Nasscom nirmalya kumar 2014


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  • Connect to internet – as everyone has a device that is with them to connect to internetConnect to cloud – so you have access to your data. Dumb to be logging around laptopsConnect to others – social media and if a regime in Egypt can be overthrown in 17 days using Facebook & Twitter, imagine how powerful it can be?Connect to things – as internet embeds products increasingly and you see traditional companies like GE, Schnieder, Bosch all making acquisitions in the technology space to understand the digital smoke signals that help develop early warning systems for budding problems in their productsAlways on person – can we inject, implant, ingest you with a sim card. Google is working on injestible device that will be foolproof identity token for a personChandra and I were on a plane and he was showing me an iPhone app that measured how stressed you are – wouldn’t it better if we had injestibleor implanted devices where remote measurement, monitoring, and an early warning system was in place without requiring us to manually measure our stress levels.
  • What we always wanted to know about our consumers Who are you – demographics, psychographics, but always problem of identification – how to know who you are – that is where facial recognition comes in. Imagine airport securityWho are your friends – you trust your friends – Google versus FB on searchWhere are you – Foursquare and mobile helps us know - promotional offers when you are shopping are much more effective than when received at home. What products/services – pinterest allows consumers to tag the products and services they wish to buy This information exhaust that is coming from consumers from multiple sources when connected to individual consumer is what makes Big Data so fascinating for marketers
  • Ngram from Google books to show often a word appears in English books mid 1950s Data overtakes oil!With data, can marketers better serve customers expressed, articulated, known needs by predicting what you want, what is your next move, what is your next purchase to perhaps even understanding your latent unarticulated needs – things you never dreamed of you wantedThis is like predictive typing that learns your vocabulary and predicts the next wordArmed with these insights, can we influence your behaviour and make our marketing more relevant, ore differentiated, and more credible
  • Too much of attention of big data is currently on targeting ads, offers, and selling more. For example, the collaborative filtering of Amazon that customizes the landing page and the recommendations you see. Or Tesco using it Club card to improve the redemption of its coupons – generally coupon redemption is less than 1% , success is usually 1%, but Tesco can achieve 13-14% via targeting coupons to more relevant cosnumersUnfortunately, too little attention of big data on companies is on improving the brand experience and customer service – I.e., the value proposition and using the information to improve the differentiation versus competitors. Eg., Tesco Price Munch program where a consumer goes into a Tesco store and checks out their basket with the club card. The program compares the prices with other stores and either send a message saying congratulations for shopping at Tesco and saving money or if more expensive issues a voucher for the difference. Helps enhance the Tesco VP and differentiation.On value network is where the challenge for companies to transform is perhaps the largest. This seems obvious for digital products like classifieds which have gone all digital, music, books, movies, newspapers which are fast following. USA last year, more time consuming digital media than TV and more devices overtook computers as primary way to access internet. Maturation here too as digital sales fell for the first time last year as streaming services like Spotify became more popular. The always connected consumer does not need to store locally music.
  • Volume 90% of all data has been created in the past 2 yearsMyth is that more granular the data, the better and big data is good data and bigger data is better data.But reality is that big data is like a sand grains which can create a sandstorm. It can blind you, it can disorient you. Bedouin saying is that 6 minutes of a snowstorm is enough to make a man mad Data has no value, only cost until you marry it with analytics extract information. Key decisions on what to keep and what to throw outVarietymyth it is big data – in reality its lots of small data stitched together.How many different sources can we stich together – all the digital exhaust that a consumer creates – do we let it let it escape in the atmosphere or capture it to make better decisions for the customerintegration across the different channels customers experience with the brandVelocity updated as close to real time as possiblemyth real time is better, but lots of noise in the system may mean more confusion and quick response when it mat require time to sit back and reflect sometimes. Most things in life that are important and worthwhile are difficult to do and big data is no exception
  • StorageSecurity – Capabilities – finding the quants and the creative and getting the capabilities that understand the analytics from a statistician perspective, ask the right question from managers perspective, communicate the results from an organization’s perspectiveTechnical knowledge combined with intuitionGoogle – our products are not used by engineers even though they are built by engineersShall we talk about the elephant in the room – privacy
  • Nasscom nirmalya kumar 2014

    1. 1. Serving the Connected Customer Nirmalya Kumar Member-Group Executive Council, Tata Sons Professor, London Business School NASSCOM 2014
    2. 2. Knowledge of the customer helps make marketing more effective Who are you? Who are your friends? What are your interests? Where are you? What products/services are right for you? Facial recognition Facebook Twitter Foursquare, Mobile Pinterest 2
    3. 3. Data is the new Oil 3
    4. 4. Using Connectivity and Big Data to enhance marketing and experience • Valued Customer – who to serve? → Relevance • Value Proposition – What to offer?→ Differentiation • Value Network – How to deliver? → Credibility 4
    5. 5. 3 V’s of Big Data Characteristic Capability Volume Analytics Variety Integration Velocity Speed 5
    6. 6. Friends, not editors, shape media consumption Broadcast Search Editor Social Networking Editor YOU YOU YOU Friends Encyclopedia Newspaper TV channels Bookstores Google Yahoo/AOL YouTube Amazon LinkedIn Facebook Twitter My Space Copyright © Nirmalya Kumar
    7. 7. decides what you watch You decide what you watch Your friends decide what you watch Copyright © Nirmalya Kumar
    8. 8. The Connected Customer throws up Challenges and Opportunities • Where is my data stored? • How secure is my data? • Who has access to my data? • How is my data being used? Storage Security Privacy Capabilities 8
    9. 9. Traditional vs. non-traditional marketing • • • • • • • Pretest & validate Known costs Targeted Known metrics Formulaic 3 hits model Controlled • • • • • • • Launch & learn Unknown (lower) costs Self selected Difficult to evaluate Creative & resourceful Self-reinforcing networks Uncontrolled Copyright © Nirmalya Kumar