Data Science is a field of Computer Science that deals with extracting, organizing and analyzing large amounts of data to help businesses make crucial decisions. For example, in the world of e-commerce, Data Scientists can use chat conversation analysis to help companies optimize specific Key Performance Indicators.
Data Mining, a process which lies at the intersection of Statistics, Machine Learning, and Artificial Intelligence, extracts data from large preexisting databases and transforms it into comprehensible information for further use. When dealing with customer support chat, companies can give their API data and conversation logs to Data Scientists to have this information analyzed and made into actionable insights. Throughout the process of chat conversation analysis, Data Mining helps detect and eliminate noise in data, understand what's relevant in customer support chat logs, and uses that information to assess future outcomes.
In the e-commerce space, data is vast and can be analyzed to solve many of the problems companies face. Data Software such as Tableau can help companies analyze their complete sales databases, their Google analytics data, and their AdWords data, too. Through this analysis, companies can understand which keywords work best for Pay per click and which don’t. Additionally, companies can understand where orders and returns originate, and in what categories minimum and maximum returns occur, which helps them strengthen their customer outreach. Through chat conversation analysis, a process in which Data Scientists analyze the customer support chat logs and compare them to the conversion funnel for orders placed and orders canceled, companies can gain great insights into what drives conversions.
Data Scientists need a powerful tool to visualize the vast amounts of data with which they work. Through Data Visualization, scientists can process, understand, and analyze information. Tableau is a widely used resource for data visualization and business intelligence, and is focused on enhancing the analytic workflow experience. It can quickly process millions of rows of data, perform basic calculations and statistics, and provide results in seconds. It has a mapping functionality capable of plotting latitude and longitude coordinates to yield interactive graphs, and can build dashboards using a Graphical User Interface. Through Dashboarding, even non-technical users can create interactive, real-time data visualizations by combining data sources, adding filters, and drilling down into specific information. Sharing dashboards requires no programming, whether it’s on Tableau Server, Tableau Online, or any portal or web page. The best part is Tableau can connect to multiple data sources, providing new opportunities for discovering new insights hidden in the data. Additionally, Tableau easily connects to the open-source programming language and software environment for statistical computing and graphics, R.
Data Visualization software enables users to directly connect to data warehouses and cubes. A data warehouse is a stable platform of a company’s consolidated, transactional, and organized data managed separately from a company’s operational database. Data warehouses support business insights and decision-making. An OLAP (Online Analytical Processing) cube is a different staging space for analyzing a multi-dimensional set of data. Tableau enables users to directly connect these databases, cubes, and data warehouses effectively.
Tableau is one of the most effective tools for Data Mining in e-commerce. It helps optimize the task of Data Visualization, increasing its efficiency and effectiveness.