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Welcome to Facts n DataTM - the specialized Marketing and Customer Analytics Company

We Are

Founded by professionals with 18-30 years of hands-on Research & Advanced Analytics experience in leadership positions in leading MNCs,

Facts n Data has pioneered over a dozen advanced Analytics algorithms to solve complex Marketing issues.

We are the Data Scientists cum Technologists for the CMO/ CEO community and help them by synthesizing facts with relevant data to provide scientific analysis and expert interpretation. We are tool and technique agnostic and our space is area of operation is depicted below:


Our Name

Our name is derived from our philosophy.

We strongly believe that analysis of data without the context (facts), and analysis of Facts without Data often provide an incomplete picture. Hence, assessment of the complete picture necessitates a scientific analysis of data in the context of facts.

Keeping the "True" business objective at the core, in the context of Facts and Data, a Scientific Analysis using techniques across subject domains, facilitated by appropriate Tools should be done. In that sense we believe that the Technique used could belong to any or multiple domains such as Mathematics, Statistics, Econometrics, Modelling, Natural Language Processing (NLP), Text Analytics, Text Mining, Data Mining, Simulation, Simulation Response Modelling, to name a few. Also that Tools are just facilitators all Tools have certain strengths and weaknesses. As such, out experience suggests that none of the Tools available is the "Ultimate" tool, and some algorithms in one tool are more efficient than those on another. Keeping this in view, Facts n Data is a Tool Agnostic Consulting Company.Our consultants use a combination of :

  • Family of Tools: SAS Base, SAS Enterprise Guide, SAS Enterprise Miner, SAS Text Miner
  • Family of Tools: SPSS Statistics, SPSS Modeler, SPSS Amos, SPSS Sample Power, SPSS Text Modeler
  • Open Source Tools: , others:




Facts n DataTM is driven by a sound Analytics philosophy, core principles of which are:

  1. Big Data implementation has no meaning unless complimented by scientific Analytics support
  2. Any analysis without keeping context and business objective in mind does not give desired benefits
  3. The boundary between Business Intelligence and Data Analytics is very thin and porous
  4. To obtain desired business objective, in the context of facts, two dimensions of data, namely, Type (Qualitative/ Quantitative) and Nature (Internal/ External) must be considered and all possible relevant data must be leveraged - data analytics is not only mathematical/ statistical analysis of structured data alone
  5. Information paucity is as bad as Information overload for an enterprise
  6. Data Analytics is NOT just Descriptive, Prescriptive and Predictive - the true potential of it lies in being able to "Make Future Happen"
  7. True Data Analytics objectives can not be reached by relying only on one stream of knowledge such as Statistics or Mathematics - its true potential lies in leveraging on a combination of streams such as Statistics, Mathematics, Natural Language Processing, Econometrics, Psychometrics, Operations Research, to name a few
  8. At times, extremely complex problems may have very simple answers and extremely complex problems may have very complex solutions - Analyst should be a slave of Business Objective, not the technique involved
  9. Analysis of unstructured data, such as Text Data, Social Media data, Customer emails, Call Centre transcripts often hold many more valuable insights than structured data



Ravi Sangal (Prof.)

Ravi is an engineering graduate from BITS, Pilani and an MTech (Management and Systems) from IIT , Delhi. He was President of IDC, a global marketing research and marketing intelligence organization, for over fifteen years. As its head, he built the organization almost from scratch and demonstrated market equity, growth and consistent profitability. Subsequently, he was President of CyberMedia Research and President (Corporate) for Cyber Media India Ltd responsible for new investments. He has more than thirty years of work experience. Due to his extensive industry knowledge and understanding, he was appointed National Consultant by UN for technology assignments. He also served as Professor and Director in one of the leading B-schools of Delhi associated with its Research and Business Analytics Program.He has been awarded a Statement of Accomplishment by JOHNS HOPKINS UNIVERSITY, US for Data Analysis. He is also a visiting faculty at many Tier I B-Schools. He has thorough knowledge of various data analytics tools, statistics, predictive modeling and several multivariate techniques with hands-on expertise on EG, Rattle and Tableau.

Mr Sangal has often been quoted in print and electronic media for his accurate observations. He has been on the cover of several leading magazines and newspapers.He leads StatLabsTM, our Statistical & Data Sciences innovation laboratory

V Shekhar Avasthy

Shekhar holds two Masters Degrees one each in Marketing Management and Pure Physics. He has a total of 20 years of experience in Advanced Analytics and Marketing Research, chunk of which has been with leading MNCs in leadership positions. His previous engagements include Program Manager for Software & Services Research as well as Head of Telecom & Internet Research at IDC India, Director of Analytics Center of Excellence at CPA Global, National Consultant (India) to United Nations International development Organization and Head of Research Operations for Cyber Media Research.

He has been extensively quoted in print and electronic media on Telecom, Software Services, and Advertising & Media industries.

He has consulted for Who`s Who of IT, ITES, Telecom, Retail, Media, and Ad Agencies on issues pertaining to Marketing Mix, Customer Segmentation, Industry Forecasts, Own Base retargeting, etc.

He is an advanced user of and & family of tools. He is one of the few Certified Predictive Modelers and Certified Business Analyst. He is a founding partner and Principal Consultant at Facts n Data and devotes most of his time to StatLabsTM.


Pabitra holds degree in Masters in Finance and Control, is an Associate of Insurance Institute of India, and has a hands on experience of close to 18 years in BFSI and e-Commerce space. He has closely been associated with ICICI Prudential, Max Newyork Life (Now Max Life), Transamerica, Reliance Retail, Tata AIG, Future Group and other leading brands globally.

A technocrat by heart, he is an expert at , and and is a hands-on expert at Data Wrangling. Some of his algorithms on Big Data Analytics and reporting have been recognized by many experts in the field. He is currently testing some innovative algorithms relating to Vehemence & Entity Relationship Modelling in Social Media space. He leads Business and Product development.


We Are ?


A.    Advanced Data Analytics and Modelling (including Big Data Analytics)


We take multi-disciplinary approach and leverage on concepts of streams such as Statistics, Mathematics, Operations Research, and have expertise over SAS family of tools, IBM-SPSS family of Tools and open source tools such as R. Our innovation and R&D is powered by StatLabs to do experiments to leverage latest developments in various academic streams of Data Sciences such as Statistics, Mathematics and Operations Research for Business use.

To help solve complex business problems such as xxxxx, we do advanced Statistical and Mathematical modelling on it. While many such time intensive tasks such as data gathering, structuring, cleansing, normalization are done in automated/ semi-automated mode using our proprietary algorithms, we continuously innovate in terms of analysis techniques to ensure that no insight is ignored. We use latest techniques and tools, while remaining tool/ technology/ vertical agnostic!

Our advanced Machine Learning algorithms manage our other algorithms to ensure that we take care of data dynamicity. This means that we are right, everytime!


Text Analytics (including Social Media):


We scientifically analyze social media data in great depth (much beyond counting the `likes`, `followers`, `Brand Mentions`, or Simple Sentiment Analysis) to get insights by using proprietary concepts such as Entity Relationship Modeling, Content & Context Analytics.

We analyze large amounts (in Hundreds of GBs) of qualitative data such as social media data/ transliteration of call center conversations/ client emails with our proprietary algorithms in great depth (much beyond counting the likes, followers, Brand Mentions, or Simple Sentiment Analysis).

Examples include Context & Content analysis, Stimulus-Response Modelling, and complex (demographic-behavioral) segmentation.

Customer expresses herself in more than one ways today. Multiple channels, varying language, multiple cultures, contrasting meaning of the same words used or same meaning of opposite words (such as Hot and Cool) make the task of analysis and interpretation very demanding. Despite all these challenges, we are able to analyze such data with very high signal to noise ratio, using our culture sensitive proprietary algorithms and techniques.



Stimulus Response Modeling

Facts n Data leverages on analyses of text data from multiple resources including Survey data, Social Media posts, Complaint & Compliment emails, amongst others to identify:

One-to-one & many-to-one relationships between stimuli and responses

Relationships between various types of stimuli and Relationships between multiple types of responses.

Perception Re-engineering

Intelligent use of concept, context, perception and mood coupled with stimulus response model helps in managing the perception of the TG and suitably re-engineer it. This has been used by various brands to move in the direction of desired position on the perceptual map of the market. This has also been used by some of our clients to arrest an adverse perceptual trend by monitoring the undercurrents and introducing the appropriate stimuli at the right time.



Welcome to StatLabsTM, our Algorithm Conceptualization, Testing, Deployment & Simulation Laboratory. It`s our Lab for doing R&D in Decision Science & Data Science (Cognitive Research, Statistics, Mathematics, Operations Research and allied areas).

Experience suggests that it takes 15-25 years for a new analysis technique to be available to be used by Business. Obviously, if a new analytics technique is made available to Business within 1-3 years of it being published in a Research Journal, it gives an unparalleled advantage in today`s competitive world.

StatLabsTM does exactly that - we keep an eye on new Techniques being available, assess their possible impact, test them in real life scenarios, and tweak them to make Business sense.

StatLabsTM consultants continuously do R&D on new techniques, develop algorithms to solve business issues, critically analyse these by putting them through the acid test of real-life data analysis, and commercialize the same. Our clients are the first ones to get the best of the world techniques.


Campaign RoI Optimization
  • Optimize RoI of various competing media channels that typically have varying
    • success rates
    • audience base
    • measuring matrix
    • Campaign objectives (Awareness/ Engagement/ Conversion)
  • Dynamic optimization algorithm that automatically adjusts itself based on data.
  • Uses multiple contradictory views - not only "Propensity to respond", but also "Propensity to Churn" based on the same campaign

ROI Prediction Model

  • Based on the RoI for first 2-3 days of a campaign, predicts the likely RoI
  • Predicts which channel - audience segment combination is likely to perform and which is not
  • Saves from the unexpected surprise at the end of campaign - flags under-performing channel-audience segments so that user can fine tune the campaign
  • Also makes it possible to leverage on over-performing segments to overshoot campaign objectives

CVI  (Customer Value Index)

  • Classic Industry Definition of  How much a customer has given in the past & therefore predicting how much will give in the future does not serve practical purpose of targeting own base
  • The model indexes an individual customer based on multiple parameters in relation to own best customer (taking care of outliers)
  • Avoids over-targeting valuable customer for not-so-valuable campaigns

Campaign Recommendation Model (C-Rec)

While the campaign is underway , it tells the following :
  • What components, channels, segments are working
  • What actions one should take to ensure it meets the campaign objective
  • How to leverage on successful segments/ channels
  • Real time  Pre warning signals
  • Ante-mortem, not Post-Mortem

Its takes away all the nasty surprising elements & drives positivity

Propensity Modelling
  • Propensity prediction
    • Individual-Channel-Campaign type complex propensity calculations- By Weekday/ day part
  • Considers "natural propensity to buy" to arrive at real incremental propensity to buy - "the best campaign candidates may not really be the best"
  • Also considers "Propensity to Churn" (opt for un-subscription) based on number of communications already sent

Digital Footprint Analyser (DFATM )

Dynamic behavioural-demographic segmentation based on digital behaviour to get Digital foot-print analyser


Facts n Data considers people as its biggest asset and offers a culture that is unique in terms of people, the passion they share and the results they deliver. We have employee centric people management policies and we respect the work-life balance of our team members.

Facts n Data is an equal opportunity employer. We firmly believe that employment generation is a corporate social responsibility. While merit prevails, we encourage underprivileged sections of society, as well as those fighting with physical challenges to come and be part of this intellectually stimulating environment.

We strive to retain our people and groom them to deliver exceptional value for our clients. We cultivate a culture of unwavering integrity.

To explore the possibility of joining our team, send us your background, interests and experience summary to info@factsndata.com.



New Delhi : +91-11-22486730
Navi Mumbai : +91-22-27526250
Bangaluru : +91-80-

New York : +1-347-329/426
Landon : +44-20-3290/426
New York : +61-280-914260
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