Every long relationship with software hits a point where you realize the tool doesn’t do what you need. It does what the vendor assumes you need, often created by engineers who have never counted units in a stockroom or looked at countless stockouts and wondered which ones really matter.
I've experienced that moment more than once: the reorder module that couldn't distinguish between an item sold out in a day and one that took a month to move; the payroll integration still requiring manual oversight; and the reporting system that produced polished charts about the past but offered nothing useful about what to do next.
Find one problem your current tools don't solve well and explore ways to build around it.
Over the past year, I have taken a different approach. Instead of looking for software that is nearly right, I started building tools tailored to how adult retail actually works. The results have been eye-opening, not just in what is possible, but in how easy it has become.
This marks a shift in direction. In previous articles, we examined what AI can do in theory and what vendors are offering. Now, I want to share what I have built in practice and why the gap between off-the-shelf software and custom solutions has significantly narrowed for adult retailers.
The Models Got Better
The AI tools available today are different from those available just 18 months ago. The improvements have been substantial in ways that matter to retail operators.
They handle complex, sustained tasks more reliably. Hallucinations, or confident but incorrect outputs, have decreased. More importantly, they are better at checking their own work and spotting errors.
For adult retailers, this alters the dynamics. When you understand your own operations, including inventory quirks, vendor relationships, margin structure, and customer behavior, you can create a custom system while AI handles the technical details.
A year ago, this needed either technical skills or a big budget. Today, it only needs clear thinking and patience.
There is still a learning curve, but it is much lower than expected and continues to decrease. When I encounter something technical I don't fully understand, I ask the system to explain it. I learn as I build. That is a meaningful shift.
Problem 1: Inventory Bloat at Scale
Every multi-location adult retailer is familiar with this problem: inventory bloat.
Our POS system stored over 455,000 items, but only around 100,000 were active. The rest were duplicates, incorrect SKUs, outdated entries, or items linked to the wrong vendors. Each new vendor’s import or receiving process caused more inconsistencies.
Lightspeed manages new item imports fairly well. However, it lacks a built-in method for cleaning duplicate vendor IDs, resolving duplicate UPCs, or archiving inactive inventory. At this level, manual cleanup is not feasible.
So, I created a system to manage it.
Using AI-assisted development, I built an archive module and a duplicate detection system that operate continuously through the API. I defined the rules for what qualifies as a duplicate, what triggers an archiving process, and what exceptions apply based on how adult retail catalogs function. The system manages execution in the background.
When managers add new items or import vendor data, the system detects issues early before they escalate.
The main point is this: value comes from domain knowledge, not coding ability. A software vendor without adult retail experience would spend months learning these edge cases. I already knew them before writing the first requirement.
That is the new dynamic. Your expertise shapes the system. AI carries it out.
Problem 2: Purchase Orders That Reflect Reality
This challenge is personal.
I was involved in early discussions with Lightspeed while they were building their dynamic reorder module. I tried to explain a fundamental retail reality. An item that sells five units in one day and sells out is very different from an item that sells five units over a month. Both show the same sales number, but they represent completely different inventory needs.
That distinction did not translate into the system.
This is not a criticism of Lightspeed. They build for a wide customer base across various industries. However, adult retail is different. It involves quick product turnover, vendor-specific case packs and demand spikes driven by trends, reviews and social media.
So I created a system that mirrors how our stores really operate.
The result is a platform called Retalyz, a customized inventory intelligence portal that updates nightly. It assesses every active item and highlights what needs attention without requiring managers to generate reports or sift through spreadsheets.
What You See When You Log In
The dashboard opens with four key metrics that define the state of the business:
- Stockouts: Items out of stock at all active locations
- Items to Order: Total reorder suggestions from vendors
- Recommended Investment: Total purchase order value if all recommendations are followed
- Active Locations: Stores currently operating on the system
Below that is the Vendors to Order table, which provides context behind each recommendation.
For each vendor, you see:
- Number of items and units to order
- Total order value
- Purchase order ratio
- Active inventory value
- Slow-moving or “dusty” inventory
- Monthly sales
- Inventory-to-sales ratio
The inventory ratio is especially important. A ratio close to 1.0 means you have roughly one month of inventory and probably need to reorder. A higher ratio indicates excess stock.
The “dusty inventory” column highlights slow-moving product. Seeing excess inventory alongside a reorder recommendation provides actionable insight. You might need to clear space before placing another order.
Vendor Analytics: Turning Data Into Decisions
The Vendor Analytics section provides detailed performance data across different vendors and locations.
Key metrics include:
- Average fulfillment time: Actual time from order placement to receipt
- Average internal lag: Time between delivery and system entry
- Average order gap: Days between orders
- Percent of profit: Contribution to margin, not just revenue
This data enables customized safety stock calculations based on actual performance, not vendor estimates or generic industry benchmarks.
There is also a Manager Efficiency component that measures how quickly staff process incoming inventory. Delays in receiving are an unseen factor contributing to stockouts in many adult retail businesses.
Why This Matters for Single-Location Stores
I manage 21 locations, which requires a scalable system. But the core logic also works well for a single-store operation.
A retailer with a few thousand SKUs and several vendors can benefit from the same level of visibility. Recognizing order gaps, spotting slow-moving inventory, and assessing purchase order ratios are not just enterprise-level concerns. They are basic retail insights that many operators simply lack access to.
The difficulty in buying software is that you must constantly adapt to someone else’s interpretation of your problem. When you create tools based on your own operation, you receive solutions that reflect your reality.
How to Build Your Own Tools
There are several paths, depending on your comfort level and goals:
- Lovable / Cursor: Best for retailers who want visual tools and quick prototypes
Trade-off: Less control over deeper customization - Replit / Codex: Good for smaller scripts and fast testing
Trade-off: Limited scalability for complex systems - VS Code + Copilot: Suitable for those with some coding experience
- Claude Code: Best for complex systems where you define behavior, and AI builds it
Trade-off: Requires more upfront learning, but offers the most control
My preference is Claude Code. It offers flexibility and delivers reliable results for more complex retail systems. When something isn't clear, I can ask for an explanation and keep building.
What’s Next: Conversion Rate Visibility
In the next article, I will discuss a conversion rate dashboard tailored specifically for adult retail settings.
If you track foot traffic and transactions, you already have the data. The challenge is that most systems don't calculate conversion accurately for this category.
A single visit can consist of multiple transactions. Arcade traffic and retail floor traffic may need to be tracked separately. The difference between traffic and transactions is one of the most actionable metrics in retail, yet many adult retailers do not measure it accurately.
I built a system that calculates conversions by location, time period and manager and updates automatically without spreadsheets or exports.
The Reality Check
Building custom tools is not for everyone.
There are valid reasons to purchase software, such as support, compliance, and integrations that may be hard to duplicate. Time is also a consideration. If managing your store already takes up your schedule, taking on development might not be practical.
However, it is important to understand what is now possible.
The gap between what you can buy and what you can build has narrowed considerably. In some cases, especially where adult retail has distinct operational nuances, building a solution can be more effective.
Retail roles are changing. The successful operators will be those who can turn their operational knowledge into systems that help with decision-making.
That skill was once unavailable to most people without a technical background. Now, it is.
If you're curious about how this could work in your own business, start small. Find one problem your current tools don't solve well and explore ways to build around it.
The best system for your store is the one built around how your store truly operates.
Zondre Watson is the general manager of technology and analytics for adult retail chain Ero-Tech. With a background in finance, chocolate and controlled chaos, he blends retail know-how with AI tools to keep 17,000 products moving smoothly.
