best practices

Making the most of your startup data—how to structure, utilize, and generate revenue

Busy growing a startup? 

We get it—we’ve been there. And we bet that the growing mountain of data you’re generating feels like one more area of your business that needs to be optimized, organized, and sorted out. All that user data and lead data and customer data and people data and third-party data and…and…and…

Yeah. It can be a little much. 

But when it comes down to it, your startup data doesn’t have to be a burden. In fact, it could become your biggest competitive advantage.

After all, the market incumbents—all those competitors with bigger pockets and brands—haven’t actually figured out how to use their data properly yet. In fact, two-thirds of executives aren’t confident about their ability to access or use data with their existing tools and resources.

And here’s where your business has the advantage. You aren’t stuck with legacy systems or a data-resistant culture. You aren’t bogged down with “how we’ve always done things.” You have the chance to come out of the gate swinging. 

So how can you go from sitting on a slush pile of valuable data to turning it into dollars and business value?

A few questions to guide your data strategy  

Before you turn your startup data into revenue, it’s best to begin with some fundamental questions. Use these to guide your thinking when it comes time to make decisions.

  • What is our data worth? Frankly, there’s a very good chance that your company’s data is currently worth more than your company. If you can identify the commercial value of your data, you’re already a huge step ahead.

  • How important is self-service analytics for our customers? If you’re not prioritizing self-service analytics for your end users, you might be missing out on a huge opportunity. Think about what functions or insights your customers most often demand and how you can put them in the driver’s seat. 

  • How should we prioritize our analytics capabilities? Does our leadership recognize analytics as a revenue driver? If not, you might want to take a look at this guide on assessing the ROI of improved analytics.

Once you have a strong grasp on the questions above, you can take action by building a reliable data infrastructure.    

How to structure your startup’s data for more value 

Step 1: Identify your sources of data

You need to understand your data, where it’s coming from, and how you’re collecting it. Audit your business processes and inventory the data you’re accumulating. Ask questions to find out why you’re collecting this data and where it’s going. 

Step 2: Build a modern data stack that can scale with you 

If you don’t create a scalable, flexible, and governable data stack, you’ll struggle to derive any value from your data—let alone use it down the line to create new revenue streams. 

You need a modern data stack: a collection of tools and cloud data technologies to take you from data sources to data insights as efficiently as possible. 

Modern data stack flow

What you need in your startup data toolkit

Your data stack needs to include: 

  • Extract, transform, and load tools (ETL) to pull data from your sources and prepare them for your cloud data warehouse in an organized, intuitive manner. ETL options for startups: Fivetran, Matillion 

  • A reliable cloud data warehouse to store and manage huge volumes of data and scale storage as needed. Cloud data warehouse options for startups: Snowflake, Databricks  

  • Data transformation tools that prepare your data inside your cloud data warehouse to make it easier to analyze. Data transformation options for startups: dbt 

  • Data experience and analytics tools that make it easy for business users to visualize, interact with, and derive insights from your data. Data experience tools for startups: ThoughtSpot, Looker 

In general, startups should look for tools that are: 

  • Scalable, cloud-native, and flexible, so they can accommodate your changing needs

  • Efficient and lean, so you don’t add unneeded complexity as you scale 

  • Scriptable, so you can easily manage and document changes, reuse solutions, collaborate, and automate 

  • Self-service analytics, so you don’t create bottlenecks for your data team 

Step 3: Offset data costs 

As a startup, we’re guessing cost may be an issue. Here are three ways to reduce your data spend while you work toward generating business value from your data: 

  1. Use metadata to get visibility over your cloud data usage 

  2. Use your cloud data warehouse’s built-in resource monitors 

  3. Optimize your data stack’s performance 

You can also offset data costs by saving money in other areas of your business or by finding opportunities to monetize your data. Let’s look at a few examples of that below. 

How to generate value from startup data 

Once you’ve structured your data stack and optimized your costs, it’s time to think about generating business value. Here are four ways startups can boost their bottom line with data: 

1. Use your data to make better business decisions  

The most obvious way to get value from your data is to use it to make better decisions at a faster rate. As a lean and agile startup, your main advantage over the competition is your ability to move quickly. 

The startup cycle of rapid prototyping, iterating, and retesting customer responses depends on quick and easy access to the data. If you’ve set up your data stack correctly, you can back up your fast-paced decisions with granular data insights. 

For example, if you’re working with an AI-Powered Analytics solution like ThoughtSpot, you can analyze billions of rows in your cloud data warehouse at sub-second speed. Even more importantly, your business users can use natural language to find answers in your data in the same way they look things up on their favorite search engine—no SQL knowledge or data modeling required. 

Healthcare SaaS startup Wellthy is a great example of driving revenue growth through better access to data. Manual reporting and one-off requests bogged down their five-person data team; they knew they needed a true self-service BI solution to scale. They turned to ThoughtSpot to help them surface insights, empower their front-line business users, and drive operational success. 

Today, Wellthy has saved at least $200K by meeting their growing teams’ data demands—without hiring additional data analysts. On top of the cost savings, Wellthy has used granular insights to inform their Client Success team and generate more value for their employer partners. 

2. Drive product adoption and reduce churn with engaging embedded analytics experiences

To keep your customers returning to your products, you need to make those products stand out. Embedded analytics is a great option for high-growth startups looking to capture market share. By incorporating interactive data into the user experience, your applications and products become stickier and more engaging.

In fact, a study by Product Led Alliance found that over 60% of product professionals that build products and applications with embedded analytics have experienced increased engagement—and 57% experience increased revenue.

Here’s an example. One of our customers, Harri, offers an employee experience platform for the hospitality sector. Their customers began to request self-serve and interactive data. So Harri decided to embed ThoughtSpot Everywhere into their platform to create a consumer-grade analytics experience for their end users. 

“The more you engage with your end consumers, and make applications compelling and easy to use, the greater the adoption—and the more we can monetize a product because it becomes an essential part of our customers’ whole ecosystem.” 

- Mike Shipley, Strategic Advisor for Data Analytics at Harri

For Harri, the ability to build AI-augmented analytics tools was key to adoption. For instance, they wanted to let their customers see which hospitality teams worked well together and match the best managers with the best employees—tasks that lean heavily on ThoughtSpot’s machine-learning functions to cross-correlate data points. 

3. Monetize your data 

But it’s not just about making your existing products better. With the right data stack and an eye out for great opportunities, startups can also create brand-new revenue streams from their data. 

Here’s an illustration of what this could look like. One of our customers is an accounting practice management software startup with about 200 employees. They’ve embedded ThoughtSpot Everywhere into their existing product to create a new, premium-level analytics solution, for which they charge an additional $1000 per user. 

This brand is currently forecasting an additional $2 million in annual revenue simply by tapping into existing data to give their customers a more valuable solution. 

AI-Powered Analytics can transform your startup’s trajectory

Whether you use business analytics to make better decisions, outpace the competition, or build stickier products, data is key to differentiating your startup. Here at ThoughtSpot, we’re big fans of startups—after all, we were there just a few short years ago. That’s why we created a special program just for startups. If you join ThoughtSpot for Startups, you’ll get: 

  • Thousands of dollars in savings off ThoughtSpot Everywhere, with unlimited data, queries, and users across up to 250 user groups

  • Tools that let you quickly and easily embed our AI-powered analytics tools into any app to unlock new revenue streams while driving adoption and retention 

  • 24/7 pro-level support and dedicated learning sessions with our team of engineers

  • Membership to a thriving community of high-velocity startups building their business on data 

Sign up for ThoughtSpot’s 30-day free trial for Startups to start monetizing your startup data today.