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Dr Venugopala Rao Manneni
Dr Venugopala Rao Manneni

Dr Venugopala Rao Manneni

Learner, Practitioner & Teacher

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Category: case studies

Understanding what activities are preferred online across age groups

January 8, 2019April 12, 2022
Venugopal Manneni
case studies

We live in a social world and it is interesting to know what activities are preferred online across varied age groups labeled as Young adults, Millennial and Gen X. To understand this more closely, an Indian online survey was conducted

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Segmentation, Targeting and Positioning (STP)

January 1, 2019April 12, 2022
Venugopal Manneni
case studies

Objective The objective was to develop a segmentation algorithm on the basis of a set of psychographic attributes like basic values, beliefs, attitudes, perceptions, motivations and needs (functional, emotional, social and situational) in order to embark on targeted marketing and

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Classification using higher order interactions: a hybrid approach

January 1, 2019April 12, 2022
Venugopal Manneni
case studies

Hybrid Modeling For representation in this blog, we have considered German credit data for classification of good and bad credit risk using the interaction of the input variables through a hybrid approach. In this approach, first we developed a decision

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Understanding the impact of TV programmes on children’s skills

January 1, 2019April 12, 2022
Venugopal Manneni
case studies

Objective Understanding impact of viewership on children’s skill levels (tested through an instrument devised by leading child psychologists) after controlling for location, socio-economic levels, gender, pre-exposure levels across a panel of over 5000 children across urban and rural India. Approach

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Developing a Recommendation Engine using Hybrid Approach

January 1, 2019April 12, 2022
Venugopal Manneni
case studies

Client: A cloud-based interactive smart video platform that delivers personalized interactive videos on-demand to consumers. Objective Business: Increase time spent on site, number of videos watched, and repeat visits. The Engine: Devise an engine that offers relevant recommendation dynamically and in

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Understanding the factors that make a brand a ‘favourite brand’

January 1, 2019April 12, 2022
Venugopal Manneni
case studies

Client: A global fast food restaurant chain Objective The client intended to find the performance attributes driving the “Favourite brand” of the category where the population is more heterogeneous. Approach Since the population was heterogeneous in nature, merely aggregating the

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Assessing market demand using Neural Networks

January 1, 2019April 12, 2022
Venugopal Manneni
case studies

Objective The objective was to assess and forecast demand for a retail outlet, using Neural Networks. Approach In order to conduct the analytics, we applied the concept of Multi-Layer Perceptron (MLP) in Neural Networks which can classify and predict the

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MaxDiff modelling for product feature optimization

December 1, 2018April 12, 2022
Venugopal Manneni
case studies

Objective To understand which product features or applications are most important to a particular market. Approach An online quantitative survey was conducted that included a MaxDiff exercise in which 40 different product features were evaluated on what is best and

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Market Mix Modelling/ROI Modelling

November 1, 2018April 12, 2022
Venugopal Manneni
case studies

Objective Identify relationships between sales and various marketing activities to understand how various elements of the marketing mix combine to drive sales in a competitive framework. Approach From the client’s transnational database, we have considered the retail audit data like

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TURF to maximize messaging reach

October 1, 2018April 12, 2022
Venugopal Manneni
case studies

Objective To understand the message bundle that makes up the most motivating brand story, differentiating from competition, and thereby capturing the largest portion of the market possible. Approach Message importance was derived from the MaxDiff design. The number of messages

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About Me

 

A doctor in statistics from Osmania University, Venugopala Rao Manneni is an experienced data analyst who has over 15 years of work experience in a diverse areas of verticals such as manufacturing, service, media, telecom, retail, pharma and education. Prior to Juxt-Smart Mandate, he has worked with reputed organizations like TNS India (Kantar, WPP) and NFO MBL and served clients across UK, France and Asia Pacific region… read more

Recent Post

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  • Unlocking the Future: How Multiagent Systems Mirror Human Intelligence Using Advanced AI Concepts
  • Generative AI Glossary

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