centre for marketing in emerging economies presents...
TRANSCRIPT
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 Wednesday twitter marketing, retail, mobile marketing. (b) 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 Current practices in big data analytics 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 analytics tool
Measure and boost user impact on Twitter.
Data aggregators do 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, academicians,
research practioners are
benefitted to a great extent.