Demand Analysis at a Grass Root Level
Currently, Demand Analysis and Market Research is done at a pin code/zip code level in the Pharmaceutical industry.
In Mumbai alone, a pin code on an average has 74 pharmacies, 4 hospitals and over 45 societies. When aggregating figures at a pin-code level, it may give the false impression that demand for a particular medicine is consistent among 45 societies and sales potential is the same at the 74 pharmacies.
But what if you could know the exact demand at each building, society, residential and commercial area?
This article demonstrates how Location intelligence can help you identify high-demand areas at 100m granularity and micro-target Doctors, Societies, Pharmacies and other points of sale across high-demand areas 10x times quicker than the traditional ways of market research.
Demand at a Grass Root Level
Location intelligence can go beyond the pin-code to identify and analyze data at a pharmacy-level. It analyses the past purchases for each pharmacy and monitors their catchment to identify the sales potential around it.
Specialized Geo-spatial algorithms are used, to predict sales potential across the entire neighborhood based on a pharmacies’ sales data and socioeconomic and demographic features such as affluence, population,income class etc.
The potential for Target societies can also be understood based on the sales potential and the number of flats in the society.
Similarly, Sales potential can be identified for various other targets such as doctors and pharmacies for which data is unknown.
What Drives Sales?
The most important feature of demand analysis is understanding, what drives sales? Who are my target customers? Which other factors is the sale of my products co-related with?
Using Machine Learning and Artificial Intelligence, Data Sutram identifies such patterns and correlations with medicine sales and socioeconomic and demographic features of the residential population such as affluence, population density, access to healthcare ,spending on entertainment and recreation etc.
For Cardiac medicine sales in Mumbai, the location factors that influence sales are as follows
Fill in the gaps: get to know sales potential even where data is unavailable
Often, in some areas pharmacy sales will be unknown. In such cases the demand can be predicted at a point based on the influence various location factors hold on the sales amount.
Hence, predicting sales potential at all locations at 100m granularity. Using this metric, store locations and business operations can be better planned to attain maximum impact.
Market research at fingertips
Once the sales potential at a location is known in order to capture the market, it is important to get the doctors’ in the region on board.
KHOJ can pinpoint the locations of all doctors in the catchment and their specialty.
Manually this could take weeks to do but with location intelligence it can be done with a few clicks.
Further, KHOJ looks at the relation between doctors and pharmacies, i.e., the pharmacies closest to each practicing doctor and from where his/her patients likely buy the prescribed medicines.
Using this technology, one can identify all the doctors near pharmacies with high potential and push products accordingly.
DataSutram’s KHOJ AI is a platform developed to solve the demand-supply gaps that exist in the pharmaceutical Industry. It allows manufacturers and distributors to analyze :
- Sales potential for various product categories at each pharmacy
- Practicing doctors nearby pharmacies so that they can push medicines into the market more efficiently
- Identify consumer hot-spots
- Find out which socioeconomic classes of the population are often susceptible to a certain disease
For Pharmaceutical Retailers, KHOJ paves a way to
- Visualize the demand at a street level
- Identifying store locations such that they can locate themselves in high demand areas
- Pinpoint societies, doctors, residential areas and other targets with high potential that they should market directly to.
To Know More contact us at: www.datasutram.com/request-demo