Which Data Should You Centralise?
For many organisations, the journey to becoming data-driven begins not with advanced analytics or third-party datasets, but with a far simpler exercise: understanding the data they already have. Most modern companies are already producing vast amounts of valuable information through their day-to-day operations. What is often missing is the structure, clarity, and focus needed to turn this information into insight.
Most Businesses Already Have the Data They Need
One of the most common misconceptions about data maturity is that it requires gathering information from external or exotic sources. In reality, many businesses already hold the data they need, often in their backend databases, web analytics platforms, CRM systems, or billing tools. These systems capture the digital footprint of customer interactions: site visits, signups, purchases, support queries, and renewals.
For example, an eCommerce business likely tracks every product added to a cart, every purchase, and every refund in its transaction logs. A SaaS company will have event-level usage data sitting in its backend. These internal, or “first-party,” data sources are typically the most accurate and relevant starting point for improving customer journeys, reducing churn, and optimising marketing spend.
Understanding What a Data Source Really Is
At its core, a data source is any digital system, platform, or file that generates information. This could be a backend server logging user behaviour, a spreadsheet tracking marketing spend, a CRM system logging support tickets, or a social media management platform. Most companies rely on a patchwork of such tools to run their business, and consequently, also end up managing data across multiple, disconnected systems. While each source serves a purpose, the real challenge comes when businesses try to combine them. How do you reconcile numbers between different platforms? How do you ensure consistency in metric definitions? And how do you know which source to trust when they disagree?
Start With Customer Journey Mapping
A useful and structured way to uncover and evaluate your data sources is through customer journey mapping. This means walking through the typical stages of a customer’s lifecycle; from awareness to acquisition, conversion, onboarding, retention, and advocacy — and identifying the systems that capture interactions at each step. For instance, social media tools and advertising platforms might play a role in the awareness stage, while your CRM system and backend database capture conversions and long-term engagement. This exercise not only helps you catalogue where data lives but also helps you determine the importance of each source in supporting key decisions. It highlights data gaps, shows which teams rely on which platforms, and reveals where inconsistencies or overlaps might be holding you back.
Whilst this exercise often results in a long list of data sources to integrate, this has a time and cost associated with it and so its important to consider which of these data sources are key, which sits across the most areas in the customer journey, has the highest spend associated with it or holds the most relevant data.
Assessing Existing Reporting Practices
In many businesses, existing reports offer a window into how data is currently being used... and misused. Teams often pull data manually into spreadsheets, download platform-specific dashboards, or rely on weekly exports from systems that were never designed for reporting. These legacy processes can lead to duplicated efforts, inconsistencies between reports, and a general lack of trust in the numbers. By taking stock of current reporting across departments, you can identify which metrics matter most, how often data is being updated, and where manual work could be replaced with automation. It also reveals whether different teams are aligned in their definitions, or if they are each working from their own version of the truth.
Deciding Which Metrics to Track
Choosing the right metrics is not about tracking everything; it is about tracking what matters. Organisations can easily fall into the trap of reporting dozens of “nice to have” metrics that offer little value. Instead, the focus should be on a small, carefully chosen set of metrics that are tightly aligned to your short and medium-term business goals.
This involves asking the right questions: What do we need to know to run the business well? What decisions are we making regularly? And what information would make those decisions faster, better, or more confident? For each key metric, it is important to define what it means, how it is calculated, and where it comes from, creating a shared language through a data dictionary.
Final Thoughts: Begin With What You Already Have
The path to better, more impactful use of data is often far simpler than it seems. You do not need to invest in complex data science projects or wait for a complete system overhaul. Begin with what you have. Map your customer journey, audit your current reports, and identify your most important metrics. Most importantly, trust in your own systems, the majority of the insight you need is already being captured. It just needs to be unlocked. And if you need help unlocking the value in your data, why not book a call with the friendly team here at 173tech?