Repackaging Mobbin to minimize redundancy and bloat

CONTEXT

Mobbin is a product + design inspo repository that aims to ensure a hassle-free browsing experience - one that's intuitive to visitors w/o compromising the grasp of experienced users.

TEAM

Rishi Sankhyayan (Designer)

STATUS

Concept

Design decisions that hinder effortless browsing:

Encouraging simplicity for gathered (not scattered) navigation

Every browsing path on Mobbin is governed by the user's platform of choice - iOS, Android or Web. It's rational but its current presentation is indiscreet and enforces scattered decision-making. Omitting filler elements (like 'Discover') and unifying navigation tabs helps consolidate browsing decisions to a singular coherent space. Said coherence also nullifies any overspilled redundancies.

'One thing at a time' as a design philosophy.

Content on Mobbin is denser than Pinterest, Savee.it, and Cosmos. Diluting the background when a user initiates interaction w core elements minimizes cognitive load and eases focus. Additionally, leveraging trays helps tuck away stuff that doesn't require immediacy. The idea is to only showcase actions when the user demonstrates interest in them.

Ensuring (not enforcing) white space

Mobbin is perceived as a library (not an exhibition). Visitors have an idea of what they want before they arrive. They search for it and if they don't find it… they leave. Ensuring success in said workflow means introducing the user to the content they're looking for asap.

The proposed design offers value upfront w/o neglecting spatial symmetry. It splits all folds b/w addl info on the left (sticky) and the screens. No matter how much a user scrolls, critical browsing actions are within reach (unlike the current design). This approach caters to the user's true motive (viewing screens asap) w/o enforcing excessive white space in the viewport.

Localized + miscellaneous value

Addl tidbits to keep browsing on Mobbin informative, delightful, and compelling.

Afterthought

A product/feature is more likely to be adoptable if it's A) Designed to complement its user's incentives and B) Accurately predicts what might matter to them tomorrow.

Rishi Sankhyayan EmailLinkedin