Analysis Paralysis: When Do You Have Too Much Data?

Analysis Paralysis

Everyone tracks data. It forms the basis of well-thought-through, effective marketing and business plans. That said, it’s important to note that data saturation is real and sometimes hard to identify.

Website traffic and conversion data are no exception. Having data and effectively analyzing it is essential to optimizing your web traffic flow, but having too much of it tends to cloud the issue. This article unpacks why we need data, what happens when we have too much of it, and how to avoid data saturation.

Why is Data Collection Necessary?

I know we’re preaching to the choir here, but there are tangible benefits to (relevant) data collection. Let’s review these first before unpacking how much data is enough.

Improved User Experience

Understanding what your clients (current and potential) need is key to adding value to their lives. Knowing how visitors interact with your website means that you can optimize their experience, leading to a better user experience, and ultimately, increased sales. Knowing this in real-time facilitates faster responses, further enhancing this. Here, you can evaluate which ad campaigns work, which don’t, and how to improve them.

Greater Agility

Since data is collected and processed in near-real time, meaningful insights garnered from data are available basically at the drop of a hat. Here, teams can respond to new situations and insights quickly. This enables agility as teams manage new business challenges and opportunities nimbly, backed by accurate data.

Cost Savings

Before the advent of data tracking and big data initiatives, innovation, research, and data gathering were tedious and, at times, downright painful. It was also highly resource-intensive, with many people involved at each step. These people would spend hours interviewing subjects and then crunch the numbers by hand.

Innovations in the data tracking and processing industry revolutionized this. Now, nearly the entire process is automated and, in comparison, not resource-intensive. With the right tools in place, all you need is a small team to review results and determine a course of action based on these results.

Greater Access

The cost savings inherent in the latest data collection, storage, and processing technologies have filtered down the system. Now, small companies and non-profits can access troves of valuable data freely or at a low cost, enabling their businesses and other innovations to thrive.

What is Data Saturation?

We tend to believe that more is better. The more data we have, the better decisions we can make, the more accurate our statistics will be, and the more our business will grow. Unfortunately, this has proven false, as underlined by Kimberly Whitler.

The challenge lies in the overwhelming volume of data and our inability to manage it effectively. Presently, we can collect far more data than ever before. The infrastructure to support, manage, and filter this data hasn’t kept pace with the rapid rise in data availability. Now, we have all this data but can’t apply it meaningfully. This challenge is akin to growing cityscapes. When cities experience rapid growth, the roads are suddenly crowded since the physical infrastructure hasn’t kept pace with the growing population.

Why is Data Saturation a Problem?

Traditionally, marketers mined all data at their disposal for valuable insights. The available data wasn’t that much, especially compared to the vast data lakes we face today. Unfortunately, this created the habit of mining every bit of data for all that it’s worth. Here, we hope that it will lead us to some holy grail, cracking the code on our marketing approach. With the vast amount of data at our disposal, analysts suddenly face reams of statistics, graphs, and “insights” that are hard to decipher and often contradictory or nonsensical. There’s just too much of it. 

This data overload leads to analysis paralysis, analyzing data for the sake of it. It wastes valuable time and headspace, leading us down the rabbit hole to nowhere. Common terms for this data overload is data saturation or InfoObesity

In large, siloed companies, you would even find that different people purchase the same dataset. This wastes time, money, and other valuable resources as people mine duplicate datasets, looking for critical insights that aren’t necessarily there.

How do we avoid this conundrum?

Avoiding Analysis Paralysis

Set the Objective

The first step is knowing where you’re headed. What are your key objectives? Does your business want to maximize profit? Enter a new market? Engage with more clients? Which key business question do you aim to answer?

Identify the Necessary Information

Once you understand the objectives, you can determine the measures needed to reach them. Now, you can find the data needed to facilitate this process. Here, you would be intentional and purposeful in the data you collect, ensuring that it suits your needs. You would also ensure that you collect data in a format compatible with your platform and needs, avoiding unusable data. This strategic, systematic approach gets you what you need. No more, and no less.

Develop Data Governance

An overarching strategy for data collection, management, and processing, guards against data duplication and collecting unnecessary data. A clear, effective strategy eliminates data redundancy, ensuring that data is leveraged effectively across the entire organization. To create such a strategy, we must involve all stakeholders in determining which data is needed and how to go about it.

Map the Data

Create a birds-eye map of your organization’s data to understand what data is already available and who can access it. This will illuminate gaps, duplications, and other situations that require intervention.

Interact Intelligently

Data comes in various formats. Social data is different from website traffic data. Use the correct tools to analyze your dataset and glean useful information from it. When you deviate from your tool’s intended application, you tend to overcomplicate matters, rendering it hard to maintain and often overly complicated. This leads to ineffective use of software that is usually expensive, which wastes valuable resources.

In Closing

Collecting adequate amounts of accurate data and processing this efficiently is essential to understanding the efficacy of your website and traffic funnel. This efficiency allows you to understand what visitors to your site want, allowing you to optimize the funnel and, ultimately, increase revenue.

When you collect too much data, especially irrelevant data, you add unnecessary noise to your decision-making process. Here, you could miss the wood for the trees, overwhelmed by stacks of statistics and graphs. Avoid this analysis paralysis by being mindful of the data you collect and why. Identify the questions you want to answer or problems you want to solve. Next, determine what data would help you do this.

With this information in mind, map out the data you already have, where it’s located, and who can access it. This bird’s eye view will illuminate the gaps in your system, allowing you to fill them. Lastly, interact intelligently with your data. Collect only what you need, and process it in a manner that fits with your objectives. 

With these principles in hand, you will decrease the amount of useless data you collect and streamline your current data analysis practices. Now, the insights gleaned from your data should lead to greater insights and, ultimately, better decision-making.

You might also like
CRO Starts At The Very First Step

There are many ways to monetize data traffic. Understanding where your web traffic comes from and what visitors do on your site is the first