ℹDemonstration scenario. An example of a possible implementation, not a completed client project of Neural2B.

Personalized Product Selection for Online Stores

Demonstration scenario: selecting sports products based on the buyer's goals, budget, and parameters. We recommend only what is in stock, with no inflated medical promises.

Business situation overview

When a store has hundreds of similar technical or sports models, the buyer gets confused. Unclear specifications, a multitude of options. If no one quickly and professionally advises, the person simply closes the site.

Data flow and architecture diagram

1Catalog: export from the database (Shopify, OpenCart, or WooCommerce) along with attributes

2Stock filtering module: removes products that are not in stock

3Semantic embedding of characteristics: matches customer goals with product properties

4CRM synchronization: selected products are stored in the lead card

The human role in the loop (Human-in-the-loop)

If the question concerns individual medical indications or non-standard guarantees, the system honestly states the limits of its recommendations and suggests contacting a senior consultant.

Synthetic test data

Example input and system response

User input request:

"I am looking for running shoes for a beginner, weight 85 kg, I will run on park paths and asphalt 2 times a week, budget up to $100, size 43"

Generated response / system action:

"For your parameters (asphalt + weight 85 kg), we recommend models with enhanced heel cushioning. Available in stock in size 43: 1) RunnerPro Cushion model ($85) — soft EVA foam; 2) GlideTrail 2 ($95) — universal tread. Both models are in stock."

Limits of the demo scenario

✕No medical promises to cure flat feet or injuries
✕Recommendations are based solely on official manufacturer specifications
✕Before providing a payment link, the system checks if the product is indeed available

What to measure during pilot testing

✓How accurate the offers are — according to the control group
✓How many conversations end with a transition to the product card
✓How often the recommended product is added to the cart

Relevant company service

Marketing and Content Automation

Service overview →

Interested in a similar architecture?

We’ll adapt the logic of this scenario to your internal software, database structure, and operating rules.

Discuss adaptation

Other scenarios

Scenario adaptation: Personalized Product Selection for Stores

Describe the process that’s eating up your team’s time. We’ll suggest what can be automated, what data is needed, and where to start.