Digikala-Seller platform optimazation(Case study)

Digikala Seller Central

Digikala seller central is a platform that allows the seller to start selling in Digikala where millions of customers are shopping every day. It was a new concept in Digikala with new challenges.

Team: Ala Davoudi(Ux Expert), Mohammad Ghaderi (UI Designer), Reza Hamzeh (Product Manager),

My Role: Competitor analysis, User Research, User interview, User story, Design refinement, Wireframes and prototyping, Usability testing, Information architecture, Analyse heat maps and recording sessions

Tools:  Pen and paper, Sketch, Axure, Invision, Crazyegg, Google Analytic, Convert

Company methodology: scrum

Overview of the challenges

The Digikala seller platform was faced too many problems with usability and many complain came to a customer service center for UX problems. Improving the usability of seller platform and create a seller acquisition process were my hot challenges.


Discover Product and the problems

At the beginning of my optimization process, I’ve started to speak with seller supports to find out the seller problems. I’ve written them as a note. I’ve checked all the issues that reported to the seller service center. Kick-off meeting, check out what are concentrates and blockers were another way to discover problems and be aline with the team and KPIs.


Competitor analysis

Research about competitors helped me to know about their products map and the existing feature in their products.

I found out how our competitor could overcome the problems? What were their solutions?

How can I improve the solutions?


Research phase

• Interview

I conducted interviews with sellers who had many problems and reported them to the seller support center. I tried to understand sellers by having deeper sight into their behaviors, needs, motivations, and fears.

Focus group

I bring seven sellers together to discuss issues and their concerns about the feature of the seller dashboard. It takes about 2 hours.

GA analyze

I have used GA during the research phase.

The bounce rate, exit rate, user flow report, average time on page and device usage were essential factors for me.

From bounce rate, I found out which pages were performing poorly and where should I optimize and improve,

From exit rate, I discovered where sellers were engaged enough to continue and where sellers were dropping off,

With user flow report I compare our ideal user flow to what is taking place

From average time on page, I  understand which pages our sellers were spending their time and where they were dropping off or leaving quickly. Was it a natural behavior as we wanted in the seller platform or not?

From device usage, I understand 45 % of our users are using their mobiles to check their new orders or even add a product, but they become bounce during the process and its a pain point for them.

Heatmap, Scrolling, Mouse movement, and recording sessions

Heatmaps showed me where the sellers click. I detected where sellers think that something was clickable, but it was not! With analyzed scrolling, I found out how often sellers scroll down, and with analyzing mouse movement, I detected what sellers were looking for and where they were going next. The recording sessions were so useful for me to discover how the sellers interact with seller panel. I find out many problems during this process.


Analysis research

Customer journey map /empathy map

I went through my notes and created an empathy map and customer journey map.


For reminding the seller’s needs in the team, the persona can help us. I make four personas based on my research phase and share them with other team members, all of us in the team understand what the main goals and frustrations for our sellers are and how they differ within disparate groups.


Card sorting

As I found in my research phase, the sellers had many problems in discovering and understand navigation menu.especially when they are new in our platform.

I’ve used the open-card sorting technique to find the best information architecture for the navigation menu. The results provided us with new patterns into both the categories breakdown and their naming.



After analyzing data, and finding new features to make the seller platform optimize. The first draft was made with pen and paper. Then, I’ve moved to Axure where I create the low fidelity wireframes.


Check the design

After finishing the low fidelity wireframes, in a meeting with PM, PO and design team we checked the design, Do the designs cover all of the aspects? In this phase, we had several times changes.


User Stories

I used user stories to build a common language and a common mental model of what the seller’s concerns are about.

I focused the end goals on concrete and tangible things that the platform should let the seller do.

As a seller, I want to quickly review stock, so I can control my inventory.


Delivery to the tech team

The screens were uploaded in Invision so that the tech team could have a better understanding of the user flows. I recreated the transition in the Principle. And explain about design in detail for the best implemented.


Test and Mesure

Usability testing

I carried out a usability test with five sellers. The usability tests helped us to assure a smooth UX.

A/B testing

With the help of the technical team, we could test our hypothesis as A/B tests variation, A/B test helped us to learn more about users behaviors.

• Check the GA

Check user funnel


From the changes, we increased

Accessibility, findability, and learnability of seller platform  50 % improved.

The calls to the seller support center 76 % decreased!!