Advanced Analytics

OVERVIEW

Advanced Analytics is a powerful combination of order data and returns data broken out into 3 categories - Product Insights, Customer Behavior, and Operational Insights. This can be found in your Loop Admin under Analytics. 

Advanced Analytics is an add-on feature for all Loop plans. Please reach out to accountmanagers@loopreturns.com if interested in adding it to your plan. 

In this article:

  • Product Insights: Understanding the Data & Use Cases
  • Customer Behavior: Understanding the Data & Use Cases
  • Operations Insights: Understanding the Data & Use Cases
  • Tips for using the Dashboards

Product Insights

Reduce your return rate with deeper insights into top returned products, top return reasons, and trends over time. 

Understanding the Data

  • All data in the Products dashboard ties back to when the order was placed in Shopify. 
  • Order data (Total Units Sold, Total Shopify Orders) includes ALL Shopify orders (includes instore/POS orders).
  • Returns data only includes returns submitted via Loop.
  • Product Insights Data Points:
    • Item Return Rate = Number of Return Items / Total Units Sold
    • Exchange Ratio = Number of Exchange Items / Number of Return Items
    • % of Total Returns = Return reason count by product / Number of Total Returns
    • Return Rate = Total Returns Orders in Loop / Total Shopify orders
    • Exchange Ratio = Total Returned Orders with an Exchange (includes Shop Now) / Total Shopify Orders
    • Refund Ratio = Total Returned Orders with a Refund / Total Shopify Orders

Use Cases

Targeted Users: Operations Managers, Merchandisers, Business Owners

  • Update Product Descriptions to ensure customers purchase the right variant the first time
  • Share with Product Development teams to adjust sizing to reduce returns
  • Adjust the manufacturing process to improve quality & fit
  • Drill down to see customers' specific issues with variants and sizing
  • Monitor results & progress to reducing returns over time

Customer Insights

Identify your best customers and your most costly customers by segmenting your data via average order value, return frequency, refund ratios, and more.

Understanding the Data

  • Data in the Returns Outcomes dashboard is driven by orders placed within the specified date range.
  • The remaining dashboards are based on customer data within the specified date range. (For example: a range set to "is in the last 12 months" will pull in orders and returns from customers from the last 12 months).
  • Customer Behavior Data Points:
    • Return Rate = Total Returns Orders in Loop / Total Shopify orders
    • Return Outcomes over time - view the breakout between refunds, store credit, and exchanges (includes Shop Now outcomes)
    • Total Customers - quantity of unique customers who have purchased during the specified timeframe
    • Average Days to Second Order - average time between customers' first and second orders
    • Orders per Customer = Total number of orders / total customers
    • Average Order Value = Total sales / number of orders
    • Total Spend per Customer = Total Shopify sales / Total customers
    • A+ Customers - Top 5% of customers by order volume, with <=20% return rate
    • Costly Customers - Top 5% customers by number of returns, with >50% refund ratio

Use Cases

Targeted Users: CX & Marketing Leaders, Business Owners, Operations

  • Customers with a Loop return vs. without a Loop return
    • Adjust return policy to encourage returns for dissatisfied customers
    • Use data to forecast the ROI of retention marketing campaigns
    • Quantify the value of Loop to justify annual contract value
  • A+ Customer data
    • Identify & tag best customers to run targeted campaigns
    • Reach out to your best customers to turn them into brand advocates
    • Model the behavior of your best customers to convert average customers to best customers
  • Costly Customer data
    • Adjust return policy to reduce the number of costly returns
    • Create win-back campaigns to encourage A+ behavior from this segment
  • Bonus & Keep Item tracking
    • Identify "bad actors" and customers who are abusing the returns policy. Consider using Loop's blocklist functionality to prevent future bad behavior.

Operations Insights

Make your return process more efficient by understanding average processing times, shipping times, label costs, and more.

Understanding the Data

  • All data in the Operations dashboard are based off of when the return was submitted.

Use Cases

Targeted Users: Operations and CS teams

  • Track the incoming return volume to make staffing decisions and reduce processing time
  • Track processing times to model and forecast customer service demand
  • Use the average label cost per Carrier to negotiate rates and reduce costs
  • Track the status of return labels to plan staffing and warehouse capacity and improve efficiency
  • Identify stuck return labels to resolve potential CX issues before it impacts my customer
  • Understand which members of your team are processing the most returns to direct team resources more efficiently

Tips for using the Dashboards

  • Filter the data by updating the available fields at the top left of the dashboard. Click the Reload button in the upper right hand corner to refresh the data.
    • Look at a specific date range by using the "is in range" option.

  • Sort the data by clicking on the column headers. 

  • Each dashboard's data can be downloaded by using the Vertical Ellipses button on the top right hand corner. This will allow you to export the data to Excel, CSV, TXT and more.
Note: The ability to download the data will not be available during the free trial through September 10, 2021.
  • Learn more about the data points shown by clicking on the Information Symbol. These contain information on what the data point is or how the data point is being calculated.

  • On the Product Dashboard - learn more details about specific variants by clicking on the product name under the Title column. Click "by Variant Title". 
    • This will break out number of exchanged items and number of refunded items at the variant level.

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