Overview

This 3-day course is designed to give attendees a broad and practical appreciation of the applications of advanced data analytics to achieve sales and marketing outcomes. It covers the full lifecycle from data acquisition and consolidation through to visualisation and storytelling and prediction and optimisation.

Training Topics

DAY 1 – ANALYTICS AND DATA STRATEGY

Strategy
• Aligning analytics with commercial objectives
• Analytics maturity models
• Moving from descriptive to predictive to prescriptive analytics

Planning
• Customer journey mapping
• Prioritising marketing use cases for data
• Mapping data assets and common keys

Measurement
• Objective and KPI setting
• Key principles of measurement design
• Relevant technologies

Data Capture and Integration
• Applying the principles of GDPR to data capture
• Joining up online and offline datasets
• Consolidating, aggregating and merging data: tools and processes

DAY 2 – DATA VISUALISATION AND STORYTELLING

Actionable Analysis
• Data analysis: What makes it actionable?
• The analysis lifecycle
• Introduction to different analytical approaches

Data Visualisation
• What makes a good versus a bad visualisation?
• Avoiding common visualisation pitfalls
• Choosing appropriate scales

Data Analysis
• Understanding the relationships between
variables
• Testing whether data and trends are significant
• Top tips to avoid mis-interpreting data

Data Storytelling
• How to find what the story is
• Understanding the audience
• Insight delivery using reports, presentations and verbal techniques

DAY 3 – DATA SCIENCE AND OPTIMISATION

Data Science Techniques
• Statistical and machine learning techniques
• Classification and prediction
• Supervised versus unsupervised learning

Business Applications of Data Science
• Segmentation and lifetime value
• Attribution and media mix modelling
• Lead scoring and churn prediction
• Recommendation and personalisation

Practical Data Mining and Modelling
• Clustering
• Regression and forecasting
• Propensity scoring Optimisation
• Planning test and learn activities (A/B and MVT)
• Using control groups for experimentation
• Commercial prioritisation and  optimisation

Key Information About the Course

Level: Advanced

Duration: 3-Day Programme

Date: 18th-20th November 2019

Fee: 7500QAR

Awarding: Excellence Training Centre

Contact: +974 7442 2210 | +974 7060 3669

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Learning Outcomes

By the end of this course, you will be able to:
• Articulate the key components of a data and analytics strategy
• Map and prioritise data assets from a commercial, technical and legal perspective
• Identify key technologies for data acquisition and consolidation
• Apply analysis effectively over a data to insight lifecycle
• Visualise data concisely for analysis and presentation
• Uncover and communicate clear stories using data to drive action
• Match the common sales and marketing applications of data science techniques
• Apply basic data mining and modelling approaches
• Plan an effective optimisation (test and learn) programme

Andrew Hood is founder and CEO of Lynchpin, an independent UK-based analytics consultancy established in 2005 with clients including Canon, Viacom, HSBC and Ticketmaster. 

He has trained in analytics and marketing effectiveness for over a decade, developing and delivering in-company courses globally for clients such as UPS, Citi, Deckers and KPMG.

Prior to founding Lynchpin, Andrew was part of the team that pioneered early online hotel reservation systems and built the largest collection of online bookable hotels at All-Hotels in 2000.

Attendee Requirements 
Attendees should have laptops with internet access for the duration of the training programme to enable them to participate in interactive exercises.

There is no specific pre-requisite knowledge required to attend the workshops, however they are at an intermediate level and some background knowledge of digital marketing concepts is recommended.

The training programme will be delivered solely in English but paced to suit those for whom English is a second language.