Leafly- Customer and Strain Analytics
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![Page 1: Leafly- Customer and Strain Analytics](https://reader038.fdocuments.us/reader038/viewer/2022100801/58a26e211a28ab94628b5203/html5/thumbnails/1.jpg)
Customer and Strain AnalyticsBy: Casey Hynes, Ryan Carlile, Nate Harris, Laurel Pauling, and Jiaqi Ye
![Page 2: Leafly- Customer and Strain Analytics](https://reader038.fdocuments.us/reader038/viewer/2022100801/58a26e211a28ab94628b5203/html5/thumbnails/2.jpg)
Agenda● Cannabis information resource
○ Products○ Dispensaries
● New company looking to reach customers to build its community ● Reports and models to explore customer demographics and strain ratings
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Leafly’s Needs● Marketing
○ Target market ■ Demographics■ Geographics
● Industry growth - legalization● Future E-Commerce model● Key business questions:
○ What target market is has the most potential for future sales in the cannabis market?○ Which strains are the most popular among specific demographics?○ Which strain type is the most widely used?
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Technology Solution
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Dashboards and Reports● Customer demographics:
○ Age, gender, income○ Location and registration dates
● Strain ratings:○ Customer demographics○ Location○ Date
![Page 6: Leafly- Customer and Strain Analytics](https://reader038.fdocuments.us/reader038/viewer/2022100801/58a26e211a28ab94628b5203/html5/thumbnails/6.jpg)
Data Upload● Flat file
○ For our fact tables we used CVS files, to insert a mass amount of data○ We Used SSIS to move the data from the CVS file to the datamart
● Manual data insertion○ For low cardinality tables, manual insertion was the most efficient method of data
creation
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Datamart
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OLAP/Cube● SQL walkthrough
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Conclusion ● Target growing industry
○ Legalization in new states○ Future eCommerce site○ New marketing strategies for existing customers
● Demographics○ Understanding customer interests by demographic○ Popularity of products