I started working with my co-founder Vincent Yang almost six years ago. And our other co-founder, Chao Wang worked with Vincent more than 10 years ago. Although EverString was incorporated and became an official company in 2012, the pain that gave rise to the business is much older.
How it All Began
It all started while Vincent and I were working together at Summit Partners, a $16 billion growth equity and venture capital firm which sought to invest in rapidly growing companies.
In growth equity, you research companies, select primary targets based on research and lead qualification, and then pitch them on why you are the right partner to help them grow their businesses and realize liquidity.
Our focus was optimizing the choice of companies we invested in by finding the companies that had the highest chance of wanting to work with us. The only way to be effective in sales was by heavily researching targets and then, since we had limited resources, carefully selecting the right companies.
Sound familiar? This is the classic marketing dilemma. You have a finite set of resources (time, money, people, etc.) and must choose your audience carefully to be as efficient as possible.
The Data Dearth
Like most B2B organizations, growth equity professionals are forced to initially qualify leads with imperfect and very limited information. The targets are almost always private companies, and are often mid-sized or emerging companies with minimal publicly available information.
In growth equity, people quickly learn that the typical commercial sources of data about company revenue, employee count, and industry are almost worthless. Those sources contain self-reported and intentionally deceptive data, out-of-date information, and generally an absence of any accurate data at all.
This data void leads many venture capital and growth equity investors to rely on large teams of cold callers. As a marketer, you probably call the cold callers Sales Development Representatives (SDRs) or Business Development Representatives (BDRs), and in the VC and growth equity world they are called Associates or Analysts. Similar to your SDRs and BDRs, those investor tele-prospectors spend their days trying to directly collect information about prospects to qualify them, so that they can be moved through the pipeline.
There are approximately six million companies in the U.S. which are large enough to have a website. If you want to have a point of view on every single one, and if you want to fast-track qualification and engagement with the subset that are a fit, that requires a LOT of cold calls.
Plus, bad leads were also a huge problem. With a highly-paid, traveling field sales organization like most growth equity firms have, the cost of spending time on bad leads is immense. As an example, I distinctly remember traveling to the Midwest to visit a prospect that was reportedly a great fit. Sitting in the room with the executive at the prospect, he told me that he used to work at one of our main competitors, and that if he were ever to do a deal, he would do it with them. Two flights, two days, and a couple thousand dollars later, I was feeling the acute pain of our team not having qualified the lead beyond the few simple variables we always started with.
There had to be a better way.
Applied Data Science and Audience Selection
Vincent and I have spent the largest chunks of our careers selling, and we have felt the pain of manually qualifying thousands upon thousands of leads and spending significant time, energy, and money to go deep chasing a lead that would later prove to have been under-qualified.
Born out of this pain and pressed against an academic background in Mathematics, Vincent developed a hypothesis that would change the way that we and others think about lead qualification and lead acquisition.
If we could collect a much broader set of signals on every possible company and then build an accurate model of what the ideal target looked like based on actual historical data, we could form an intelligent point-of-view on every single company in the market. This was the genesis of EverString’s Account-Based Audience Selection.
After Vincent left growth equity, he began building the core of the EverString platform. With $1.7 million of seed funding from Sequoia Capital, IDG Ventures, and others in late 2012, Vincent and a small team of data scientists set out to build a minimum viable product.
Almost nobody in predictive marketing has managed to turn data science into software-as-a-service, but we knew early on that automating model building would be key to success. Following the initial 18-month R&D phase, I shifted from part-time Advisor to full-time President of EverString in March of 2014.
Vincent finished his Stanford MBA in May of 2014 (and had his first child during the same time period), and we shifted the business into high gear, signing our first few customers, and then raising a $12 million Series A led by Lightspeed Venture Partners in August 2014.
What’s in a Name: EverString
We get asked all the time how we came to our name, and of course there is a logical answer rooted in science. EverString, and our logo for that matter, refers to the connections or relationships between nodes in a model. EverString helps you define the relationships between your business and the world of others in your addressable market…so that you can optimize audience selection for your business.
Realizing a Vision
EverString has proven the hypothesis that with predictive audience selection, we can analyze and validate a total addressable market (TAM) for every B2B company, and help them optimize their sales and marketing funnel in a wholly new way. We started by helping companies score accounts and leads in their existing funnel, so they could be more efficient in the way they approached their prospects.
However, our vision was much deeper than this, as our goal since the early days was to enable the use of predictive analytics both inside and outside existing sales and marketing pipelines. More than a year ago, we extended the use of our audience selection to enable predictive demand generation, feeding millions of high-potential accounts and leads into the tops of our customers’ funnels. An algorithmic point-of-view on every single company in your addressable market can now be harnessed to optimize top-of-funnel demand generation.
And there is more to come. The EverString Predictive Labs team is busy creating new ways to apply predictive technology across (and beyond) the funnel. We all share a common vision—to use data to change the way we market and sell.
We envision a world where artificial intelligence will enable organizations to compete more efficiently, and to have more control than ever over driving growth and performance within their businesses—and this journey is already well underway.
2015 and Beyond
The past three years have been amazing, but we are even more excited about the years ahead. The early days with six people in tiny offices quickly evolved into our first San Mateo headquarters, with room for 30 people. Today we are headquartered in a new San Mateo office, with more than 100 team members worldwide.
Our rapid growth is exciting, but the fact that we have built most of our book of business using our own product, is an inspiration for where we can go from here. Along the way, we have built the single best team in the business. We have leaders across all parts of our organization, and we are positioned to not only outperform in this rapidly growing market, but to become the category-defining business. Our team is comprised of the deepest bench of data scientists, with advanced degrees from Stanford, MIT, and CMU and experience from companies like Netflix and BlueKai. Our go-to-market team is similarly filled with the best-of-the-best, with experience from technology leaders such as Marketo, Hortonworks, and Salesforce.
EverString’s is a great story, but this is only the beginning. Over the coming months and years, we will be fundamentally changing the way that marketers and sales professionals perform. We look forward to the adventures ahead, and we sincerely thank the investors, team members, family members, and customers who have made EverString’s today and tomorrow possible.