26-28 November, 2019, Vilnius

Regular Prices End in:

Day(s)

:

Hour(s)

:

Minute(s)

:

Second(s)

Santiago Cabrera-Naranjo

Teradata Corporation, Germany

Biography

Santiago is Consulting Director, AI and Big Data at Teradata. He is thereby part of the Consulting Leadership Team in Germany. Furthermore, he is responsible of Consulting Services, advising Enterprises within their big data and advanced analytics strategy; leading them to innovative best-practice implementations with the goal to speed up time-to-market regardless their technology stack and initial organization.

Furthermore, Santiago has been responsible to launch and grow Teradata’s Hub in Berlin and is active as keynote speaker. His computer science studies helped him to collect experience from different point of views across several sectors. From building up data infrastructures for Rocket-Internet Ventures to founding himself stampfy after winning the German StartupBus in 2011 at the Age of 24. Before joining Teradata, Santiago was responsible of building up the Analytical Landscape for BILD and for the adoption of new cutting-edge technologies at Axel Springer SE.

Talk

The Future of Traditional Shopping Driven by Customer Centric Approaches

Artificial Intelligence gives retailers a great opportunity to evolve from point of sale to point of experience, convenience and omnichannel. In the coming years e.g., it will be easy to use bots for purchases perceived as boring and monotonous. As a consequence, offline retailers will have to be customer obsessed, keeping them engaged and loyal to their products if they don’t want to fall into an only-transactional buying category.

Together with a major European retailer, we leveraged a 6-step Multi-Genre-Analytics approach with the objective of making the current range management customer centric. This required information to determine the wider impact of range changes, understanding e.g. the transferable demand of removed items and shopping missions. The desired outcome was not only to catch affinity effects but also to identify whether customers are loyal to a product or to a brand as removing a loyalty enabling product impacts negatively visits and sales.

With the help of deep learning and video analytics, we aim now to be even more efficient optimising range and customer experience. The goal is to give the point of experience the equivalent capability of Web Analytics in the online world. How did this evolve as a business success story?

Session Keywords

Deep Learning
Video Analytics
Web Analytics