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Decentralised Retail Marketplace

Case study on Decentralised Retail Data Marketplace

Case study on Decentralised Retail Data Marketplace


The current Retail industry lacks authentic insights for Consumer behaviour patterns which can be leveraged for better products, thereby generating higher revenue.

  • The industry is still crippled by the lack of access to relevant and usable datasets.

  • Online retailers have huge benefits of reaching out to mass audience and do targeted marketing. This is a huge gap between online retailers and offline retailers.

  • Online retailers can study consumer’s online behavior but cannot study offline retail consumer behavior.

  • 1. Problems faced in data collection

  • Data collection does not tell about the customer behavior & buying patterns are difficult to collect.

  • The current method used in collection of data is manual & thus involves a lot of human intervention

  • The cost of collection of data is very high due to the field force that is deployed in the collection of such data on a regular basis

  • The data collected is not real time data

  • Updating of data involves incurring of recurring operational cost

  • 2. Problems in Data cleaning & sorting

  • Huge operational costs are involved to refine, sort & clean the data collected through manual processes.

  • Due to large volume of data & high degree of human intervention, the data processed is not real time in nature.

  • 3. Problems in Data buying/selling

  • The data buyer has to buy huge amount of data at hefty prices. A small scale entrepreneur who wishes to buy small size of data cannot afford to pay such high prices.

  • Distributors & consumers from whom the data is being collected are not compensated for the sharing of information.

  • Data buyers cannot request to buy data according to their relevance.

  • 4. Problems faced by Retail Industry due to lack of inaccurate data

  • No centralized customer database

  • Marketing strategies based on assumption due to lack of data

  • Difficulty in analyzing consumer buying behavior

  • Difficulty in knowing your specific target audience

  • Difficulty in analyzing store operations

  • Time consuming vendor & supply chain management

  • Lack of scalability of data

  • Difficulty in market research

  • Solution:-

    We aim to provide the retail industry with comprehensive industry and use specific datasets and create a direct channel between various industry stakeholders (manufacturers, distributors, data analysts etc.) and the end consumer.

    1. Data Collection

  • Sales data should be collected from point of sale (B2C). Consumer data should be collected

  • The sample size to analyze consumer behavior should not be restricted to a certain number of consumers

  • There should be a way to record consumer behavior which is important for designing marketing & promotional strategies.

  • Automated collection of data with minimum human intervention which will enhance the quality of data

  • There should be single channel of communication which will reduce the cost of data collection.

  • Incentivizing the data contributors & ensuring the confidentiality of the same.

  • Real time data collection methods

  • Data Cleaning & Sorting

  • An automated solution will help to cut down the time required in processing of data & in elimination of errors caused due to human intervention

  • Buying & Selling

  • No distinction should be made between different data buyers. Also there should not be minimum buying size of data.

  • As the valued information comes from distributors & consumers, they should be compensated for their contribution.

  • As the market scenario & consumer behavior is changing due to penetration of technology, the data buyer should be given liberty to choose from a large number of data sets.

  • There must be a platform where the data buyer can directly

  • What we have developed:-

    Here we are collecting Users Offline and Online shopping ,retailers sales data and storing data in a decentralized way using Ethereum Blockchain, BigchainDB and integrating AI on data for analysis, prediction.

    We are building a platform:-

  • Which can merge its online and offline marketing strategies.

  • That can identify duplicity of consumers and identify specific target markets.

  • That gives power to vendors and retailers to analyze both the market behavior together on one platform.

  • That can allow companies to make one marketing strategy and implement it through this platform.

  • That will reduce cost of customer acquisition & retention

  • That will allow companies to reach out to its end seller (Retailer)

  • That will allow companies to incentivize its retailer for pushing their sales, promoting their product, clear their dead stock, achieving higher secondary sales, etc.

  • That will allow companies to incentivize their consumers directly for being loyal to them.

  • That will allow companies to design tailor made reward and loyalty programs.

  • That allows consumers to aggregate their reward points in one place and utilize them wherever they want.

  • A platform which gives the liberty to do research, analysis, implementing marketing strategy and recording of sales.

  • This platform will allow industrial experts to understand the market more prominently.

  • This platform keeps the data encrypted for all the stakeholders.

  • This platform incentivizes customers for their data being shared.

  • This platform is totally decentralized that will make the operations true and impartial
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