Background

During my time at Aalto, the business strategy focused on building a product to essentially replace buy-side real estate agents with an app.

Buyers were incentivized and empowered to use Aalto for the rebate they’d receive for doing the work traditionally provided by agents.

Timeline: Jan–Feb 2024 (2 months)

The Team

• Lead Product Designer (Me)

• Brand & Systems Designer

• UX Researcher

• Product Manager

• Engineers

My Contributions

• User Research

• Concepting & Strategy

• User Journey Mapping

• UI/UX Design

Insights

By early 2024, buyers were still leaning heavily on the traditional approach of consulting with an agent for insights on the market and their search criteria, which meant the product was not yet fulfilling that buyer need.

Buyers wanted to understand things like:

• Is now a good time to buy? When will I get the best deal?

• What is inventory like in the area I’m searching, and how will it fluctuate?

• What can I do to improve my chances of finding a home?

• How does Aalto support me through this process?

The Problems

• Buyers joining Aalto filled out search criteria, but were dumped into a map with no context about their search or the market.

• This was one big reason buyers were leaving Aalto to go back to working with traditional agents.

• Our customer support team spent a lot of time answering search-related questions that should have been answered with the product.

Approach

Given that we were still working on finding product market fit, the strategy with this work was to go wide and big in discovery, then execute an MVP we could test and validate.

Idea #1

Provide new Aalto buyers with a landing experience that delivers the insights and support they need through the search phase of their journey in order to trust and use our platform for their home purchase.

Buyer needs

• I need to know the most vital insights based on my stage in the process to set me up for finding and winning the home.

• I need to understand what next steps I could/should consider taking to set myself up for success.

• I need to understand how Aalto is going to work with me or serve me.

Narrowing decisions

• Focus on just the market analysis for MVP

• No more milestones, no more team

• Avoid home cards, users go straight to those and may miss the valuable analysis we want to test

Idea #2

Infuse the market analysis into the browse experience, rather than fully separating it as its own page.

The biggest challenge revealed itself as a need to support two opposing buyer jobs to be done:

1. I need an analysis of my “core” search criteria, so that I can understand what adjustments to consider making to improve my ability to find a home.

2. I want to adjust the filters of this analysis to explore how the results change, and may or may not want to then apply those as updates to my core home search.

This exploration surfaced just how difficult it would be for us to avoid a confusing user experience for either user need without supporting a “Saved Search” type of feature as part of the release.

Solution

For the purposes of meeting our lowest-scope MVP goals and technical limitations while maintaining the lowest level of UX friction possible, we ultimately landed on a solution to have separate screens for the buyer’s search analysis and the browse experience.

This all-new feature showcased a data-driven analysis of the buyer’s saved search market—whether they had identified one to many disparate locations—based on their max budget and bed/bath minimums.

A buyer could edit filters applied to the Market Analysis for the purpose of exploring changes in data based on different parameters, with the optional ability to save those updated filters as their (new) saved search parameters, thereby updating the filters powering their email notification system.

This direction also supports a standard exploratory browse functionality, with the ability to edit filters within the map/list views as users normally would.

Buyers were now not only able but empowered to make data-based decisions about how they should refine/expand their search, a natural part of the home-hunt journey.

This product also automated more of our customer support team’s work, including automation of weekly analysis update emails traditionally sent manually and proactively from top agents.

Impact

Equipped with an all new data-driven home search analysis, early adoption data showed that buyers had gained an effective tool for enhanced market understanding and search refinement strategies.

Despite the company shuttering shortly after launch, it demonstrated strong user engagement and received excellent feedback for its innovative approach to simplifying home buying decisions.

Planned Next Steps:

• Run A/B testing with and without this new feature to measure retention and monitor outreach to CX team

• Iterative improvements:

  • Data viz design & content

  • Support for multiple location searches

  • Week-over-week changes in data