Huddling For Community and PMF

Huddling For Community and PMF

I joined NPE at a critical time for the Huddle team. The app’s first iteration of was not landing in user testing and beta versions released to dog-food groups saw very low engagement – so we scrapped it. As the Design Lead, I jumped right into workshopping with the team, questioning assumptions and designing new 0-1 frameworks, user journeys, and interfaces from the ground up. The end result was a deeply resonant community-based, bespoke social-goaling experience that slotted naturally into the norms of our core audience – Black women and people of color.

Type:

0 - 1 Design, UX Strategy, Research

Role:

Lead Product Designer

Timeline:

8 weeks

Team:

UX, Eng, Dispensary Staff

Read time:

3m

Between canna-lingo & unmapped attribute data, we had our pipes full.

Between canna-lingo and unmapped attribute data, we had our pipes full.

Between canna-lingo and unmapped attribute data, we had our pipes full.

Between canna-lingo & unmapped attribute data, we had our pipes full.

THE OBSTACLE OF LANGUAGE AND WAYFINDING

Emjay customers, connoisseurs and novices alike, were having difficulty finding products and understanding which products met their consumption preferences. Regulation requires packaging to have much more data than the average retail product, however, that language is objectively complex and difficult to derive personal meaning from. Still, very little of the available data was being captured in Emjay’s databases or surfaced to customers unless shopping in-store at Emjay.

SOLVING THE LINGO GAP

Filter Mapping - Audit product metadata by SKU, category, and consumption method, scaling shared attributes across categories as quick filters.

Plain Language & Usefulness - Make filters useful by using plain language for key attributes and convey use-case wherever possible.

Buoy Important Info - Push the most important details to the surface showing them early, often, and contextually.

Searchable Menu - Give connoisseurs and product-focused customers a direct path to their destination.

Proper makes perfect… (partnership).

Very early on I recognized Proper, a company who at the time focused on cannabis reviews and were a good friends of our founder, did plain language and human-centered use cases pretty well. I knew there was much we could learn and much we could share. With our newly mapped product data and Proper's vast database of cannabis reviews – how cool would it be to collaborate on getting the right products into the hands of people looking for them? I designed strain cards to live in product detail pages as a way to surface effects data with well-placed and friendly education powered by Proper.

Let's see it all in the wild…

The trick with e-comm is not to give in to the Amazon.com model of throwing everything everywhere all at once.

Striking a balance between the wealth of meta-data available from mapping and the deficit of detail from where things started, I began to layer in attribute and usage data into product tiles, filter panels and menus across browsable surfaces.

From there I expanded the framework into product detail pages and worked with engineers to establish a user-generated attribute component allowing us to pull in user's real words from reviews, surfacing them to other users looking for insight and training our own systems to read and capture new language – bringing the effort full circle.

Results

Numbers in the trailing months took a steady climb upward, while calls about product mismatch or dissatisfaction to the Customer Support line meant to field account and delivery questions saw a decline.

+26%

+26%

Increase in conversions

+4

+4

Point increase in CSAT to 81 (new high)

1M

1M

Accelerated path to

1 million deliveries completed

Let's

📟

Talk

© 2088 Nayzak Design

Let's

📟

Talk

© 2088 Nayzak Design

Let's

📟

Talk

© 2088 Nayzak Design