Pitchbook Guided Buyers Search

Background
PitchBook is a data platform providing investors with valuable information on companies, investors and other service providers. Our users include Venture Capitalists, Investment Banker Analysts, Private Equity Investors, Corporate Development Teams or Law Firms, among others. PitchBook’s data is used to learn more about emerging companies or to search for companies in a specific industry. They are known in the capital market industry to be the “top provider of global financial data, research, and insights”. PitchBook was purchased by Morningstar in 2016 and has since expanded its data set into the public equity market.

Challenge
A pain point highlighted by customer service, our users, and leadership was the complexity involved in building a search for users in need of assembling a list of buyers for a company they are trying to sell. Professionals were unable to figure out how to build this search query on their own. It was identified as a recurring request of the customer service team to run this search for our users.

Business Impact / ROI
Before the project was green lit, the business impact of allocating resources to developing this tool was scrutinized. In identifying new revenue, cost savings, end customer size, value and competitive differentiation, leadership decided to move forward into research and implementation.

Goal
Develop a Guided Buyers List tool to help PitchBook users assemble a list of buyers for a company they are trying to sell.

The feature has 3 stages

Create a broad search
Filter the results in compelling ways
Collaborate, project manage, and export a list of potential buyers

Process | Understand and Define
Who will use it?

Users want to find buyers for a specific client
Users want buyers with historical deals or investment preferences in the same space as their client
Users want to combine different approaches to finding buyers into 1 single buyers list
Users want the flexibility to decide who can /cannot be a buyer for their client

As UX Design Lead, I worked with my Product Manager to fully understand the problem and did generative research. We met with customer service, listened to customer support calls, and brainstormed other companies or industries who utilize guided search.

Process | Design Sprint
In order to better understand the use problem, user flow, feature list, and to prepare our interview questions I hosted a shortened design sprint with internal stakeholders and leadership including Customer Support, Sales, and Machine Learning teams. This exercise proved very valuable and guided the rest of the project.

Everyone brought their unique perspective to the table during the exercises which included HMW (how might we), four step sketch, notes & ideas, crazy 8s and ended with a solution sketch. It was incredibly insightful to extract their ideas and expertise and at the same time everyone was very excited to be involved at such an early stage of the project.

The information gathered in the design sprint directly informed our feature list, user flow and was invaluable in guiding the rest of the project.

Process | Problem Statement
The design sprint yielded our problem statement:

How might we guide our users through the creation of a custom buyers list, so that they can present their clients with an exhaustive, unique, and personalized list of options.

User Interviews
Our next step was conducting user interviews with PitchBook clients identified by customer service as interested in the ability to create a buyers list. We interviewed 10 individuals including analysts, CFO, associates, VPs, and internal PitchBook folks from Customer Success.

The interview transcripts were then color coded and grouped by topic, and printed out. We then invited internal stakeholders to review and move the information into buckets to identify a user flow, common requests, patterns, pain points, and to identify our feature list.

User Flow
In order to visualize the workflow and align expectations with product leadership, I created a user flow of an IBank Buyers List Workflow. From this user flow we were able to add in pain points from the interviews and data points that PitchBook could include in the creation of a list of buyers.

Insights
Based on our analysis we found five insights that stretch across the selling journey (and 1 bonus insight!)

Get acquainted with my clients space
Show how changing criteria affects my set of buyers
Use my expertise to decide if a buyer should be excluded
Create meaningful groupings of buyers
Quickly reach out to gauge initial interest

Bonus Insight
Often our users have an existing list of potential buyers they have identified and filed away over the years. This information lead us to include the ability to add individual companies or upload a list in the process of creating their custom buyers list.
“I maintain and expand my network of buyers throughout my entire career - one a company approaches me about finding a buyer - I already know who in my network wants to participate.”

“Creating a ‘Network’ based approach to creating buyers lists mimics the way our customers actually build these out. You aren’t going to PB to find 200 buyers you have no connection to. Instead you are analyzing your existing buyer network and seeing who would be a good fit - and, when PB does suggest other buyers you don’t know, can someone in your network make an introduction.”

Key Features
All of our due diligence, research and understanding led us to our key features and high level requirements for the feature including sub-requirements.

Should be future - proofed and cohesive with future Investor and Buyer initiatives. This is the search that existed before this project, and we wanted to make sure that it allowed integration into profiles and the advanced search.

Should help the user with the process of building a buyers list
Should help the user with the process of evaluating a buyers list

Use Case
Identifying our primary user and their use case was essential to understanding who would use it, what exactly they want to do, and why.

Primary Users

As an investment bank, I want to build a buyers list for my client, so that I can identify buyers for my client

Secondary Users

As a venture capital firm, I want to evaluate the most likely buyers and relevant deals for my aging portfolio company, so that I can have more information to negotiate with a prospective buyer for my company.

Other

As a company looking to exit, I want to evaluate the most likely buyers and relevant deals for my company as I’m looking at potential exit strategies so that I can understand what a competitive price looks like and what buyers would be willing to pay.

Key Features
In cross referencing all of the information we gathered with the capabilities of our data, and the machine learning team we homed in our key feature list.

Initial filtering
Ability to start with my network, existing relationships
Active investors graphic
PitchBook defined buckets (Financial, Strategic, Financial Capacity, Network, Similar Companies, etc)
Who got kicked out
Deep look at each investor
Custom Buyer groupings within a list
Relevant contact info
Management of the list, ability to include/exclude specific buyers. Ability to pull logos, charts, past deals, timelines, and add notes
Master List and ability to save, collaborate, and download

Data Map
This extensive data map was made after identifying which data points users depend on in determining a buyer cross-referenced with what data we had available in PitchBook.

Paper Prototyping
With the goal of making this search intuitive, straightforward and user friendly from the start, I proceeded with paper prototypes. Here we focused on a simplified entry point, followed by robust filtering options, three main results views, and data visualization that we knew we could support and represent.

Active Investors
Strategic
Financial

These were presented to stakeholders for iterative feedback before we moved to mockups.

Mockups
After agreeing on a direction with the paper prototypes, we moved onto low fidelity mockups. This is when I went on maternity leave and the project was taken over by a Senior and Junior UX designers on the team.

Results
The product launched in Q2 of 2021. Preview the tutorial below to see the feature in action.

0:02 Use pre-built filters to unearth new potential buyers
0:15 Take control and filter by additional criteria based on your expertise
0:25 Utilize spotlights to create personalized lists and discover buyers you might have missed
0:35 Perform diligence on potential buyers by reviewing their background, preferences, and precedent transactions
0:50 Manage your personalized list of potential buyers in the ""My List"" section
1:00 Add unknown buyers to your list
1:10 Load, edit, and add to existing lists from saved Guided Buyers searches
1:20 Share and collaborate on buyers lists with your team