, enabling more reliable budget planning.

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