Sales Analytics and Excel Dashboards Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Sales Managers, Sales Operations Managers and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-S-076

Before you join: Participants should be confident using Excel worksheets, basic formulas, sorting, filtering and simple charts.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Sales leaders often receive reports that list activity and revenue but do not explain where performance is changing, why targets are being missed, or which accounts require action. This course addresses that gap by turning sales, pipeline, quota, customer and product data into controlled Excel models and decision-ready dashboards. Participants learn to define measures consistently, test data quality, analyse performance drivers and present findings that support forecast reviews, territory decisions and sales coaching.

The course covers the full workflow from source data to dashboard. Participants work with Excel Tables, XLOOKUP, SUMIFS, PivotTables, PivotCharts, Power Query, Power Pivot and DAX measures. They build sales KPIs for revenue, margin, quota attainment, conversion, pipeline coverage, velocity, customer retention and forecast accuracy. They also apply RFM, Pareto, win-loss, cohort and variance analysis to identify concentration risks, stalled opportunities, underperforming territories and commercial growth opportunities.

Instruction combines short technical briefings with guided case work, group analysis and dashboard-building activities using realistic sales datasets. Participants practise creating refreshable data pipelines, validating calculations, designing dashboard pages around management questions and communicating insights with clear recommendations. They leave with a reusable Excel sales dashboard pack, including a metric dictionary, data-preparation workflow, KPI model, dashboard wireframe, reconciliation checklist and 30-day implementation plan.

The course is suited to sales managers, analysts, commercial operations teams and marketing professionals who need stronger Excel-based reporting without moving immediately to a dedicated business intelligence platform.

What you will be able to do

  • Define sales KPI specifications using metric dictionaries, calculation rules and decision questions
  • Prepare sales data using Excel Tables, Power Query transformations and quality checks
  • Build controlled sales calculations using XLOOKUP, SUMIFS, date functions and formula auditing
  • Create PivotTable and PivotChart analyses for revenue, pipeline, quota and customer performance
  • Develop Power Pivot Data Models and DAX measures for repeatable sales reporting
  • Design Excel dashboards using visual hierarchy, KPI cards, slicers and decision-first layouts
  • Analyse pipeline, forecast, territory and customer performance using named sales analytics methods
  • Produce a governed dashboard refresh process with reconciliation and stakeholder review controls

Benefits of attending

For you

  • Build credible sales dashboards without depending on manual spreadsheet consolidation
  • Explain revenue and pipeline movements using defensible measures and variance analysis
  • Identify stalled opportunities, weak conversion points and territory performance gaps faster
  • Present sales insights with clearer charts, KPI context and recommended actions
  • Create repeatable reporting workflows using Power Query and Power Pivot

For your organisation

  • Reduce manual effort spent consolidating recurring sales reports and CRM extracts
  • Improve consistency of revenue, pipeline, quota and forecast measures across management reviews
  • Expose data-quality issues before they distort sales forecasts and performance decisions
  • Provide managers with earlier warning of coverage gaps, stalled deals and underperformance
  • Establish reusable dashboard controls for refreshes, reconciliations and authorised reporting access

Course modules

10 modules over 5 days

Participants can define controlled sales measures that answer specific management and coaching questions.

  • Sales funnel definitions, stage criteria, conversion rates and velocity measures
  • Revenue, margin, attainment and activity KPIs linked to decision questions
  • SMART metric specifications defining owner, formula, frequency, source and threshold
  • Leading and lagging indicators distinguished for coaching and forecast review
  • Calendar, fiscal period and comparable-period logic for sales reporting
  • Metric dictionary structure documenting definitions, exclusions and calculation assumptions

Participants can assess whether sales data is fit for reliable analysis and dashboard reporting.

  • Fact tables and dimension tables mapped using a star schema
  • Unique customer, opportunity and product keys reconciled before analysis
  • Data quality checks for duplicates, blanks, outliers and invalid dates
  • Grain defined for transactions, opportunities, monthly targets and salesperson records
  • Source-to-report lineage captured in a sales data inventory
  • Data protection controls for customer identifiers and restricted commercial fields

Participants can build auditable Excel calculations for segmented sales and pipeline analysis.

  • Structured Excel Tables established with consistent headers and data types
  • XLOOKUP, INDEX-MATCH and XMATCH used for controlled dataset joins
  • SUMIFS, COUNTIFS and AVERAGEIFS calculate segmented sales performance metrics
  • IFERROR, LET and named ranges improve formula readability and control
  • Date functions create fiscal periods, ageing bands and rolling windows
  • Formula auditing traces precedents, flags errors and tests reconciliations

Participants can transform and combine recurring sales extracts into refreshable reporting datasets.

  • Power Query imports CSV, workbook, CRM and ERP extracts
  • Applied Steps document transformations for repeatable sales-data refreshes
  • Merge queries joins opportunities, accounts and quota reference tables
  • Append queries combines monthly extracts using consistent field structures
  • Unpivoting converts wide monthly targets into analysis-ready transactional rows
  • Parameters and refresh controls support repeatable reporting cycles

Participants can produce interactive analyses that reveal sales performance patterns and exceptions.

  • PivotTables summarise revenue, units, margin and pipeline by dimension
  • Slicers and timelines filter dashboards without altering source calculations
  • PivotCharts select appropriate comparisons, trends, composition and ranking views
  • Waterfall charts explain variance between target, forecast and actual results
  • Conditional formatting highlights exceptions using thresholds, data bars and icons
  • Chart source ranges controlled through Tables and dynamic named ranges

Participants can create Data Model measures for repeatable and scalable sales reporting.

  • Data Model relationships connect sales facts with shared business dimensions
  • Power Pivot measures separate calculations from worksheet-level reporting logic
  • DAX CALCULATE modifies filter context for controlled performance measures
  • Time-intelligence measures calculate month-to-date, year-to-date and prior-period comparisons
  • Distinct counts prevent duplicate-account inflation in customer and pipeline reporting
  • Measure validation reconciles Data Model totals against approved source reports

Participants can design Excel dashboards that direct attention to decisions, risks and actions.

  • Decision-first dashboard wireframes align pages with management review questions
  • Visual hierarchy uses position, scale, contrast and proximity deliberately
  • KPI cards show actual, target, variance and directional context
  • Chart selection matches trend, ranking, distribution, relationship and contribution questions
  • Dashboard layouts avoid misleading axes, clutter, decoration and excessive colour
  • User journeys define filters, drill-down paths and action prompts

Participants can analyse forecast reliability, pipeline coverage and target variance using Excel models.

  • Weighted pipeline forecasts combine stage probabilities, values and close dates
  • Forecast accuracy measures compare committed, best-case and actual revenue
  • Quota attainment calculations distinguish annual targets, adjustments and ramp periods
  • Sales variance analysis separates volume, price, mix and timing effects
  • Scenario tables model upside, downside and base-case assumptions
  • Exception rules identify stalled deals, coverage gaps and forecast risks

Participants can identify commercially significant segments, concentration risks and growth opportunities.

  • RFM analysis segments customers by recency, frequency and monetary value
  • Pareto analysis identifies revenue concentration among accounts, products and territories
  • Win-loss analysis compares outcomes by source, segment, competitor and salesperson
  • Territory performance maps attainment, pipeline coverage and account potential
  • Cohort analysis tracks customer retention and repeat-purchase patterns
  • Opportunity ageing exposes stalled pipeline and follow-up priorities

Participants can govern dashboard delivery and communicate findings through clear commercial recommendations.

  • Dashboard acceptance criteria specify metrics, refresh timing and authorised users
  • Reconciliation checklist confirms totals, filters, periods and source extracts
  • Workbook protection controls safeguard formulas, reference data and report layouts
  • Refresh runbooks assign steps, owners, dependencies and escalation points
  • Insight narratives distinguish observations, implications, recommendations and required decisions
  • Thirty-day application plans schedule dashboard deployment and stakeholder review

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Sales KPI metric dictionary template
  2. Power Query sales-data preparation workflow
  3. Excel sales performance dashboard template
  4. Pipeline and forecast variance model
  5. Dashboard reconciliation and refresh checklist
  6. Thirty-day dashboard implementation plan

Who should attend

  • Sales Managers — need evidence for coaching, forecast reviews and target interventions
  • Sales Operations Managers — need controlled reporting processes across teams and territories
  • Commercial Analysts — need advanced Excel methods for analysing sales performance drivers
  • Business Development Managers — need visibility of pipeline quality, conversion and opportunity ageing
  • Marketing Analysts — need to connect campaign sources with lead, opportunity and revenue outcomes
  • Finance Business Partners — need reconciled sales measures for planning and commercial performance reviews

Skills and tools covered

Sales KPI designExcel data modellingPower Query transformationDashboard designPipeline forecastingCustomer segmentation

Tools and standards

Microsoft Excel, Power Query, Power Pivot, DAX

How the course runs

Training methodology

The course uses short instructor briefings followed by guided Excel builds, sales-data case work, peer review and structured group discussion. Participants work through realistic extracts covering opportunities, accounts, targets, products and salespeople. Activities include defining metrics, cleaning data with Power Query, building PivotTable and Data Model analyses, and reviewing dashboard designs against management questions. The final sessions focus on interpreting findings, documenting refresh controls and preparing an application plan for participants' own reporting responsibilities.

Requirements and prerequisites

Participants should be confident using Excel worksheets, basic formulas, sorting, filtering and simple charts. Familiarity with sales terms such as pipeline, opportunity, quota, revenue, margin and conversion rate is assumed. Participants should have experience working with sales reports, CRM exports, customer data or commercial performance reviews. Prior use of PivotTables is helpful but not essential. No programming, database administration, Power BI, VBA, SQL or prior Power Query and DAX experience is required.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants should be comfortable with worksheets, basic formulas, sorting, filtering and simple charts. The course teaches Power Query, Power Pivot and DAX from the ground up, although prior PivotTable experience is helpful.

Bring a laptop with a current desktop version of Microsoft Excel, ideally Microsoft 365 or Excel 2021 or later. Course files and datasets are provided; participants may also bring non-sensitive examples of their own sales reports.

It is designed for sales managers, sales operations staff, commercial analysts, business development managers, marketing analysts and finance partners. It is most useful for people who prepare, review or act on recurring sales performance reports.

This course applies Excel methods specifically to commercial questions such as quota attainment, pipeline coverage, conversion, forecast accuracy and account concentration. It includes Power Query and Power Pivot, but does not focus on Power BI publishing or general spreadsheet administration.

Participants can adapt the dashboard template, metric dictionary and refresh checklist to their CRM, ERP or sales-planning extracts. The 30-day application plan helps them prioritise a first dashboard, agree definitions and establish a reporting cadence.

The five days provide approximately 32.5 contact hours, running from 08:30 to 16:30 each day. Time is allocated across KPI design, data preparation, Excel modelling, dashboard construction, forecasting analysis, governance and application planning.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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