A codeless implementation may save you time up front, but it’ll expose you to serious problems, like bad data and security leaks down the road.
A codeless implementation sounds like a great shortcut when it comes to implementing analytics. But you’ll end up with limited, unreliable data, which means you’ll spend even more time and resources on fixing data inconsistencies. This is not to mention the serious security and privacy risks codeless implementations open up.
What if there are multiple ways to perform a certain event, like “Complete checkout”, that include pressing “Enter” on a keyboard, or clicking the “One-Click Checkout” button? In order to ensure your data is accurate, you’ll need to address all of these cases individually when you set up your events, which often requires a software developer consultation to do thoroughly. Otherwise, you’ll be making decisions using incomplete & therefore inaccurate data.
Codeless implementations also don’t give you the granularity needed for some of your KPIs. Here’s what might happen: You decide you want to see how many users have attempted to purchase item ID 2853 – but that data is not collected or included in your events because the one-size-fits-all event collection doesn’t know where to find your item IDs. It only knows that users are clicking a button with the text “Place Order.”
Many interactions that end up being very important to you are not tracked at all, such as watching a video, scrolling, or interacting with a pop-up modal. You’ll need a software developer to build a custom solution for these.
Websites are changing almost daily, as teams work to optimize performance or conversions. So even a simple edit, like changing the text of the checkout button from “Place Order” to “Finish Order” breaks your tracking. The one-size-fits-all model doesn’t know it’s the same button, so your event count drops to 0.
There are two ways to address security risks. First, you can manually blacklist every possible place you might collect sensitive information, which requires engineering resources and puts the onus on you to ensure you don’t miss anything. Second, you can reduce the information that is automatically collected (such as form fields) which exacerbates the missing-important-data problem.
Neither solution is great, which is why one analytics product that offers codeless tracking says in their own documentation: “To ensure we don’t collect any PII (Personally Identifiable Information) or PHI (Personal Health Information), you need to be extremely cautious.”
Due to the nature of how this data is collected, when you export the data to other tools you’re going to get a lot of raw data that’s named differently. Instead of seeing a list of events that say “Checkout attempted,” you’ll see a dump of data that looks like “{action: ‘click’, selector: ‘div#el_1235’}.” It’ll also require engineering resources to make it usable again.
Mixpanel’s implementation process was 70% faster compared to U.S. Bank’s legacy provider and saved $300K annually.Frank Stanton Vice President, User Experience
Data collections coverage across all Guidebook’s software has never been as complete as it is today. Our ability to collect immense amounts of data from our apps and examine how our users interact has never been stronger.Patrick McNally Director of Research and Development
Our approach is fundamentally different. All the data is deliberately structured and defined in code, to capture the unique logic that is specific to your business. Mixpanel’s award-winning professional services team will help you build your analytics strategy, specifically tailoring it to your key business goals. We work backward from there, helping you build a complete spec for your developers, who use our SDK to instrument the events and logic.
