Your Tech Stack Is a Liability

The average Shopify Plus merchant runs 47 third-party apps. The average BigCommerce Enterprise customer runs 52. Some brands we've audited are running over 80.

Each app costs money, creates integration points, and generates data silos. Most merchants accept this as the cost of doing business online.

They're about to discover they're catastrophically wrong.

The Hidden Cost of App Sprawl

E-commerce businesses have been building their tech stacks like teenagers downloading mobile games — if it solves a problem, install it. Need email marketing? Add Klaviyo. Want reviews? Install Judge.me. Need inventory management? Grab TradeGecko. Want better search? Add Searchanise.

Before you know it, you're paying £3,000+ per month for apps, managing 40+ integration points, and wondering why your data never matches between systems.

But monthly fees are just the beginning. The real cost is operational complexity.

Every app requires setup, maintenance, and troubleshooting. Every integration can fail. Every data sync can break. Every update can cause conflicts. When something goes wrong with your checkout flow, you're not debugging one system — you're debugging the interactions between a dozen systems.

We recently worked with a brand spending £127,000 annually on apps. They had three different inventory management systems that didn't agree on stock levels, two email platforms sending conflicting campaigns, and a loyalty programme that hadn't synced customer data in four months.

Their 'sophisticated' tech stack was actually making them less capable than a business running on basic Shopify with no apps at all.

Why AI Makes This Worse, Not Better

The conventional wisdom is that AI will solve integration problems. Smart systems will automatically sync data, resolve conflicts, and orchestrate complex workflows across dozens of applications.

This is fantasy thinking.

AI doesn't eliminate the underlying architectural problems with fragmented tech stacks — it amplifies them. AI systems need clean, consistent data to function properly. When your customer data is spread across 40+ applications with different formats, naming conventions, and update frequencies, AI can't perform miracles.

Worse, AI failures cascade across integrated systems faster than human failures. When a human makes a mistake in one app, it usually stays contained. When an AI agent makes a mistake, it can propagate that error across your entire stack in seconds.

We're seeing this already. Brands using AI-powered inventory management are experiencing stockouts because their AI is making decisions based on data from systems that aren't properly synced. AI personalisation engines are sending irrelevant emails because customer behaviour data is fragmented across multiple platforms.

AI isn't fixing broken architectures. It's exposing how broken they really are.

The Consolidation Imperative

The businesses that will thrive in 2026 aren't the ones with the most sophisticated app ecosystems. They're the ones that consolidate ruthlessly before their competitors do.

This means making hard decisions about functionality trade-offs. Yes, that specialised app might have better features than the built-in alternative. But does the incremental improvement justify the integration complexity, ongoing maintenance, and data fragmentation?

Usually, the answer is no.

The brands winning right now are running lean, integrated stacks. They're choosing platforms over point solutions, accepting 80% functionality from integrated tools rather than 100% functionality from specialised apps that don't play well with others.

Shopify merchants are migrating from Klaviyo to Shopify Email, from ReCharge to Shopify Subscriptions, from third-party inventory apps to Shopify's native tools. Not because the native tools are better — but because integrated mediocrity beats fragmented excellence.

Platform Strategy Beats App Strategy

The fundamental shift is from app thinking to platform thinking.

App thinking says: find the best individual solution for each problem, then integrate them together.

Platform thinking says: choose platforms that solve multiple problems adequately, then build additional functionality within those platforms rather than adding external tools.

This isn't just about reducing app counts. It's about architectural simplicity. When most of your functionality runs within a single platform, data stays consistent, integrations are reliable, and problems are easier to diagnose.

The platforms themselves are recognising this shift. Shopify isn't just building better individual features — they're building an ecosystem designed to replace entire categories of third-party apps. Their recent acquisitions (Deliverr for fulfilment, Shopify Balance for financial services) aren't about feature expansion. They're about platform consolidation.

Merchants who bet on platform consolidation are betting on the winning architectural approach for the AI era.

The Great Stack Simplification

We're entering what will be remembered as the Great Stack Simplification. The businesses that recognise this early and act decisively will have a massive competitive advantage.

While their competitors are managing complex integrations between dozens of systems, they'll be running lean, fast, reliable operations on consolidated platforms. While others are debugging AI failures across fragmented architectures, they'll be scaling AI capabilities on clean, consistent data.

The simplification process isn't easy. It requires auditing every app, evaluating every integration, and making tough decisions about functionality trade-offs. But the alternative — continuing to build on fragmented foundations while AI demands architectural coherence — is business suicide.

Your tech stack is either a competitive advantage or a competitive liability. In the AI era, there's no middle ground. The businesses that consolidate first will dominate their markets. The ones that don't will be buried under the operational complexity of their own tools.

Start consolidating now. Your future self will thank you.