Hidden Costs of an Overloaded Tech Stack

In the race for growth, many DTC businesses have built extensive tech stacks. These tools promise improved customer experience, increased conversions, and boosted sales. Without validation, many tools remain unoptimized or underused, quietly draining resources and, worse, they can negatively impact site performance.

Tech Overload and Site Speed

An overloaded tech stack can slow down your website. Even if each tool provides a positive return on paper, the combined weight of too many platforms can hurt site performance, leading to slower load times. 

Studies show even a few seconds of added delay can significantly decrease conversion rates, as customers become frustrated and leave before buying.

For instance, imagine a tool that offers excellent product recommendations. But the added scripts slow down page loading, customers may bounce before even seeing the recommendations. This makes site speed an indirect but real factor in purchase behavior, affecting overall revenue and undermining the ROI of these tools.

Optimizing your tech stack with A/B testing helps avoid these pitfalls by identifying which tools contribute to the customer experience without dragging down site speed.

Built-In Analytics Suck

Relying solely on a tool’s built-in analytics can be incredibly misleading. 

Many reports only track users who engage with a tool, leaving out those who bounce or never visit certain pages. This can give a false sense of the tool's value, making it seem more effective than it really is.

For example, a pop-up tool might show high engagement rates, but those reports ignore visitors who leave before seeing it or avoid the pages where it appears. Without comparing your site’s performance with and without the tool, you cannot know if it truly boosts conversions or just engages users who were already likely to convert.

A/B testing is the only way to get a clear, accurate picture. By testing both scenarios, you can see the tool’s real impact.

Using A/B Testing to Validate ROI

A/B testing is more than just a tactic for optimizing conversion rates—it is an essential tool for assessing the true impact of your tech stack. Instead of cutting tools based on gut feeling, A/B tests allow brands to measure real-world performance and make data-backed decisions about which platforms and integrations are driving profitability.

Real Example: Video Use Platform

Take an experiment conducted for Posh Peanut as an example. Using A/B testing, Prismfly was able to measure the actual impact of the video tool Lyvecom on key financial metrics. 

The results? A staggering 91x ROI. This kind of experiment shows the ability of A/B testing to validate decisions with data and ensure tools which actually improve profitability stay in the stack.

Tech for Tech's Sake

Many brands make the mistake of investing in expensive, advanced tools such as Customer Data Platforms (CDPs) when they do not actually need them. If your marketing is not sophisticated enough to use the features, signing a multi-year contract is a waste of money.

Kind of like slapping a fresh coat of paint on the laundry room if the washing machine is broken. It might look nice, but it will not fix the problem. Lipstick on a pig as they say.

Before investing in new tech, make sure your business is ready to fully utilize it. Otherwise, you are just draining resources that could be better spent elsewhere. 

For example: We run experiments on custom built product recommendations sections before recommending high performance tools such as Nosto. In the wise words of Warren Buffet, “Risk comes from not knowing what you’re doing.”

How to Perform a Tech Stack Audit

Here are key steps DTC brands can take to conduct a comprehensive tech audit using A/B testing:

1. Identify high-cost, low-visibility platforms: Start by focusing on tools with significant costs but unclear results.
2. Set KPIs for success: Determine what success looks like for each tool—whether it is an uplift in conversions, increased average order value, or better customer retention.
3. Run A/B tests: Use A/B testing to compare the performance of each tool against a control. Measure its impact on core metrics to see if it delivers the expected ROI.
4. Analyze the data: Once the results are in, review which tools are genuinely contributing to profitability and which are not.
5. Deciding What to Keep, Cut, or Adjustsome text
   1. Keep: Tools that drive measurable improvements in revenue, conversion rates, or customer satisfaction.
   2. Cut: Platforms that show little to no impact, despite their costs or have a negative impact on site speed.
   3. Adjust: If a tool is underperforming but still holds potential, work with your team to optimize it based on the test data.
6. After running A/B tests on your tech stack, the data will tell you which tools should stay, go, or be optimized.

The Prismfly team can provide tool and tech stack recommendations. As data-driven, performance-driven marketers there is nothing more annoying than bad tooling so contact us if you’d like our audit template or need platform recommendations (check out our favorites). 

In today’s profit-driven DTC world, there is no room for unnecessary tech expenses or platforms that slow down your site. 

Using A/B testing to validate your tools’ ROI ensures that every dollar spent is delivering value. Whether you are keeping, cutting, or adjusting tools, data-driven decisions are key to maintaining long-term profitability.

About Prismfly

Yes, we do tech stack audits focused on Shopify. Prismfly also builds and runs high-performance optimization programs for DTC brands.