Take your customers to the shopping cart

Juliia streamlines the buying process by interacting with your site: it guides the user, updates the results in real time and can add a product to the basket. Less friction, more conversions.

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A customer left to himself is a lost customer

Overly dense menus, inadequate filters, unclear results: each poorly optimized step increases the risk of abandonment.

With Juliia, you offer a smooth buying journey. Elle interacts directly with the site, updates the results based on user responses, and can add a product to the cart, without breakage.

You guide your visitors like a store advisor... but 24/7 and at the scale of your entire catalog.

Shorten the path between intention and action

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Julia synchronizes her conversation with your e-commerce interface

It acts on the page: sorts the results, relaunches the correct filter, suggests an action.

The user stays on their journey, without ever dropping out.

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Navigation synchronized with the conversation
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Real-time update of results
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Adding the product to the cart from the chat

and allows you to respond in a more relevant way from the first exchange.

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What your customers get out of it

Juliia allows a smooth journey, without unnecessary clicks or breaks. An experience that reassures, guides and transforms.

Fewer unnecessary clicks, less frustration
An intuitive experience, just like in store
Real continuity between research, advice and action
The feeling of being accompanied, not left to themselves
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What you gain

A smoother journey means fewer abandonments... and more concrete actions towards purchase, without redesigning your interface.

An optimized shopping funnel from the home page
Fewer dropouts between research and the product sheet
More products added to the cart
A more efficient interface, without redesign

Move your customers forward, click by click

Here's how Juliia can guide your customers step-by-step, from recommendation to action without ever leaving the journey.

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“Juliia helped me choose a dress... and added it to the basket.”

By analyzing the criteria mentioned in the conversation (morphology, event, weather), Juliia proposed 3 options and finalized by putting it directly into the basket.

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“I hesitated between two canapes, Juliia helped me decide.”

She detected the preference (size, style), asked a question about the space available, then proposed a selection with the “add to cart” button.

“I was looking for a compatible accessory, Juliia offered it to me.”

After consulting a product sheet (e.g. smartphone), Juliia suggested compatible accessories, then guided them to purchase.

“Do I need a consumable for my machine? Juliia offered it to me”

Based on a consulted industrial product, it triggered a compatible refill recommendation, which could be added directly to the basket.

“I was looking for a screwdriver, she offered me the complete case.”

Juliia recognized the need and contextualized it with associated accessories or packs, all ready for purchase.

“I was looking for a refrigerator, Juliia recommended a stainless steel range.”

By analyzing the selected product and the constraints mentioned (cleaning, standards), she guided towards complementary options.

Concrete results, where it counts!

71%

Recommendation rate

90 sec.

Average recommendation time

90%

Relevance rate

40%

Engagement rate