Customer Intelligence

Learn how marketing analytics is redefining the customer experience

Advanced Analytics | Analytics | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: Decision management, machine learning, and digital marketing

A typical day brings countless business decisions that affect everything from profitability to customer experience. What is a reasonable price point? Which audience segments should I personalize offers for? When should I recommend specific content earlier in a customer journey? Daily decisions like these can alter the trajectory of a

Artificial Intelligence | Customer Intelligence
Gerhard Svolba 0
Real-Time Scoring und Customer Behavior Analysis: Das konnte Frau Cerny schon in den 1970er Jahren!

Nicht erst im Zeitalter von künstlicher Intelligenz (KI) und Real-Time Decision Engines werden historische und aktuelle Verhaltensweisen von Kunden analysiert. Die Praxis, anhand dieser Informationen Entscheidungen zu treffen und sie in Echtzeit auf die Kundeninteraktion anzuwenden, gab es bereits in den 1970er-Jahren. Frau Cerny betrieb den Lebensmittelladen im Wohnhaus meiner

Advanced Analytics | Analytics | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: Model management for competitive differentiation [Part 1]

The universe of customer experiences, digital analytics, personalization and decisioning is massive. At times, it can seem as complicated and vast as the galaxy itself. With intricate subjects underneath this umbrella, you can lose direction, wander aimlessly, or feel a misleading sense of success or failure. When you lose vision,

Artificial Intelligence | Customer Intelligence
Gerhard Svolba 0
Real-Time Scoring and Customer Behaviour Analysis Are Not New! Mrs. Cerny Applied These Methods Decades Ago

The epoch of artificial intelligence and real-time decision engines is not the first time that historical and actual behaviour of customers has been tracked and analysed. The practice of making decisions based on these findings and applying them in real time to customer interactions was already going on in the

Advanced Analytics | Analytics | Artificial Intelligence | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 3]

In parts one and two of this blog posting series, we introduced machine learning models and the complexity that comes along with their extraordinary predictive abilities. Following this, we defined interpretability within machine learning, made the case for why we need it, and where it applies. In part three of

Advanced Analytics | Analytics | Artificial Intelligence | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 2]

In part one of this blog posting series, we introduced machine learning models as a multifaceted and evolving topic. The complexity that gives extraordinary predictive abilities also makes these models challenging to understand. They generally don’t provide a clear explanation, and brands experimenting with machine learning are questioning whether they

Advanced Analytics | Analytics | Artificial Intelligence | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 1]

As machine learning takes its place in numerous advances within the marketing ecosystem, the interpretability of these modernized algorithmic approaches grows in importance. According to my SAS peer Ilknur Kaynar Kabul: We are surrounded with applications powered by machine learning, and we’re personally affected by the decisions made by machines

Artificial Intelligence | Customer Intelligence | Students & Educators
Mayra Pedraza 0
Data, models and accountability: AI education for marketers

Developments in artificial intelligence (AI) are expected to change the world of work across the board. We have already witnessed the impact on marketing communication endeavours and strategies. The ripples spreading across the water include ethical issues and questions of accountability. I caught up with Anabel Gutiérrez, Senior Lecturer in

Analytics | Artificial Intelligence | Customer Intelligence
Gustavo Gutman 0
¿Cómo enfrentar la recesión a partir de los datos?

En situaciones donde la reducción de costos es un imperativo y las empresas carecen de presupuestos óptimos, los datos se vuelven aún más importantes de lo que eran antes de una recesión de datos. Priorizar libera resultados reales, y analizar la información de manera correcta se convierte en un punto clave. Determinar y definir qué clientes tienen mayor probabilidad

Analytics | Artificial Intelligence | Customer Intelligence
Pedro Felipe Cerón 0
Ciudades conectadas, el camino hacia ciudades inteligentes

En los últimos 25 años las ciudades colombianas han venido expandiendo su territorio y han aumentado su demanda de recursos naturales y servicios vitales. Esto lo sustentan las cifras del DANE que muestran que en 2017, 76% de la población colombiana se concentró en ciudades frente a un 24% que

Advanced Analytics | Customer Intelligence | Data Visualization
Suneel Grover 0
SAS Customer Intelligence 360: Visual forecasting, traffic acquisition, and digital media

Every brand offers a digital experience for a reason. But to achieve on your mission, raising awareness and attracting visitors through online media is critical. No visitors? Game over. Let’s dive into a business case using website visitor data to sas.com. Suppose that a manager asks: What did our web

Analytics | Customer Intelligence
Greg Heidrick 0
Retailers: is your customer experience strategy working?

Smart retailers know that omnichannel customer experience isn't just about marketing anymore.  It’s about bridging all your digital and physical channels to recognize customers wherever they are, collecting data and understanding the retail customer’s purchasing journey. By taking customer data, product data, and supply chain data - and applying predictive and prescriptive

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