spocto :: credentials

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BRIDGING GIGABYTES TO GIGASMILES

THE BIG DATA CRISIS

only 0.5%of big datais being analyzed

(According to estimates by IDC)

40 Billion(2010)

>250 Billion(2016)

PHOTOS STOREDON FACEBOOK

25%(2000)

98%(2016)

AMOUNT OFINFORMATION

STORED DIGITALLY

AMOUNT OF DATAPRODUCED IN....

2 days in 2016

All of History - 2003

$31 Billion(2013)

>114 Billion(2018)

AMOUNT SPENTON BIG DATA(estimated)

We now live in a world where datais not rare. The amount of datacampanies collect keeps growing.

They urgently need a strategy tomake sense of it all.

Confidential | Do Not Forward Without Prior Authorization spoctoTM

WELCOME TO THE ERA OF ‘SMALL DATA’

Hi

Small data yields native metrics!

spoctoTM

Confidential | Do Not Forward Without Prior Authorization

SMALL DATA CAN CAPTURE ACTIONS NOTVISIBLE TO TYPICAL ANALYTICS

Millenials Gen-X Baby Boomers

Mentioned tosomeone else

Emailed

Posted Link

Printed

Happy to sharetheir information

66%

34% 32%

66% 74%

39%

19%

10% 15%

52%

9%

5%

35%

91% 5%

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MULTI-SOURCE, BIG & SMALL DATA

Multiple-sources ofdata - may requirebig data platforms

Connection of datasources for holisticallyunderstanding attitudesand behaviors

Triangulation of multipledata sources to connectstory

Actionable insights maybe more inferentialthan exact

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COLLECT ATONLINE SCALE

UNDERSTAND ATHUMAN SCALE

spoctoTM


BRIDGING GIGABYTES TO GIGASMILES

COLLECT ATONLINE SCALE

UNDERSTAND ATHUMAN SCALE

spoctoTM


BRIDGING GIGABYTES TO GIGASMILESspoctoTM


ABOUT SPOCTOWho are we ?

A Big Data Analytics Company focused on ‘Individual Consumer Data driven

Insights’ on mass scale to significantly enhance effectiveness of business

and marketing actions. We provide unique tailored solutions to each client

as compared to offering a standard package.

What makes us unique ?

Our proprietary algorithms apply machine learning to multiple digital touch-points

of 200+ million individual persona sourced from 47+ data sources, and continually

curate them to keep it “LIVE”. Thereon, we use trademarked predictive artificial

intelligence to draw insights and provide specific recommendations. These unique

capabilities allow us to enrich persona data from public domain with

not only demographic, but also behavioral & psychographic information on a

hyper-personalized scale.spoctoTM


OUR APPROACH

UNDERSTAND APPLY ANALYZE CREATEREMEMBER

REFERENCE: BLOOM’S DIGITAL TAXONOMY

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OUR OFFERINGS

UNDERSTAND APPLY ANALYZE CREATEREMEMBERINSIGHTS ACTIONABLESPERSONACURATEORGANIZE

SPOCTOFYING THE DATATHE NEED | THE SOLUTION | THE PROCESS

INSIGHTS ACTIONABLESPERSONACURATEORGANIZE

ORGANIZE

WE PROVIDE

ORGANIZE

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Aggregate data from repositories across the organization

Normalize the data

Refine the data fields to eliminate duplicates

Define useable data to enable efficient data processing

DATA SUMMARY7500 -

7000 -

6500 -

6000 -

5500 -

5000 -

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3500 -

3000 -

2500 -

2000 -

1500 -

1000 -

500 -

0 -

100%

1,148

19%

38%

10%33%

63%HIT RATIO

Issues Faced : “Systems Silos”, “Different Formats”

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WE PROVIDE

CURATE

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CURATE

DATA ENRICHMENT

Demography Behaviour Psychography

ADDEDCLIENTAMENDINCORRECT

47+ data sources - to Evaluate, Amend, Purge, Enrich data depth

Customers constantly change preferences, 24x7 data capturing is the key

Seamlessly joining all the digital touchpoints/footprints of a consumer

Issues Faced : “Dynamic-Data Lifecycle Management”

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WE PROVIDE

PERSONA

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PERSONA

Not just Demographic but also behavior & psychographic data

500-1000 data points per customer

Service as a Software - Single View Platform

Issues Faced : “Uni-Dimension View Of Customer”

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INSIGHTS

WE PROVIDE

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INSIGHTS

Machine learning algorithms to learn and understand sharper & accurate insights

Defining segments to create insights, to learn more about your customers needs

Data becomes asset, newer insights for various functions across the organisation

INSIGHTS

Issues Faced : “Tools Ignore Behavior & Psychographic Data”

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ACTIONABLES

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RECOMMENDATIONS

ACTIONABLES

Significantly improve marketing media mix

Consumer led segmentation to identify new sources of growth

“Look alikes” to identify newer potential consumers .

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WE PROVIDE

Issues Faced : “Action Indicators only Highlight Problem Areas”

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SPOCTOLOGYTHE EDGE THAT DEFINES US

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SPOCTOLOGY - THE 4 V’STHE EDGE THAT DEFINES US

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VARIETY VELOCITY VERACITY

DATA IN MANY FORMS

Structured, Unstructured, Text,

Multimedia, Images

DATA IN MOTION

Streaming data, milliseconds to

seconds to respond

DATA IN DOUBT

Uncertainty due to data

incompleteness & latency

105

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Understanding Big Data is the key topersevering in an enviornment that has gotten so large and so multi-dimensional that it can no longer be managed by traditional mindsets, thought process or tool.

VOLUME

DATA AT REST

Terabytes to Exabytes of existing

data to process

SPOCTOLOGY - 9 CATEGORY SOURCESTHE EDGE THAT DEFINES US

DOCSXLS, PDF, CSV, Email, Word, HTML,

Plain Text, XML, JSON etc.

MEDIAImages, Videos, Audios, Flash,

Live Streams, Podcast, etc

DATA STORAGESQL, NoSQL, Hadoop, Doc

Repository, File Systems, etc

BUSINESS APPSMarketing Automation, CRM, ERP, HR, Google Docs,

Intranets, Portals, Expense Management, etc

PUBLIC WEBGovernment, Weather, Traffic, Census,

Wikipedia, IMDB, Public Finance Stock, etc

SOCIAL MEDIATwitter, LinkedIn, Facebook, RSS, YouTube, Quora,Blogs, Slideshare, Flickr, Instagram, Snapchat etc.

MACHINE LOG DATAEvent Logs, Server Data, Applications Logs, Business

Process Logs, Mobile Location, Mobile App Usage,Clickstream Data, Audit Logs, etc

SENSOR DATAFitness Devices, Car Sensors, Road Cameras,

Satellites, Processors in Vehicles, VideoGames, Cable Boxes, etc

PUBLIC ARCHIVESScanned Documents, Statements,

Forms, Paper Archives, Public Records of Customers, etc

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SPOCTOLOGY - COHESIVE ASSESSMENTTHE EDGE THAT DEFINES US

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DOCS

MEDIA

DATA STORAGE

BUSINESS APPS

PUBLIC WEBSOCIAL MEDIA

MAC

HIN

E LO

G DA

TA

SENS

OR D

ATA

PUBL

IC AR

CHIV

ES

INTELLIGENCEBY

VERACITYManaging the reliability &

predictability of inheherentyimprecise data types

LOWMEDIUMHIGH

CLUSTERS & SEGMENTATIONS

VARIETY

VELOCITY

VOLUME

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The preceding is intended to outline ourgeneral product direction. It is intendedfor information purpose only, and may notbe incorporated into any contract. It is nota commitment to deliver any material, code,or functionality, and should not be relied uponin making purchasing decisions. The development,release, and timing of any features orfunctionality described for spocto’s productsremains at the sole discretion of spocto.

WE TAKE DATA PRIVACY VERY SERIOUSLY

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THANK [email protected]

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Bridging GigabytesTo Gigasmiles......

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ANNEXURES

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COMPANY INDUSTRY

EMPLOYEES TYPE

Starbucks Coffee Food & Beverage

10,000+ Persona Analytics

PURPOSE:

Starbucks collects data on its customer’s purchasing habits in order to send

personalized ads and coupon offers to the consumer’s mobile phones. The

company also identifies trends indicating whether customers are loosing

interest in their product and directs offers specifically to those customers in

order to regenerate interest.

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COMPANY INDUSTRY

EMPLOYEES TYPE

Heineken Food & Beverage

10,000+ Customer Segmentation

PURPOSE:

Thanks to its partnership with Google and Facebook, Heineken has access to

vasts amount of data about its customers that it uses to create real-time,

personalized marketing messages. One project provides real-time content to

fans who happen to be watching a sponsored event.

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COMPANY INDUSTRY

EMPLOYEES TYPE

Nestle Food & Beverage


PURPOSE:

Customer complaints and PR crises have become more difficult to handle,

thanks to social media. To better keep track of customer sentiments and

what is being said about the company online., Nestle created a 24/7

monitoring centre to listen to all of the conversations about the company

and its products on social media. The company will actively engage with those

that post about them online in order to mitigate damage and build customer

loyalty.

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COMPANY INDUSTRY

EMPLOYEES TYPE

Kotak Mahindra Bank Finance - ARC

10,000+ Fraud Detection

PURPOSE:

Kotak Mahindra bank partner with spocto to detect the frauds, customers

intention of defaulting, and analysing the customers stature of repayment.

In case of any fraud, the ARC team receives his demographic data to track

the customer and take due legal actions.

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COMPANY INDUSTRY

EMPLOYEES TYPE

Lodha Group Real Estate

1001-5000 Customer Segmentation

PURPOSE:

Lodha combines psychographic, behavioral, deographic and internal data of

its walk-in customers, and then create segments. This enables its various

functions i.e., marketing, pre-sales & sales to do very targeted communication.

Lodha also uses this data to give priorities to all the segments, in regards with

conversions.

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COMPANY INDUSTRY

EMPLOYEES TYPE

Spotify Entertainment

1,000-5,000 Customer Segmentation &Behavioral Analytics

PURPOSE:

Spotify uses data from user profiles and user’s playlists, and historical data

on music played to provide recommendations for each user. By combining

data from millions of users, Spotify is able to make recommendations even if

a particular user doesn’t have an extensive history with the site..

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COMPANY INDUSTRY

EMPLOYEES TYPE

Celcom Axiata Berhad Communication

1000-5000 Optimize Funnel Conversion

PURPOSE:

Celcom Axiata Berhad adopted a big data solution in order to improve customer

retention and boost its market share by improving the marketing campaign

process. The company used real-time data to create a personalized campaign

for each customer based on which products or offers the customer would most

want or need.

spoctoTM


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COMPANY INDUSTRY

EMPLOYEES TYPE

MasterCard Finance


PURPOSE:

With 1.8 billion customers, MasterCard is in the unique position of being able to

analyze the behavior of customers in not only their stores, but also thousands

of other retailers. The company teamed up with few big data and analytical

partners to collect and analyze data on shopper’s behavior, and provide the

insights it finds to other retailers in benchmarking reports.

spoctoTM


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COMPANY INDUSTRY

EMPLOYEES TYPE

Time Warner Cable Entertainment

1,000-5000 Persona Analytics &Customer Segmentation

PURPOSE:

With services like Hulu and Netflix competing for viewer’s attention, Time

Warner collects data on how frequently customers tune in, the effect of

bandwidth on consumer behavior, customer engagement and peak usage

times in order to improve their service and increase profits. The company

also segments its customers for advertisers by correlating viewing habits with

public data - such as voter registration information - in order to launch highly

targeted campaigns to specific locations or demographics.spoctoTM


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COMPANY INDUSTRY

EMPLOYEES TYPE

John Deere Farming

10,000+ Industry Specific

PURPOSE:

Sensors placed on John Deere equipment, along with historical

and real-time data on soil conditions, the weather and corp

features are all used together to help farmers determine where

and when to plant to get the highest yield, and how to boost the

efficiency of their work to reduce fuel cost.

spoctoTM


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COMPANY INDUSTRY

EMPLOYEES TYPE

Kayak Travel

200-500 Industry Specific

PURPOSE:

Kayak uses big data analytics to create a predictive model that tells

users if the price for a particular flight will go up or down within the

next week. The system uses one billion search queries to find the

cheapest flights, as well as popular destinations and busiest airports.

The algorithm is constantly improved by tracking the flights to see if

its predictions are correct.

spoctoTM


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COMPANY INDUSTRY

EMPLOYEES TYPE

Zions Bank Finance

1,000-5,000 Fraud Detection

PURPOSE:

Zion Bank uses data analytics to detect anomalies across channels that

indicate potential fraud. The fraud team receives data from 140 sources,

some in real-time, to monitor activity, such as if a customer makes a

mobile banking transaction at the same time as a branch or an ATM

transaction.

spoctoTM


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COMPANY INDUSTRY

EMPLOYEES TYPE

Walmart Retail

10,000+ Customer Segmentation

PURPOSE:

Walmart combines public data, social data and internal data to monitor what

customers and friends of customers are saying about a particular product

online. The retailer uses this data to send targeted messages about the product,

and to share discount offers. Walmart also uses data analysis to identify the

context of an online message, such as if a reference to ‘Salt’ is about the

movie or the condiment.

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Data & Analytics