Is Democratised Data a Double-Edged Sword? Navigating Brand Tracking Challenges

Brands have realised that siloing and restricting access to data doesn’t work. During a recent survey by MIT Sloan Management, more than 77% of respondents stated that their access to data has increased. With the proliferation of data sources, leaving data in the hands of the insights department simply isn’t practical anymore - information has to be democratised so that business users can explore trends and insights on their own.

In theory, this is a game-changer. Democratised data speeds up decision-making, reduces costs, and makes data more impactful:

• Faster Access: Brand and marketing teams no longer have to wait weeks for an agency to deliver a report. Instead, they can access real-time brand tracking data instantly, allowing for quicker decision-making and more responsive strategies.

• More Informed Decision-Making: Data accessibility means different teams can better understand customer sentiment, brand strengths, and areas for improvement. Instead of working off gut instinct or outdated reports, teams can make decisions based on the latest insights.

• Cost Reduction: With less reliance on external agencies to generate manual reports, organisations cut costs while increasing efficiency. Resources once spent on data collection and formatting can be redirected towards analysis and strategy.

• Improved ROI: When data is easily accessible, insights can be used across multiple functions—marketing, product, and sales—maximising the value of brand tracking research.

• Increased Accountability: When stakeholders have direct access to data, they take greater ownership of their decisions. This not only makes the decision-making process more transparent (because everyone has access to the same data), but reduces reliance on gatekeepers. Democratised data also ensures that actions are based on factual evidence - not assumptions.

The Challenges of Democratised Data

Despite its benefits, democratised data presents several risks. With great accessibility comes great responsibility. If not carefully managed, it can lead to misinterpretations, inefficiencies, and decision-making based on flawed insights.

Conflicting Interpretations

Data is powerful, but it’s also open to interpretation. Different stakeholders may focus on different data points, leading to competing narratives. Some might prioritise short-term fluctuations, while others emphasise long-term trends. Worse still, confirmation bias can creep in—where individuals cherry-pick data that supports their existing beliefs while ignoring conflicting insights.

Let’s say that marketing sees a spike in brand awareness and celebrates a campaign's success. At the same time, the brand team notices a decline in brand preference and calls for urgent action. Who’s right? Without context and proper analysis, both interpretations could lead to poor strategic decisions.

Market Research Literacy Gaps

Not everyone is a research expert. Many users may not fully understand the methodologies, sample sizes, or statistical significance behind the data they’re looking at. This can lead to misleading conclusions and flawed decision-making. Suppose a stakeholder misinterprets survey results, assuming that a 2% increase in brand consideration is a major shift—without realising that the margin of error makes the change statistically insignificant.

Overwhelming Data

Giving users unrestricted access to raw data can be overwhelming. This leads to “analysis paralysis” - when teams are overwhelmed by too much data, leading to inefficiency, missed context, and unreliable insights. Instead of driving decisions, excessive information slows progress as teams waste time sifting through reports without a clear framework. Data without proper context becomes meaningless, making it easy to misinterpret trends. Worse, when overloaded, businesses often cherry-pick insights that confirm biases rather than reveal actionable truths. The result? Stalled strategies and missed opportunities - all because there’s too much data and not enough direction.

Without the right guidance, they may create custom metrics or segment audiences in ways that aren’t statistically valid, leading to unreliable insights. For example: a user builds a custom audience segment based on a small sample size, drawing conclusions that don’t hold up in broader analysis. Action is taken that ultimately doesn’t benefit or appeal to the target audience.

Enlyta’s Role in Mitigating These Challenges

That’s not to say that democratising data is a mistake - quite the opposite. With the right safeguards in place, democratised data can empower teams without leading to misinterpretation or misuse. This is where Enlyta comes in.

Guardrails and Control

Enlyta ensures that insight teams maintain control while still giving stakeholders access to valuable data. Our clients often say that this balance - between control and accessibility - is what makes the platform so valuable.

Key Features:

• Flexible Permissions: Different teams get access to the right level of data, cutting through the noise to find actionable insights.

• Predefined Data Cuts and Filters: Keeps analysis consistent and prevents users from creating misleading or statistically weak segments.

• Automatic Hiding of Data Below a Certain Sample Size: This prevents decisions from being made on unreliable data points.

Insight Stories: Turning Data into Actionable Insights

Raw numbers don’t tell a story—context does. Enlyta helps insight teams craft compelling, easy-to-digest narratives that ensure the data’s real meaning isn’t lost. Instead of just presenting data tables, Enlyta allows teams to create insight stories—quick, mobile-friendly summaries that are easy to share with your stakeholders, highlighting key takeaways and recommendations.

Statistical Significance Testing

Enlyta automatically flags which data points are statistically significant, preventing users from acting on random fluctuations or misleading trends. This ensures that teams improve transparency and trust. When we first democratised data for our telecoms client, their insight team initially feared that opening up data access could lead to misinterpretation. But by using Enlyta’s controlled environment, they found that democratised access actually strengthened confidence in their insights. To quote the client, “Democratised data actually allows us to show how transparent we’re being, and that can build trust.”

Intuitive to Use, Easy on the Eyes

A democratised data system is only as good as its usability. Enlyta’s attractive, reader-friendly, and intuitive interface ensures that users can quickly find and interpret the insights they need without extensive training.

When we first engaged a leading global bank, they initially restricted access to 100 key insights professionals. As confidence in Enlyta’s controlled system grew, access expanded to the entire global organisation—including external agency partners. This showcases a typical adoption journey: starting small, gaining trust, and then scaling up.

The Future of Democratised Data: AI-Powered Insights

In the coming months, Enlyta will roll out AI-driven tools that will transform our users' ability to quickly identify and narrate insights from complex data. These AI tools will take data democratisation to the next level by:

• Identifying key trends automatically.

• Generating summary reports with actionable insights.

• Offering recommendations based on historical data and trends.

By streamlining analysis and interpretation, these AI-driven tools ensure that insight teams can focus on strategy instead of getting lost in raw data.

Democratised data is a powerful tool—but it’s not without risks. Without the right structure in place, it can lead to misinterpretation, poor decision-making, and lost credibility for insight teams.

Enlyta ensures that brand tracking data remains both accessible and reliable. Through controlled permissions, predefined data filters, statistical testing, and in-depth insights, Enlyta empowers teams to harness the full potential of their brand data—without the pitfalls.