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Creating a Unified Experience

Artificial intelligence throughout the real estate marketing cycle.

Company: G5 

Duration: 6 months

Lead Designer: Davin

Overview

G5 provides websites and digital advertising for customers in the property management space. Their customers operate multiple properties and are continuously making changes to ad campaigns and associated images, text, and more—all while seeking objective measures of advertising performance.

 

All of this work is highly manual for both G5 and its customers. Independently, G5 had invested heavily into machine learning to help automate and better measure the effectiveness of its digital advertising campaigns.

Writing on Glass
Discovery

I had a prior relationship with G5, but was hired as an independent product design consultant to develop user personas, journey maps, requirements, and prototypes.

 

I worked with their internal teams and several customers with the goal of developing a solution that leveraged G5’s new technology, surfacing enhanced reporting and self-service capabilities. The result was branded as the “Intelligent Marketing Cloud” and was released over time, following my initial involvement.

Objectives

  • Identify the most time consuming tasks for internal users and develop a workflow that customers could better handle themselves.

  • Work with G5 engineering and product management to understand the new automated (AI-driven) campaign product components and research the best methods for demonstrating campaign performance in a web interface and provide customers with better reporting and insights. An additional requirement was to aid their supervised machine learning by providing a mechanism for users to label examples in the training data.

  • Systematize and design a modern web UI that also provides a dashboard serving internal and external users with direct access to other G5 products. Pressure-test the prototype with live data and user interactions, then deliver API requirements for G5’s data team, as well as information architecture and UI requirements for their front end developers.

  • Conduct internal and external user interviews to identify challenges and opportunities to help guide feature development, following an alpha release. Deliver these insights in the form of high-level product requirements.

Deliverables

Main Menu

Once logged in, users are presented with a unified menu of options and a selector for choosing individual properties and internal users may switch among client profiles.

Floor Plan Management

The ability to manage floor plans (for web sites) and categories (for advertising) was identified as a crucial self-service need.

I created a simple table editor with drag and drop sorting to address this need. Both views support inline editing with the ability to expand and access additional data fields. In addition, I wanted to make it easy for users to easily hide things like floor plans that need to be invisible (published) on their property websites. They also needed to be able to create and delete these—and where needed, modal confirmations were displayed.

Analyzing Graphs

Intelligent Insights: Lead Scoring

The Lead Scoring feature provides a listing of advertising leads and a way to quickly score individual leads. The results of the interaction were fed as labels back into G5’s machine learning system.

Grey Monster Cube
In order to score a lead, users needed context and so a simple click reveals a chart paired with a roll-up of interactions. In the case of phone calls, recordings are made available for playback.

I ran analytics and heat-maps to make some other improvements and to optimize for quick scoring. Later, some indicators of “what the AI thinks is a good lead” were added, exposing users to the underlying machine-derived decisions.

Intelligent Insights: Channel Comparison

The goal of this part of the application is to demonstrate G5’s advertising performance, across different channels over time. Users also required a way to search and compare channels.

I developed an interface that provides a few ways to filter the view and maintain the items they want to compare in the view by “pinning” them to the top. This worked surprisingly well and users immediately asked for various export capabilities including images they could drop into presentations.

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