Why does it take to create Actionable Predictions using current methods?
Here is a high-level timeline of the workflow from exporting a CSV file from a CRM system and using data science techniques to create actionable predictions uploaded into the same CRM system, including the expected time taken for each step:
- Export CSV file (0.5 – 1 hour): The first step is to export the customer data from the CRM system in the form of a CSV file. This step typically takes between 30 minutes to an hour, depending on the size of the data and the efficiency of the CRM system.
- Data Cleaning and Preprocessing (1 – 2 days): Once the data is exported, it needs to be cleaned and preprocessed to ensure that it is ready for analysis. This step typically takes between 1 to 2 days, depending on the size and complexity of the data.
- Exploratory Data Analysis (EDA) (1 day): The next step is to perform exploratory data analysis to gain insights into the data and understand the relationships between different variables. This step typically takes around 1 day.
- Model Development (2 – 5 days): Based on the insights gained from the EDA, a predictive model is developed using data science techniques such as regression analysis, decision trees, or neural networks. The model is trained using the historical data and validated using a test set. This step typically takes between 2 to 5 days, depending on the complexity of the model.
- Model Evaluation (0.5 – 1 day): Once the model is developed, it is evaluated to determine its accuracy and reliability. This step typically takes between half a day to a day.
- Model Deployment (1 – 2 days): If the model performs well, it can be deployed and used to make predictions on new customer data. This step involves integrating the model into the CRM system so that predictions can be made in real-time. This step typically takes between 1 to 2 days.
- Actionable Predictions (ongoing): The predictions generated by the model can be used to make informed decisions and take action to improve customer engagement and retention. This step is ongoing and will depend on the frequency of customer data updates and the need to make predictions.
- Upload Predictions into CRM System (0.5 – 1 day): The final step is to upload the predictions back into the CRM system so that they can be easily accessed and used by other departments within the company. This step typically takes between half a day to a day.
Overall, the entire process can take anywhere from 7 to 14 days, depending on the size and complexity of the data, the type of model used, and the efficiency of the CRM system. This timeline assumes that the data scientist has the necessary skills, tools, and resources to complete the steps in a timely manner.
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