Allie Beazell is director of developer marketing @ Census. She loves getting to connect with data practitioners about their day-to-day work, helping technical folks communicate their expertise through writing, and bringing people together to learn from each other.
Welcome to part one of our series on evaluating reverse ETL tools. This was updated December 2, 2022 to better capture the current state of reverse ETL tooling. We recommend grabbing our new-and-improved companion guide, The definitive guide for evaluating reverse ETL tools, to complete the set. 📚
In this installment, you’ll learn why you should invest in reverse ETL, and, more importantly, why you should invest it now. We’ll focus on:
Why reverse ETL now ⏱️, including:
How business teams have contributed to this need 👩💼
How data engineers have contributed to this need 📊
How a dedicated reverse ETL tool can streamline and simplify your data architecture 🧰
How reverse ETL can help you adapt at the flip of a switch 💡
How the push toward more personalized contributed to this need ❤️
The new era of data for business and data teams made possible by reverse ETL right now 🙌
Every day, your customers get up in the morning, make some coffee, go to their computer, and start a conversation with you.
No, they aren’t using words. They’re communicating with data.
If you’re like most modern, data-driven companies, you’ve invested a ton of money to figure out how to listen to these conversation points (about $467 billion globally in 2020, according to Gartner) with new data pipelines. But you still haven’t cracked that final piece: How do you turn all that data into a two-way conversation? After all, while every solid relationship should be mostly listening, you need to show you understand your partner’s needs, too.
Reverse ETL can drive personalization and growth like never before while unlocking the data team’s ability to do their best and brightest work to operationalize analytics across the company. This means happier data teams, and stronger, more communicative dialogue with customers. But only if the new generation of data leaders and RevOps experts know how to evaluate and implement these tools successfully.
That’s why we’ve created our reverse ETL evaluation content series. This collection of resources (starting with the installment you’re reading right now and culminating in The definitive guide to evaluating reverse ETL tools) are designed to help you parse why reverse ETL is so important, examine the trade-offs of build vs. buy, and understand the key things to look for when partnering with a reverse ETL vendor.
Why reverse ETL (and why reverse ETL now)? ⏱️
Reverse ETL is a doorway that allows you and your company to step into the new era of Operational Analytics. Instead of just using business intelligence to look in the rearview mirror and identify trends for long-term strategy, you can leverage your insights to take action in your day-to-day operations.
But why reverse ETL now? Well, that comes down to five things:
1. Business teams are using more SaaS apps than ever 👩💼
According to the 2020 SaaS reports, companies have an average of 137 unique apps! 😱 Every day, teams need to buy more and more specialized software to stay competitive and serve the ultimate customer experience. But they can’t get the lifetime value out of all these specialized (read: expensive) apps without trustworthy, real-time data access. Instead, operations teams end up tangling integrations together or data teams get saddled with building custom connections to and from these apps that cause more issues than they fix.
2. Data engineers are too valuable to be pipeline babysitters 🧑🍼
The increasing number of applications used by business teams has caused the number of support tickets and custom requests from Ops teams to surge, leaving in-house engineers and analysts scrambling to keep up. Or even worse, they fail to manage your data product, making the data less valuable (and reducing everyone’s trust in data along the way).
Building an integration once is easy. Maintaining it and the corresponding SLAs is awful. And without a dedicated reverse ETL solution, data teams waste their skills buried under error messages and integration maintenance. Companies should instead be leveraging their high-value data folks on transforming data to unlock new value for the business, whilst simultaneously enabling business teams to be more self-service.
3. Companies need better personalization and engagement to be competitive
Customer journeys are longer and the relationships we build with each user in our CRMs are more complex than ever before. Sales, marketing, and customer success teams need a way to action customer data from each customer touchpoint to ensure they convert. Reverse ETL enables you to automate personalization at scale and ensures the data you’re collecting and ingesting makes it back to the front-line teams that need it most.
4. Dedicated services do a better job than other tools in your data stack doing things “half-well”
The plug-and-play nature of point-to-point platforms like Workato, Zapier, or Tray often entices teams with quick fixes. But relying too heavily on these duct tape solutions can quickly get messy. Fully integrating point-to-point solutions requires exponentially more connectors as your data stack grows, adding more complexity to your tools and increasing your costs. In fact, the number of connections grows by the square of the number of applications, meaning just eight apps could require as many as 64 distinct connections to keep your entire modern data stack in sync.
So, instead of a messy, spaghetti pile of point-to-point integrations, you can use reverse ETL to architect your data infrastructure as a series of orderly spokes around your central hub (data warehouse). This creates a single source of truth informing each application and workflow within your stack, eliminating silos, and making you truly data-informed. Plus, by centralizing, you reduce the overall complexity and number of connections, thereby reducing your bills.
5. You don’t need to build new for a different use case. Adapt with just the flip of a switch.
Connecting teams throughout your organization to the warehouse using reverse ETL empowers them with data-enriched, valuable context about what your customers are doing in real-time. By quickly and easily tapping into powerful data insights, reverse ETL is often the difference between a missed connection and a life-long customer bond.
Marketing, for example, is one of the core use cases for reverse ETL. Here, speed really matters. Why? The faster you get data into your marketing tool, the faster you can reach your customer and delight them with personalized messages. For example, with reverse ETL, marketing teams can build hyper-personalized marketing campaigns in HubSpot by merging product, customer support, and sales data to power customer segmentation. Now, successful business teams can self-serve deep, useful data so there are no more missed opportunities.
Why? For business users, reverse ETL puts fresh, actionable product usage data in all their frontline business tools whenever they need it. For data teams, reverse ETL allows their data to reach its full potential to fuel operational excellence for every business team that consumes it.
So, whether you’re in sales, marketing, data, or RevOps, you can use reverse ETL to operationalize your data, make decisions based on that data, and drive more revenue.
It’s time for a new era for the data team
This scenario probably sounds familiar to everyone reading this: The business team gets a shiny new tool. They hack together as much functionality as they can in self-serve mode before pushing the remaining work over to the data team like a wonky game of telephone. The data team, overloaded with similar requests from every stakeholder in the business, churns out a “good enough” solution as quickly as possible. Three months later, the connection breaks. We’ve said it once and we’ll say it again: Building a data integration once is easy, but maintaining it is awful.
So, we’re not doing that era of data anymore.
The flow of data from a cloud data warehouse (like Snowflake) into operational systems is no longer a nice-to-have stream of information, but an integral part of the modern company’s critical path, with data teams and tooling the shepherds that deliver it safely. After all, investment in quality reverse ETL tooling is like taking a well-engineered data cruise liner to your destination rather than an error-laden tugboat. Hint: The tugboat might sink your business.
In part 3.1 of our series on evaluating reverse ETL vendors, we dive into four key considerations to keep in mind while you shop: Data connector quality, sync robustness, observability, and security & regulatory compliance.