‍No-Code Product Analytics — And How It Solves Your Problems

When you’re building and selling a digital product, timely analytics can make all the difference.

Understanding the ways customers interact with your app can help you fine-tune the experience you deliver. A/B testing of features and campaigns can guide optimization efforts to increase engagement and satisfaction. Insight into viral adoption patterns can inform where and how to invest your marketing and social media resources.

By translating data into knowledge throughout the product lifecycle, you can acquire the right customers, maximize their revenue potential, drive growth, and increase retention.

With benefits like these, it’s no surprise that the Product Analytics market is booming. In 2021, companies spent $9.3 billion worldwide on Product Analytics tools — with total revenue projected to reach $29 billion globally by 2028. However, these investments may not always yield the hoped-for returns. In reality, Product Analytics can only deliver a meaningful business impact if you can access the right insights at the right time, quickly and easily. And first-generation Product Analytics tools fall far short of that requirement.

Let’s dive into a few reasons why no-code Product Analytics can be a game-changer.

An Obstacle Course of SDKs, ETLs, and Silos 

In a business environment where speed is everything, most Product Analytics tools are still architected as if teams have all the time in the world.

Before you can even think about insights, you need to instrument your SDK to capture your data or build an ETL pipeline to load data from your cloud data warehouse into the vendor’s siloed black box. That’s especially challenging given the way data is stored in a data warehouse like Snowflake or Big Query, which call for a structure or schema that’s hard for legacy product analytics tools to ingest without extensive transformation. These time-consuming and resource-intensive projects will add weeks or months to your timeline. Even then, you’ve got to comply with their data model, not your own.

If the word “silo” sends chills up your spine, you’re right to be wary. Creating an alternate sense of truth invites no end of complications and confusion. Keeping both sets of data in sync will now be a constant concern to avoid issues resulting from data movement, data duplication, and irreconcilable differences – and an even greater challenge when you have to ask the vendor to make changes on their end and hope that they do it. As governance and transformation take place within the vendor’s environment, that data needs to be pushed back to your own data warehouse — creating yet another copy of your data. Your security and compliance teams won’t be happy about that loss of control, either.

Higher storage costs add insult to injury. With a pay-as-you-go cost model, companies often worry about event volume, leading them to either sample or cut back on the different events they are capturing with the product. That limits the amount of analysis they can perform.

All that extra effort and cost might be worth it if you ended up with the Product Analytics tools of your dreams — but no such luck. Instead, you face additional delays and friction every step of the way. Want to build a dashboard? Add a table and backfill data? You’d better not be in a hurry. Meanwhile, Product teams have no idea what’s actually happening inside that black box — how their queries are being run, how the resulting insights are being derived, or even whether the vendor understood their request in the first place.

When you’re spending millions on customer acquisition, going head-to-head with fast-moving competitors, and trying to retain customers in constantly shifting consumer markets, you need fast access to insights you can trust. That calls for the new approach to Product Analytics now offered by Kubit, the first warehouse-native Product Analytics platform.

The architecture of traditional Product Analytics tools might have made sense in the past, before companies developed their own metrics collection capabilities. These days, they want the flexibility, security, and control that comes with building their own data stack, complete with a modern cloud data warehouse. When you have your own environment, why should you have to move your data anywhere else?

No-code Product Analytics is built for the way companies capture and use data today. Instead of having to move your data to a vendor’s environment, and deal with all the resulting silo costs and headaches, a new generation of solutions let you connect the vendor to your live data right where it is, in your own cloud data warehouse.

That means you can skip all that SDK and ETL business, while maintaining a single source of truth that eliminates the need to coordinate data backfilling or scrubbing across multiple copies.

Just as importantly, you know exactly how your data is being secured because you’re doing it yourself. Also, the ability to share data as read-only with control over which columns to share or mask makes regulatory compliance a lot easier.

For users, no-code Product Analytics replaces inefficient workflows with direct control over both data and queries. Analysts can see exactly how each analysis is constructed, and can add new dimension tables, data, and properties as needed without a lot of time-consuming back-and-forth or development work.

Queries can be performed on complete data, not just a sample, enabling more accurate and comprehensive insights. Results can be compared easily with other data in the cloud data warehouse for deeper understanding. As a result, analysts can get fast answers to key questions like:

• Which product features are customers using most often—and which are they overlooking?
• Where in the user journey do we tend to lose the most customers, and why?
• Did a recent campaign bring in customers with high lifetime value or better retention, or should we rethink our targeting?
• How long is it taking people to perform various tasks, and how did this change in our latest update?

As customers demand more personalized experiences and recommendations, digital competition continues to intensify, and data becomes a key differentiator, the importance of Product Analytics will only grow in the coming years. Product teams need to escape the limitations of traditional tools and embrace a faster, simpler, more flexible, and more secure way to access insights. Designed for cloud-native speed and agility, no-code Product Analytics can help businesses make the right decisions at the right time to improve engagement, increase retention, drive growth, and succeed in the modern digital marketplace.