Centre for Marketing in Emerging Economies Presents Workshop In Association with MRSI Presents Workshop in Noida & Mumbai Topic ‐Leveraging the Power of Data Driven Marketing for Achieving Marketing Excellence Date – 23rd to 25th April’15 in IIML, Noida Campus & 15th and 16th in May’15 in Sea Princess Hotel, Mumbai Today, We are pleased to announce that Centre of marketing in emerging economies (CMEE) is taking a giant leap forward by starting a new workshops on ‘Leveraging the Power of Data Driven Marketing for Achieving Marketing Excellence’. Sandeep Saxena, Director General MRSI & Prof S B Dash, IIM Lucknow inaugurated workshop & welcomed participants. About CMEE The Centre for Marketing in Emerging Economies (CMEE) at IIM Lucknow aims to be a globally‐recognized center of excellence for pursuing original research and imparting quality education in the area of marketing. Apart from conducting advanced research and running continuous education programs, the center also acts as a platform for academicians and practitioners in selected emerging geographies to collaborate with each other effectively. The center is in active collaboration with premier business schools in major emerging economies, namely Brazil, Russia, China, South Africa, Indonesia and Turkey. New research agenda of CMEE is to focus on bottom of pyramid consumer behavior & health care. About MRSI MRSI strives to uphold the highest standards of professionalism in the industry and showcase the developments and innovations taking place in this field in India and to help develop common tools for the industry. It is running two vital programmes 1. Researcher’s education‐ Which includes (a) Webinar retail, mobile marketing. (b) Wednesday twitter marketing, Skills building (c) building repository of all papers presented for connecting dots‐ bank of knowledge. 2. Quality data generation which includes showing interview tech, recording interview videos 1st session ‐ Prof S B Dash Emerging Trends that favor Data Driven Marketing This session started with tools & techniques used by marketing practitioners, to get consumer insights since 2001. Forces behind data driven marketing is economics of consumers & budgeting, advancing technology due to marketing automation, optimization & growing business analytics. Intensifying competition is making it imperative for companies to get into data driven marketing. Prof explained benefits of data driven marketing by using one recent survey. Key emerging trends in Data driven marketing are 1. Marketing and Sales Co‐own the Revenue production 2. First Touch, Last Touch and Everything In Between now Matter. 3. Big Data is Becoming Bigger in Marketing. 4 The Emergence of the Marketing Technologist Will Come to Full Glory 5. Marketing is taking Big Steps toward Customer Intelligence Professor also used one marketing software to make participant familiar with recent development in data analytics & to explain, how they can use it to get richer information? Conjoint analysis, factor analysis, cluster analysis & preference mapping discussed with the participants with the help of case studies. 2nd session ‐ Mr Titir Pal data analytics Current practices in big Big data analytics evolved to cater to changed data environment. Companies are doing same thing even today i.e. creating & communicating value, But the change in variety, volume & velocity of data has changed the mathematics of attracting new customers & retaining older one. More data does not mean you have new problem, it means you have more insights of consumer. Which can be used to design new products, preparing communication content & provide quick service recoveries. Big data analytics is a movement from Causation to correlation. Fallowing four cases are example of clever data analytics to get operational efficiency, new revenue modes etc. Case1 Hotel loyalty programmer‐decision engineering in hotel industry to make travels more holistic Case2 FMCG retail‐ Retailer’s segmentation to make supply chain more organic Case 3 ‐ Telecom‐ maximizing potential of geospatial data & monetizing this data i.e. How to suggest where to set up store? Case 4 ‐ Mining machine‐ internet of things (geospatial data for traffic management) ‐predictive maintenance of trucks saved huge maintenance cost. Session 3 Mr Vinit Goenka Listening consumers through social network Listening is a skill that we can all benefit from improving. By becoming a better listener, you will improve your productivity, as well as your ability to influence, persuade and negotiate. What's more, you'll avoid conflict and misunderstandings. All of these are necessary for workplace success!BJP listened to the consumers during elections & used those insights to plan their political campaigns. BJP also segmented whole India into 144 segments based in gender, age, income, social media usage etc. Session 4 Mr Arun V. Chearie Big Data & Big Data Analytics in Customer Value Management: Strategies and Execution Analytics is extracting information from data. Big data is large variety of data accumulating with great velocity. Among new industries, automobile companies are using sensors in cars to gather data of drivers i.e. driving style, speed etc. For big data two things are important 1. Analytics 2. Deriving information from data In big data world essentially the way of reporting has been changed, now it’ more than simple reporting. Ethnographic studies are now taking place inside houses to get instant data, ethnographer is now watching actual data more closely. A new age of real‐time insight driven customer centric decisioning in marketing is coming out. Retargeting is new phenomena where online companies track a customer purchase for the products, it does not have. Retail stores are using sensors to track buyer’s eye movement, product search. The four p of marketing are gradually being retired & few new A’s are taking place i.e. anytime, anyplace etc. Session 5 Prof Moutusy Maity Gaining Consumer Insights through Social Network Analysis Everything is connected: people, information, events and places, all the more so with the advent of online social media. A practical way of making sense of the tangle of connections is to analyze them as networks. SNA provides both a visual and a mathematical analysis of human relationships. To understand networks and their participants, we evaluate the location of actors in the network. Measuring the network location is finding the centrality of a node. These measures give us insight into the various roles and groupings in a network ‐‐ who are the connectors, mavens, leaders, bridges, isolates, where are the clusters and who is in them, who is in the core of the network, and who is on the periphery. SNA provides important strategic information. Seed marketing can be more effective by using SNA. Session 6 ‐Dr Ranjit Nair Competing in the Age of the Customers: Social Media Intelligence to the Rescue Large bundle of social media tools are available. To know which tool is to use is very important. Social media intelligence in action is possible with listening, engaging & measuring. Now real time data tracking is possible. Through sentiment analysis, one can understand the real mood of customer. Historical information tracking & decoding market trends are also possible. MTV Coke studio when it failed to garner good TRPs, It took help of social media analytics tools to get insight episode by episode. Integrating data driven analytics helped Coke studio to improve its content & quality. Day2 ‐Session1 ‐Prof. S. Venkat Real Time Consumers and Supply Chain Analytics Akshya Patra brought the best thinking in manufacturing, supply chain, innovation and logistics management to create a central kitchen model whereby food is centrally cooked and delivered by truck to local schools. In addition, it also constantly innovates – including using data analytics, cooking using clean energies and constantly improving ingredients to have healthier food – while keeping the cost the same. The goal for the Supply chain analytics category is to link together all the different statistical, mathematical and optimization methods that would be beneficial to any supply chain professional. Similarly, Forecasting can be used in supply chain management to ensure that the right product is at the right place at the right time. Accurate forecasting will help retailers reduce excess inventory and thus increase profit margin SESSION 2 ‐Mr Himanshu Chopra Uses of Data to mitigate fraudulent activities and maintain health of online platform Digital India is the new anthem. In 2015, Internet penetration in India is 16% & smartphone penetration is 20%, It shows emerging potential in online domain. Analytics value chain starts from description of what happened, diagnosis, prediction & finally prescription. Analytics combined with digital surveillance is new tool for price discrimination over online platform. E‐commerce is facing various types of risks i.e. payment frauds, high product return, B2B transaction, damaged product, empty parcel etc. To mitigate risk, e‐commerce players have taken several measures like seller rating (based on delayed delivery, empty parcel, damaged product, package lost). Sellers rating has solved 20‐30 % problems. Seller evaluation on multiple parameter i.e. complaint HOSTORY, SALES data, subjectivity in raising complain decides their future commercial relations with the e‐commerce companies Session 3 Banking on Analytics‐ Mr Anup Kumar Sinha Middle class is growing rapidly & willing to do things differently. Appropriate provisioning of technology purchase is need of the hour. Definition of data is also changing now. The Banking anytime anywhere resulted into near real time convergence of channel, single view of customs (means 360 degree information), mobility: banking on the move. Some New technology trends like Network connectivity, NFC, RFID, beacons, big data & in memory, machine data has changed the banking services delivery. In coming future, Physical papers work needs to go away. GPS based Geocoding i.e. coded pin codes will strategies future course of actions like, Determine growth potential of new branch location, gauge market share, identifying sources of lagging & priorities growth potential. Analytics integration with banking domain requires domain expert, analytics expertise, technology expertise. Heat maps are also now used frequently by bankers Session 4‐Mr Pratul Chandra Changing Paradigm in Analytics and how SAP Analytics addresses the same Analytical needs and the consequences in IT architecture is now visible in tangible form. High variety if information coming at great speed. Different approach & tools are required to utilize its potential. Real time data platform integration & real time analytics will provide the competitive edge. An entity, which is willing to make break into analytics should 1.Democratize predictive analytics‐ productive predictive solution for all. 2. Real‐time predictive analytics for big data‐anticipate risks & opportunities in real time 3. Embed predictive analytics‐ incorporate Sap predictive analytics tool 4.incorporate predictive results into business processes. Sap HANA will address above issues. Day 3 ‐ Prof Bharat Bhaskar Recommendation system & collaborative filtering People leave trails during net surfing, online domain players use cues to reduce cognitive effort of people & generate more sales .Online surfing provide inputs in click through phase, basket placement phase & basket to purchase phase. Among two product categories different tools are used to generate consumer insights. For example 1. LIP (do‐feel‐think)= collaborative filtering + data mining 2. HIP (think‐fee‐do)= automobile recommender different set of tools used by companies Rank of a web page depends on the rank of the webpages pointing to it, companies are using above insights to improve their page rank. Content filtering is also one of the tools to filter content & get more specific insights. Retail stores are using Association rule mining to sale more product & making shopping experience more convenient TS Mohan Krishan ‐ Using Big‐ness data Using operational data with GIS map secondary data A GIS cannot function without data, and that generally the more data there is then the greater versatility that a GIS will have and the greater will be the potential functionality of any GIS. With regard to the usage of GIS generally, the situation has now been arrived at whereby considerations of data are more important than issues concerning hardware or software. GIS related data can be used Use case 1: basic analytical tools Sales data can be dynamically managed to locate shop and plan routs to reach target groups. It also enable predictive model to see demand & sales. Use Case 2: Mobile sales long hours is negatively correlated to sales effectiveness, women make better sales person, significant improvement in productivity by sifting sales man closer to their home area. Rural opportunity is even bigger‐ Bt cotton companies concerned of farmers suicide so they sell GM cotton seed to farmers who have soil depth data , not primarily rain fed area & they are also Empowering decision makers to gain important insight. Session 3 Mr Deepak Goel – CEO & Mr Manas Kar –Practice Lead Analytical Engines Drizzlin AND juxt‐ Uses and Application of Social Media Information for Strategic Marketing Decision Availability of vast quantities of social‐media data points has spawned an array of new analytic methods that can structure and derive insight from complex information. Social intelligence will sharpen strategic insights, and leaders must be immersed in the new information currents. Few social intelligence tools are‐ Social media platform Twitter Measure and boost user impact on Twitter. Data aggregators do analytics tool Data aggregation, which is a type of data and information mining process where data is searched, gathered and presented. Twitter streaming API, ‐ The Streaming APIs give developers low latency access to Twitter's global stream of Tweet data. Sentiment analysis library is available‐ create your library & classifiers. Session 4‐Mr Shailesh Kumar From Data to Decisions: Completing the Analytic Cycle Google wants to create intelligent machine. Intelligence is ability to generalize. From data to decision, data‐insights‐features‐
domain knowledge Date your data‐ Your data needs will depend very much on your offering but it’s important to identify what information you can easily obtain and use. That’s the key here. Before you go on a mass data collection campaign, decide what you need and more importantly what you can use to make your communications more targeted before. The key is to start small and go back to the data’s roots: the customer. After all it’s about them, you’re doing it for them so it’s important you get to know each individual customer first before we attempt to build our data monopolies. Session 5 – Dr Lipika Dey Mining Consumers Generated Text for Marketing Insights Prosumer is new phenomena, consumer are now co‐producing with companies. . Consumer thoughts, beliefs, wishes, experiences, interactions are important to understand new trends. Consumer footprints analysis can improve brand image, increase retention, helps in new product development & get competitor intelligence. Sentiment viz‐ Recent tweets that contain your keyword are pulled from Twitter and visualized in the Sentiment tab as circles Social media monitoring has become a primary form of business intelligence, used to identify, predict, and respond to consumer behavior. Listening to what your customers, competitors, critics, and supporters are saying about you is key to getting great results from your social media campaigns. There are countless tools out there, offering many ways to analyze, measure, display, and create reports about your engagement efforts. Gather own your data through dedicated crawlers/ use site‐provided API. Clean it then Store & Process data using NLP toolkit, Tokenize‐break into words & finally use data analytics tools Prof BK Mohanty Understanding Consumers Search Behavior e‐ commerce platform in Fuzzy Environment Latent connectivity in human decision making In any business, particularly through the Internet, a customer normally develops in his/her mind some sort of ambiguity, given the choice of similar alternative products. The ambiguity is mainly due to two reasons. Firstly, how to make a final product choice to purchase, and, secondly, on what basis the other products will be rejected. In order to answer the above questions, the customer may like to classify the products in different preference levels, preferably through some numerical strength of preference. Based on the customer's fuzzy choice of the product attributes, products are classified into hierarchical preference levels. This classification is an aid to the customer in making a final choice of the product. Thus, a buyer can select a product being fully aware of the hierarchical preference order. The hierarchical product classification acts as a decision aid to the customer, in the sense that the customer himself/herself will come to know the information about where his/her chosen product stands in the product profile. This will also help him/her to upgrade his/her product choice to a different level should the situation so demands. Prof. Rajiv Srivastava‐ Director, IIML, Noida Campus. He thanked all for creating such a wonderful and successful workshop! He assured CMEE will be conducting these kind of workshops in future too where the industry, research academicians, practioners benefitted to a great extent. are