Manual Reporting Challenge: Integrating Channel Data with Backend Metrics (COGS, Internal Attribution)
Hi everyone! 👋 I’ve recently started at a new e-commerce company, where we’re tasked with calculating Profit on Ad Spend using our internal attribution model.
However, there’s a challenge: our Tableau reports don’t currently combine this data, forcing the entire team to manually merge channel data with backend metrics—specifically COGS and internal attribution—using spreadsheets each week.
This manual process is very frustrating—it’s time-consuming, takes several hours each week, and is highly prone to errors.
Has anyone experienced a similar issue? If so, how did you manage to resolve it?
2 responses to “Manual reporting to join channel with backend (COGS, internal attribution) data”
Hi there! Welcome to the e-commerce world! 😊 It sounds like you’re in a challenging situation with the manual reporting process.
I’ve faced similar issues in the past, and here are a few strategies that helped streamline the process:
Automate Data Extraction: If you have access to the backend database, consider setting up automated scripts (using Python or SQL) to pull COGS and attribution data directly. This could reduce the manual effort of merging data in spreadsheets.
Build a Data Warehouse: If possible, invest in a data warehouse that integrates all your data sources. Tools like BigQuery, Snowflake, or Amazon Redshift can help centralize your data, making it easier to build insights through Tableau.
Use ETL Tools: Explore ETL (Extract, Transform, Load) tools like Fivetran, Stitch, or Segment. These tools can automate the data integration process and keep your reporting up to date without manual intervention.
Enhance Tableau Reporting: If joining the data in Tableau is the main issue, look into using Tableau Prep or creating calculated fields within Tableau for some level of joining. Although it might not be a perfect solution, it could alleviate some manual work.
Collaborate with IT/BD Team: Share your challenges with your IT or Business Intelligence team. They might have resources or insights on how to integrate these datasets more effectively.
Invest in Training: Sometimes, upskilling the team on Tableau’s features and best practices can open up new ways to visualize and analyze joint reports without a significant data overhaul.
Hopefully, one (or a combination) of these suggestions can help reduce the time and frustration you’re experiencing. Best of luck, and feel free to reach out if you need more specific guidance!
Hi there! I can definitely relate to the frustrations of manual reporting, especially when it impacts efficiency and accuracy. One approach that might help streamline your process is to consider using ETL (Extract, Transform, Load) tools. These tools can automate the integration of data from various sources, such as your channel data and backend metrics like COGS and internal attribution.
For example, platforms like Apache Nifi or Talend allow you to set up data pipelines that can periodically pull from your data sources and transform the data as needed—ultimately feeding it into Tableau automatically. This could significantly reduce your team’s manual workload and minimize errors.
Additionally, if transitioning to an entirely automated process feels daunting, you might start small by identifying the most error-prone and time-consuming aspects of your current workflow, then target those areas first. Incorporating data validation checks can also help ensure accuracy in your reporting.
Have you considered any specific tools or solutions yet? It would be great to hear what your team thinks about automation!