In the past, I have taught classes on Use Case Analysis, Functional Analysis and Survey Analytics. I wanted to combine those three into a single “integrated” analytics class that focuses on how best to understand your customer’s online behavior and the drivers of consumer decision-making. This class will do just that. We will start with a look at developing use-cases and understanding their performance with Functional techniques. Then we will focus on how to re-engineer your online survey program to analyze the drivers of choice within each use-case. Finally, we will walk through the use of the analysis in structuring a testing program and driving site change. It is designed to be a complete survey of the analytic techniques necessary to drive ongoing site improvement.

The Online Analytics Maturity Model (OAMM), developed by Stéphane Hamel, is a framework that helps organisations assess their current situation and provide a structured, actionable path towards improving competence at leveraging data and analytics for enterprise-wide business decision-making.

In this workshop, Stéphane will present the six key areas of maturity and share a tremendous amount of tips and pitfalls gleaned from hundreds of practitioners and managers who gave the model the test of fire.

This workshop will be particularly useful for experienced analysts and managers who seek to understand the strengths and weaknesses of their organisation.

Coming away of the workshop, you will be empowered with a tool and methodology to assess, address and bring changes to move your organisation to the next maturity stage.

We all know analytics is a good thing. After all, we’ve been told how much data we have that describe customer behavior and little insight organizations actually gain from that data (see Wall Street Journal article on “The Big Asset Must Companies Ignore: Customer Data”).

However, we must do more than just build interesting measures and models: we need to define them properly and build them robustly!

In this workshop, Dean Abbott will describe five great measures and models you should build, how they are built wrong, and ways you customize them for your particular organization. The measures and models will include:

1. Engagement
2. Customer Lifetime Value
3. Purchase Propensity
4. Churn and Retention
5. Product Recommendations

We have been doing it all wrong… the idea was to gather business requirements from stakeholders, define KPIs, and create a solution design. The thing is… either your stakeholders (if client side) or clients (if agency) do not have a clue or they do not know how to properly articulate their needs. Do not ask them!

Instead, take the lead - be the expert; Show them the light; pave the way!

In this workshop, Stéphane Hamel, a recognised industry leader and author of the Digital Analytics Maturity Model, will propose a radical new approach to digital analytics. He will share tricks and examples that could transform the way you do your job. Utopia or Nirvana? It will be yours to decide!

Retailers collect big data to understand and message their customers. However, this data is typically put into silos, separating customer information from websites, mobile apps, call centers, and instore. Moreover, retailers are beginning to see the value in applying predictive analytics to augment their already extensive efforts to report on and visualize their data. Integrating big data collected from multiple channels so that predictive models can provide insights in the total customer experience is a gamechanger and is revolutionizing how retailers bring more timely and relevant messaging to their customers.

In this workshop, Dean Abbott will describe principles for how to approach multi-channel customer intelligence for retailers, why it’s critical, and what results can be expected. You will come away from this workshop with a clear vision of how to tackle your multi-channel insight strategy.

While this workshop will focus on retail practitioners in other sectors will find the principles covered as valuable to them.

We increasingly want to make our reporting predictive and analytic. A forecast is just a predictive model. But how do you build forecasting into your work? In this class, we will start at a very basic level and work our way up to more advanced forecasting techniques. We will introduce and review concepts like smoothing, banding and breakouts. We will then consider different kinds of forecast challenges – limited data, seasonality, variation, product cycles – and potential ways to model and handle the difficulties they present.

We will examine the role of exogenous variables and discuss how/whether to include them in a forecast. Since our problem set is focused on digital, attendees with experience with different variable types are encouraged to share their knowledge. Finally, we will cover the forecasting life-cycle and the ways you can embed continuous improvements into the process.

Whether you have made the switch to GTM or are considering the move, industry veteran Stéphane Hamel will walk you through a best practice deployment of Google Analytics and other tags through GTM. Plan your implementation, define tagging conventions, place tags, triggers and variables to good use with the aim to deliver value quickly and efficiently.

This workshop is also an opportunity to ask questions about best practices and any technical challenges you might be facing (Stéphane will get in touch with you a few days ahead of the workshop to get your questions - be prepared!). As a post workshop bonus, get one hour of free, private consulting to review and improve your implementation.