Empowering car sellers by letting them directly auction their car to dealers and get complete visibility on car selling journey behind the scenes.
Figma, Miro, Sketch
UX Design, UI Design, Illustration, Prototyping
Contribution
Collaboration with the product analytics, tech, business, marketing, operations teams.
Skills and Tools
Team
2 Designers(including me)
Following numerous iterations and collaboration with Product Managers, Developers, and Testing teams, the feature was ultimately launched for our users' utilization.
The feature was introduced as an experiment to 25% of users, aiming to analyze user behavior and assess the impact of our designs.
Final Designs
Result
Direct Auctions: Full Visibility of Your Car Selling Process
UX DESIGN | RESEARCH | PROTOTYPING
SUMMARY
What is Direct Auctions?
Direct Auctions is a feature enabling car sellers to auction their vehicles directly to Car Dealers within OLX’s network. This benefits both parties involved. Dealers gain access to detailed information on cars to bid on, while sellers receive immediate visibility into the offered price. By bypassing intermediaries, this system enhances user trust in the platform.
OLX Autos is an online Car trading platform. User can sell their Car, buy one from the car listings from the platform or get their purchase financed by OLX. Selling, Buying and Finance are the three verticals OLX Autos deals with. They have Android, iOS as well as Web platforms.
About OLX Autos
Seller comes to OLX
Approximate quote provided
Final price offered
Books a car inspection
Existing process
Analysing the existing process for opportunities to increase trust and transperancy
Seller fills all the car details: Self Inspection
Let’s look at the existing flow to dig deeper and identify areas of intervention.
Identifying opportunities
Users appreciate getting the chance to Negotiate, something thats missing in online experiences.
Drawing from our experience with car sellers, we endeavored to pinpoint potential areas for improvement by scrutinizing the end-to-end flow and contrasting it with on-field practices.
Users show lack of trust towards the pricing models as how we arrived at the final quote is not transperant.
For users the most important factor is the final price offered. Users always compare prices across different platforms and will choose the best price offered for their car.
After this, the entire process becomes offline, making it difficult to keep users engaged beyond this stage.
Users aren't certain if this is the best price available, so they might leave and check other platforms.
If users don't like the price, they're likely to leave without scheduling an inspection.
Stage: Approximate quote offered
PART 3
Let users sell directly to dealers
Give a sneak into how price is generated
We considered allowing users to express dissatisfaction with the offered price and also propose alternative offers.
Letting the users negotiate the offered quote.
PART 2
After conducting interviews with inspection engineers and dealers, we identified additional information that should be incorporated into the existing data collection:
Additional car photographs from all perspectives.
Comprehensive details regarding any dents and scratches.
Inclusion of interior car photographs.
Adjusting the information collection flow to provide dealers with sufficient details, thereby bypassing the need for an inspection process.
Solution Ideation
PART 1
Designing for transparency of process and letting users directly auction their car
Enable users see track their entire end-to-end process
Current process: The OLX algorithm generates an approximate price, and after the inspection, the cart details are shared with the dealers' network. Dealers bid on the car, and the highest bid wins, determining the final price offered.
Approximate quote provided
Auction your car directly to dealers
Additional information capture
USER FLOW
Seller comes to OLX
Seller fills all the car details: Self Inspection
New Experimental flow
new
new
new
new
Final Price
Books a physical car inspection
Negotiate offer price
Explorations around how to capture additional photos
Explorations for different ways of introducing the auction proposition
DESIGN CHALLENGE
Low Fidelity Designs and Exploration
How do we design for a complex auctioning process?
The design challenge was to simplify the concept of auctioning a car to dealers so that users can easily grasp the process and participate effectively. Additionally, it's difficult to retain users through a slightly longer flow. To address these challenges, we implemented several design interventions.
Final Designs
Introducing the auction proposition
approximate price
value proposition of direct auctioning
clear CTA to start
explanation of the auction process to help people be informed
Additional images captured
previous image capture requirement
new image requirement
new
Designed special stencils to help users capture photos accurately
Provide end to end process tracking
Helping users have complete visibility of their car selling process
Letting users negotiate the quote online after dealers have bid on the car
if offer accepted
The expectations provided by the user are noted and visible.
A new quote is offered. They can choose to accept or reject it.
Users can provide a counter offer if they do not accept the auction offer. Use cases accounted for:
If user provides a counter offer within 15% of the offered price we give positive feedback that the chances of getting the desired price are higher.
If user provides a counter offer more than 15% of the offered price we give negative feedback that the chances of getting the desired price are lower.
If user mistakenly provides a lower value counter offer we let the user know that.
if offer rejected
Results
After a lot of iterations, collaboration with Product Managers, Developers and Testing teams, the feature was finally launched for our users to use.
The feature was launched as an experiment to 25% users to analyse user behaviour and impact of our designs.
How might we design the flow to give users more visibility and transparency on the price offered?
How might we enable OLX to give the best and more accurate price?
How might we let the user have a chance to negotiate?
What Problem are we trying to solve?
PROBLEM STATEMENT
I believe in the enchanting power of good design, capable of weaving magic into every experience. Let's work together and make magic!
Feel free to drop an email at mrunal.dhaygude@gmail.com.
MRUNAL DHAYGUDE
Direct Auctions: Full Visibility of Your Car Selling Process
UX DESIGN | RESEARCH | PROTOTYPING
Empowering car sellers by letting them directly auction their car to dealers and get complete visibility on car selling journey behind the scenes.
Contribution
Collaboration with the product analytics, tech, business, marketing, operations teams.
2 Designers(including me)
Figma, Miro, Sketch
UX Design, UI Design, Illustration, Prototyping
Skills and Tools
Team
SUMMARY
What is Direct Auctions?
Direct Auctions is a feature enabling car sellers to auction their vehicles directly to Car Dealers within OLX’s network. This benefits both parties involved. Dealers gain access to detailed information on cars to bid on, while sellers receive immediate visibility into the offered price. By bypassing intermediaries, this system enhances user trust in the platform.
Final Designs
Following numerous iterations and collaboration with Product Managers, Developers, and Testing teams, the feature was ultimately launched for our users' utilization.
The feature was introduced as an experiment to 25% of users, aiming to analyze user behavior and assess the impact of our designs.
Result
OLX Autos is an online Car trading platform. User can sell their Car, buy one from the car listings from the platform or get their purchase financed by OLX. Selling, Buying and Finance are the three verticals OLX Autos deals with. They have Android, iOS as well as Web platforms.
About OLX Autos
Existing process
Seller comes to OLX
Approximate quote provided
Final price offered
Books a car inspection
Seller fills all the car details: Self Inspection
Analysing the existing process for opportunities to increase trust and transperancy
Let’s look at the existing flow to dig deeper and identify areas of intervention.
Identifying opportunities
Users appreciate getting the chance to Negotiate, something thats missing in online experiences.
Drawing from our experience with car sellers, we endeavored to pinpoint potential areas for improvement by scrutinizing the end-to-end flow and contrasting it with on-field practices.
Users show lack of trust towards the pricing models as how we arrived at the final quote is not transperant.
For users the most important factor is the final price offered. Users always compare prices across different platforms and will choose the best price offered for their car.
After this, the entire process becomes offline, making it difficult to keep users engaged beyond this stage.
Users aren't certain if this is the best price available, so they might leave and check other platforms.
If users don't like the price, they're likely to leave without scheduling an inspection.
Stage: Approximate quote offered
How might we design the flow to give users more visibility and transparency on the price offered?
How might we enable OLX to give the best and more accurate price?
How might we let the user have a chance to negotiate?
What Problem are we trying to solve?
PROBLEM STATEMENT
Let users sell directly to dealers
Give a sneak into how price is generated
Solution Ideation
PART 1
Designing for transparency of process and letting users directly auction their car
Enable users see track their entire end-to-end process
Current process: The OLX algorithm generates an approximate price, and after the inspection, the cart details are shared with the dealers' network. Dealers bid on the car, and the highest bid wins, determining the final price offered.
PART 2
After conducting interviews with inspection engineers and dealers, we identified additional information that should be incorporated into the existing data collection:
Additional car photographs from all perspectives.
Comprehensive details regarding any dents and scratches.
Inclusion of interior car photographs.
Adjusting the information collection flow to provide dealers with sufficient details, thereby bypassing the need for an inspection process.
PART 3
We considered allowing users to express dissatisfaction with the offered price and also propose alternative offers.
Letting the users negotiate the offered quote.
Approximate quote provided
Auction your car directly to dealers
Additional information capture
Seller comes to OLX
Seller fills all the car details: Self Inspection
New Experimental flow
new
new
new
new
Final Price
Books a physical car inspection
Negotiate offer price
DESIGN CHALLENGE
How do we design for a complex auctioning process?
The design challenge was to simplify the concept of auctioning a car to dealers so that users can easily grasp the process and participate effectively. Additionally, it's difficult to retain users through a slightly longer flow. To address these challenges, we implemented several design interventions.
Explorations for different ways of introducing the auction proposition
Low Fidelity Designs and Exploration
Explorations around how to capture additional photos
Final Designs
Introducing the auction proposition
approximate price
value proposition of direct auctioning
clear CTA to start
explanation of the auction process to help people be informed
Additional images captured
new
previous image capture requirement
new image requirement
Designed special stencils to help users capture photos accurately
Provide end to end process tracking
Helping users have complete visibility of their car selling process
Letting users negotiate the quote online after dealers have bid on the car
if offer accepted
The expectations provided by the user are noted and visible.
A new quote is offered. They can choose to accept or reject it.
Users can provide a counter offer if they do not accept the auction offer. Use cases accounted for:
If user provides a counter offer within 15% of the offered price we give positive feedback that the chances of getting the desired price are higher.
If user provides a counter offer more than 15% of the offered price we give negative feedback that the chances of getting the desired price are lower.
If user mistakenly provides a lower value counter offer we let the user know that.
if offer rejected
Results
After a lot of iterations, collaboration with Product Managers, Developers and Testing teams, the feature was finally launched for our users to use.
The feature was launched as an experiment to 25% users to analyse user behaviour and impact of our designs.
I believe in the enchanting power of good design, capable of weaving magic into every experience. Let's work together and make magic!
Feel free to drop an email at mrunal.dhaygude@gmail.com.
Mrunal Dhaygude