API: What Are The phases Of An API Project?

To maximize value early on, we recommend starting small with a clearly defined use case. This article walks you through the steps our most successful customers follow.

1.  Identify the Initial Use Case

Choose a focused use case that delivers quick wins and encourages collaboration between business and technical teams. Examples include:

• Automating a single report that is currently manual.
• Landing and validating data for a defined set of competitors.

2.  Establish a Meaningful Scope of Data

Define the data needed to answer your chosen use case.

• Automating a report: scope may be defined by a time period and relevant filters.
• Competitor set: scope may be defined by time period and retailer IDs (known as slugs)
  

3.  Land The Data

Decide how to retrieve and where to store the data. Options depend on the scope:

• Small scope / proof of concept: retrieve manually (e.g., with Postman) and store locally on a work machine.
• Larger scope / ongoing needs: automate retrieval (e.g., with Python or other tools) and store in a central data warehouse.
  
  

4.  Analyze & Visualize

Use the landed data to answer your business question.

• Compare results back to the original use case.
• Identify what works well, what’s different, and where improvements are needed.

5. Operationalize

Plan for ongoing data management:

• How will new data be collected and refreshed?
• Where will it be stored so it’s easily accessible?
• What is the update process?
  
  

6.  Repeat & Expand

Our most successful customers start with a narrow proof of concept and gradually expand. Consider:

• Are there more reports to automate?
• Are there additional competitor sets or datasets to land?
• Can you scale from manual processes to automated pipelines?