Running an online store means making decisions with incomplete information. You hire staff before you know if they'll fit. You run ads before you know if they'll convert. You launch features before you know if customers want them.
So when someone tells you an AI assistant can handle your customer support, recover abandoned carts, and track Econt shipments automatically — the right response is not "sounds great, let's go." The right response is: let me test it with real data first.
Here's what a proper AI pilot looks like, and why it matters more than any demo.
What you're actually testing
A demo is someone else's best-case scenario. A pilot is yours.
When you test with your own data — your product catalogue, your customers' actual questions, your courier integrations — you discover things no demo will show you:
- Does it handle Bulgarian addresses and Econt codes correctly?
- Can it answer questions about your return policy without inventing details you never wrote?
- What happens when a customer asks something the system hasn't been trained on?
These aren't rare edge cases. They're Tuesday.
Three numbers worth measuring
Most pilots get derailed by vanity metrics. "It answered 200 questions!" means nothing if you don't know how many of those answers were correct, how many needed escalation, and how many actually resolved the issue.
Three numbers that matter:
Resolution rate — What percentage of conversations did the AI close without human intervention? For a well-configured assistant on a typical Bulgarian e-commerce store, you should see meaningful containment within the first two weeks. Near-zero after week one signals a configuration problem, not a technology problem.
Escalation quality — When the AI hands off to a human, does it pass the right context? A useful escalation includes the customer's question, what the AI tried, and why it couldn't resolve it. A bare "customer has a question" creates more work than no AI at all.
Repeat contacts — If the same customer writes three times about the same issue, the assistant isn't resolving — it's deflecting. Watch for this pattern in week one and fix it before week two.
Two weeks is enough to know
A 14-day pilot gives you enough signal to make a real decision. In the first week, you calibrate — filling in gaps, adding answers for the questions the system couldn't handle. In the second week, you measure — does the calibrated system actually perform under real traffic?
If after 14 days the resolution rate is improving, escalations are clean, and your team is fielding fewer repetitive questions — you have your answer. If nothing is improving after two weeks of adjustment, either the configuration needs a deeper rethink or the use case isn't right for AI yet. Both are useful conclusions.
What makes Bulgarian e-commerce different
Off-the-shelf AI tools aren't configured for the Bulgarian market:
Econt and Speedy have their own tracking logic and customer expectations that don't map neatly onto generic courier templates. "Кога ще ми дойде пакетът" is not just a translation — it's a specific question with specific answer patterns your customers expect.
Many Bulgarian shoppers write in a mix of Cyrillic and Latin, especially on mobile. The assistant needs to handle both without confusion.
Your return and exchange policy is yours — the AI needs to learn it precisely, not approximate it from a generic template. A pilot surfaces exactly where the approximations break down.
Ready to run a real test?
Pragma AI offers a free 14-day pilot for Bulgarian online stores. We configure, monitor, and adjust — you evaluate the results using your own data, with no commitment required.
Get in touch at to start.