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Internally-built analytics tools often start as quick fixes but quickly grow into costly liabilities. In this article, Frederik Werner breaks down the hidden expenses, risks, and long-term trade-offs of going custom when better solutions already exist.
The cost of building and maintaining custom analytics tools can quickly outweigh the perceived benefits. Frederik Werner shares why you should consider industry-relevant solutions for added value and cost-effectiveness.
When you’ve worked long enough in any industry, you start to notice patterns. Ideally, those are positive—best practices, proven approaches. But often, you also see anti-patterns: outdated solutions and persistent misunderstandings.
Most days, I prefer to write about the positive side of the analytics industry. There is plenty to be excited about, from new tools gaining traction to unlocking more value from existing platforms. Today, however, I want to focus on one of the most common missteps I see: the tendency to build custom, internal tools.
Even with increasingly user-friendly tools like Adobe Analytics and Customer Journey Analytics, digital analytics remains a technical field. We deal with frontend JavaScript, backend attribution models, and occasionally dive into SQL or Python. It’s no surprise that many analysts come from web development, statistics, or programming backgrounds. And that’s a good thing.
Given those skills, it’s common for analysts to write scripts, automate small tasks, or even create internal tools. But just because we can build something doesn’t always mean we should. Creating a script to automate a task is very different from building a scalable platform for business-critical operations.
The ongoing need for support, updates, and feature requests can quickly turn side projects into full-time responsibilities. This adds pressure, increases risk, and often leads to growing frustration on all sides.
We tend to operate on a fine line between boredom and being overwhelmed. Escalating internal projects often add unnecessary complexity, frustrating the very stakeholders they were meant to help. Instead of simplifying workflows, they introduce bottlenecks and confusion—especially for non-technical business partners.
Let’s break down a common scenario. Many marketing and analytics teams manage campaign data in Adobe Analytics through classification imports. Typically, metadata is stored in Excel sheets, campaign codes are created manually, and analysts are responsible for uploading everything correctly.
This creates several challenges:
At some point, someone suggests building an internal tool. And at first, it works. The team is happy. Campaign codes can be generated automatically. But soon the tool starts showing its limits.
It is too technical, hard to maintain, not user-friendly, and fails to meet IT or compliance standards. When usage expands, issues with accessibility, stability, and security appear. Handing the project to IT only increases delays and reduces adoption.
Let’s assign some conservative estimates:
Total over one or two years: nearly $200,000—and that’s without accounting for opportunity cost or lost insights.
The most concerning part? With many stakeholders involved, no one sees the full cost in real time.
Yes, this is where Accutics comes in—but not just for the sake of promotion.
When I was managing these challenges at my previous companies, I didn’t know there were better alternatives. Once I saw what Accutics offered as a customer, it completely changed how I thought about building vs. buying.
The features, usability, compliance, and scale of a dedicated platform simply cannot be matched by internal tools cobbled together in Excel or with custom code.
If this sounds familiar, take a moment to evaluate how you are managing your campaign tracking or analytics infrastructure today. If you are relying on homegrown tools, you might be spending more than you think—for far less value than you need.
Staying curious and open-minded is part of what makes working in this field rewarding. We all start somewhere. What matters is knowing when it’s time to evolve—and letting go of what no longer serves you.
Many companies believe they can save time or budget by building tools in-house, especially when teams include technically skilled analysts. However, these tools often lack long-term scalability, usability, and compliance support.
Custom tools often consume significant staff time for maintenance, introduce operational risk, and lead to inefficiencies in campaign tracking and reporting. Over time, these costs can exceed the price of a professional solution.
Manual tools can cause delays, errors, and misattributed campaign data when managing classifications or metadata. This compromises performance visibility and decision making for marketing teams.
When internal tools begin requiring constant support, lack user adoption, or fail to meet cross-functional requirements, it is a signal that it is time to evaluate industry-grade platforms built for scale and governance.
Dedicated platforms are designed with scalability, user experience, security, and evolving industry standards in mind. They reduce complexity and free up internal teams to focus on insights rather than infrastructure.