Engelbart Design - Amazon Pharmacy

Summary

Customers should have the best possible pricing and insurance coverage information to commit to sign-up for Amazon Pharmacy (AP), make an informed prescription chase decision, and make a fully informed purchase decision before cart, especially given our desire to drive competition (e.g., 3P vs 1P, coupons, Prime Rx etc.) on featured offers - enabling pharmacy to be "shoppable" like any retail category. Customer feedback post the general availability (GA) launch of AP has highlighted pricing visibility as a key customer expectation and point of friction with the current experience. 50% of post-GA feedback has been related to pricing and, from the latest customer feedback survey, 40% of customers didn't initiate a chase after signing up because they wanted to understand pricing. To address this complexity, give customers choice and transparency while simplifying decision making, and face out prices which are meaningful to the majority of customers, we will enable an insurance pricing experience in 2021.

Tenets

With all of my projects, I track key decisions that I revisit for all presentations, in order to make sure all stakeholders are aligned or if they have alternative suggestions or debate that needs to be had. For Insurance Pricing, the tenets we arrived at were:

Lean into lowest prices: We will default to form/strength with the lowest price. For Prime customers this should be the lowest Prime Rx unit price, for NPA or cases where the Prime price isnt present this should be the lowest U&C unit price.
Bias for prices, not perfection: We are proposing to build on what we launched for GA + test/provisional claims. We’ll layer on a payer API, once available.
Make it scalable for future feature launches: We have 2 related projects (Flex supply, EDS) that this project should build toward.
Simplify where possible: We removed form, strength, and prescriber from the chase flow, in lieu of corresponding twisters on the MIP.

Scope

Introduce dynamic cash AND insurance pricing based on N number of presciption attribute variations (i.e. strengths, forms, supply, etc.).
Allow for required elements, like prescriber and insurance information to be input before pricing can be made available.
Allow for 4-6 second delay in running new insurance costs (until ML model could be build to provide estimation/formulary, without calling Insurance company).

Iteration

Given that there wasn't really anything like it in the market, I utilized existing Amazon frameworks and best practices around the "buy box" to provide the clearest messaging. I always try to aim for as many concepts as possible, give them unique mnemonics to keep them straight, and provide pros and cons to objectively narrow to the best options (see below). This recommended idea then is floated around to management and leadership to continue vetting it's viability. In this case, option 3 was agreed upon and we continued forward.