Many companies have a clear vision regarding digital analytics: they plan to outsource the technical work while keeping the strategic, value-creating work in-house.
The idea is simple:
- Outsource technical tasks such as tag management, data engineering, and dashboard development to agencies or contractors.
- Insource analytical work, ensuring that internal teams drive insights, make recommendations, and create business value from data.
This sounds like a solid plan. Focus internal efforts on high-value, strategic, ongoing analytical activities and use external technical experts when necessary.
In practice, things often don’t go as planned.
The Reality: Data Collection Without Analysis
In many companies, agencies and contractors handle the technical implementation, setting up tracking and building dashboards.
Precisely as planned by decision-makers.
However, it often sits untouched once the data is collected and visualised.
The intended “insourced” analytical work doesn’t happen. Not because it’s unimportant, but because no one is responsible for it.
Product owners and marketers are expected to handle analysis on top of their full plates. Unfortunately, they rarely have the time, skills, or mindset required for working with digital analytics data.
Analysts are missing. In some cases, because the company never hired them. In other cases, their role is unclear in the organisation.
(Analysts focus on business data, and BI teams consider digital analytics data unimportant.)
Dashboards become reports, not decision-making tools. They show numbers but don’t tell a story or provide actionable insights.
For this, we still need humans, not generative AI.
The result?
Companies hoard data that could drive business growth but remains unused.
How to Fix the Problem
There are two ways to improve the situation:
1. Use consultants for analysis, not just implementation
Many companies are comfortable hiring agencies for tag management and dashboard setup. They hesitate to bring in external help for data interpretation.
A good analytics consultant can bridge this gap by providing ongoing analysis, recommendations, and strategic guidance.
Their client-specific knowledge might be lacking, but they know their digital analytics data and its possibilities inside out.
This is particularly useful for companies that don’t yet have the scale to justify a full-time analyst.
2. Hire analysts and define their role clearly
It is unrealistic to expect product owners and marketers to analyse data on top of their responsibilities.
They may use reports to track performance but won’t have the time to dive deep into trends, correlations, and strategic insights.
Instead, hire dedicated analysts whose primary job is to extract value from the digital analytics data. These professionals should work closely with marketing and product teams to answer questions starting with Why.
When using the BI team for digital analytics, ensure they understand website and advertising data and processes.
BI specialists often lack experience in marketing, conversion optimisation, and advertising. Because of this, they can be less effective in deriving insights from marketing and web analytics data.
Conclusion: Don’t Let Your Data Go to Waste
Collecting data isn’t enough.
Implementing tracking and building dashboards are necessary steps in my CARE framework (Collect, Analyse, Recommend, Experiment).
But without a clear responsibility for analysis, the value of digital analytics remains untapped.
Companies need to ensure that someone is actively analysing the data and turning it into recommendations.
Otherwise, digital analytics will remain a dream.
A dream where data flows perfectly into dashboards that no one uses.