P K Mallik

New TechnologiesPrinciples, Types, Views, Components, Design

P K Mallik

Technology Trends• Big Data• Social networks• Publicly available information• Large amounts of unstructured data

• Mobile Apps• Depth rather than coverage

• Internet of Things

P K Mallik

Big Data• Structured to Unstructured• Centralised to Distributed• Signal to Noise• Data Virtualisation

P K Mallik

Classification Algorithms

• Define Key attributes on which to classify

• Create Training Set from earlier classifications (manual or legacy)

• Run on new data• Compare attributes with training set• Make corrections• Re-Run

• Classify results based on probability• Send results for analysis

• Customer profiling• Basket Analysis• New location selection• Product aggregation

Retail

• Census Analysis • Categorization for

commercial offeringGovernment

• Preventive Medication• DemographicsHealthcare

• Product RecommendationInsurance

ClassifyRun on new data

Define Training

Set

Identify Key

attributesAnalyse

P K Mallik

Segmentation

• Get data points• Private (e.g. loyalty program)• Public (government and social media)

• Perform k-Means clustering• On defined attributes• 2 to n dimensions

• Interpret clusters• Buying behaviour

• Perform analysis• Offers• Campaigns

• TargetingRetail

• Policy formulation for benefits

Government

• Identifying travel behaviour for different segments

• Prospect DemographicsTravel

• Price ComparisonsInsurance

Interpret clusters

Perform K-means

clustering

Get data points

Analyse

P K Mallik

Sentiment Analysis

• Create List• Polarity (+ve or –ve)• Emotion (joy, anger, sadness etc.)

• Collect Text• Apply keyword based classification

algorithm• Create word clouds• Analyse

• Plot graphs• Create profiles• Identify trends

• Customer feedbackRetail

• Impact of policies• Public view of

proposalsGovernment

• Trends• Impact of eventsTravel

• Customer Feedback• Impact of eventsInsurance

Create word

clouds

Apply classifica

tion algorithm

Collect Text

Create list Analyse

P K Mallik

Competitive Analysis

• Competition is identified manually• Identify the Product SKU’s for

which you want the analysis• Crawl the web to collect

information from competitive sites• Tabulate price or ratings

information• Send data for analysis (trends,

market share etc.)

• Price AnalyticsRetail

• Cross Country Benchmarking

Government

• Price AnalyticsTravel

Tabulate Informa

tion

Crawl the Web

Define Product

Identify Competition

Analyse

P K Mallik

Text Analysis

• Get dictionary• Key value pairing

• Read Text• Any document • Website• Plain text

• Extract Concepts• Apply rules• Match words

• Convert to structured data• Send for analysis

• Product Trend AnalysisRetail

• Medical UnderwritingInsuranc

e

• Travel Trend AnalysisTravel

Get structure

d data

Extract conceptsRead text

Get dictionar

yAnalyse

P K Mallik

Data Enrichment

• Identify Data Sources• Get data for targeted

group• Augment existing

database

• Customer single view• Customised services

and offers• Deep dive analysis

Retail

• Enhance census data• Impact of policies • Affected segments for

proposed policies

Government

• Auto complete forms• Targeted updatesInsurance

Augment existing

database

Get data for

targeted group

Identify Data

SourcesUtilise

P K Mallik

User Experience• User Experience• Social Media Vs Portals• Push instead of Pull• Engagement Vs Throughput• Vanishing Keyboard

P K Mallik

Social Vs Portals• Interaction to Collaboration• Transaction to Knowledge • Status to Events• User Single View to 360 degree view• User desktop• Community driven App space

P K Mallik

Push instead of pull• AI driven notifications• Most suitable device

P K Mallik

Engagement Vs Throughput• Stickiness to Gamification• Peripheral or secondary use• Reveal more information• Usage analysis

• Cross Sell/Upsell to Lifetime Value• From selling process to participating in buying journey

P K Mallik

Vanishing Keyboards• Touch increasingly becoming default• Voice gaining popularity• Thought control

P K Mallik

Internet of Things• Connected devices• Wearables• Cars• Homes• Cities• Industrials

• Reduction of human intervention• Fog Computing Architecture• Most data will be noisy and latency sensitive• Too expensive to be carried back to the central servers or cloud

P K Mallik

Thank You