I will discuss the use of ML/AI at DoorDash to power its on-demand. Although there are challenges In providing a three-sided marketplace, the company mitigates these challenges through reinforcement learning and supervised learning algorithms. Moreover, the company also uses operations research to tackle multiple decisions by feeding objective goals and constraints to retrain the models. Overall, DoorDash is one of the most successful food delivery companies in America as it is evidenced by its ability to outperform its competitors such as Foodora and Ubereats.

Rickaby hardware is a company which supplies the hardware peripherals to different clients such as nomad stores etc. They have a head office in Mumbai India, and they have different regional offices in different cities of India. Dumisani Sagas is the sales director of this company, and he Is managing the business from the head office. So, what is happening with this company is that sales are declining and Dumisani as a sales director is having a lot of struggle tracking where the business is failing due to the size of the company which is big. When Dumisani calls his reginal mangers asking for information on why the sales are declining, unfortunately, his reginal managers are always giving him fuzzy and unclear information which can help him understand the root cause. In addition to that, they always give him big excel files of all transactions which is very difficult for Dumisani to transform all those excel sheets into insights. However, Dumisani calls for an emergency meeting with the sales director, marketing, customer, data analysis and IT teams.

This analysis is for a Google Analytics Certificate capstone project. Kevin Hartman’s case study was the inspiration for this piece. A company called Cyclistic developed a successful bike-share program in 2016. Since then, the initiative has grown to include a fleet of 5,824 bicycles that are geotracked and locked into 692 stations throughout Chicago. Until date, Cyclistic’s marketing strategy has focused on building general awareness and appealing to a wide range of consumers. “Casual” riders are customers who purchase single-ride or full-day passes. Cyclistic “members” are customers who purchase annual memberships. Annual members are substantially more profitable than casual riders, according to Cyclistic’s financial analysts. The company’s future prosperity, according to the director of marketing, hinges on increasing the number of yearly subscribers. The full document to the case study can be found in the Google Data Analytics Capstone: A Complete Case Study