Things were always moving fast, but the global pandemic has fundamentally changed the face of marketing.  The dramatic e-commerce growth over the past 18 months shifted our focus, but it is the holistic journey that presents a new type of challenge harnessing data, technology and insights to connect not just digital BUT all commerce moments.  

The reality is that while the majority of organizations are gathering massive amounts of data, data alone is a commodity.  For brands, the opportunity is to demonstrate an understanding of how a consumer thinks, acts and buys – and adapt quickly to deliver channel-agnostic solutions across a unified commerce landscape. 

But how do you ingest data, audience segments, retargeting and performance frameworks to gain a holistic view of your shopper, consumer and media landscape.  And what ways can you break down organization silos to make data more useful and accessible across teams rather than only your analysts, engineers, and people whose jobs are directly linked to data functions.

In this interactive 2.5-hour Learning Lab, you’ll elevate your understanding of how to use, collect and organize data across workstreams to:

• Enable focus, comprehension and relevance of 1st and 3rd party data across all operational stakeholders 
• Create holistic commerce strategies that connect shoppers to the most relevant commerce channels, not just the digital ones 
• Draw insights that enable the delivery of heightened and personalized experiences, removing friction at the point of purchase 
• Optimize and measure the results of your media and shopper investments for greater impact on the total brand or category

Who Should Attend: 

This course is for commerce leaders who want to get a broad understanding of data and how to apply it to solving problems and optimizing commerce output.

The focus of the course is:

• understanding the types of available data,
• their application to business decisions within the commerce sphere, and
• their application to commerce processes that lead to better outputs.

For example:

• How to acquire and analyze data that helps with shopper mindset segmentation when most available information is on consumer profiles.
• The collection and application of data to optimize the PDP.

We will start with the broad and end with more granular applications while going through a few case-studies along the way.