This paper simply develops a new SAS^® macro, which allows you to scrap user textual reviews from Apple iTunes store for iPhone applications. It not only can help you understand your customers experiences and needs, but also can help you be aware of your competitors user experiences. The macro uses API in iTunes and PROC HTTP in SAS to extract and create data sets. This paper also shows how you can use the application ID and country code to extract user reviews.

The operational tempo of marketing in a digital world seems faster every day. New trends, issues, and ideas appear and spread like wildfire, demanding that sales and marketing adapt plans and priorities on-the-fly. The technology available to us can handle this, but traditional organizational processes often become the bottleneck. The solution is a new management approach called agile marketing. Drawing upon the success of agile software development and the lean start-up movement, agile marketing is a simple but powerful way to make marketing teams more nimble and marketing programs more responsive. You don't have to be small to be agile agile marketing has thrived at large enterprises such as Cisco and EMC. This session covers the basics of agile marketing what it is, why it works, and how to get started with agile marketing in your own team. In particular, we look at how agile marketing dovetails with the explosion of data-driven management in marketing by using the fast feedback from analytics to rapidly iterate and adapt new marketing programs in a rapid yet focused fashion.

Many different neuroscience researchers have explored how various parts of the brain are connected, but no one has performed association mining using brain data. In this study, we used SAS^® Enterprise Miner^™ 7.1 for association mining of brain data collected by a 14-channel EEG device. An application of the association mining technique is presented in this novel context of brain activities and by linking our results to theories of cognitive neuroscience. The brain waves were collected while a user processed information about Facebook, the most well-known social networking site. The data was cleaned using Independent Component Analysis via an open source MATLAB package. Next, by applying the LORETA algorithm, activations at every fraction of the second were recorded. The data was codified into transactions to perform association mining. Results showing how various parts of brain get excited while processing the information are reported. This study provides preliminary insights into how brain wave data can be analyzed by widely available data mining techniques to enhance researcher s understanding of brain activation patterns.

In our previous work, we often needed to perform large numbers of repetitive and data-driven post-campaign analyses to evaluate the performance of marketing campaigns in terms of customer response. These routine tasks were usually carried out manually by using Microsoft Excel, which was tedious, time-consuming, and error-prone. In order to improve the work efficiency and analysis accuracy, we managed to automate the analysis process with SAS^® programming and replace the manual Excel work. Through the use of SAS macro programs and other advanced skills, we successfully automated the complicated data-driven analyses with high efficiency and accuracy. This paper presents and illustrates the creative analytical ideas and programming skills for developing the automatic analysis process, which can be extended to apply in a variety of business intelligence and analytics fields.

Digital data has manifested into a classic BIG DATA challenge for marketers who want to push past the retroactive analysis limitations of traditional web analytics. The current groundswell of digital device adoption and variety of digital interactions grows larger year after year. The opportunity for 'digital intelligence' has arrived, as traditional web analytic techniques were not designed for the breadth of channels, devices, and pace that fuels consumer experiences. In parallel, today's landscape for data visualization, advanced analytics, and our ability to process very large amounts of multi-channel information is changing. The democratization of analytics for the masses is upon us, and marketers have the oppourtunity to take advantage of descriptive, predictive, and (most importantly) prescriptive data-driven insights. This presentation describes how organizations can use SAS^® products, specifically SAS^® Visual Analytics and SAS^® Adaptive Customer Experience, to overcome the limitations of web analytics, and support data-driven integrated marketing objectives.

Discover how SAS^® leverages field marketing programs to support AllAnalytics.com, a sponsored third-party community. This paper explores the use of SAS software, including SAS^® Enterprise Guide^®, SAS^® Customer Experience Analytics, and SAS^® Marketing Automation to enable marketers to have better insight, better targeting, and better response from SAS programs.

Energy companies that operate in a highly regulated environment and are constrained in pricing flexibility must employ a multitude of approaches to maintain high levels of customer satisfaction. Many investor-owned utilities are just starting to embrace a customer-centric business model to improve the customer experience and hold the line on costs while operating in an inflationary business setting. Faced with these challenges, it is natural for utility executives to ask: 'What drives customer satisfaction, and what is the optimum balance between influencing customer perceptions and improving actual process performance in order to be viewed as a top-tier performer by our customers?' J.D. Power, for example, cites power quality and reliability as the top influencer of overall customer satisfaction. But studies have also shown that customer perceptions of reliability do not always match actual reliability experience. This apparent gap between actual and perceived performance raises a conundrum: Should the utility focus its efforts and resources on improving actual reliability performance or would it be better to concentrate on influencing customer perceptions of reliability? How can this conundrum be unraveled with an analytically driven approach? In this paper, we explore how the design of experiment techniques can be employed to help understand the relationship between process performance and customer perception, thereby leading to important insights into the energy customer equation and higher customer satisfaction!

Vistaprint saw the opportunity in the printing market to get more out of high-volume printing by grouping similar orders in large groups. They heavily rely on technology to handle design, printing, and order handling and use the Internet as a medium. With their successful expansion across the world, the issue they were facing was a lot of one-time buyers and a lot of registered users who didn't finish the check-out. The need to implement a retention strategy was the next logical step, for which they chose SAS^® Campaign Management. In this session, Vistaprint explains how they use campaign management for retention and how the project was addressed. They will also touch on how the concept of high performance could open up new possibilities for them.

PROC TABULATE is a powerful tool for creating tabular summary reports. Its advantages, over PROC REPORT, are that it requires less code, allows for more convenient table construction, and uses syntax that makes it easier to modify a table s structure. However, its inability to compute the sum, difference, product, and ratio of column sums has hindered its use in many circumstances. This paper illustrates and discusses some creative approaches and methods for overcoming these limitations, enabling users to produce needed reports and still enjoy the simplicity and convenience of PROC TABULATE. These methods and skills can have prominent applications in a variety of business intelligence and analytics fields.