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Helping B2B Businesses Identify Their Ideal Customers with Ease

Helping B2B Businesses Identify
Their Ideal Customers with Ease

Overview

About the Company and Project

Enlyft helps businesses discover new customers by providing access to data on millions of companies and their employees. Companies can use Enlyft’s powerful features to find businesses and contacts that match their ideal customer profile, making it easier to target the right audience.

This case study explains how we designed a new feature that helps users identify their best prospects, prioritize them, and understand why they are a good fit.

My Role

As the sole UX Designer, I owned the project end-to-end, collaborating with the Lead PM, CEO, engineers, and the sales team. My responsibilities included research, ideation, wireframing, prototyping, and delivering the final UI.

Duration

The project spanned multiple quarters, involving several sprints and milestones, with additional milestones still to come. This case study focuses on the implementation of V1.

Problem

Businesses need to focus on customers who are most likely to buy their product or service. To do this, they create an Ideal Customer Profile (ICP) based on factors like company size, location, industry, or technology used. But with so many potential customers, it’s hard to decide who to focus on first. This can lead to wasted time, effort, and missed sales opportunities.

Requirements

These are the key requirements I received from the Product Manager and CEO for this project:

  • TAM and ICP Definition: Allow users to define their Total Addressable Market (TAM)* and Ideal Customer Profile (ICP)*.

  • Account* Ranking: Rank accounts based on the TAM and ICP setup.

  • Score Preview: Enable users to preview account score immediately after defining their TAM and ICP, making it easy to fine-tune the setup.

  • Score Transparency: Show users why each account receives its specific score to build trust and provide transparency.

  • Recommendations: Allow users to upload their existing customer lists and provide tailored recommendations to refine their TAM and ICP setup based on the characteristics of their current customers.

Definitions

TAM & ICP

Total Addressable Market (TAM): The total number of companies that could potentially use the product.

Ideal Customer Profile (ICP): The specific type of company most likely to benefit from the product.

Consider Microsoft Power BI, a data visualization tool. The sales team at Microsoft would probably define its TAM and ICP as follows:

  • TAM: All mid-sized to large enterprises globally needing data visualization and BI tools.

  • ICP: Companies in Financial Services and Healthcare sectors with 500+ employees already using Microsoft Azure or Office 365.

Account

In sales terms, an Account is a business or organization that is a potential or existing customer.

Constraints

Data

We had access to specific company data points, such as location, industry, revenue, employee count, technologies used, etc. The scoring process was limited to these, as adding new data points or using other information was outside the project’s scope.

UI

The app utilized an existing legacy visual language with a predefined set of UI components, including tabs, buttons, and input fields. Creating new visual styles or components was not within the project’s scope due to a lean team and tight deadlines.

Design Process

User Story

Research

Competitive Analysis

I explored the scoring models of some of the competitor's to understand the data they use to score, the ranking system etc. Some of the competitors I could get my hands on are:

  • Apollo.io

  • RollWorks

  • Zoominfo

  • Madkudu

Enlyft's Sales and Marketing Team

  • The first users for all the features that are built are the Sales and Marketing team at enlyft itself. We had multiple discussions with the team to understand how they are currently managing without the scoring model and which competitor apps they prefer.

The first users for all the features that are built are the Sales and Marketing team at enlyft itself. We had multiple discussions with the team to understand how they are currently managing without the scoring model and which competitor apps they prefer.

Insights From Research

  • After evaluating competitor offerings and discussing with internal users, we selected key features that stood out as impactful. We then refined and improved them to better align with user needs and our product vision.

  • We developed basic wireframes and shared them with the engineering team to evaluate feasibility, identify constraints, and explore opportunities

  • After evaluating competitor offerings and discussing with internal users, we selected key features that stood out as impactful. We then refined and improved them to better align with user needs and our product vision.

  • We developed basic wireframes and shared them with the engineering team to evaluate feasibility, identify constraints, and explore opportunities

Solution

Userflow

Step 1 - TAM and ICP Definition

To help users define their TAM and ICP effectively, we developed a simple, intuitive process with multiple ICP levels for more precise customer targeting.

ICP Levels:

  • Best Match: Companies that fully align with the ideal customer profile.

  • Good Match: Companies that meet most of the ICP criteria.

  • Fair Match: Companies that meet some ICP criteria but are less likely to convert.

Categorizing Criteria
Categorizing Criteria

Categorizing Criteria

When defining TAM and ICP, different types of criteria are considered, such as location, industry, number of employees, and technologies used. Some criteria, like the number of employees, have smaller, defined ranges (e.g., 1-10, 10-100, 100-500). Others, like location and industry, have broader ranges.

To simplify the process, we categorized these criteria into 3 categories and designed appropriate UI components to make it easier for users to set their TAM and ICP effectively.

When defining TAM and ICP, different types of criteria are considered, such as location, industry, number of employees, and technologies used. Some criteria, like the number of employees, have smaller, defined ranges (e.g., 1-10, 10-100, 100-500). Others, like location and industry, have broader ranges.

To simplify the process, we categorized these criteria into 3 categories and designed appropriate UI components to make it easier for users to set their TAM and ICP effectively.

Linear Scale Options
Linear Scale Options
Linear Scale Options
Freeform Options
Freeform Options
Freeform Options
Boolean Options
Boolean Options
Boolean Options

Step 2 - Account Fit Scoring

Based on the TAM and ICP definitions, the system automatically calculates:

  • The total number of accounts within the TAM.

  • The number of accounts scored as High, Medium, or Low Account fit.

As users adjust their setup, the account counts update in real time.

Step 3 - Real-Time Score Previews

Account List Preview: Users can instantly preview the account fit score by adding preferred accounts or randomly chosen accounts.

Step 4 - Visualize Account Fit

  • Fit Distribution Chart: A chart shows the overall TAM divided into High, Medium, and Low sections. Users can adjust these sections by moving sliders.

  • Dynamic Score Updates: Account fit scores adjust automatically when slider positions change, providing instant feedback.

View Account Fit Scores

Once the setup is saved, the account fit score for each company will be calculated in the range of High, Medium, Low or Outside TAM and displayed at multiple places with in the app.

List View

Company Profile Page

The company profile page displays data points of the criteria defined in Account Fit setup, each marked with color-coded icons to indicate whether they are a best match, medium match, fair match, or outside the TAM.

Dashboard

The Dashboard displays a matrix that combines the Account Fit score with another key metric called the Buying Signals score. This helps users gain confidence in a company when both scores are high.

Impact and Learnings

  • Since the launch of V1, this feature has become the go-to tool for our sales teams during product demos with potential customers. User feedback has been overwhelmingly positive, with many praising the feature's value.

  • We continue to collaborate with the sales and customer support teams to gather user feedback, which will inform improvements for the next version of the feature.

  • This is a large-scale project with numerous pages, user flows, and edge cases. This case study covers the main features, but there are many other user flows and integrations with external tools that could be separate case studies on their own.

  • Working on a project of this scale has provided valuable lessons, including the importance of assessing the impact of a new feature on the entire app, collaborating with cross functional teams, managing designs in Figma, writing PRDs, handling iterations, and effectively handing off designs to developers.