Aptible Culture

Talent & Compensation Philosophy

Aptible’s has an ambitious mission and strategy that we cannot achieve without a highly talented and motivated team.

We’ve always endeavored to attract and retain the best possible team members. We are writing down our philosophies on Talent Density and Compensation to help current and prospective team members understand how we think about our team, and how we compensate it.

Talent Density

We won’t achieve our mission, or really anything of any importance, without a highly talented and motivated team. We seek to attract and retain the best possible team members. We look for team members who embody our values, who will drive Aptible’s success, and will be great colleagues to collaborate with.

Netflix describes the concept of creating a team filled with talented people as creating “talent density.” Aptible has adopted this language because it provides convenient shorthand for how we seek to build our team. High talent density companies:

• Get more done, faster
• Are more collaborative
• Continuously learn and improve
• Attract more talented team members
• Are just better companies to work for

And, we believe, high talent density companies are more likely to create and deliver more valuable products to a wider customer base than those with average or low talent density.

We have lots of ideas about how to continuously improve our talent density, but with just over a dozen employees and needing to significantly grow our team quickly, the most important thing to focus on is attracting (and retaining) the highest talent individuals.

Compensation Philosophy

We believe that having a transparent and highly competitive compensation philosophy is the only way we’ll be able to attract great team members and retain them.

Aptible’s compensation philosophy is designed to be simple, transparent, and an effective tool for creating a high talent density team. We update our compensation philosophy as the needs of the business change. Our compensation process is based on industry-standard data sources, and seeks to ensure we are always paying our employees a highly competitive market rate at all times.

Compensation Packages

Compensation at Aptible consists of:

• Base Salary (+ Commission for some roles, but not most roles)
• Employee Equity
• Professional Development Budget
• Hardware, Software, and Office Setup
• Unlimited Vacation Policy
• Paid Parental Leave (14 Weeks for All Parents)
• Fully Remote Team: Work from Anywhere in U.S. Pacific-Eastern Time Zones

Base Salary

Aptible’s goal is that 100% of our employees’ total compensation is in line with 90th percentile for their personal market and Aptible’s market.

For most employees, Base Salary at Aptible is equivalent to Total Cash Compensation according to benchmarks. Save for a few select roles, Aptible does not use bonus compensation based on performance, opting instead to reward employees with generous top of market salaries in exchange for the expectation that every employee will make significant contributions to Aptible’s success.

Personal Market

For Aptible, personal market means:

• Job Title
• Level (ex. Option Impact leveling and Pave leveling, side-by-side)
• Founding status (founder / non founder)

Option Impact and Pave levels

When there is no clear comparable job title in the data set (e.g. Developer Relations) or sample sizes are small, we may average together data from more than one job title (for DevRel: Software Engineering and Marketing).

Our Market

Aptible competes the entire market of software companies for talent. This is especially true for software engineering. As a result, for individual contributor roles Aptible benchmarks compensation against all companies.

Executive roles are a bit different. Because Aptible is still small (but growing fast), it’s very different to be the CTO of Aptible vs. being the CTO at Netflix. For that reason, we pay executives using comparables based on companies like Aptible. For Executives, we draw data from:

• Companies that sell enterprise software
• Companies with similar revenue
• Companies with similar estimated market valuations

We may update the definition of comparable companies as Aptible grows.

Data Sources

Aptible uses Option Impact and Pave. We may adopt new data sources in the future.

For every role, we generally select one source. After reviewing the data, it sometimes become obvious that one source is more relevant than another due to one source having poor sample sizes or discrepancies in data; at those times, it’s obvious which source to select. If necessary, we will search for other data to help inform whether Pave or Option Impact.

As of the last teamwide compensation review, January 14, 2022, we’ve selected the following sources for individual contributor roles:

Individual Contributor Job Levels

Manager, Director, Executive Job Levels

We perform similar analysis for Managers through C-Level roles to determine appropriate compensation.

Compensation Review Process

1. We download applicable salary data from our data sources
2. We collect leveling information from managers (e.g. managers define what level each team members is performing or expected to perform at)
3. We review each source and determine if one of or some combination of sources is the best data set to use
4. Once we determine the most competitive compensation offer, we share the data with the employee. We share: level, comp for their level and the other levels for their role, and what source or sources we used to determine the compensation.

Compensation Review Timing

Each of the following trigger a compensation review:

• Creation of a new role
• Significant market changes (e.g. the great resignation)
• Significant role changes due to outperformance or title promotion
• At least 1x per year otherwise
• Employee request

If employees believe the market salary for their role has changed, they should collect their own compensation data (e.g. comparable company job descriptions with comp data, offers, etc.) to share with their manager and request a compensation review. However, since we target 90th percentile, we generally rely on data sources with larger samples sizes, we can’t promise to match every new input. That said, new data points will be helpful in verifying our data sources.