trelora
messaging
filters

Helping real estate agents find important details faster so that they don’t lose clients’ trust

The problem

Real estate agents were spending too much time searching for details

MyT is a home-grown CRM system that helps high-volume real estate agents track the status of the transactions in their book of business. Trelora agents were spending too much time searching for information in the messaging module, which affected the response times, the NPS, and caused agents to make mistakes when processing deals.

The solution

Bookmarking and additive
filters give immediate context and flexibility

The final design featured bookmarking (starring) messages and additive filters and was a part of a global redesign of the messaging module. After several prototypes, we arrived at the solution that allowed the maximum flexibility to agents, allowed them to find the information faster, and reduced the transaction page's loading time.

Team

As a sole designer, I collaborated with a Front-End Engineer and Product Manager

Tools

Sketch, InVision, Adobe XD, Miro

Timeline

Mar 2020-Apr 2020

User interviews
Wireframing
Prototyping
UI design

User research

From the research, we knew that agents were using messaging feed as a unified source of information about the deal. Texting with clients, agents would learn details about the property and update their teammates about the progress. Frequently, a message contained an answer to a common question, and agents would be searching for the same information multiple times a day. Other times, unable to find answers, they'd ask clients repeatedly about the same things, 
which caused frustration.

28+

user interviews

14+

contextual inquiries

20+

cognitive walkthroughs

Design iterations

After observing agents go through the same flow repeatedly, we had a lot of ideas: we could improve the search functionality or allow agents to add essential messages to the notes section automatically. However, after evaluating tradeoffs and technical challenges associated with different options, we decided with the most lightweight solution – allowing agents to bookmark, or star messages so they could quickly return to those later.

3+

iterations with user and engineering feedback

5+

prototypes

20+

usability tests

Iteration 1

Add bookmarking

If agents repeatedly go back to the same messages, can we allow bookmarking messages so that they can find information faster?

Bookmarking would be helpful: instead of searching through all of the messages, I’d just bookmark the first message with the answer.”

Usability study participant
Usability findings

Filters are not discoverable

  • Most of agents didn’t realize there was a dropdown with filters
  • Filters were not relevant to agent’s needs
Iteration 2

Make filters visible

After adjusting the layout of the page and making the messaging module wider, we also made existing filters visible.

I don't really need to see all the auto messages or even @signs from my team. Sometimes I just want to see what the client sent us and the reply.”

Usability study participant
Usability findings

Filters should be more specific

  • The filter labels were not immediately obvious to agents
  • More specific filters would be more useful: i.e. by person
Iteration 3

Test with real data

To experiment with filters and observe how agents use them, I made a prototype using real data. Surprisingly, agents fell in love with something that initially was the limitation of the prototype – additive filtering functionality.

I really like these filters – it's easy to access the important messages, and I can customize what I want to see beyond that."

Usability study participant

The results

The final solution was a part of a global redesign of the messaging module. The new module allowed agents more flexibility and control over the feed. In addition to filtering and starring functionality, the updated module allowed agents to quickly scroll to different time stamps throughout the transaction and incorporated the task history.

32%

faster page loading

28%

reduced search time

 

 

final solution

Bookmarking and additive filters

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