Events

5 Data Leaders on Product Category Creation | Census

Boris Jabes
Boris Jabes May 14, 2021

Boris is the CEO of Census. Previously, he was the CEO of Meldium, acquired by LogMeIn. He is an advisor and alumnus of Y Combinator. He enjoys nerding out about data and technology, 8-bit graphics, and helping other startup founders.

If investing in a new data tool is a mix of emotions, investing in an entirely new approach to data is an avalanche. It’s a flurry of excitement for a shiny new solution, apprehension about its worth as an investment, impatience to get it up and running, and so on. I first knew Census was onto something big when I could see all these emotions play out in real-time during my conversations with early prospects. This emotional state is a decent indicator that you’re on the verge of creating a new product category.

Our early prospects recognized that they were investing in something new: operational analytics powered by reverse ETL. They asked tough questions, poked holes, hemmed and hawed, and then bought into a new approach to data.

All of this was brought to mind thanks to a fantastic question we received in the first session of our Operational Analytics Conference.

The conversation was between:

An audience member asked the panel about category creation (i.e., creating a product so unique, it defines a new category of products) and how to be heard in a loud marketplace. It was one of my favorite questions in the whole conference.

The main takeaway is that creating a category is messy and difficult. We often described it as “like eating glass” because it’s “probably the toughest route that you can take as a founder,” as Martin said. Even so, there are a few things you can do to ease the transition and become an industry leader.

Have a unique vision that aligns with existing customer behavior

Entering a market with a unique point of view is always going to be an uphill battle. If you have a totally unique vision, you’ll spend a lot of time getting people on the same page. On the other hand, if your perspective isn’t unique, you’ll become another copycat product.

In our discussion, we landed on the conclusion that you should generally aim for what we called the “middle way,” where you have a unique perspective that rides on the momentum of current customer behavior.

Barr described this middle way as a situation where “you have a vision for what the world should look like, but the pain is here and now—very real and immediate.” This is in contrast to the “hard way,” where you have a unique vision that no one else sees, and the “simple way,” where your point of view is an iteration on existing perspectives. All three approaches can work, but, as Martin put it, which approach you choose comes down to asking yourself, “How much glass do I want to eat?”

The hard way is an uphill battle the entire time – you’re convincing others that both a problem or opportunity exists that no one has noticed yet and that you have a solution for it. An example of the hard way might be Concur, the true first software as a service (SaaS) business, introducing the SaaS business model in 1998. It worked out well for them as they were acquired by SAP in 2014  – at the time the largest SaaS acquisition – but it took a lot of upfront work.

The simple way is much less of a battle, but the victory isn’t as sweet. There’s typically a problem or opportunity that most recognize and that has existing solutions, but your solution has a unique enough spin.

The middle way strikes a balance between these two approaches, where the problem or opportunity is well known, but no one knows how to solve it (or even if it’s solvable). Your job in creating a category would be to educate people on how to think about the problem or opportunity, and present the solution.

Barr’s company Monte Carlo is a good example of the middle way. She identified a clear problem most of us in the data world know and have dealt with: “data downtime.” The unique perspective she brings is that data downtime is a much bigger problem than most realize. The existing customer behavior is dealing with data downtime manually, and the unique perspective is that you don’t have to.

Define the vocabulary of your category with marketing

When you create a category, you’re articulating problems and solutions that haven’t been articulated effectively before. As Jeremiah put it: “People will only seek a solution for the pain that they know how to describe.” Describe the solution and pain points for your audience using your product, content, and messaging.

George pointed out that any new category comes with the baggage of the previous generation of tools. If a customer has been approaching a problem one way for the last decade, they might assume that’s the only way to think about it. And if your product is truly unique, it might go over their head unless you provide clear language to explain what it solves and how.

This is essentially the same problem Henry Ford ran into when he coined his axiom quoted by MBAs the world over: “If I had asked people what they wanted, they would have said faster horses.” This isn’t because people lack vision; they just don’t know what a car is yet. They don’t have the vocabulary to talk about cars.

This is where product and content marketing come in. Explain the category, demonstrate the solution your product provides, and partner with others that tackle related issues. Tell your customers what a car is before they can start asking for it.

“People will only seek a solution for the pain that they know how to describe.” - Jeremiah Lowin, Founder and CEO of Prefect

In the end, Jeremiah summed it up well: “Good companies build what their customers ask for, and great companies built what their customers want.” What people want when they ask for a faster horse is what a car achieves—faster travel. Define what a “faster horse” is and what a “car” is, and along the way, explain why your category-creating product is the first—or best—“car.”

Be disciplined about what you fix and when

Category creation is a courageous thing—you’re really putting yourself out there and making yourself a target for naysayers. To tell when those naysayers are right or when they’re pulling a classic Hacker News moment, you need to establish a disciplined approach to rolling out your product.

George observed that “Snowflake was extremely disciplined about which things they innovated on and changed. They even kept Oracle’s damn capitalization conventions!” Snowflake didn’t fix everything at once. They have a surgical approach to what features they think a data warehouse should have. They focused their whole attention on those features to the exclusion of other very real pain points they could solve later.

I recommend choosing signposts for what’s worth fixing now and what’s worth fixing later. At Census, we first focused on operational analytics and reverse ETL, which can sync data from your data warehouse with your favorite tools. We want to perfect this function, establishing it as an important development in the data world, before moving on to other supporting features, like code-based data orchestration and deeper data validation. The order in which you innovate matters. Essentials first, nice-to-haves later.

Pick something right at the edge of achievable, achieve it, then do move on to the next thing.

Just start

Experience is the only way to know for sure if you’re creating a category correctly. This is perhaps an unsatisfying answer, but you should find it motivating because the best way to create a category is to just get started.

Barr shared an anecdote that captures the need to get started. She started three companies at the same time, one of which is her current company, Monte Carlo. As we mentioned above, she and her team defined the “data downtime” problem and category.

The way Barr knew that Monte Carlo was onto something big was that she had to do way less work selling it to customers than her other two ventures. She said:

“I could really see what a bad product market fit looks like. It looks like people not calling you. When I worked on the idea behind Monte Carlo, people would call me before I could call them. When you actually go through those experiences, it becomes pretty clear where there’s pull and where you’re just eating glass all the way.”

George at Fivetran, Jeremiah at Prefect, and myself at Census can all echo this sentiment. I can tell you that, as a founder, you will eat a lot of glass. But by just starting, you’ll gain the experience needed to know what it feels like when your diet becomes less glass-centric.

When you’re in the same position as Barr, where people are calling you, you’ll know you’ve found the middle path of category creation. But Barr would not have reached that point without her experiences with her other ventures. Here, two failures weren’t failures—just a part of her overall success with Monte Carlo.

Data is how you differentiate

The prerequisite to creating a category is having a product different enough that it’s in a category all its own. And, as Martin said early on in our discussion, “What differentiates apps has to do with how they manage data.”

This statement matches the trends we’ve seen develop in the industry and what we’ve seen among our customers. Those who manage their data well and put their data into action see compounding benefits that only improve over time.

Census, Fivetran, Monte Carlo, and Prefect all help you manage your data better. Schedule a Census demo today, and we’ll show you how we can help you differentiate your product.

Related articles

Product News
Sync data 100x faster on Snowflake with Census Live Syncs
Sync data 100x faster on Snowflake with Census Live Syncs

For years, working with high-quality data in real time was an elusive goal for data teams. Two hurdles blocked real-time data activation on Snowflake from becoming a reality: Lack of low-latency data flows and transformation pipelines The compute cost of running queries at high frequency in order to provide real-time insights Today, we’re solving both of those challenges by partnering with Snowflake to support our real-time Live Syncs, which can be 100 times faster and 100 times cheaper to operate than traditional Reverse ETL. You can create a Live Sync using any Snowflake table (including Dynamic Tables) as a source, and sync data to over 200 business tools within seconds. We’re proud to offer the fastest Reverse ETL platform on the planet, and the only one capable of real-time activation with Snowflake. 👉 Luke Ambrosetti discusses Live Sync architecture in-depth on Snowflake’s Medium blog here. Real-Time Composable CDP with Snowflake Developed alongside Snowflake’s product team, we’re excited to enable the fastest-ever data activation on Snowflake. Today marks a massive paradigm shift in how quickly companies can leverage their first-party data to stay ahead of their competition. In the past, businesses had to implement their real-time use cases outside their Data Cloud by building a separate fast path, through hosted custom infrastructure and event buses, or piles of if-this-then-that no-code hacks — all with painful limitations such as lack of scalability, data silos, and low adaptability. Census Live Syncs were born to tear down the latency barrier that previously prevented companies from centralizing these integrations with all of their others. Census Live Syncs and Snowflake now combine to offer real-time CDP capabilities without having to abandon the Data Cloud. This Composable CDP approach transforms the Data Cloud infrastructure that companies already have into an engine that drives business growth and revenue, delivering huge cost savings and data-driven decisions without complex engineering. Together we’re enabling marketing and business teams to interact with customers at the moment of intent, deliver the most personalized recommendations, and update AI models with the freshest insights. Doing the Math: 100x Faster and 100x Cheaper There are two primary ways to use Census Live Syncs — through Snowflake Dynamic Tables, or directly through Snowflake Streams. Near real time: Dynamic Tables have a target lag of minimum 1 minute (as of March 2024). Real time: Live Syncs can operate off a Snowflake Stream directly to achieve true real-time activation in single-digit seconds. Using a real-world example, one of our customers was looking for real-time activation to personalize in-app content immediately. They replaced their previous hourly process with Census Live Syncs, achieving an end-to-end latency of <1 minute. They observed that Live Syncs are 144 times cheaper and 150 times faster than their previous Reverse ETL process. It’s rare to offer customers multiple orders of magnitude of improvement as part of a product release, but we did the math. Continuous Syncs (traditional Reverse ETL) Census Live Syncs Improvement Cost 24 hours = 24 Snowflake credits. 24 * $2 * 30 = $1440/month ⅙ of a credit per day. ⅙ * $2 * 30 = $10/month 144x Speed Transformation hourly job + 15 minutes for ETL = 75 minutes on average 30 seconds on average 150x Cost The previous method of lowest latency Reverse ETL, called Continuous Syncs, required a Snowflake compute platform to be live 24/7 in order to continuously detect changes. This was expensive and also wasteful for datasets that don’t change often. Assuming that one Snowflake credit is on average $2, traditional Reverse ETL costs 24 credits * $2 * 30 days = $1440 per month. Using Snowflake’s Streams to detect changes offers a huge saving in credits to detect changes, just 1/6th of a single credit in equivalent cost, lowering the cost to $10 per month. Speed Real-time activation also requires ETL and transformation workflows to be low latency. In this example, our customer needed real-time activation of an event that occurs 10 times per day. First, we reduced their ETL processing time to 1 second with our HTTP Request source. On the activation side, Live Syncs activate data with subsecond latency. 1 second HTTP Live Sync + 1 minute Dynamic Table refresh + 1 second Census Snowflake Live Sync = 1 minute end-to-end latency. This process can be even faster when using Live Syncs with a Snowflake Stream. For this customer, using Census Live Syncs on Snowflake was 144x cheaper and 150x faster than their previous Reverse ETL process How Live Syncs work It’s easy to set up a real-time workflow with Snowflake as a source in three steps:

Best Practices
How Retail Brands Should Implement Real-Time Data Platforms To Drive Revenue
How Retail Brands Should Implement Real-Time Data Platforms To Drive Revenue

Remember when the days of "Dear [First Name]" emails felt like cutting-edge personalization?

Product News
Why Census Embedded?
Why Census Embedded?

Last November, we shipped a new product: Census Embedded. It's a massive expansion of our footprint in the world of data. As I'll lay out here, it's a natural evolution of our platform in service of our mission and it's poised to help a lot of people get access to more great quality data.