MarketingAutomation
The customer
The client company, a company operating in the energy market, has been developing a marketing campaign aimed at acquiring new customers for more than 2 years through the Google Ads and Facebook Ads platforms.
The problem
The marketing campaigns launched by the aforementioned company suffer from the lack of an analysis of the results, so it is difficult to evaluate their effectiveness.
The solution
The solution provided has a dual objective, namely to provide the client company with detailed reports on the impact of the major reference metrics in the Social Marketing field in relation to the campaigns already carried out and to equip the company with powerful forecasting tools in view of the new campaigns to be start in order to correctly target their promotional activities.
Planning and Implementation
The project implemented by Koros Consulting required access as an Analyst to the Google and Facebook Ads accounts of the client company, so as to be able to carry out a data mining activity followed by a data cleaning activity using tools such as Office and Power BI.
At a later stage, Power BI reports were created in the form of dashboards concerning the analysis of the aforementioned data relating to the time interval from 30/01/2017 to 25/10/2019.
The last phase involved the goal of designing machine learning algorithms using libraries developed ad-hoc in Python language to be implemented on a web interface using the Flask microframework for the backend and the Vuejs framework for the frontend.

Google Ads Analysis
In order to evaluate the implementation of the customer assistance service, Koros Consulting has analyzed the data relating to the telephone call log resulting from the results of the Google Ads campaigns in the period from 06/10/2017 to 04/10/2019 . In addition, the main Social Media Marketing metrics were analyzed to plan future marketing campaigns and establish the most suitable content to increase engagement, including: impressions, coverage, CTR, cost per conversion. The goal was to pay attention not only to the content, but also the time and date of publication on Google, in order to become aware of the variables that affect user feedback.
