Process millions of IP addresses via Clearbit to create enriched, actionable leads
Replace time-consuming manual process with automated workflow that seamlessly integrates Clearbit, Redshift, Salesforce, and Slack to instantly alert sales with new opportunities
Immediately identifies hottest accounts for sales team to engage
Gives sales leadership ability to deploy sales teams to most opportune locations
Empowers executives to strengthen go-to-market to nearly 20% of Fortune 500
Developers from around the globe solve development, operations, and security challenges with the company’s tools so that their own firms can focus on business-critical tasks by using consistent workflows to provision, secure, connect, and run any infrastructure for any application.
The cloud leader knew that millions of IP addresses had downloaded the free versions of its open-source software. Its marketing and sales teams were looking for an opportunity to utilize this enormous volume of interest to drive new revenue by connecting with these users to begin new sales conversations. However, the company lacked the tools and internal process to track the ongoing stream of IP addresses continuously at scale.
The company had been collecting IP addresses for several years in an Amazon Redshift database. It tracked every visitor who came to the website and downloaded the open-source software directly. While the company found it could use the data to frame general trends and analysis, as its sales team began to grow, it needed more intelligence about which firms were downloading which products, how frequently, and what the attributes of those firms were in order to target similar, “look-alike” firms for sales. “We had an enormous amount of IP address data on file,” says the company’s marketing operations lead. “Unfortunately, we didn’t have a good way to turn that data into something actionable for our sales team.”
The company initially tackled the problem with a one-time, manual process: Running a reverse IP lookup through the lead enrichment solution Clearbit to get company names and attributes in order to get a sense of the value of that user’s particular workflow to the sales and marketing teams. The company used the characteristics it gathered from that initial run to identify companies that were already downloading its software and would be worth targeting for sales reps. It also attempted to use this information to determine the best geographic locations to hire salespeople in proximity to large clusters of companies downloading software, as well as to pull up the attributes of those companies in order to find look-alikes for new target accounts.
Additionally, executives were able to use this information to support and refine organizational go-to-market (GTM) strategy by understanding the mix and type of companies with which the open-source products were resonating, along with the depth, breadth, and frequency of downloads within those companies. However, running this one-time process was far too time-consuming, and most importantly, it wasn’t scalable. As the company continued to collect thousands of new IP addresses, despite scaling its sales hires, this process wasn’t fast enough to be actionable for its sales team. “Running a manual Clearbit batch job to enrich the millions of leads we already had on file was a stopgap,” admits the marketing operations team. “With so many new users constantly downloading our software every day, we knew that one-off jobs wouldn’t scale the way we needed them to.”
In order to successfully scale the process of looking up IP addresses and enriching them for its revenue team, the open-source leader needed the means to build automated processes that could process such huge volumes of data, and could then distribute that processed data to a variety of different revenue stack applications.
As such, the company especially needed the ability to connect with a variety of application APIs and data formats, as well as the ability to add complex conditional logic, branches, and loops to efficiently deal with millions of potential leads while iteratively enriching and de-duplicating lists of thousands of leads.
The company needed a solution that would help it integrate its internal IP address data with its entire cloud stack, which included Redshift for data warehouse, Clearbit for enrichment, and Salesforce for CRM. It also needed a way to create this process without expensive IT resources - ideally one that was user-friendly enough for business users. It found the Tray Platform. “We’re a technology company,” explains the company’s marketing operations team. “Some of the most successful enterprise companies in the world use the enterprise versions of our software. So we tend to focus our development resources on building better products, rather than solving internal process issues like lead enrichment.”
Using the Tray Platform, the company created a customized, automated workflow that integrated its cloud applications to regularly run the processes it needed, at scale.
The team’s powerful, multi-step workflow began by automatically reading the IP addresses stored in its Redshift data warehouse, then fed these IP addresses into Clearbit’s API to enrich them into fully-baked leads with fleshed-out company information. The workflow then sent this information directly its sales team via its internal messaging app, Slack, while also logging key demographic, firmographic, and technographic details on each company into its CRM, Salesforce.
As a result of building this automated workflow on the Tray Platform, the company is now able to continuously process incoming IP addresses of new users that download its software, and instantly translate that data into enriched leads for its revenue team. This workflow now immediately flags which priority accounts to engage, as well as when specific accounts engaged with the company’s software to identify the optimal timeframes for follow-up.
Having implemented the Tray Platform for sales intelligence and enablement, the open-source cloud leader is now actively working on building new automated workflows that integrate additional parts of the company’s collective tech stack.
For instance, the team is now building workflows to automate additional parts of its sales cycle, such as integrating Salesforce to Slack to send real-time alerts once sales deals hit the review stage.
The company is also looking to use the Tray Platform’s integration with the popular helpdesk solution Zendesk to empower its customer support team by automatically sending alerts to prep its support team once sales deals reach a specific stage.
“We’re a company poised for growth, which is why we need deep integrations throughout our stack to get us to where we’re going, faster,” said the company’s marketing operations lead. “We’re finding that the Tray Platform is giving us more opportunities to store and flow important data to our teams, so we can focus less on operational tasks and more on growing our company.”