Delali Agbenyegah, CAP

The need to extract useful information from large amount of data to positively influence business and government decisions is on the rise especially with the hyper expansion of data collection and storage and the advancement in computing capabilities. Many enterprises and government institutions now have well established databases to capture data on every interaction that goes on within their organization. Link Analysis is a data mining technique that is used to identify and evaluate… Show more

The need to extract useful information from large amount of data to positively influence business and government decisions is on the rise especially with the hyper expansion of data collection and storage and the advancement in computing capabilities. Many enterprises and government institutions now have well established databases to capture data on every interaction that goes on within their organization. Link Analysis is a data mining technique that is used to identify and evaluate relationships or connections as well as sequences among various types of objects including people, organizations and transactions. This analytic technique can be applied in fraud detection, counterterrorism, computer security analysis, search engine optimization, market research and medical research. However, creating an efficient and robust statistical algorithm to conduct link analysis on big data can be a daunting task. Fortunately, the newly added Link Analysis node in SAS ® Enterprise Miner TM provides a simple to use but yet powerful analytical tool to extract, analyze, discover and visualize the connections (links) and sequences that exist in any dataset. In this paper, we discuss the basic elements of link analysis from a statistical perspective and provide a step by step example of how to conduct link analysis using SAS Enterprise Miner. Show less

The need to extract useful information from large amount of data to positively influence business decisions is on the rise especially with the hyper expansion of retail data collection and storage and the advancement in computing capabilities. Many enterprises now have well established databases to capture Omni channel customer transactional behavior at the product or Store Keeping Unit (SKU) level. Crafting a robust analytical solution that utilizes these rich transactional data sources to… Show more

The need to extract useful information from large amount of data to positively influence business decisions is on the rise especially with the hyper expansion of retail data collection and storage and the advancement in computing capabilities. Many enterprises now have well established databases to capture Omni channel customer transactional behavior at the product or Store Keeping Unit (SKU) level. Crafting a robust analytical solution that utilizes these rich transactional data sources to create customized marketing incentives and product recommendations in a timely fashion to meet the expectations of the sophisticated shopper in our current generation can be daunting. Fortunately, the Link Analysis node in SAS® Enterprise Miner TM provides a simple but yet powerful analytical tool to extract, analyze, discover and visualize the relationships or associations (links) and sequences between items in a transactional data set up and develop item-cluster induced segmentation of customers as well as next-best offer recommendations. In this paper, we discuss the basic elements of Link Analysis from a statistical perspective and provide a real life example that leverages Link Analysis within SAS Enterprise Miner to discover amazing transactional paths, sequences and links. Show less

Even though marketing is inevitable in every business, each and every year the marketing budget is limited and prudent fund allocations are required to optimize marketing investment. In many businesses, the marketing fund is allocated based on the marketing manager’s experience, departmental budget allocation rules and sometimes ‘gut feelings’ of business leaders. Those traditional ways of budget allocation yield sub optimal results and in many cases lead to money wasting on certain irrelevant… Show more

Even though marketing is inevitable in every business, each and every year the marketing budget is limited and prudent fund allocations are required to optimize marketing investment. In many businesses, the marketing fund is allocated based on the marketing manager’s experience, departmental budget allocation rules and sometimes ‘gut feelings’ of business leaders. Those traditional ways of budget allocation yield sub optimal results and in many cases lead to money wasting on certain irrelevant marketing efforts. Market Mixed models can be used to understand the effects of marketing activities and identify the key marketing efforts that drive the most sales among a group of competing marketing activities. The results can be used in marketing budget allocation and take out the guess work that typically goes into the budget allocation. In this paper, we illustrate how to develop and implement Market Mixed Modeling using SAS procedures from a practical perspective. Real life challenges of market mixed model development and execution are discussed and several recommendations are provided to overcome some of those challenges whenever possible. Show less

Traditional marketing predictive models target customers who are likely shop, make more trips or spend more. Whiles this approach generally yields higher marketing campaign performance results over random selection, it can sometimes lead to money wasting on customers who will shop regardless of marketing offers and ‘do not disturb’ customers who will rather stop shopping if you ‘disturb’ them with marketing offers.Net lift models are used to identify ‘persuadable’ customers who have higher… Show more

Traditional marketing predictive models target customers who are likely shop, make more trips or spend more. Whiles this approach generally yields higher marketing campaign performance results over random selection, it can sometimes lead to money wasting on customers who will shop regardless of marketing offers and ‘do not disturb’ customers who will rather stop shopping if you ‘disturb’ them with marketing offers.Net lift models are used to identify ‘persuadable’ customers who have higher likelihood to respond to marketing campaigns and help marketers maximize their return on marketing investments. This paper simplifies the basic concept of Net Lift modeling using
real life examples and shows how this can easily be accomplished using SAS® Enterprise Miner TM .The paper concludes with real life challenges of Net Lift modeling and suggests ways to handle some of those challenges as well as recommended situations where Net Lift models work best. Show less

The measurement of factors influencing consumer purchasing decisions is of interest to all manufacturers of goods,retailers selling these goods, and consumers buying these goods. In the past decade, conjoint analysis has become one of the commonly used statistical techniques for analyzing the decisions or “trade-offs” consumers make when they purchase products. Although recent years have seen increased use of conjoint analysis and conjoint software, there is limited work that has spelled out a… Show more

The measurement of factors influencing consumer purchasing decisions is of interest to all manufacturers of goods,retailers selling these goods, and consumers buying these goods. In the past decade, conjoint analysis has become one of the commonly used statistical techniques for analyzing the decisions or “trade-offs” consumers make when they purchase products. Although recent years have seen increased use of conjoint analysis and conjoint software, there is limited work that has spelled out a systematic procedure on how to do a conjoint analysis or use conjoint
software. The goals of this paper are as follow: 1) Review basic conjoint analysis concepts,2) Describe the mathematical and statistical framework on which conjoint analysis is built; 3) Introduce the TRANSREG and PHREG procedures, their syntaxes, and the output they generate using simplified real life data examples. This paper concludes by highlighting some of the substantives issues related to the application of conjoint analysis in a business environment and the available auto call macros in SAS/STAT®,SAS/IML® and SAS/QC® to handle more complex
conjoint designs and analyses. The paper will benefit the basic SAS® user, statisticians and research analysts in every industry, especially in marketing and advertisement. Show less