In 2019, the company changed its strategy for obtaining Leads, which are any type of contact provided to the company by another company or individual. It chose to acquire a lower number of Leads, but with a higher average ticket value, or average revenue per sale, going in search of opportunities with "higher quality". As a result of this change, the question arose as to which variables most influenced the company's results and if the average ticket was in fact one of those variables. Therefore, the relationship between several variables was studied in order to obtain the weight of each one in the revenue. To obtain this relationship a predictive analysis was performed, where the Multiple Linear Regression method was applied. In addition, a descriptive analysis was also performed, through the creation of dashboards in PowerBI software, where several KPIs were explored and analyzed. The data used in the analyses were extracted from the Bitrix24 management software and are relative to the Customer Relationship Management (CRM) of the company ERP24. In the predictive analysis were used as study variables the "Average Ticket", which corresponds to the average revenue of each sale, the "Lost Deals", referring to the number of failed sales, the Leads to Deals Conversion Rate, henceforth "L-D Conversion Rate", concerning the conversion rate into sales, of contacts left by companies or individuals to the company, and the Conversion Time from New Deals to Deals Won, hereinafter "ND-DG Conversion Time", which represents the time it takes from the time a potential deal is entered into the CRM until it becomes a sale. The analysis resulted in a model consisting of the "Average Ticket" and the "ND-DG Conversion Time", which were able to explain 55.5 % of the variation in Revenue. It was concluded that Revenue will vary about 3.5 for each additional unit of the Average Ticket and 7488.16 for each additional unit of the ND-DG Conversion Time. In conclusion and after analyzing the model created we can state that the variable "Average Ticket", as well as the "ND-DG Conversion Time", has a considerable impact on the company's revenue, thus having positively influenced the company's results to the change of strategy adopted. The results lead us to the conclusion that the company should continue to invest in a strategy to increase the average ticket and in businesses that take longer to convert, because they are the ones that generate more revenue, which turns out to be counter-intuitive because the company could be more concerned with quick-wins, i.e., quick cash conversions.
|Date of Award||13 Oct 2022|
- Universidade Católica Portuguesa
|Supervisor||Mário Filipe Amorim Faria de Oliveira Lopes (Supervisor)|
- Descriptive analysis
- Predictive analysis
- Multiple linear regression