Improving the Product Discovery - Search

Overview

Product Discovery is an extremely important aspect of any e-commerce application, which allows the customers to find and purchase the desired product. Inspite of the brand gaining attention, the search feature was not able to cater to the customer requirements as desired. Our goal was to identify the problem and assist our customers to achieve a fulfilled shopping experience.

Project Info

Feature Design

Tools

Figma
Miro
Microsoft Clarity

Timeline

Jan 2021 - Feb 2021
5 weeks

Status

Production

My Role

I was the primary Product designer for this project and checked in regularly with the other designer on the team and other stakeholders. The niche context of the project required close collaboration with the content strategist and the developers.

Design

Designed concept low-fi wireframes, refined features and designed high-fi prototypes.

Research

Conducted competitive analysis of the search query formulation.

UX Benchmarking

Analyzed the task completion rate using the search module, Led the current system audit, Conducted usability test for the proposed solution.

Problems with the MVP eCommerce Search

Users were struggling to find products using search

  • System was failing to respond to non-product specific user queries.
  • No auto suggest to assist the users
  • User queries included keywords in local languages

solutions with the redesign

Unification of visual, interaction patterns

We are providing an informed visual and interaction pattern to enforce the natural behavior of the users towards the search. It has been understood that queries entered in search bars are primarily used for navigation, finding information. The redesign of the search is about providing a well defined copy and iconography resonating a informed and natural rhythmic flow.

Grouped Suggestions

We are separating the suggestion list for the input query into different groups based upon the content of the QF( Categories, Products ). This separation does not mean different results but highlights the differences in the information types, effectively reducing the visual noise.

Typo-Resistant Search Suggestions

We bringing accurate & meaningful content to our customers. The new search enables seamless onsite search, minimizing discovery effort, even when customers make a mistake. With an aim to reduce the bounce rate the new search QF suggestion gives result even with unmatched relevant query input reducing no results.

Local Language QF Results

We are introducing a multi-lingual Search to handle 10+ different local languages. This means we reframes entire search framework to handle multi-lingual query input and provide relevant results. But does not change the way we search, the new design simply understands the input type and provides QF results with balanced copy anticipating customers intent.

Approach

Identifying the problem

We conducted UX audits to examine the performance of each module for the current platform. We used Heatmaps and Session Recordings of the users using Microsoft Clarity.

UX Audit

Analyzing the existing workflow

Why the existing system failed

Perfect Query Input

Despite having a fully functional MVP search, it did not fulfill the needs of our customers. The current system work well for ideal use cases, but in reality our customers are not aware of the offerings by the brand and hence required the eCommerce to assist the customers find information.

Zero Search Results

Today internet users are supported by intelligent systems which are focused towards solving problems for human. The onsite search supporting The Nature's Bowl eCommerce was set to index exact parsed query input which works perfect for exact query match and does not tolerate any human error. Customers need to be precise in order to use the tool. Also, the current design did not incorporate any error feedback experience, this degraded the perceived quality of the brand.

Competitive Analysis

Understand the approach taken by our competitors

After getting a fair understanding of the current search feature and learning about the issues faced by our users, we undertook the task of understanding the approach taken by our competitors.

Explorations

Workflows to validate our hypothesis

Based on the issues identified and the observations from the competitive analysis, we started brainstorming solutions for the targeted issues.

1. Non- Product specific query results

As someone with no familiarity with the product range, I would want to explore the range of product offered by the brand using my limited knowledge

Proposed Workflow

2. Search Suggestion and Typo- Correction

As someone who frequently uses various search engines, my objective would be to find the desired products with minimal efforts.

Proposed Workflow

3. Multi-Lingual Support

The goal of this framework is to make the product discovery and search experience intuitive by incorporating multi-lingual keyword search assist in order to increase the sales conversion.

Proposed Workflow

Final Design

Guiding customers straight to the products they’re looking for with an enhanced eCommerce site search.

Reflections and Takeaways

Some of the key takeaways through this project

  • Learning about the user requirements and their goals, to fulfill these needs through designing the experience of the application
  • Work in a faced paced environment to finish deliverables by setting timed goals and accomplishing them.
  • Working in a direct collaborative environment of cross-functional teams of designers, developers, marketing, content and project owners.
  • Importance of a collaborative iterative process of design. During this project I learned to question myself about my every design decision and to see what could be done to make this more efficient.

Thank You