Case study

How Moliv scaled expert skincare advice without scaling their team

Moliv, the first Polish manufacturer of skincare with live probiotic bacteria, gives every customer personalised, expert product guidance 24/7 — with AskSpot AI Chat and Inbox Agent, without adding a single hire to its team of microbiologists.

4 min read

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Client

Moliv Cosmetics

Industry

Probiotic skincare / cosmetics e-commerce

Scale

~4,600–5,800 users per month · team of 1–5

Channels

Own stores (PL, DE, GB) + marketplaces incl. Allegro

Implementation results

Key results

AI Chat on molivcosmetics.com and the Inbox Agent on Allegro messages and contact forms — effects visible across the whole sales funnel.

16–26%

sales conversion among chat users

59%

click-through rate on AI product recommendations

10–25%

of orders preceded by a chat conversation

24/7

expert product advisory — without adding headcount

Challenge

A patented formula that needs explaining — and a team of 1–5

Moliv is not a typical cosmetics brand. Founded by microbiologists, it is the first Polish manufacturer of skincare containing live probiotic bacteria — a patented, science-backed formula that genuinely requires explanation. Visitors to molivcosmetics.com arrive with specific, complex questions: which product suits acne-prone skin, how live bacteria survive in a jar, whether the oleogel can be used with retinol.

With a team of 1–5 people, there was no capacity to give every visitor a personalised, expert answer. Enquiries were handled manually, creating delays and a disproportionate burden on the founding team — while the brand’s value lies precisely in its scientific depth.

Expert knowledge didn’t scale

  • Complex ingredient and formulation questions behind every purchase decision
  • Manual handling of enquiries — delays and pressure on a small team
  • Unanswered questions at the product page level were costing conversions
  • Post-sale requests (order status, delivery, returns) consumed time meant for product work

Solution

Expert consultation on the site, an automated inbox — two steps

The implementation goals: instant, accurate answers to complex ingredient questions at the point of purchase, less manual handling of pre- and post-sale enquiries, and a consistent experience across the website and Allegro — so the small team could focus on science and product.

Step 01

AI Chat on molivcosmetics.com

The chat is integrated with the WooCommerce product catalogue and a custom knowledge base covering formulations, ingredients and skincare routines. It handles all three language versions of the site — Polish, English and German — and is available 24/7.

  • Skin type advisory — acne, dryness, sensitivity, ageing, combination skin
  • Explaining live probiotic bacteria, Lactobacillus strains, Formula 3P and GRAS safety status
  • Product comparisons and routine guidance — e.g. oleogel with cream, day vs night use
  • Order status checks and delivery information
  • Returns and complaints — with structured data collected for the team

Step 02

Inbox Agent on incoming messages

Following the chat rollout, the Inbox Agent was connected to Moliv’s incoming message channels — Allegro’s messaging system and the website contact forms.

  • Classifies messages by intent: product question, order status, return, complaint or general enquiry
  • Retrieves order and product data to generate accurate, contextual responses
  • Resolves routine cases autonomously — order tracking, delivery information, return procedures
  • Prepares summaries and draft replies for complex cases, with context already in place

Results

More conversion from conversations, no team expansion

Measurable improvements across the funnel — from pre-sale advisory to post-sale service.

16–26%

Sales conversion among chat users

Beauty and specialised niche brands on AskSpot consistently achieve this range in chat sessions — versus a typical store-wide average of 2–4%.

59%

Click-through on AI recommendations

Nearly 6 in 10 users click through to a recommended product — well above the 1–3% typical of passive recommendation widgets.

10–25%

Orders preceded by a chat

Across AskSpot’s partner base, a chat conversation precedes 10–25% of completed orders — up to 1 in 4 purchase journeys.

Why it worked

Science-depth knowledge base

AskSpot was trained on Moliv’s full product knowledge — ingredients, formulations and skin type guidance — answering accurately and on-brand, at the level customers expect.

Full-funnel coverage, lean team

Chat and Inbox Agent together handle pre-sale advisory and post-sale service — on the website and Allegro, end to end.

A fast start in three languages

The WooCommerce integration was live within 2–3 business days, with no dedicated technical resource required from Moliv. Polish, English and German worked consistently from day one.

MOLIV

“AskSpot helped us serve customers faster and better. Multilingual and marketplace integrations were crucial, as well as the ability to answer even hard product questions.”

EK

★★★★★

Ewa Kosiorek

Head of Customer Service at Moliv

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