Today I’ll talk about something that’s crucial but often overlooked in a portfolio of products: data consistency. In simple terms, data consistency means making sure that your information is uniform, accurate, and coherent not just within your databases and applications, but across all your products and services. Why should you, as a productizer, care? When your product teams focus on data consistency, you’re not just avoiding confusion and cutting down on customer support requests; you’re building a solid foundation for growth and innovation.
If the data you share isn’t consistent across your different SaaS offerings, you risk your customers making poor strategic decisions, losing their trust in your company, and stunting both your own company’s and your customers’ growth. Imagine your customers trying to use information that doesn’t match up across different tools—they’ll waste time trying to sort out discrepancies or fix errors, they’ll be hammering your support team with inquiries, asking for credits and sharing their lower overall satisfaction with your products with the market at large.
For businesses starting to scale, it’s easy to feel confident when you finally have some data to work with. But don’t let that initial excitement fool you into thinking that data quality issues will fix themselves. As you develop your products, it’s crucial to understand the challenges and investments required to ensure robust data solutions. A significant challenge is integrating data from various sources is no small feat. Different sources often have unique structures, formats, and rules, leading to mismatches and errors. For example, when combining third-party data sources, you might encounter inconsistencies because of their differing data handling processes. These mismatches can make it difficult to establish a single version of “truth” for your data.
And let’s not forget about data governance—or rather, the lack of it. Without solid data governance practices, there’s no systematic way to validate, clean, or monitor data. This can let inconsistencies slip through the cracks and make it harder to spot and fix data issues. Incomplete updates, whether from rate-limited APIs or even data scraping, can lead to incorrect calculations and reporting errors. This, in turn, can impact key business decisions, from purchasing to campaign strategies.
In summary, having a robust, consistent data solution isn’t just a nice-to-have—it’s essential. It helps your customers focus on their own business instead of struggling with unreliable data. So, invest in data consistency right away and continue to invest as you grow – this paves the way for smoother operations and better decision-making down the line.