Relocation of job
Relocation of job
A relocation occurs when you move to another city or state for a job. People relocate for jobs every day for a variety of reasons. A relocation takes a lot of thought and planning. Fortunately, you can take certain steps to evaluate whether a job-related move is right for you. And, if it is, you can begin to plan for your next home.
A relocation occurs when you move to another city or state for a job. People relocate for jobs every day for a variety of reasons. A relocation takes a lot of thought and planning. Fortunately, you can take certain steps to evaluate whether a job-related move is right for you. And, if it is, you can begin to plan for your next home.
Redesign To Make Search Experience Better
Search is an AI-driven eCommerce search platform that understands shoppers’ intent and connects them to the products they are most likely to buy — across purchase journeys
OVERVIEW
The Search Console optimizes e-commerce search by providing insights, relevance tuning, and merchandising controls.
Key Features:
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Search Analytics: Tracks queries, conversions & zero-result searches.
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Relevance Tuning: Boost, bury, or pin results; AI-driven query intent.
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Merchandising: Rule-based promotions, filters, and banners.
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A/B Testing: Optimize ranking strategies with experiments.
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Real-time Monitoring: Alerts for anomalies & performance tracking.
MY ROLE
Senior UX designer
Usability testing, User Research, Interactive Prototypes, System design, High-Fidelity Mockups
Jan 2019 - Dec 2020
CONTEXT AND MY ROLE
When I joined the product team, a version of the search console was already in place. After engaging with business colleagues, I gathered their insights on the search domain. User analytics revealed that 20% of users churned during the onboarding process, while others cited a lack of trust and the absence of impactful new features.
This prompted me to take a deep dive into the entire process as it was currently structured.
Collaborating closely with a team of Six engineers, one product manager, one data scientist, and 1 designer (the other 2 designer was involved in other products), I took the lead on developing the autosuggest, help documentation for search, Feature a glance (help user to make it self serve)Searchable facets and algorithms. Did a navigational change to improve space.
The Problem
CHALLENGES TO BE SOLVED
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Non-scalable design interface which can’t grow with the customers’ requirements.
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Onboarding use to take 3–4 months for new customer which result in churning
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Retention of customers as building new features use to be the pain points
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Building trust in the customers.
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In Information layout can be well arranged so it is easier to read for end user. The left navigation is occupying left column of your page.
USER ANALYTICS DASHBOARD
User Research
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To understand their behavior, need
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How to shape the business use case with the user needs
APPROACH
Meaningful Experience
Whenever a user types a query and giving a relevant result is a cumbersome task. Understand each shopper’s intent by understanding every word in the search query. Site Search uses a Machine Learning model — Named Entity Recognition (NER) — which tokenizes each search query to map it to the desired attributes and return the most relevant products with high precision. It goes beyond simple text-pattern matching techniques.
For Example - Integrating very closely with the Lenskart interface to enhance the seamless experience between offline and online, ensuring shoppers are able to see and buy the most relevant product every single time they visit the site.
Lean UX Method
I went ahead with the agile approach process which emphasizes rapid sketching, prototyping, feedback from stakeholders and design mockups. This helped in meeting the deadlines and keeping a constant flow of design screens and feedbacks.
OBSERVATIONAL RESEARCH
Using the observational research method, we captured farmer’s behavior in their natural environment. It helped us directly look at what farmers are actually doing, what kind of routines they could have with the application, and how the application can be used in different contexts of their lives.
Search domains are very complex. Giving the right information to the user is a huge task. It was very important to take a few knowledge transfer sessions with the stakeholders to understand the product and the pain points. Also, to design an optimal. (Without harming the existing customers was another challenge) doing a persona study, competitive analysis of the market into the same business was a necessity and users asked.
Insights
After UX research, Search Console Insights help validate and refine search experiences by providing data-driven analytics on user behavior. It tracks query performance, click-through rates, and conversions, identifying opportunities to enhance relevance and reduce friction. By analyzing zero-result searches, engagement patterns, and AI-driven query intent, businesses can optimize product discovery and improve search efficiency. These insights enable continuous refinement through merchandising strategies, A/B testing, and personalization, ensuring a seamless and conversion-driven search experience.
New prospect engagement
You can extract and engage new prospects by offering the most compelling, easy to use tools designed for customers as a self-serve tool.
To win the trust of the product
Whenever there a query in a search box written a lot of AI works happens at the backend. To make the user know what exactly happening to their search query, the Algorithms function was brought upfront. Also, the immediate preview of the console brought upfront which helps the user to see their results. In Parallel to as a next step we do Search, Autosuggest and Category Pages integration. Showing it upfront in UI was another challenge.
Easy onboarding of customers
The challenge comes when a customer takes 3 — 4 months because of feed induction as a result of a complex catalogue.
Execute
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To understand their behavior, need
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How to shape the business use case with the user needs
KEY FEATURES DEVELOPED
Navigational Change
We shifted from the left navigation to the top navigation. (When it comes to designing for users, context is king.)
The main reason for the change was because:-
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Space - It conserves more vertical page space than left navigation. With left navigation, the navigation links occupy the left column of your page. This shrinks and narrows the content area of your page, which means you will have less space for your content.
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Scanning - The top navigation forces a horizontal scanning direction that people often use when they’re reading. While the left navigation also facilitates a vertical scanning direction
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Visibility - Top navigation items are more visible because they are always above the fold and are easier to find.
Websites with Specific Topics and Interests
Product Branding
Branding, at a high level, is a promise to your customer. A promise that lets the customer know what to expect. A promise that informs how you will look, speak and act.
Earlier version
New version
Autosuggest
This feature provides query suggestions that appear when shoppers start typing their intended query in the search bar. Having a query suggestion enhances a shopper’s search experience once by: Ranking Suggestions, a Variety of Suggestions, Engagement Insights
To do this, I ensure that whatever a user does, they can see the result immediately. As we read from left to right. I have taken that principle in my design too.
Searchable fields & Facets
Searchable Fields define which product attributes (e.g., name, description, SKU) are indexed for search, ensuring relevant results. Merchandisers can prioritize key fields to refine search accuracy.
Facets enhance filtering by allowing users to refine search results based on attributes like price, brand, category, or ratings. Dynamic and rule-based facets ensure a personalized and efficient browsing experience, improving product discoverability and conversions.
Algorithims
Site Search uses AI and ML algorithms that monitor purchase behaviour and self-optimize to connect shoppers to products that they are most likely to buy.
AI-driven search algorithms optimize relevance by understanding user intent and ranking results dynamically.
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Query Understanding: Uses NLP to process keywords, synonyms, and spelling corrections.
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Relevance Scoring: Weighs factors like keyword match, popularity, and personalization.
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AI-Powered Ranking: Adjusts results based on engagement, purchase history, and real-time behavior.
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Contextual & Semantic Search: Understands meaning beyond keywords for better accuracy.
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Merchandising Rules: Allows boosting, burying, or pinning products to influence ranking.
Parameters
Choosing right method
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The feature/product we're testing
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The type of data we’re looking for
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The design stage
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The time and resources are available
Tree testing
As we are redesgning the process we started taking up this process. It was helpful to employ tree testing as a method when adding new features, particularly alongside card sorting.
Sketched task flows to understand where new features would fit in the interface and created mockups
For each new feature, I sketched user flows based on the tasks and scenarios. They helped me understand where these features would fit in the existing interface. Based on this understanding, I created mockups for the new design.
Outcome
Below are samples of a few of the screens of the entire application.
REFLECTION
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Created a self serve journey for the users but introducing Feature at a glance
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More intuitive and easy to use for end customers.
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Every screen has the auto assist feature to glance.
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Customizations requirement to the user is also taken care
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Probability to sell AI or any other feature as a separate layer is also taken care of.
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Created a seamless responsive site, journeys become more predictable and more comfortable assisting task completions and conversions.
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With the help of "X product" (Name changed), catalogue feed upload became easy and intuitive which can work in a week time.
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The whole design moved to the top navigation. Top navigation conserves more vertical page space than left navigation. With left navigation, the navigation links occupy the left column of your page. Top navigation, however, uses minimal vertical space, which allows you to occupy the content area of your page with content only.
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Causality in feature level had been maintained.
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Revamp the whole product architecture. Creating a common interaction and design language across all other product and documentations.