Order Issue Reporting Flow Redesign

Enabled more accurate, item-level issue submissions and evidence collection—reducing fraud-related costs while protecting legitimate customer claims.

Instacart’s appeasement system has delivered meaningful cost savings, but a significant portion of rejected issue reports were found to be valid. To further optimize costs—primarily by reducing fraud and over-appeasement—Instacart needed more granular data from users to make smarter, fairer decisions.

Goals

Enable clear understanding of order issue types on the most detailed level possible and collect the proof needed to validate appeasement requests

For Customers: 

• Ensure that legitimate order issues are resolved fairly and consistently, improving trust in the platform and reducing the number of valid claims that go unsupported.
  

For Instacart: 

• Gain deeper insight into the nature and frequency of order issues to make more informed, cost-effective decisions.
• Improve shopper performance by collecting actionable evidence that enables better coaching and reduces repeat issues.

Client: Instacart

Role: Lead Designer

Service: Product design, User Experience & UI design

Previous design limitations

• The original order issue flow lacked the structure and detail needed to validate the legitimacy of requests.
• It didn't support item-level granularity or evidence collection, which meant we couldn’t confidently determine the accuracy of claims—or offer partial appeasements when only part of an item was affected.

The New Order Issue Flow Experience

We redesigned the order issue reporting flow to support item-level granularity and richer context—making it easier for customers to report what went wrong, and easier for Instacart to make accurate, defensible decisions.

Item-First Mental Model

We restructured the flow to align with how users naturally think about order problems: they recall the item first, then the issue.

• Mirrors how customers mentally recall order issues.
• Reduces cognitive load by anchoring the experience around specific products.
• Allows for multiple, diverse issues to be reported in a single, seamless flow.
  

Context-Aware Issue Options

The new flow dynamically surfaces issue types that are directly relevant to each item, based on its fulfillment type (e.g. found vs. replacement) and attributes. This ensures customers only see appropriate issue categories—for example, "Does not match my preference" for replacements or "Melted or thawed" for damaged items.

This improvement:

• Reduces the chance of user error by removing irrelevant options.
• Increases accuracy and consistency in reported issues.
  

Evidence Collection for Specialist Review

Customers are now prompted to upload optional image evidence when reporting issues like damaged or spoiled items. This visual proof serves two critical functions:

• Enables specialist review to validate complex or high-risk claims before issuing appeasements.
• Feeds into shopper performance management, allowing Instacart to coach or flag shoppers when patterns of poor fulfillment emerge.
  

By building in lightweight evidence collection, we strengthened both the fairness of appeasement decisions and the accountability of the fulfillment experience.

Business Impact

• Achieved a significant reduction in appeasement spend per order, driven by improved issue accuracy and fewer invalid reports.
• Delivered a net cost-per-order improvement through the combined impact of the redesigned reporting flow and accessibility enhancements.
• Maintained customer retention and engagement, with no negative impact on key metrics like order frequency or order size.