Lean Data

Evan Liang had the problem staring him in the face. As VP of products at caring.com—where he'd built a division described as "a Yelp for senior care"—he was managing an inside sales team selling to both SMBs and large enterprises. The company brought in Marketo to automate their sales process, but there was a critical issue: the Salesforce data was, in Evan's words, "kind of a mess." Marketing automation was just getting going in 2011, and when you layer automation on top of bad data, you don't just have one problem—you multiply it. "When you have bad data inside Salesforce, it's one problem. When you try to automate with bad data, you're going to create a ton of problems," he explained.

Before starting Lean Data, Evan had spent time on the VC side at Shasta Ventures and Battery Ventures, giving him rare insight into both the founder's journey and investor mentality. That background proved invaluable when he decided to leave Salesforce hell behind and start his own company.

Lean Data launched in 2012 with a PowerPoint pitch and two co-founders. Thanks to Evan's VC network, they raised a seed round of $1.3 million *before they wrote a single line of code*—an unusual move that required both sides to agree on a fair valuation with limited information. "You're going to convert it anyway, you might as well do it as a fair price round," Evan reasoned.

Development took about a year, with significant work on the algorithmic side of the product. During that time, the team didn't chase product-market fit in a vacuum. Instead, they took on services work—essentially acting as Salesforce admins and data cleanup specialists for customers. This wasn't a distraction; it was the foundation. "A lot of big SaaS companies come out of agencies," Evan noted. By serving many clients with similar problems, they identified the core product they needed to build: an engine that intelligently routes leads to the right sales reps based on account ownership, opportunity status, geography, or other custom segmentation. For a company like Cloudera, Lean Data figured out which sales rep should follow up with each inbound lead—not just which lead was hottest, but which human should get it.

First-year revenue came to "a few hundred thousand dollars," mostly from services. The transition from services to product was organic—as Evan scaled beyond hand-built solutions, the product naturally emerged. By 2017 (five years in), Lean Data had landed approximately 250 enterprise customers.

Growth channels have been unconventional and deliberate. Most famously, the company tried an ABM strategy involving pizza delivery. The playbook: identify a prospect, email them an offer to have lunch on them, let them pick a pizza place, and pitch the product over lunch via video call. It worked once—they traced at least one deal back to pizza—but it required an SDR to physically drive pizzas to locations that wouldn't deliver. "This is crazy," Evan admitted. Not scalable.

What *did* scale was events. Lean Data deployed a sophisticated event strategy with two components: booth presence at major conferences like Dreamforce, and more importantly, events-within-events. They'd rent out restaurants near Dreamforce, host lunch-and-learns and panel discussions, and run mini-conferences outside the booth. In the last 12 months, this conferencing strategy cost roughly $600,000 but drove significant pipeline. By contrast, digital paid acquisition was minimal—less than $10k/month—and largely untested. Evan flagged scaling paid ads as a key initiative after raising $10M in Q4 2016.

Evan's VC background shaped how he thought about unit economics. He capped lifetime value calculations at five years to avoid inflated metrics that obscure CAC payback reality. With $30k ACV, 10% annual logo churn, and 5-10% ARPU expansion, he derived roughly $150k LTV per customer—high enough to support a direct sales motion.

The Salesforce App Exchange integration became a strategic moat. Because Lean Data is a native Salesforce app, customers pay Salesforce for hosting, bandwidth, and storage—not Lean Data. This kept gross margins in the 80% range (versus 85-90% for pure SaaS) but eliminated infrastructure costs and positioned the product inside the ecosystem where every enterprise Salesforce customer could discover it. "Longer term, there's nothing about our business methodology that doesn't allow us to expand to other CRMs," Evan said, but in the short term, being embedded in Salesforce's 900-pound-gorilla ecosystem provided unmatched scale.

Building in Salesforce also meant the company had no custom backend servers—just basic admin infrastructure. Processing and everything else was handled by Salesforce. This made Lean Data capital-efficient but also raised an interesting exit question: could anyone buy them besides Salesforce? Evan saw it as a non-issue long-term.

Logo churn ran around 10% annually with 5-10% net revenue expansion per customer, driven by upsells to the attribution product (sold separately from the routing product). The company wasn't trying to be SMB-friendly; they were all-in on enterprise.

By the time of this interview, Lean Data had raised $18M total, built a team of 50 (15 engineers, 15 sales, 5 marketing, 8-9 customer success), and was generating approximately $7.5M ARR from 250 enterprise customers. The playbook was events + direct sales outreach, with a small R&D budget allocated to proving out paid acquisition at scale. Evan remained CEO and focused on executive coaching and scaling the organization itself—he slept eight hours a night, had two kids, and was married. At 38, he reflected that he wished his 20-year-old self had known he wanted to be an entrepreneur earlier, rather than spending time in VC and finance first. But that detour had given him the network, knowledge, and confidence to raise before building—a luxury few founders get.