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#5
Decentralised Retail Marketplace

Case study on Decentralised Retail Data Marketplace

Case study on Decentralised Retail Data Marketplace

Problems:-

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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