Tableau for Marketing Analytics Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Marketing Analysts, Digital Marketing 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-DM-077

Before you join: Participants should have working experience with marketing metrics such as impressions, clicks, conversions, cost per acquisition, leads, revenue or retention.

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

Marketing teams hold data from advertising platforms, web analytics, CRM systems, email tools and ecommerce platforms, yet reporting often remains fragmented. Campaign results may be measured with inconsistent definitions, duplicated records or channel metrics that do not connect to revenue, retention or pipeline. Tableau provides a practical environment for combining marketing data, testing assumptions and presenting decisions through governed dashboards that managers can use.

This course develops intermediate Tableau skills for marketing measurement and reporting. Participants prepare campaign, customer and conversion data; create calculated fields and Level of Detail expressions; analyse channel performance, funnels, cohorts and customer segments; and design dashboards for executives and operational teams. The course also addresses attribution limits, experiment interpretation, data quality, dashboard performance and controlled publishing. Participants learn to turn questions such as "Which campaigns should receive next month's budget?" into clear metrics, data requirements and Tableau views.

Teaching combines short technical briefings with marketing cases, guided builds, group analysis and dashboard review. Cases reflect common reporting situations including paid media performance, lead-generation funnels, ecommerce conversion and customer retention. Participants apply methods to supplied marketing datasets and create a documented dashboard blueprint covering KPIs, source data, calculations, audience needs and governance controls. Delivery is instructor-led over five days, available in classrooms in 50+ cities or live online. Participants receive a certificate of completion.

The course suits marketing professionals who need stronger analytical reporting skills and analysts responsible for converting marketing data into useful Tableau outputs. It is particularly relevant where marketing, sales and finance need a shared view of performance, spend and commercial outcomes.

What you will be able to do

  • Define marketing KPI trees, metric definitions and decision-focused dashboard requirements
  • Prepare campaign, CRM, web analytics and transaction data for Tableau analysis
  • Build calculated fields, parameters, sets and Level of Detail expressions
  • Analyse channel performance using spend, conversion, revenue and ROAS measures
  • Create funnel, cohort, RFM and customer journey analyses in Tableau
  • Evaluate attribution models, incrementality results and experiment evidence
  • Design accessible Tableau dashboards using appropriate charts, actions and reference lines
  • Publish governed Tableau reporting with QA, permissions, refresh and adoption controls

Benefits of attending

For you

  • Produce Tableau dashboards that connect campaign activity to commercial outcomes
  • Explain ROAS, conversion and retention metrics with traceable calculations
  • Identify data-grain and duplication issues before they distort campaign reporting
  • Present attribution and experiment findings with appropriate assumptions and limitations
  • Create a reusable dashboard specification for a current marketing reporting need

For your organisation

  • Creates consistent definitions for spend, conversion, revenue and marketing-qualified leads
  • Reduces manual reporting effort through structured Tableau data preparation and refreshes
  • Improves budget decisions with channel, campaign and audience performance evidence
  • Connects marketing activity with CRM pipeline, sales outcomes and customer value
  • Applies publishing, permission and QA controls to shared marketing dashboards

Course modules

10 modules over 5 days

Participants can translate marketing decisions into defined KPIs, data requirements and dashboard questions.

  • Marketing measurement questions translated into decision-focused dashboard requirements
  • Funnel stages mapped from awareness through conversion, retention and advocacy
  • KPI trees connecting media inputs, customer actions and commercial outcomes
  • SMART metric definitions documented with owner, grain, refresh and target
  • North-star metrics separated from diagnostic metrics and operational measures
  • Measurement plans align business questions, sources, calculations and decisions
  • Vanity metrics distinguished from actionable indicators using decision criteria

Participants can assess marketing data structures and document reliable metric definitions.

  • Marketing data architecture spanning CRM, web analytics, media and commerce
  • Grain assessed before joining campaign, customer, session and transaction tables
  • Primary keys, foreign keys and bridge tables prevent duplication errors
  • UTM parameters standardised using source, medium, campaign, content and term
  • GA4 event parameters interpreted for acquisition, engagement and conversion analysis
  • Data dictionaries record field meaning, refresh cadence, owner and limitations
  • Consent status and PII fields classified before dashboard publication

Participants can connect, clean and structure marketing data for accurate Tableau analysis.

  • Tableau connectors configured for spreadsheets, databases, extracts and web data
  • Live connections compared with extracts for latency, load and refresh needs
  • Tableau Prep flows clean nulls, split fields and standardise values
  • Joins, unions and relationships selected according to data grain
  • Pivoted media reports reshaped into analysis-ready campaign records
  • Extract filters reduce volume while retaining required reporting detail
  • Data quality checks reconcile totals against source-system reports

Participants can create Tableau calculations that support marketing measurement and scenario analysis.

  • Calculated fields create conversion rates, CPA, ROAS and engagement measures
  • IF, CASE and ZN functions handle marketing classification and missing values
  • Date functions build campaign periods, cohorts and rolling comparison windows
  • Parameters enable scenario views for targets, attribution assumptions and budgets
  • Sets identify high-value segments, campaign groups and exception populations
  • Level of Detail expressions calculate customer-level values despite visual granularity
  • Table calculations produce running totals, percent differences and moving averages

Participants can analyse campaign results by channel, audience, creative and budget performance.

  • Channel performance compared using spend, reach, conversions, revenue and ROAS
  • Paid search analysed by campaign, ad group, keyword and device
  • Social advertising segmented by audience, placement, creative and frequency
  • Email performance assessed through delivery, opens, clicks, conversions and unsubscribes
  • Landing-page analysis links sessions, engagement, form completion and conversion
  • Campaign pacing charts compare actual spend against planned budget trajectories
  • Pareto analysis isolates campaigns producing disproportionate cost or revenue

Participants can visualise customer progression, segment value and retention patterns in Tableau.

  • Customer journeys visualised from first touch through purchase and repeat behaviour
  • RFM segmentation scores recency, frequency and monetary customer value
  • Cohort tables compare retention patterns by acquisition month or campaign
  • Funnel drop-off quantified between visits, leads, opportunities and closed sales
  • CRM opportunity stages reconciled with marketing-qualified and sales-qualified lead definitions
  • Customer segments filtered using attributes, behaviours, lifecycle and value
  • Time-to-conversion distributions reveal delays between acquisition and purchase

Participants can interpret attribution and test results without overstating marketing impact.

  • Attribution models compared: last touch, first touch, linear and position-based
  • Multi-touch attribution limitations explained when journeys cross devices and channels
  • Controlled experiment results separated from observational campaign performance
  • Incrementality measured through holdout groups, test cells and conversion lift
  • Statistical significance interpreted using confidence intervals, sample sizes and power
  • Marketing mix context distinguished from user-level attribution reporting
  • Assumption logs document attribution windows, exclusions and known bias

Participants can design Tableau dashboards that support fast, accurate marketing decisions.

  • Chart selection matches comparison, composition, distribution, relationship and geographic questions
  • Pre-attentive attributes direct attention toward targets, exceptions and trends
  • Dashboard actions connect executive summaries with channel and campaign detail
  • Filters, parameters and tooltips support controlled self-service analysis
  • Reference lines and bands display targets, benchmarks and acceptable ranges
  • Colour, labels and accessible formatting improve interpretation without visual clutter
  • Mobile layouts prioritise essential KPIs for compact screens

Participants can publish marketing dashboards with appropriate security, refresh and performance controls.

  • Tableau Server and Tableau Cloud publishing workflows compared
  • Projects, permissions and row-level security control appropriate data access
  • Certified data sources identify approved metrics and governed connections
  • Extract refresh schedules align reporting timeliness with source availability
  • Subscriptions and data-driven alerts distribute exceptions to accountable owners
  • Performance Recorder identifies slow queries, calculations and dashboard rendering bottlenecks
  • Version control practices document dashboard changes, releases and metric revisions

Participants can plan a governed Tableau reporting improvement for a defined marketing use case.

  • Marketing reporting operating models define owners, cadences, audiences and decisions
  • Dashboard requirements prioritised using user stories and acceptance criteria
  • QA checklists test data accuracy, filters, calculations and rendered views
  • Stakeholder feedback converted into scoped improvements and release priorities
  • Adoption metrics track usage, recurring questions and unused dashboard content
  • Insight narratives connect observed variance, likely drivers and recommended actions
  • 90-day implementation plans sequence data work, dashboard releases and governance

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

What you take back to work

  1. Marketing KPI tree template
  2. Metric definition and data dictionary template
  3. Tableau calculated fields reference sheet
  4. Campaign performance dashboard blueprint
  5. Marketing dashboard QA checklist
  6. 90-day reporting implementation plan

Who should attend

  • Marketing Analysts — build reliable campaign, funnel and customer performance dashboards
  • Digital Marketing Managers — assess channel results and allocate budget using consistent metrics
  • Marketing Operations Specialists — connect CRM, automation and campaign data into managed reporting
  • Business Intelligence Analysts — develop Tableau outputs for marketing stakeholders and commercial teams
  • Growth Managers — investigate acquisition, conversion and retention patterns using customer data
  • Sales Operations Analysts — align lead, opportunity and revenue reporting with marketing measures

Skills and tools covered

Marketing KPI designTableau data preparationCalculated field developmentCampaign performance analysisCustomer segmentationDashboard governance

Tools and standards

Tableau Desktop, Tableau Prep Builder, Tableau Cloud, Google Analytics 4

How the course runs

Training methodology

The course uses short instructor briefings, demonstrations and guided Tableau builds to introduce each technique. Participants work with realistic marketing datasets covering paid media, web analytics, CRM and ecommerce activity. Case work and group exercises focus on metric definitions, data preparation choices, dashboard critique and interpretation of campaign results. Simulations address stakeholder requests, reporting exceptions and governance decisions. Application planning helps participants translate course methods into a defined reporting improvement for their own marketing function.

Requirements and prerequisites

Participants should have working experience with marketing metrics such as impressions, clicks, conversions, cost per acquisition, leads, revenue or retention. They should be comfortable using spreadsheets, filtering data and interpreting basic tables and charts. Prior Tableau experience is helpful, particularly opening workbooks and creating simple views, but advanced calculations are not assumed. Participants do not need programming, SQL, statistical modelling or data engineering experience. Access to Tableau licences, marketing platforms or organisational data is not required for attendance; course datasets are used during instruction.

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

You should be comfortable with marketing metrics, spreadsheets and basic data filtering. Prior exposure to Tableau is useful, but the course introduces the Tableau methods needed before progressing to calculations, dashboards and publishing.

Bring a laptop if attending in person and, where permitted, a non-sensitive example of a reporting challenge you face. You do not need to bring organisational data, platform credentials or a Tableau licence.

It is designed for marketing analysts, digital marketing managers, marketing operations specialists and BI analysts supporting commercial teams. It also suits growth and sales operations professionals who need joined-up campaign and pipeline reporting.

General Tableau courses usually focus on generic datasets and visual analysis techniques, while digital marketing courses focus on channel strategy and execution. This course applies Tableau directly to campaign, funnel, CRM, customer and marketing measurement problems.

Participants can use the KPI tree, data dictionary, calculation reference and dashboard QA checklist to improve an existing report or specify a new one. The application plan helps identify an initial use case, stakeholders, data dependencies and release priorities.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours, totalling approximately 32.5 contact hours. Time is divided between marketing measurement, data preparation, Tableau analysis, dashboard design, 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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