General Market Trends
Help brokers better situate themselves in the private market world. Usually this market is incredibly opaque and decentralized. There isn’t a lot of information on the landscape of private market trading and knowledge/proficiencies will make buyers/ sellers pick one broker over another.
UX Design Principles & Tools Applied
Data Visualization
The Challenge
As the private market industry continues to grow, ZX aims to be the platform where brokers go to consider, research, and submit orders. One of the key processes here is for brokers to stay up to date with how the market as a whole is doing and be able to qualify and quantify the market to their clients. As of now, a lot of this is done via phone calls with our operators, mostly based on an operator’s individual memory and knowledge. We want to equip or brokers with the concrete information they need to complete their job at the highest level of efficiency vs any other resource.
This means we need provide some visibility into the market to make the brokers seem smart
Whats happening in private markets? whats affected by the news and how, which sectors/companies do people care about? what’s trading and what are people talking about
Problem Statements
Brokers have no clear way to independently obtain trend information about the private market industry
Operators don’t have clear market data to provide, they often give a feel for the market through anecdotes and word of mouth
Goal
Create a space for brokers to gain their footing in the general private market and be equipped to answer client questions, do their own market research, and ultimately feel more confident in their ticket submission process.
Answer the questions:
What’s happening in the private market today?
What companies are of interest?
What can I do to execute trades?
My Role
I worked with a product manager, a business operator, and an engineer to see this project through end to end.
Research
Given our goals, we went into research with the intention to discover what would questions users need answered about the market before they feel confident advising their clients.
We discovered the decided that our brokers needed information that
Gave a clear high level overview of the landscape of the private market industry.
gave the broker an edge compared to other brokers. insider privy
gave the broker details that were actionable. significant / recent / valuable data points that give them reason to act
Solution
To satisfy these requirements, the following metrics were chosen
Overview
average ticket size
average ticket size
connection rates
Growth of market
Insider
ticket submissions by category
bid ask ratio
Actionable
Market Swing
popular companies
liquidity
Market Swing Chart
The purpose of the Market Swing chart was to highlight any company that had any drastic change in market sentiment. Brokers needed to know if a market was shifting and they needed it know it as early as possible. With the private markets being decentralized, brokers relied almost entirely on word of mouth. Having the market swings available would allow them to effectively manage client interests.
One iteration strove to show the movement of companies from a buyer’s market to a seller’s or vice versa.
Under testing, users intuitively understood the movement, however the bars were also incorrectly interpreted as interactive
This next version removed the scrollbar affordance, however the colors were a bit distracting and didn’t focus the attention on the important pieces of the data
The version that was chosen was clear in the intention, and removed any excess flourish in both design and information
Bid Ask Ratio
The Bid/Ask Ratio breaks down the spread of bids/asks each month, giving brokers an idea of whether the market is skewing towards a buyers or a sellers market and how that has changed with time.
In an early iteration, bars were used to represent the 100% of orders submitted, but the center alignment didn’t allow
This iteration overlaid the bids and asks, which very clearly showed buyer’s or seller’s markets and the point of transition. However individual month, and rolling average was hard to interpret
The chosen iteration more clearly showed the trend month on month and how this has changed with time
Connection Rates
The connection rate gives brokers an idea of how their tickets would preform and how they can improve their chance of moving their tickets into execution phase
One iteration of the connection rates chart was easy to understand at a glance, however the free floating design was too informal for Zanbato’s brand voice.
Another iteration was clean, however didn’t really showcase the narrative of the statistics well.
The final iteration was easy to understand and clearly displayed the variance between each ticket type
Results
With the first iteration of the data dashboard released
increase in logins/ click throughs / ticket ratios