An aging homegrown CRM held back 1,700 agents. Now, an AI co-pilot helps them draft faster, higher-quality emails from a single screen.
A British multinational retailer serves over 10 million customers across 127 countries, handling approximately 653,000 monthly support tickets with 1,700 service professionals speaking 11 languages.
A 15-year-old homegrown CRM system struggled with performance, stability, and availability, forcing agents to navigate multiple clicks and up to six...
“We have more than 10 million customers across 127 different countries, with different preferences for contacting us. With contact centers on multiple continents, employing agents offering 11 different languages, we can’t operate without efficient technology.”
Multichannel retailer of fashion, beauty, and home products.
AI-powered customer service and employee experience software platform.
Next's Customer support co-pilot is part of this use case:
Related implementations across industries and use cases
Manually triaging each support ticket took agents 20 minutes. Now, AI routes inquiries and a copilot helps agents draft empathetic replies.
Onboarding staff for the holiday peak was a bottleneck. Now, AI handles routine chats and new agents train in a sandbox, ready for day one.
Returns and ID checks slowed global support. AI now automates these flows on WhatsApp and voice, matching tone to local markets.
Manual categorization delayed revenue. Staff-built agents now auto-classify products for 91% faster onboarding, with human oversight.
Scattered data left staff using risky shadow AI to keep up. Now, employees use Copilot to securely review policies and simplify reports.
300+ receipt layouts forced manual entry. GenAI now reads raw images with 98.6% accuracy, cutting costs 90%.
Employees previously broke work into rigid tasks. Now, they delegate high-level goals to agents that work autonomously for hours.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
An aging homegrown CRM held back 1,700 agents. Now, an AI co-pilot helps them draft faster, higher-quality emails from a single screen.
A British multinational retailer serves over 10 million customers across 127 countries, handling approximately 653,000 monthly support tickets with 1,700 service professionals speaking 11 languages.
A 15-year-old homegrown CRM system struggled with performance, stability, and availability, forcing agents to navigate multiple clicks and up to six...
“We have more than 10 million customers across 127 different countries, with different preferences for contacting us. With contact centers on multiple continents, employing agents offering 11 different languages, we can’t operate without efficient technology.”
Multichannel retailer of fashion, beauty, and home products.
AI-powered customer service and employee experience software platform.
Next's Customer support co-pilot is part of this use case:
Related implementations across industries and use cases
Manually triaging each support ticket took agents 20 minutes. Now, AI routes inquiries and a copilot helps agents draft empathetic replies.
Onboarding staff for the holiday peak was a bottleneck. Now, AI handles routine chats and new agents train in a sandbox, ready for day one.
Returns and ID checks slowed global support. AI now automates these flows on WhatsApp and voice, matching tone to local markets.
Manual categorization delayed revenue. Staff-built agents now auto-classify products for 91% faster onboarding, with human oversight.
Scattered data left staff using risky shadow AI to keep up. Now, employees use Copilot to securely review policies and simplify reports.
300+ receipt layouts forced manual entry. GenAI now reads raw images with 98.6% accuracy, cutting costs 90%.
Employees previously broke work into rigid tasks. Now, they delegate high-level goals to agents that work autonomously for hours.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.