Welcome to StatLabs®, 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.

StatLabs® 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.

StatLabs® consultants continuously do R&D on new techniques, develop algorithms to solve business issues, critically analyze 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.

StatLabs is our registered Trademark.

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 the 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 the 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

CVI  (Customer Value Index)

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 (DFA)

Dynamic behavioral-demographic segmentation based on digital behavior to get Digital foot-print analyzer gets amazing insights to a seasoned Digital Marketer – these insights are way ahead of the insights provided by any other tool available in the market today.

About Us:

We are the Data Scientists cum Technologists for the CMO/ CEOP community and help them by synthesizing facts with relevant data to provide scientific analysis and expert interpretation. We are tool and technique agnostic focusing only on the business Issue.

Contact Us:

New Delhi, India: +91-98 10 22 84 02

New York, USA: +1-347-53 53 001

Reading, UK: +1-118-20 40 001

Mumbai, India: +91-70 11 90 06 96

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