|12/5/13||DMA Analytics Council Presents: Solving Difficult Research Problems with Bayes Nets|
|1/16/14||DMA Analytics Council Presents: Predicting Multi Channel Online Behavior: Easy and Effective Non-Linear Methods|
|2/13/14||DMA Analytics Council Presents: Your Customers Want to Love You – Transforming Customer Experiences With Big Data & Technology-Enabled Predictive Analytics|
|archive||DMA Analytic Council Presents: Your Diamond in the Rough: Making Analytics Shine in your Marketing Organization|
|archive||DMA Analytics Council Presents: Will Machine Learning Algorithms Transform Real Time Digital and Social Interactions?|
|archive||DMA Analytics Council Presents: 7 Ways to Amp Up Your Marketing Using Customer Analytics|
Your Diamond in the Rough: Making Analytics Shine in your Marketing Organization
Data and analytics will experience an 18% – 25% growth rate during the next five years. There is clearly intense interest the differentiating capabilities of analytics-driven insights to improve marketing decision making. A well-integrated analytic competency that embeds a culture of data-driven decision making is now essential table stakes for any brand that wants to compete effectively.
Are you ready for this transformation? Growing a data-driven culture does not happen easily; core skill sets are varied and some are highly technical. And far too often, people with the right mix of technical skills don’t have the ideal “emotional intelligence” to effectively lead. This webinar will help you define a vision and learn a proven methodology for building a best-practices Analytics organization
CEO and Founder of Data Square, Devyani Sadh, Ph.D, is a recognized thought-leader, industry expert, popular speaker, advisor, judge, board member and thought leader at national conferences, councils, and competitions in CRM, Database Marketing and Analytics. Dr. Sadh has served as adjunct faculty at top tier universities such as NYU and University of Connecticut and published extensively. She currently teaches the Direct Marketing Association’s CRM and Database Marketing Seminar and is chair of the DMA’s Analytics Council. Dr. Sadh has delivered the opening (most-attended) concurrent session at NCDM for several years and was amongst the top 10 spot lighted sessions at the DMA Annual Conference a few years ago.
Leo Kluger is a Program Director with IBM’s Business Analytics Transformation team, whose mission is to help IBMers embed analytics to improve the business. Previously, Leo was the founding manager of the worldwide database analytics team in IBM’s Market Intelligence organization.
Prior to his IBM career Leo helped lead the market analytics team at Columbia House, where he optimized offers such as “Buy 7 get one free.” He started his career working for NASA. Leo received his Bachelor’s degree from the University of Pennsylvania, and a dual MBA in both Information Systems and Marketing, from New York University’s Stern School of Business. Outside IBM, Leo is the vice chairman of the Direct Marketing Association’s Analytics and CRM Council, where he’s also editor of their yearly Analytics Journal. Leo and his wife, Dr. Karin Kluger, have nine children, including two sisters recently adopted from Yaroslavl, Russia.
(Missed it? Check out the DMA Advance blog post summary.)
Will Machine Learning Algorithms Transform Real Time Digital and Social Interactions?
The promise of machine learning tools is to aid marketers in rapid digital interaction and more relevant proactive outreach. Despite a flurry of innovation, three are still gaps – creating pitfalls for the uninformed.
Consider that while consumers can access information and interact with brands at the palm of their hands anywhere and anytime, brand marketers have failed to adapt to this pace and leverage consumers’ “moments of truth”:
- Most social marketers still react to consumer concerns and address brand reputation issues during business hours as oppose to 24/7
- SEM marketers make bid decisions on a daily basis as oppose to on the fly based on pre-set business rules
- Most digital and content planners still serve content based on pre-set scheduled campaigns, confined by their marketing calendars, not consumer needs during the interaction.
Silicon Valley has reacted with the launch of hundreds of startups focusing on machine learning tools and applications in the areas of social listening tools, media display RTBs, and search bid yield algorithms. All that is helping marketers strengthen ROI.
However, a couple of key components are missing:
1) Marketers have been slow to partially adapt to “always on” consumers and social technology innovation
2) Technology providers have developed industry algorithms, yet these are sub-optimal to fully address specific brand considerations and needs.
Partner, Technology, Digital and Social Analytics, JubaPlus
With over 15 years of experience working with Fortune 500 companies across retail, automotive, consumer electronics, CPG and travel & entertainment, Yoram Greener has identified analytically driven marketing opportunities and developed and implemented highly customized solutions across marketing, service and technology. Yoram has been providing technology, data and analytics services to advertising agencies in digital, social and CRM. A few of JubaPlus Optimization Agency clients have been Vivaldi Partners, Salorix a social media technology company, Big Fuel a Publics social media agency and several brands. Prior to JubaPlus Yoram held executive positions at Merkle as a Senior Director Strategy and a Managing Director Analytical Solutions for MBS Insights. Yoram Greener is Adjunct Professor at NYU. He holds BA degrees in Economics and Statistics, and an MBA from Hofstra University.
(Missed it? Check out the DMA Advance blog post summary.)
7 Ways to Amp Up Your Marketing Using Customer Analytics
It is no secret that leading marketers are using analytics to bring a whole new level of sophistication to marketing. Now marketing can be truly personalized, cross-channel, and real-time. But what are the technical and practical steps to turn shoppers into buyers? What analytics should marketers be using to optimize online, mobile and offline channels? Attend this session to learn how you can use analytics across typical data silos, take an omni channel approach, and make the most out of every moment with your customers and prospects.
Strategy Director, Enterprise Marketing Management, IBM
Jay leads product strategy within IBM’s Enterprise Marketing Management group. His team is responsible for market analysis, customer insight, and industry marketing functions. He came to IBM through its acquisition of Unica. Henderson has over fifteen years’ experience in multi-channel marketing and customer analytics. Prior to joining Unica, Jay ran marketing at text mining innovator ClearForest (acquired by Thomson Reuters). Previously, he served in various marketing roles at predictive analytics leader SPSS (also now part of IBM), web analytics pioneer NetGenesis, and management consulting firm Cambridge Technology Group. Jay holds degrees from MIT’s Sloan School of Management and the Sorbonne (Paris IV).
Solving Difficult Research Problems with Bayes Nets
This is an Intermediate level overview of how to use Bayes Net to solve marketing analytics challenges. We will cover a brief background on conditional logic and compare Bayes Net with other regression-based models. Several practical applications will be covered:
a. Finding structures that make sense starting with a messy questionnaire
b. Predicting market share from questionnaire questions
c. Tackling data mining and text analytics.
Dr. Steven Struhl
Dr. Steven Struhl has more than 25 years’ experience in consulting and research, focusing on applying advanced methods to strategic goals, and framing results and explanations so decision makers can use them effectively. His work addresses how buying decisions are made and understanding consumer groups and their motivations. Steven’s experience includes serving 15 years as Senior Vice President, Senior Methodologist at Total Research (later Harris Interactive), where he focused on strategy and analytics for pricing, product and service optimization, decision making and customer loyalty. He also served as head of analytics for the life sciences/pharmaceutical group there for many years. Earlier experience includes working as Director of Market Research at SPSS, Inc., where he guided development of new statistical software, and senior positions in financial services and communications.
Predicting Multi Channel Online Behavior: Easy and Effective Non-Linear Methods
It’s easy to buy into the promise of big data-driven marketing, but challenging to actually implement. With data coming at us from Data Management Platforms (DMPs), social networks, our own web properties, email, point of sale, promotional, and even old fashioned call centers and direct mail, our scary old terabytes of marketing data have turned into petabytes.
All sorts of companies have demonstrated the ability to store and analyze massive data sets, but few talk about the best methods to use for “massive marketing.”
Dr. Matthew Schall,Ph.D. has been data mining since before the term was invented, sold solutions as a consultant; delivered on engagements, contributed over to companies’ bottom lines by putting together new analytic teams, increased campaign ROI 561%, all while working as a sole contributor and a manager of up to 30 scattered across 8 countries. Recently, he has sequenced “patterns to purchase” in strings of 300 URLs for 6M visitors on an eCommerce site, made an extra $37K in two months for a non-profit, and has been putting together hardware and software recommendations as the analytics lead for Catalysis, a customer engagement company
Your Customers Want to Love You – Transforming Customer Experiences With Big Data & Technology-Enabled Predictive Analytics
As the number of interaction channels have exploded, it has become harder to maintain a consistent customer experience across interaction touch-points. Only 15% of CIO’s say their companies do “very well” in maintaining a consistent user experience across all communication channels.* Since most interaction channels are siloed, and channels do not share information with each other, most customer experience breakdowns occur at the boundaries between interaction channels. Think about a service issue you may have had and the number of times you had to repeatedly provide the same information about yourself and your issue not only across interaction channels but also when transferred from one touch-point to another within the same channel. In this day and age, where customer expectations are high, companies face some high-stake risks. Not only do customers switch brands when faced with a poor customer experience (62% of US consumers have switched brands in the past year due to poor customer service and one in four cite being shuffled from rep to rep with no issue resolution as their top reason for switching brands), ** they also broadcast their bad experiences, leading to negative word-of-mouth. .
*The CIO’s Mandate: Creating Compelling Customer Interactions, Adobe
** Parature, June 18, 2013 INFOGRAPHIC: The Financial Impact of Customer Service
Niren Sirohi, Ph.D. is Vice President, Predictive Analytics at iKnowtion and responsible for leading the company’s predictive analytics practice. For more than 20 years, Dr. Sirohi has been developing and implementing strategic analytic solutions for global brands across a variety of industries including financial services, retail, consumer goods, hospitality, and telecommunications. Dr. Sirohi earned his Ph.D. in Management at Cornell’s Johnson Graduate School of Management. He earned an MBA with a major in marketing from Bombay University and an undergraduate degree in Mechanical Engineering from the Indian Institute of Technology.