StartupViz – Explore the Startup Landscape

Summary

StartupViz is a fully interactive visualization of the U.S. startup landscape. We designed StartupViz to provide a user-friendly way to understand and analyze the Crunchbase dataset about startup funding information.

StartupViz allows you to make your own discoveries, and you can explore everything starting from general trends to details about individual funding rounds.

Type:

Project with Allison Chambliss, Jordan Vincent and Arpita Kulkarni

Role:

UX Designer, Product Manager

Time:

10/2014 -12/2014 (3 months)

Project Scope:

User Research, Prototyping, Usability Testing, MVP Launch


Problem

When people think of startups, the first place that comes to mind is probably Silicon Valley. It is true that the Silicon Valley is home to the largest number of startups in the United States, but that is not where the story ends. Startups have been popping up all over the US and investors are noticing. With this ever-changing startup landscape, interested individuals need a way to stay up-to-date.

There are a variety of visualizations that were made with such goals in mind, but it is impossible to find a visualization that provides both depth and clarity. We set out to create an interactive visualization that provides a large amount of information on startups in an easily understandable way. Rather than communicating one specific story it was our goal to create an exploratory tool that gives users more control. This enables users to make their own discoveries about detailed trends regarding investors, regions, markets and funding rounds.

Explore Trends

Show overall trends and general information on startups (e.g. which cities have the highest number of startups, which market has received the most funding, which markets are growing and which are shrinking, how cities compare in terms of funding rounds, etc.).

Help in Decision Making

Show detailed information for those looking to become a part of a startup (e.g. which markets are dominant in which cities, the startup growth rate in a particular city, etc.), and information on investors for those who are a part of a startup and are looking for funding (e.g. which startups and markets investors have funded, during which round they contributed, etc.).

How can we design an interactive system that visualizes the U.S. startup dataset?

Initial Steps

Identify User Groups

Through multiple interviews and a survey we were able to identify our users. Based on our user research we developed three personas:
  • The Novice, who is generally interested in the startup ecosystem.
  • The Enthusiast, who wants to learn more about different regions and sectors.
  • The Established Entrepreneur, who needs to know how much funding he can ask for in his next round.

Dataset

After analyzing various datasets we decided to use the Crunchbase dataset. With its API and more than 650k profiles about companies and investors, it was by far the richest dataset. We created the following entity relationship diagram in order to get a better understanding of our data.
In order to be able to feed the data into Tableau properly, we went through various steps of data cleaning/manipulation:
  • Filtering: Focus only on U.S. startups founded after 2004. Exclude incomplete values and outliers.
  • Organizing: Group the more than 900 markets into 15 sectors.
  • Joining: Combine different tables and add other relevant data sources.

Milestone 1: Sketches and Paper Prototypes

Based on the user interviews and our understanding of the data, we created initial sketches that aimed at answering the questions that our users had about the data. We grouped the 40 questions into four categories and created a sketch visualization for each of the 40 questions.
The image below shows an example sketch for each of the categories:
  • 1 Overall Trends
  • 2 Details on a Sectors
  • 1 Details on Regions
  • 4 Details on Investors

First Paper Prototypes

The sketches helped us to identify the potentially most interesting and important visualizations for our users. With this in mind we created prototypes that used varying graph types and also had different user interactions and layouts.

The image below shows an example sketch for each of the categories:
  • 1 This prototype used a tab approach that allowed users to view a group of graphs and then switch to another tab that displayed a different group.
  • 2 In another prototype the layout of the different graphs (size and position), changed according to the users’ selection.
  • 3 The last prototype used a fixed one-page layout.

User Testing

Guerilla testing helped us to evaluate our prototypes. The fixed one-page layout was the easiest to use for most users. While it may have been overwhelming for some initially, its effectiveness was evident after the participants familiarized themselves with the prototype. This prototype was additionally the only one that allowed users to immediately make connections between all graphs.

An additional card sorting activity (see picture), that included 30 possible insights regarding startup landscape, allowed us to identify the most important features.


Milestone 2: Medium Fidelity Prototype

Following the user testing we created a clickable medium fidelity prototype, using the one-page layout.

Based on the user feedback we tried to separate the visualization into three parts:

  • The top section showed the overall trend and had filtering options on both sides.
  • The middle section showed details on regions and sectors
  • The bottom section provided detailed information about funding rounds.

User Testing

At this round of user testing we mainly asked task-oriented questions such as, “What is the top startup in the US?”. Insights from testing the medium fidelity prototype resulted in these recommendations:
  • Reducing the number of graphs in the middle section.
  • Removing the short bio of the city.
  • Reorganizing the bottom part, since it is still confusing.

Milestone 3: High Fidelity Prototype

Based on the feedback we received during the user testing, we built our first interactive high fidelity prototype in Tableau.

1 The pie charts on the map show the biggest sector for each region, and the color corresponds to the sector button at the top of the page. We also added the option to filter by individual markets on the right side, to satisfy the user demand for a more detailed filter option.

2 Similar to the medium fidelity prototype, the ranking and trends section is displayed below the map. The colors show the breakdown of each bar by sector. We also tried to use a gradient to show the distribution of markets within each sector.

3 We found that, although Seed or Angel rounds are usually first and Series A is usually second, this was not always the case. Therefore we decided to number the funding rounds instead, and show a breakdown by type of funding round rather than by funding type. For this section we used a different color palette in which each color represents one funding type.

We built multiple iterations of these high fidelity prototypes and made modifications in response to the user feedback. The image below shows a later iteration of the prototype.

1 We added a short description in the beginning and also added section titles for sections 2 and 3. We also made the colors more prominent and changed them to match them to their corresponding market categories(e.g. clean tech = green).

2 Compared to earlier versions, we decreased the number of bars initially shown in each chart. This proved to be an effective approach in order to reduce the initial feeling of mental overload for users.

3 We added a slider that allows the users to easily explore individual funding rounds instead of having an additional row entry for each round.

User Testing

For this round of testing, we went to Startup Hall and tested the high fidelity prototype with founders that worked in this coworking space. Insights from testing the high fidelity prototype resulted in these recommendations:
  • Offer a tutorial that helps users to understand how they can interact with Tableau.
  • Put all filtering options in one central location of the interface.
  • Reduce the number of colors in the middle section.
  • Have a clearer separation between the three different sections.

Final Visualization

The final visualization is composed of three distinct sections interacting with one another when filtering or searching. The three sections are:
  • An overview of the startups in the US
  • Rankings and Development Over Time
  • Funding Rounds
This breakdown allows us to present information on different level of granularity and answer the needs of our three personas (novice, enthusiast and established entrepreneur).
Considering the feedback from the last round of user testing, we made several adjustments to the final product. We added a tutorial that explains how to interact with Tableau and also shows two of the most common use cases. We put the filters and search bar in one central place at the top of the visualization, which now acts like a control panel of the visualization. We also reduced the color complexity in the middle section. In general, we gave the visualization a more clear separation and a cleaner design. For our visualization we followed Tufte’s principles of graphical excellence, by focusing on “conveying the most knowledge in the shortest time with the least ink in the smallest space”.
We also made each design decision carefully, keeping in mind Schneiderman’s Visual Information-Seeking Mantra:
  • Overview: The user is first shown an overview of the startup scene. The map and all the graphs are aggregating the values in order to show the overall situation.
  • Zoom: The map allows zooming on specific parts of the country.
  • Filter: Every graph can be filtered by sector, market or region. In addition, it also filters when clicking on any data point
  • Details-on-demand: Tooltips appear when hovering over any data point, showing the exact values as well as additional information.

Feature Highlights

Tutorial

Built on top of Tableau, a tutorial guides new users through two use cases: "What's in my sector", and "I'm looking for funding".

Overview

The map shows an overview of the startup landscape. For each city is shown the amount of funding as well as the dominating sector.

Filters

For in depth analysis, users can filter by a specific region, sector, or even search for a company by its name.

Trends

Time series show how funding evolves, what sectors are trending, or in decline. It also allows to compare sectors.

Funding Time

Getting funding is a key activity to any entrepreneur. Box plots indicate for each round the time it takes to get funded at each stage.

Details on-demand

Tooltips present additional information on any sector, region, or company. Users can open even open the corresponding CrunchBase article.

Outcome

We made StartupViz available online and even presented our work in front of an audience composed of entrepreneurs at the Startup Hall (University of Washington).

It went very well, and we even have been featured in HCDE's annual publication Designing Up 2015.

The overall feedback we received from entrepreneurs has been very positive:

Normally I have to google competitors or look through all individual entries in CrunchBase to find startups that are similar to ours. Once we even bought a report that contained similar information for around $4000. Seeing how much funding these companies got in their investment rounds can help us to ask for the right amount from our investors. I would definitely use this tool and pay for it! Probably not $4000, but I would pay for it.

– Greg Robinson, CEO at Wovn Energy

Designed & built by Lukas Eiermann 2016
Always happy to chat .