MARKETING INTELLIGENCE

Transcription

1 MARKETING INTELLIGENCE Professor: SONIA CASADO SUAREZ Corporate Experience Chief Data & Analytics Officer, Prisa Group (since June of 2016) Managing Director in Big Data & Analytics in Spain & Portugal. Accenture Digital (Dec 2015 May 2016) Senior Manager in Big Data & Analytics. Accenture Digital (April 2012 Nov 2015) Managing Director in Business Analytics. Neometrics (June 2005 March 2012) Consultant in Risk & Finance Analytics. Ernst & Young (March 2003 May 2005) Academic Background Degree in Business Administration, Complutense University, Madrid (1999) Master in Finance, CUNEF, Madrid (2002) Program in Digital Advertising and Marketing on the web, ESIC, Madrid (2011) Published by IE Publishing Department. Last revised, January

2 MATERIALS All materials required to support the course would be deliver in the classroom or referred before the class when previous preparation would be needed. Every session will contain a specific set of resources. Depending on the session content, materials suggested could include different formats like videos, articles, papers, book chapters, professor material, real use cases, dataset to run analysis, etc. METHODOLOGY The methodology of the course will include the presentation of the topics and concepts linked to each topic, and in some cases references to additional material to be read in advance to the sessions. During the session, discussions will be addressed as a part of the learning process. Besides class work, a team project will be developed during the course, and also an individual project will be requested. LEARNING OBJECTIVES Motivation: Marketing intelligence and customer relationship management have been one of the more popular areas for applying analytical techniques over the last descades. Although it could be expected to be a mature discipline, challenges of the digital disruption bring new opportunities to perform better interactions in near real time with customers and achieve higher success rates. Focus: Marketing intelligence and customer relationship management are an extensive space within a lot of subdomains. The purpose of the program is to review the foundations of marketing intelligence getting a global overview of potential data scientist contributions to optimize marketing activity in terms of effectiveness and uplifts. The course will pay attention to the moments of truth at client interactions by providing a customized experience and meaningful answer for each individual. However, it doesn t pretend to go through other topics, i.e., product and price configuration when defining a marketing plan, virtual assistance for customer service, boots for content generation, real time biding for advertising inventory, etc. Objectives: Given that several businesses require a customer centric approach to run successfully, after this course as a data scientist collaborating in marketing areas, you should be able, at least, to: 1. Gather the right data to get a clear picture of client interest and needs 2. Estimate the interactions with higher likelihood to develop client engagement 3. Support marketing activities for specific goals along the customer life cycle 4. Contribute to budget optimization 5. Activate an omnichannel conversation with your clients 2

3 PROGRAM SESSION 1 Introduction: Marketing intelligence Communication channels: ATL, BTL, social Audience Vs Client Leveraging analytics for customer interactions Description of the team project to deliver at the last session Recommended readings: Davenport, T. H., & Harris, J. G. (2007). Competing on analytics : The new science of winning. Boston: Harvard Buss School. Clark, S. D. (2010). Marketing metrics: the definitive guide to measuring marketing performance. Choice, 48(1), 147. SESSION 2 Marketing Plan Media Plan addressed to physical and digital touchpoints Campaign definition: goal, product, time, place, price Target Recommended reading: Scott, D. M. (2010). The new rules of marketing and PR : How to use social media, blogs, news releases, online video, & viral marketing to reach buyers directly (2nd ed.). Hoboken, N.J.: John Wiley &. SESSION 3 Customer Knowledge (I/II) Customer understanding: demographics, social, products, interest, intention, behaviour, etc SESSION 4 Customer Knowledge (II/II) Where can we collect the data? Data sources integration Customer profiling and qualification 3

4 SESSION 5 Customer Database and connections Data Lake Data Management Platform SESSION 6 Customer lifecycle management (I/III) Anonymous or unqualified Lead Registration Acquisition Recommended reading: Inbound Marketing: get found using google, social media, and blogs (new rules social media series). Brian Halligan / Dharmseh Shah SESSION 7 Customer lifecycle management (II/III) Engagement Cross selling Up selling SESSION 8 Customer lifecycle management (III/III) Retention Reactivation Recovery SESSION 9 Life Time Value Satisfaction, Net Promote Score Social value versus individual value Share of Wallet Net present value Vs Potential 4

5 SESSION 10 Campaign and Client Prioritization Drivers for making decisions: propensity and economic value Omni channel: consistent user experience Campaign optimization according business constrains SESSION 11 Campaign activation. Measuring campaign performance Activation: Push and Pull actions Batch decisions or near real time decisions to launch communications Performance A/B testing Control group Campaign impact: success metrics Recommended reading: Real time marketing. David Meerman Scott SESSION 12 Group presentations EVALUATION METHOD Criteria Score % Class Participation 20% Team Project 40% Individual Project 40% CLASS PARTICIPATION Active student participation in class is essential to the learning process and to the success of the class. Please note that you will be evaluated based on the quality and quantity of your interactions. Quality participation contributes to collective learning and it might require preparing the session in advance. Because most learning process is done during the sessions, attendance is required. TEAM PROJECT All students will be assigned to a group to elaborate an approach for a specific use case that should be presented at the last session of the course. Further information about the case would be provided at the beginning of the course INDIVIDUAL PROJECT During the course, each student will have to deliver an individual exercise. The purpose of these 5

6 individual exercises is applying technical learnings to marketing discipline. 6