Lacework, which automates cloud security at scale for its customers, uses Oracle DataFox Data Management to accelerate revenue growth.
Lacework provides automated threat defense and intrusion detection for cloud workloads and containers across AWS, GCP, and Azure environments. On average, customers who use Lacework can remove between two to four security products from their environment and reduce alert investigation time by 90% or more. Founded in 2015, the venture-capital backed company has achieved unicorn status, announcing in January 2021 a $525 million investment at a valuation of more than $1 billion. Lacework’s revenue grew 300% year over year for the second year in a row.
To achieve this fast growth, Lacework needed an account scoring model to help identify accounts where the company not only had the best probability of winning, but could also increase its average deal size and shorten sales cycles.
Lacework was also looking to improve its operational efficiency and have sales teams focus more time on selling activities rather than researching activities. This meant providing the team with a simple, prioritized view of accounts so salespeople could be strategic in their outreach, but also receive alerts when compelling events were happening in their territories so they could be reactive as well.
In the end, sales reps needed to have a strategic, proactive approach to selling into target accounts where they had the best probability of winning, while also being able to react to changing market conditions and being opportunistic when the situation called for it.
I definitely consider Oracle DataFox core to our sales and marketing tech stack. From identifying our Ideal Customer Profile (ICP) to prioritizing target accounts to filling in whitespace in our database, DataFox is at the center of our strategy. I couldn't do my job without it. It has helped us drive 3X revenue growth year over year.
Vice President, Revenue Operations, Lacework
Lacework selected Oracle DataFox Data Management for ease of use and seamless integration with the rest of the company’s tech stack.
For example, Oracle DataFox integrates with Slack, alerting sales reps via Slack channels when an account is mentioned in the news or triggers one of the many growth signals that they monitor, allowing reps to react in a timely and contextual manner. The DataFox Chrome Extension makes account intelligence available directly within the web browser, helping to reduce rep research time.
DataFox allows Lacework sales reps to focus on a single data feed, instead of having to manage hundreds of data sources. It reduces a lot of noise and administrative work, helping reps make better decisions.
Using Oracle DataFox, Lacework was able to increase its database from 30,000 target accounts to more than 100,000 in less than a year, filling in whitespace exclusively with accounts that were highly scored and showing technical fit. With account scoring and sales alerts supported by DataFox, company revenue grew 300% over the past year—using the same sales process as before, with the addition of pointing sales reps toward the right accounts and giving them context on why and when they should be going after those accounts. Marketing took advantage of the same techniques, focusing spend on the top 20% of accounts. Thus, the company created better alignment between sales and marketing and gained marketing spend efficiency.
Lacework used Oracle DataFox to establish an account scoring model that helps scale and prioritize sales opportunities. This has been an important factor in helping the company maintain fast revenue growth.
The account scoring model is based on five attributes based on technographic and growth data and signals. Rooted in the company's ideal customer profile, these attributes are unique to Lacework's target market and serve as the foundation of the targeting strategy.
Oracle DataFox scores not only the 100,000 accounts in Lacework's internal database, but also more than 7 million companies DataFox has visibility into. The company takes these scores and translates then into a simple grade of A,B,C,D,E,F. Typically, fewer than 5% of accounts meet A-grade criteria, and fewer than 20% have grades greater than C—a nod to the importance of using account scoring to surface high-value prospects and opportunities. Before this scoring, accounts were tiered solely based on static cloud spend data, employee headcount, and industry designation.
Reps typically have 50 strategic accounts that they're actively pursuing, plus another 1,000 that round out their territory. The team understands that a rep can't manage 1,000 accounts, so DataFox monitors these accounts and alerts the rep when there is a compelling reason to engage, whether it be a funding announcement, acquisition, new key executive hire, and so on.
“What we've found is that reps pay attention to their top 50 accounts. They go after them, and DataFox acts like a personal assistant, tapping them on the shoulder and saying, ‘You might want to also include this company in your prospecting because they have just received funding, or had a data breach, or maybe they just showed user growth of 300% and they probably have some security needs we can address,” says Palen Schwab, Lacework’s vice president of revenue operations.
Lacework can use the account scoring model to look across its internal database, but also to look across millions of accounts provided by Oracle DataFox to boost their database with accounts that make sense.
Oracle DataFox works the way it’s positioned. It is the easiest tool to use in our tech stack. It works like a personal assistant.
Vice President of Revenue Operations, Lacework