3 myths about autocapture and why you should ignore them.

I started my career as a product manager for a financial services company. When building new features, we would include a plan to measure each feature’s success.

But, inevitably, something would go wrong.

We would either forget to track something or the measurement plan would be incorrectly implemented by the development team. And then, to have the analytics team implement those tags would require another 2 week sprint. Even in the era of tag management systems, so goes the story of manual tracking tags.

What surprises me is that there are still so many in the industry that don’t know or don’t believe there’s a better alternative that can enhance and complement your manual analytics tracking strategy: autocapture.

There are a few naysayers who throw shade at autocapture. The suspicion hasn’t come out of nowhere. It is really hard to do at scale, and even harder to make sense of the data without significant computing power. The concerns may have been valid in the early days of autocapture, when technology had not progressed as quickly as theory. It didn’t help that early iterations of autocapture were often implemented poorly.

Concerns from those who grew up in the era of old school web analytics probably come from their early experiences, not from new experiences.

But, my friends, change is in the air.

Autocapture technology has advanced to where we no longer need to compromise speed or security in exchange for confidence in our data and decisions. Advances in cloud computing have made data storage economics much more favorable, while advances in processing and AI have made it possible to analyze and derive insights from autocaptured datasets. Even the old school players are getting into the autocapture game – with GA4’s Enhanced Measurement, Google Analytics now allows for autocapturing of certain behaviors, with more expected soon.

Common autocapture myths and misconceptions.

First off, you may be wondering what is autocapture and why is it better than manual tracking? Check out our earlier blog on the topic here.

My big knock with advocates of manual tracking – and manual tracking only – is that they’ve proposed a lot of potential negative scenarios. Sure, these scenarios are possible, but technology has advanced to the point where they’re also avoidable.

So join me in busting the most common autocapture myths:

Myth 1: Capturing too much data is a bad thing.

The premise behind this objection is an assumption that capture and organization are blended, leading to chaotic, unusable datasets. Savvy data technologists will eliminate this chaos by separating capture (capture everything) from organization (apply semantic meaning to key events). The result is a comprehensive, usable dataset, not chaos. You can decide when an event is meaningful, organize it accordingly, and benefit from retroactive data.

Myth 2: Autocapture doesn’t save time.

Speed is the most important competitive advantage today. And having real-time access to data and insights allows organizations to move more quickly. When it comes to answering pressing business questions, you should have insights in hours and minutes, not weeks and days. Whether it’s running A/B tests or optimizing marketing campaigns, updating tracking code takes time – and we all know that time is money. By leveraging the modern semantic application techniques mentioned above, autocapture certainly does save time.

Myth 3: Autocapture poses a security risk.

Security should always be top of mind when embracing any digital technology. Calling autocapture a security risk reminds me of on-premise advocates who claimed adopting SaaS was a bad move due to the security risk. They continued to push their server boxes. Having Google or Amazon managing your data center turned out to be a lot safer than managing it yourself. Similarly, advancements in AI and ML have significantly reduced autocapture risks around PII (see here). And when you combine that with a multi-layer control process (see here), you minimize the risk to a point where it is far exceeded by the benefits.

6 autocapture benefits for digital analytics practitioners.

Autocapture breeds a culture of collaborative curiosity. It empowers any member of an organization who might be uncertain about something to follow the data towards new questions and new answers. The cultural benefits to decision making are significant.

There is an implicit bias in any analytics or customer experience platform that requires you to know what questions you want to answer before you have the data in hand. If you allow the data to be your guide, you will stumble upon answers you didn’t expect.

Here are a few use cases to help you understand why you should embrace autocapture.

1. Kick start your tracking implementation – Autocapture can kick start your entire tracking implementation with instant access to critical business metrics, session replay, and frustrating user behavior (such as errors and rage clicks). You can start capturing customer insights as you wait for analytics from more traditional analytics tools that rely on a manual data layer.
2. Backup your analytics data layer – Autocapture can serve as an “always available” data source for tracking validation or whenever your data layer inadvertently breaks with ongoing product releases–it’s not a matter of ‘if’ but ‘when.’ Ultimately, using a hybrid approach that combines autocapture and manual data layer can be wise. This way, you get the two-fold advantage of preserving and standardizing critical success events (such as conversion and revenue) across the range of marketing and analytics tools that use a data layer. You also benefit from the speed and flexibility of autocapture.
3. Instant click tracking – Autocapture will completely streamline and automate tracking for every click, scroll, tap and swipe on every link of every page using heatmaps and clickmaps. Each user action is tied to conversion. You never have to worry about dedicating valuable developer time and resources towards building and releasing individual link tracking code, only to watch it break a few weeks later. Plus, you’ll get intelligent click events such as rage clicks and frustration indicators that are otherwise unavailable in standard analytics solutions.
4. A/B testing – An A/B testing program is usually evaluated by experiment velocity. And velocity is often constrained by the manual tagging required to support measurement on each experiment. The more tests you can run, the higher likelihood of finding winning treatments (and thus the higher likelihood that your experimentation program becomes an engine for business growth).
5. Internal apps – Building standout digital experiences is no longer just about customer facing websites and applications. Now, we see more companies investing in their employees and the digital experiences of their internal facing apps. These apps don’t have the same flexibility or support to make manual tracking practical. In these cases, having a one-time deployment and remote configuration will allow for tracking that would not otherwise be possible.
6. Capture all your errors, not just the ones you know – Traditional analytics tools rely on teams to define what an error or point of customer friction “looks” like, and which errors or friction points to track. It’s practically impossible to manually pre-define every error. Autocapture can identify all application and system errors out of the box, regardless of whether they’ve happened before. This helps ensure you are aware of all errors, not just the ones you were looking for.

The benefits of autocapture are clear. The risks are either outdated or can be addressed. When you hear fear, uncertainty, and doubt (also referred to as “FUD”) raised about autocapture, I encourage you to think critically about the author’s or speaker’s motivations and biases.

Autocapture detractors may have adopted their position because someone else made the decision years ago to architect their platform in an outdated fashion. Changing to a more tech-forward platform would be costly to correct. Thus the FUD.

At Quantum Metric, we have embraced autocapture since our founding. We believe autocapture is a catalyst for growth because it is a better, faster, and more secure technology upon which to run a digital business.

Digital analytics practitioners will inevitably head towards a world where they can leverage the advantages of autocapture, simply because business and end-customers demand a new level of speed, security, confidence, and iteration.

I hope you’ll join me for the ride.