AI Assist
Online stores that sell "spec-heavy" products — tools, equipment, spare parts — all face the same problem: buyers almost always ask something before purchasing. The questions repeat every day. Managers reply manually and only during business hours, while the customer who wrote in the evening often goes to whoever responded faster. Here is a real case study of how an AI consultant solves this problem.
The challenge: power tools and questions that can't wait
Our client is LEADER battery tool online store, a Ukrainian brand making home and garden equipment: drills, angle grinders, saws, pruners, trimmers, and batteries. The niche's defining trait is that buyers rarely order silently.
Questions that came in every day:
- Compatibility. Which battery fits a specific model, whether a pack from one tool will work on another in the same line.
- Selecting by task. "I need to trim hedges in the garden" or "drill concrete at home" — they need advice, not the most expensive model.
- Stock and delivery. Is it in stock? How long via Nova Poshta? What payment methods?
- Warranty. Terms, duration, what to do if the tool doesn't hold a charge.
Inquiries peak in the evening and on weekends. Running 24/7 operators isn't cost-effective at this store's scale, and losing evening orders is direct lost revenue.
The solution: an AI consultant trained on the store's own data
We built an AI consultant using real data: the catalogue, product specs, battery compatibility charts, price lists, and warranty conditions. This is fundamentally different from a standard button-based chatbot: the agent understands the meaning of a question and answers about specific products rather than delivering a scripted response.
What the consultant can do:
- Selects compatible batteries and chargers for a given model — by series and voltage.
- Recommends the right tool for a task, explaining the differences between options.
- Checks stock availability and calculates delivery costs.
- Answers questions about warranty and returns based on the store's actual policies.
- Hands complex cases to a live manager with the full conversation history — the customer doesn't have to repeat themselves.
Works wherever buyers write: on the website and in messengers.
How the implementation went
We follow an approach where the client sees results before full payment:
- Analysis (2 weeks). We studied the catalogue, common questions, and the store's sales scripts.
- Training the agent. Loaded real data: product specs, compatibility tables, service conditions.
- Connecting channels. Integrated the inventory system and Nova Poshta delivery.
- Testing and tuning. Ran it through live inquiries, adjusted answers and escalation rules.
The full cycle took about a month.
Results
- First response time dropped from 1–2 hours to a few seconds and became round-the-clock.
- Up to 75% of routine questions are resolved without a manager.
- Managers shifted from answering compatibility questions to handling complex consultations and calls.
What your online store can take from this
The LEADER case is not only relevant to tool retailers. The same approach works anywhere a consultation is needed before purchase:
- Spec-heavy products (equipment, spare parts, building materials) — the bot handles compatibility and selection questions.
- Off-hours peaks — evenings, weekends, and holidays stop being "dead zones".
- Seasonality — no need to urgently hire operators at peak load.
The key rule: an AI consultant delivers the greatest impact not where there are few questions, but where they are repetitive and high-volume. That's when automation frees the team and recovers lost orders.
Bottom line
For a tool store, a fast answer to pre-purchase questions is directly tied to sales. An AI consultant responds instantly around the clock, never confuses specs, and frees managers for more complex tasks.
If customers at your store also ask questions before buying — get in touch. We'll show how it works on your own products, as a free consultation.
