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ShopNova

E-Commerce ยท 250 employees ยท Berlin, Germany

ShopNova Saved โ‚ฌ2.1M/Year by Replacing 80% of Their Support Team With AI

Multilingual AI agents handling order tracking, returns, and upsells across 6 European markets.

E-CommerceMultilingualShopifyZendeskUpselling

โ‚ฌ2.1M

Annual Support Cost Saved

Deployed in 8 weeks

Conversational Voice & Chat Agents

Results

Key Performance Metrics

AI Resolution Rate

Before

0%

After

82%

+82%

Avg. Resolution Time

Before

4.2 hrs

After

8 min

-97%

CSAT Score

Before

68

After

87

+28%

Annual Support Cost

Before

โ‚ฌ2.8M

After

โ‚ฌ0.7M

-75%

Support Team Size

Before

45

After

9

-80%

Upsell Revenue (Annual)

Before

โ‚ฌ0

After

โ‚ฌ340K

+โ‚ฌ340K

Data

Performance Over Time

Annual Support Cost (โ‚ฌK)

Customer Satisfaction (CSAT)

Before vs After: Key Metrics Comparison

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The Challenge

ShopNova, a DTC fashion brand operating in 6 European countries, was drowning in support tickets โ€” 18,000+ per month across email, live chat, and phone. Their 45-person support team handled queries in 4 languages (EN, DE, FR, ES) with inconsistent quality. Average resolution time was 4.2 hours. CSAT was declining (68/100), and support costs consumed 22% of operating budget at โ‚ฌ2.8M annually.

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Our Solution

We deployed a multilingual agent fleet: (1) live-chat agents on their Shopify storefront handling order tracking, size recommendations, and return initiation in all 4 languages; (2) WhatsApp agents for post-purchase communication (shipping updates, review requests, cross-sells); (3) email triage agent that auto-resolves 70% of inbound emails and routes complex issues to specialized human agents with full context summaries. Integrated with Shopify, Zendesk, and Klaviyo.

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Implementation

Week 1โ€“2: Analyzed 6 months of ticket data (108K tickets), identified top 23 issue categories covering 91% of volume. Week 3: Built multilingual response library and agent personas for each market. Week 4: Soft launch on DE market only. Week 5โ€“6: Rolled out to remaining 5 markets. Week 7โ€“8: Upsell agent trained on purchase history to recommend complementary products during support interactions.

Outcome

The Results

Within 4 months: AI agents now resolve 82% of all support interactions without human escalation. Average resolution time dropped from 4.2 hours to 8 minutes. CSAT rose from 68 to 87. The support team was reduced from 45 to 9 senior specialists (handling only complex returns, fraud, and VIP accounts). Annual support cost dropped from โ‚ฌ2.8M to โ‚ฌ0.7M. Bonus: the upsell agent generates โ‚ฌ340K in additional annual revenue through contextual product recommendations during support chats.

โ€œWe went from 45 support agents across 4 languages to 9 specialists โ€” and our customer satisfaction actually went UP. The AI agents handle German grammar better than some of our previous hires. The upsell feature was a surprise โ€” we didn't expect support interactions to become a revenue channel.โ€

Lena Hofmann

VP of Customer Experience, ShopNova