Stories

How Augment Code drove 70% more pipeline from developer sign-ups

The Problem#

Reps wasting hours on unenriched leads

Augment Code's AI coding assistant attracts thousands of developer sign-ups daily, many using personal emails. Hidden among these Gmail addresses were engineers from target accounts, often six-figure opportunities invisible to the sales team.

Sales reps received these leads with virtually no context - just an email address and maybe a name. There was no way to plug this into real-time LinkedIn data, which is often the best resource to identify a team's fit to Augment's product. Without this enrichment data, the sales team couldn't tell if a lead was a solo developer or part of a 500-person engineering team actively evaluating the product.

"Our reps were going to LinkedIn and manually filling spreadsheets before they could even start outreach. They'd spend 45-60 minutes per account just gathering basic information," says Amanda Sieglock, Senior Operations Manager at Augment Code.

The lack of upfront enrichment created a cascade of problems. High-value leads sat untouched while reps researched. Personal emails from Fortune 500 engineers looked identical to hobbyist developers. Despite strong product demand, sales reps missed quotas and their best opportunities remained buried in thousands of anonymous records.

Hot inbound leads turned cold due to routing delays

When enterprise prospects submitted contact forms, the process was entirely manual. Forms came through Zapier into Salesforce and awaited an ops person to take action.

During business hours, this might take 30 minutes for them to get to it before manually routing it. Outside business hours? The leads sat untouched until the next day.

By the time sales reps called back, often 24 hours later, prospects had already signed up with competitors. Developer tools need fast response times. Engineers won't wait.

The sales team had limited access to data

The engineering team maintained a database tracking how people used the product, which features they tried, how often they logged in, if they invited teammates.

But the sales team couldn't easily leverage this information to run their experiments. For instance, the team couldn't link users from the same company. If 16 engineers from one company signed up with personal emails, sales saw 16 separate leads, not one interested account. They suspected certain behaviors meant someone was ready to buy, like heavy API usage or inviting colleagues, but had no way to build segments on these hypotheses and collect evidence.

"We were guessing which leads to prioritize. Meanwhile, companies with multiple active users who were deeply testing our product often went completely unnoticed" - Amanda Sieglock, Senior Operations Manager at Augment Code.

The Solution#

Use Case 1: Custom waterfalls improve coverage across all sign-ups

Augment Code now enriches every Gmail or work email through custom waterfalls built on Cargo. Their custom waterfall combines multiple data sources to maximize coverage and accuracy.

"We went from zero Gmail enrichment to catching 15-20% of personal emails, plus improved our work email coverage by 15%. That's thousands of previously invisible developer sign-ups we can now identify and route to sales" - Amanda Sieglock, Senior Operations Manager at Augment Code.

Use Case 2: Leads now reach the right rep in minutes

When someone fills out a contact form, this immediately gets sent to a Cargo Play that performs multiple steps:

First, a dedicated custom waterfall tool searches for and fills in missing company data, while another tool detects any fraudulent submissions. Next, the Play passes the entire context of the submission to an AI action that determines what they want—a sales conversation, support help, or just spam.

For sales inquiries, Cargo's AI-powered persona classifier analyzes the enriched data to identify if someone is an "engineer decision maker" (their highest-value persona) versus non-technical roles or unknowns. This classification acts as a filter: engineering decision makers from companies with sufficient size and engineer count get routed straight to sales reps via Salesforce with a Slack alert. Non-technical contacts or unknowns get deprioritized or filtered out entirely.

"If someone comes in as an engineer decision maker, we know to prioritize those people for outreach. We won't be syncing over the unknowns or the non-technicals as much," explains Amanda.

This intelligent routing cut response times from 24 hours to under one hour, with qualified leads getting callbacks within minutes during business hours.

Use Case 3: Account intelligence reveals hidden opportunities

Augment Code built an account tiering system in Cargo that automatically evaluates every company based on size, engineer count, and persona fit. Using enrichment data from LinkedIn and other sources, the system identifies which accounts match their ideal customer profile.

This allows them to connect individual sign-ups to see the full account picture. When multiple engineers from the same company sign up—even with personal emails—Cargo links them together and alerts sales when an account shows strong interest.

"If we know someone on their team is using our product a lot, or maybe they have multiple users, we can reach out to higher-level decision makers with personalized context about what their team is doing," explains Amanda.

This account-level view ensures reps focus on qualified accounts rather than random individuals.

The outcome#

Lead enrichment jumped to 70%

Personal email coverage is going from zero to 20%. This unlocked thousands of previously invisible opportunities for developers using Gmail addresses.

24x faster speed to lead

The introduction of the automated workflow drove inbound conversion rates to 80%, capturing deals that previously went to faster competitors.

2x sales productivity

By cutting 45-60 minutes of manual work per account. Reps now focus exclusively on selling rather than data gathering.