How to laverage data for e-commerce business growth

Franco, Gabriele (A.A. 2020/2021) How to laverage data for e-commerce business growth. Tesi di Laurea in Entrepreneurship, innovation and technology, Luiss Guido Carli, relatore "Jose" D'Alessandro Giuseppe, pp. 55. [Bachelor's Degree Thesis]

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Overview on DTC. The direct to consumer brand into the online retail (digital to real). The D2C model. The biggest problem for DTC businesses. Why do e-commerce businesses stop growing? Experience. How to develop a data-driven decision process that generates growth. When an e-commerce wants to grow, it needs to optimize these KPIs. The gross profit formula. The problem pt.2. Data validity. KPIs range. Data silos. Dispersion of information. Solution. How to transform raw data into growth’s KPIs. How to organize data for centralization. KPIs logic into a centralized dashboard. Dashboard objective & description. Why and how to predict future sales. Models are illustrated by studies of econometrics. What can econometric modelling do? What makes sales go up and down? How to create a model with input variables that predicts sales. Business view on Cassandra. Applications of Cassandra. Acquisition strategy and validation. Learnings. Target market and customer’s qualifying characteristics. Competitors in our market. Business model-lean canvas representation. Pricing hypothesis. Medium-term strategy. Financial plan.


Bibliografia: p. 55.

Thesis Type: Bachelor's Degree Thesis
Institution: Luiss Guido Carli
Degree Program: Bachelor's Degree Programs > Bachelor's Degree Program in Economics and Business, English language (L-33)
Chair: Entrepreneurship, innovation and technology
Thesis Supervisor: D'Alessandro Giuseppe, "Jose"
Academic Year: 2020/2021
Session: Autumn
Deposited by: Alessandro Perfetti
Date Deposited: 28 Feb 2022 13:44
Last Modified: 28 Feb 2022 13:44


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