I joined as the 2nd content designer, just as the company was dealing with an exponential demand surge due to the pandemic. Over 3 years, my projects included feature launches on both the customer and shopper apps, as well internal initiatives like content standards and a revamped candidate assignment (that helped grow the team to 15 in just one year).

ProblemIn late 2023, Instacart made changes to how batch pay was calculated. These change increased pay for some batches, but many batches (ones that were smaller/easier) suddenly paid much less.
Solution: To offset the optics of this change, and provide something more positive to mention in the press release announcing it, my team created a feature that would nudge customers to tip higher when the weather was bad.
Customers saw messaging and visuals that were customized to the current weather, and shoppers saw messaging letting them know to expect higher tips at that time. Importantly, this feature was only implemented when the weather was still considered safe—serious weather still shut down the ability to order or shop.
Result: In our experiment, this feature increased the average tip by nearly 10% (rel).

The assignment: Update and propagate the existing ‘quality guarantee’ offered by Instacart.
The hypothesis: Better explaining our existing appeasement policies (e.g., via an order-level “satisfaction guarantee”) will improve activation and early user retention.​​​​​​​
Existing quality guarantee was only found on item detail pages, giving it limited discoverability (since most customers shopped from item cards), and also limited scope. 
Our first exploration (not launched) articulated the guarantee differently. It was better, but still too focused on explaining Instacart vs. focusing on the guarantee (the third bullet).
My product designer and I brainstormed various ways we might reframe the guarantee. I was particularly bullish on the 'Thumbs-up guarantee' since it felt more unique and human, and aligned with how customers were to rate shoppers. But our UXR participants preferred clarity. 
Once we landed on final language, we launched the new guarantee across many surfaces—storefront, item details, cart, and checkout. 

A couple Slack screenshots showing the excitement of our data scientist upon seeing the results!


As we planned to scale the team, I redesigned our team take-home assignment to make it more clear, and also abstracted from actual Instacart work. It helped us evaluate dozens of candidates, and scale from 4 to 15! I later wrote a Medium article for our team blog about the redesign.
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