How Augment Code routes developer sign-ups to reps in under an hour
Amanda SieglockWe 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 salesAmanda Sieglock
Before Cargo
Thousands of sign-ups a day, and no way to tell who they were
Augment Code’s AI coding assistant brings in thousands of developer sign-ups a day, many from personal email addresses. Hidden among those Gmail addresses were engineers from target accounts, often six-figure opportunities the sales team could not see.
Reps got an email address and maybe a name. Nothing connected that to live LinkedIn data, which is usually the best way to judge a team’s fit, so a rep could not tell a solo developer from 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.
High-value leads waited while reps researched. A Fortune 500 engineer on a personal email looked the same as a hobbyist. Demand for the product was strong, and reps still missed quota because their best opportunities were buried in thousands of anonymous records.
Inbound forms waited for a person to route them
Contact forms went through Zapier into Salesforce and waited for someone in ops. In business hours that took about 30 minutes, then the lead was routed by hand. Outside business hours, it waited until the next day.
Reps often called back 24 hours later, by which time the prospect had signed up with a competitor. Engineers do not wait.
Product usage data sales could not use
Engineering kept a database of how people used the product: which features they tried, how often they logged in, and whether they invited teammates. Sales could not build on it. If 16 engineers from one company signed up on personal emails, sales saw 16 separate leads, not one interested account. The team suspected that heavy API usage or inviting colleagues meant someone was ready to buy, and had no way to segment on those behaviors and test it.
“We were guessing which leads to prioritize. Meanwhile, companies with multiple active users who were deeply testing our product often went completely unnoticed,” says Amanda.
What runs on Cargo
Every sign-up and every form now goes through Cargo before it reaches Salesforce. Cargo enriches it, classifies it, links it to its account and routes it. Three pieces do the work.
A custom enrichment waterfall on every sign-up
Every sign-up, Gmail or work email, runs through a custom waterfall built on Cargo. The waterfall combines several data sources so that each one covers what the others miss.
“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,” says Amanda.
Routing that reaches the right rep in minutes
A contact form now goes straight to a Cargo play. A waterfall tool fills in the missing company data, and another tool flags fraudulent submissions. The play then passes the whole submission to an AI action that decides what the person wants: a sales conversation, support help, or just spam.
For sales inquiries, a persona classifier reads the enriched record and decides whether the person is an “engineer decision maker”, Augment’s highest-value persona, or a non-technical role or an unknown. Engineer decision makers at companies with enough size and engineers go straight to a rep in Salesforce, with a Slack alert. The rest are deprioritized or filtered out.
“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.
Account linking that shows the whole team
Augment built an account tiering system in Cargo that scores every company on size, engineer count and persona fit, using LinkedIn and other sources. Sign-ups from the same company are linked to that account, personal emails included, and sales gets an alert 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.
Reps work qualified accounts instead of scattered individuals.
The outcome
Callbacks in under an hour, not 24
Routing that used to wait for a person now runs as soon as the form arrives. Response time fell from 24 hours to under one hour, and qualified leads get a callback within minutes in business hours. Inbound conversion reached 80%, winning deals that used to go to faster competitors.
Personal-email sign-ups identified, from zero to 15-20%
Before Cargo, no personal-email sign-up was enriched. Now 15 to 20% are, and work-email coverage is 15% better. That is thousands of developer sign-ups sales can now see.
45-60 minutes of research gone from every account
Reps no longer research each account by hand before outreach. They spend that time selling.
"Cargo gives everyone superpowers to build what they need without waiting for engineering. Our sales team gets fully-enriched, qualified leads instantly instead of orphaned records that they have to research manually. That's the difference between missing quota and exceeding it,"
Augment Code is an AI coding assistant that helps developers write code faster and more efficiently.
- Thousands of sign-ups a day, and no way to tell who they were (1 min)
- Inbound forms waited for a person to route them (1 min)
- Product usage data sales could not use (1 min)
- A custom enrichment waterfall on every sign-up (1 min)
- Routing that reaches the right rep in minutes (1 min)
- Account linking that shows the whole team (1 min)
- Callbacks in under an hour, not 24 (1 min)
- Personal-email sign-ups identified, from zero to 15-20% (1 min)
- 45-60 minutes of research gone from every account (1 min)
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