customer service

Implementing AI in Customer Care

Integrating AI in Customer Service

Customer Service is one of those disciplines that is ideal for AI innovation: “up to 70% of customer service inquiries are repetitive and easy to automate (McKinsey)”.  

The advantages of AI in customer service are endless: it drastically reduces cost, it leads to higher customer satisfaction, and it improves employee happiness by taking away the repetitive requests. 

With such clear advantages, you’d expect that most ecommerce businesses would have already integrated AI in their customer service. This is not the case. Why?  Properly implementing AI in your ecommerce set-up isn’t exactly easy nor fast, it’s a challenging process. 

The challenges of implementing AI in customer service

1) Picking the right AI tool
There are many AI applications and solutions, and new ones appear every day. When the market starts consolidating, will your AI solution still be there? Do you have to start over? We structure your data and policies in such a way that they are instantly applicable for most AI solutions and CMS/ ticketing-systems.

2) Where to start?
Do you have a properly structured overview of all incoming requests? With that information you know where to start and what category to automate first to make the biggest impact.

3) How?
Now the real work starts; structure and organise customer service data and product information the right way, create and implement the right policies and train the AI solution to become the best customer service agent possible.

3 colleagues planning a strategy on a window with office materials

AI Customer Service implementation by Salesupply

Schematic overview of AI Implementation flow

Salesupply is the specialist in ecommerce customer service. We have redefined ecommerce internationalisation by offering flexible pay-per-use service in 25 languages regardless of your CMS.

Now we are redefining ecommerce customer service again with flexible AI Integration:

  • Our experts will implement the most suitable AI solution in your current CMS.
  • Automating a large part of your written customer service with AI.
  • Together with trained customer service agents your customers will be served by the ultimate AI Hybrid Customer Service team.

AI Solutions & Customer Service integrations

As a specialist in ecommerce customer service, we have integrations for the most widely used ecommerce platforms and ERP systems. Below an overview of the AI solutions we can implement as well as the systems we can implement them in. Do you miss your solution or system? Please get in touch

Overview of AI solutions and Customer Service systems we can integrate

Futureproof your Customer Care with AI

Fashion models on the catwalk

For well-known luxury fashion brand from the Netherlands, we implemented an email AI solution.

The results after two months:

  • 40% of all written communication is automated and fully handled by AI.
  • The main customer service requests category has been automated for 70%.
  • A cost saving of 30% in the first 2 months, aiming for 60%.
  • Next steps: Connecting external systems to automatically create return labels and execute refunds.
Industrial role of plastic

For a successful European B2B platform in plastics, we have integrated both an AI email and a new AI chatbot solution.

The results after three months:

  • 95% accuracy in chat.
  • 99.5% of all written communication is automated and fully handled by AI.
  • Cost savings of 15% on all existing support channel by introducing the new chat channel. 
Store rack with hoodies

For a leading Polish sportswear brand we recently integrated Salesupply Email Aigent, in agent assist mode to assist the customer care agents. 

The first results:

  • Email handling time per agent reduced by 90%
  • Next steps: fully automate email

FAQ: Implementing AI in Customer Service

We are passionate about quality customer service. Currently, AI is not yet capable to fully take over the role of customer service department. If you have your own customer service department, we gladly implement the AI solution for you and prepare your team to work together with it.

Use AI as your first-line virtual agent for repetitive tickets and as agent assist for the rest – with human handoff on low confidence and with clear quality checks.

Steps:

  • Deflect FAQs
  • Build Policies
  • Order Integration (order status/WISMO, returns,).
  • Automate triage, tagging, routing, and post-interaction notes.
  • Escalate with context when confidence is low or the customer asks.
  • Review low-confidence answers.

Start with clear KPIs, connect your knowledge base, OMS/CRM/logistics, and prioritize the highest-volume categories to accelerate ROI. Ship a pilot in one channel, add confidence thresholds and human handoff, then iterate on deflection, accuracy, AHT, and CSAT weekly.

  • Define use cases + KPIs
  • Audit & connect data
  • Choose approach: virtual agent, agent assist, or workflow automation
  • Prioritize high-volume categories
  • Design prompts & policies: tone, refund rules, do/don’t answer lists etc.
  • Train & seed examples
  • Quality gates: confidence thresholds, hallucination filters, restricted topics.
  • Pilot → A/B rollout
  • Monitor & improve: review misfires, update knowledge, tune prompts and routing.

AI can fully resolve FAQs (WISMO, returns), draft and translate replies, summarize threads, auto-tag/route, and escalate complex cases with context. In practice, AI now handles 45-70% of the written requests received by our AI clients – generating major cost as well as time savings.

Core capabilities AI:

  • Self-service: resolves FAQs, order status (WISMO = “Where Is My Order?”), returns, exchanges.
  • Agent assist: suggests replies, drafts emails, live knowledge lookup, conversation summaries.
  • Intelligence: intent detection, sentiment, priority scoring, language detection/translation.
  • Operations: auto-tagging, routing, QA scoring, post-interaction analytics.

Map 1–3 intents (e.g., WISMO, returns), structure policies/product data, define prompts and guardrails, integrate OMS/CRM, and design a human handoff. This way, as much as 50 percent of customer care interactions could be automated. (McKinsey)

A practical setup:

  • Map intents and pick 1–3 categories to start;
  • Structure knowledge;
  • Build prompts & system rules;
  • Train with examples and negative cases;
  • Guardrails: confidence thresholds, sensitive-topic blocks;
  • Design escalation: handoff to human with full context;
  • Measure;
  • Scale.