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Data Milling
What we do
Our business model is based on providing simple, direct and scalable access to data to all stakeholders involved in a transaction.
Current data business models are based on companies that invest increasing amounts of data to obtain biased, partial and incomplete data from their potential or existing customers and then attempt to use that data through different communication channels to attract their attention and stimulate sales.
The analysis of the purchasing decision process has advanced significantly in recent years thanks to the ability to analyze consumer behaviour, both by technical means (internet, webcams, face recognition, etc.) and by advances in psychological models and Neuroscience. However, these developments face the lack of adequate data needed to shed light on how to retain and keep their customers satisfied.
Consumers now have a wealth of information at their fingertips allowing them to compare products, select versions, check prices, etc. As a result, traditional communication channels between businesses and users/consumers are now inefficient and their reach is diminishing. New communication channels can be effective, but their lifecycles and impact are difficult to predict, leading to frequent misallocations of advertising and marketing resources.
Consequently, albeit paradoxically, companies now have more data on their potential customers/clients than ever before, but the distance between each of them and their potential customer/clients is becoming ever greater.
As of the above, conversion, client retention, client/user turnover rates and client/user feedback remain highly elusive and can only be inferred from indirect data often collected by third parties for other purposes.
Data Milling bridges this gap by providing direct access to the relevant data.
Current data business models are based on companies that invest increasing amounts of data to obtain biased, partial and incomplete data from their potential or existing customers and then attempt to use that data through different communication channels to attract their attention and stimulate sales.
The analysis of the purchasing decision process has advanced significantly in recent years thanks to the ability to analyze consumer behaviour, both by technical means (internet, webcams, face recognition, etc.) and by advances in psychological models and Neuroscience. However, these developments face the lack of adequate data needed to shed light on how to retain and keep their customers satisfied.
Consumers now have a wealth of information at their fingertips allowing them to compare products, select versions, check prices, etc. As a result, traditional communication channels between businesses and users/consumers are now inefficient and their reach is diminishing. New communication channels can be effective, but their lifecycles and impact are difficult to predict, leading to frequent misallocations of advertising and marketing resources.
Consequently, albeit paradoxically, companies now have more data on their potential customers/clients than ever before, but the distance between each of them and their potential customer/clients is becoming ever greater.
As of the above, conversion, client retention, client/user turnover rates and client/user feedback remain highly elusive and can only be inferred from indirect data often collected by third parties for other purposes.
Data Milling bridges this gap by providing direct access to the relevant data.
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