IoT data science and consumer behaviour with assortment planning , pricing on eyeball gauging

Sandeep Sharma TOGAF CISA MEngg's picture
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Sandeep Sharma ...
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Sandeep Sharma ... wrote:

IoT data science and consumer behaviour with assortment planning , pricing on eyeball gauging

Consumer behaviour with pricing Assortment planning based on eyeball tracking. 2. Categories: Retail Future 3. Summary:. Gauging consumer behaviour based unstructured data from sensor network. 4. Idea Description. Most important factor in any Retail mall is the performance of its assortment planned and pricing for goods based on estimated demand. Inside Store when person walks in The eyeball sensors Can gauge eye ball movements. Now the sensors inside store can track eyeball of consumer inside. Wide eye shows interest in object. Out of The planned assortment 2 Cases: 1. Planning assortment based on same category people interest in retlated things. So people walk it they look first at shoes (eye ball sensors counts and pass track to another sensors), then person goes forward looks at tie , then laces, then shorts etc. Customer A{shoes,tie ,laces, shorts} and count of each item is taken Each such list is generated of each customer entring store. Which things Counts more relative to each other based on data mining technoques like Lift Calculation details List of item sets {} and rules are generated based on which element occur most with each Other giving details of Assortment should have A followed by B. Now Association of A with B has to be tested for which data mining measureas like lift calculations are helpful as described below: Extension to this if pupil expands os the item its demand is high which can fetch more proce hence prices can be increased. Lift Calculation for 2 data sets A and B shown below: Antecedent Consequent A 0 A 0 A 1 A 0
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