With data growing at an exponential rate, it is getting difficult for companies to analyze patterns. The situation becomes more aggravated with the need for using this analysis to generate revenues. A data science team can help slice and dice everything, right from the customer’s buying history to preferences, which can help you increase sales and reduce customer turnover. Thus, having a well-organized data science team is of utmost importance.
Why does an organization need a data science team?
1. Collect data
A data science team uses predictive analytics to analyze past data that suggests the behavior of people in the future. They try to correlate data from various sources using algorithms and statistical methods to bring out various patterns that can help the company improve its efficiency, streamline the processes, and know where to invest and how to increase revenue streams. Data science teams are required across various professions. For instance, in the retail industry, they could help figure out shopping habits of potential customers. In the healthcare industry, they can look for vital statistics that can diagnose infections.
2. Analyze social media
Social media sites like Facebook and Twitter have the power to manipulate public opinion. Analysis of social media conversations provide real-time information of what and how intensely consumers feel about a product. A data science team can perform a sentiment analysis to either know what customers are looking for or the impact of the company’s product on the masses. They can analyze whether the customers feel positive or negative about the product by classifying tweets as either a question, praise, or complaint.
3. Segment customer base
A data science team helps find like-minded groups from a vast customer base. Data analytics helps segment the market in a better way by analyzing both the common and unexpected interests of potential customers. It uses advanced mathematical techniques such as ‘K means clustering’ to find disparate similarities and differences in the customer base that are otherwise not visible to the human eye. Data science teams can differentiate customers based on parameters such as demographics, providing valuable data to the company to develop a targeted marketing strategy.
4. Optimize modeling
Data science teams help optimize modeling by representing various business processes mathematically with the objective to improve production and reduce costs. For example, an electronic business would want to evaluate various factors like number of component suppliers, different component quality trade-offs, efficient delivery, and budgets. By optimizing the model, the company can then find the best combination of the various inputs.
Having a data science team is of enormous benefit. It acknowledges data as a tactical asset by analyzing predictive models and datasets on the basis of which it efficiently forecasts about people and processes. All of this ultimately leads to unprecedented growth and huge profits.
