Inside Bosch’s AI-first efficiency playbook
Unify customer feedback across surveys, calls, support tickets, reviews, and communities to automate insight work, speed decisions, and cut the cost of mis-bets.
“Efficiency isn’t just doing work faster—it’s removing work. NEXT AI helps us automate synthesis across sources so teams can focus on decisions and execution.”
– Bernd Wiesenauer, Director of User and Customer Experience
Results at a glance
Lower cost-to-insight
No manual tagging, synthesis, and reporting—AI handles the heavy lifting.Weeks → minutes
Teams move from periodic analysis cycles to self-serve answers with evidence.More confident decisions
Ranked drivers backed by counts and verbatims reduce debate and risk.Broader adoption
A shared intelligence layer usable across marketing, strategy, product, CX, UX and customer care.
Inside Bosch's rollout
Bosch built an always-on customer intelligence layer that:
Unifies customer voice across channels into one governed system
Understands what’s driving outcomes (ranked themes, quantified drivers, supporting quotes)
Activates insights back into execution—roadmaps, campaigns, service improvements, and stakeholder updates
Connected sources:
Surveys (e.g., Qualtrics)
CRM and account context (e.g., Salesforce Sales Cloud)
Service and operational systems (e.g., SAP, Salesforce Service Cloud)
Social/listening and community feedback (e.g., Brandwatch, Sprinklr)
Calls (e.g. Microsoft Teams, Zoom)
Reviews and app feedback
UX research artifacts (interviews, studies, open-text responses)
Signature workflows
1) Cross-source customer intelligence (from fragmentation to one story)
Goal: Give teams a single, reliable view of what customers say, need, and want—across tools and business units.
How it runs: Bosch teams unify surveys, service signals, reviews, and research inputs into NEXT AI, then ask questions like:
“What are the top drivers of dissatisfaction this quarter—and which are growing fastest?”
“What’s changing by market, segment, or product line?”
“Which issues are hurting adoption or driving avoidable support load?”
Outcome: Faster alignment across functions, fewer blind spots, and a clear “fix-first” shortlist grounded in customer evidence.
2) AI-accelerated UX and product discovery (from research to decisions)
Goal: Make UX research and product discovery more scalable—without lowering rigor.
How it runs: NEXT helps teams gather feedback across the journey, then applies semantic analysis to cluster themes and quantify what matters. Teams can quickly generate decision-ready outputs—summaries, concept directions, and early-stage artifacts—so they can iterate sooner and test earlier.
Outcome: Shorter iteration cycles, faster market testing, and reduced risk in product development decisions.
3) Decision-ready outputs into the flow of work (from insights to execution)
Goal: Ensure customer intelligence doesn’t stop at “insight”—it reliably becomes action.
How it runs: Teams produce structured outputs (drivers, evidence, recommended actions) and route them into the tools and rhythms where execution happens—product backlogs, stakeholder updates, marketing planning, and service improvements.
Outcome: Higher throughput, fewer mis-bets, and compounding speed—because decisions happen with less coordination overhead.
Why NEXT AI (and why not just ChatGPT)
Bosch teams already have access to ChatGPT. The gap isn’t access to AI capabilities—it’s doing the ongoing work that makes answers reliable at Bosch scale.
NEXT AI continuously does the heavy lifting in the background: it ingests signals from the tools Bosch teams already rely on, cleans and structures messy feedback, normalizes taxonomies across sources, clusters themes, and builds an evidence layer (counts + verbatims) so answers aren’t just plausible—they’re covered by real customer data. That preprocessing is what enables accurate, decision-grade responses on demand.
What Bosch needed was a system that:
Connects to real sources continuously (not copy/paste snapshots)
Works at scale across many tools and teams with governance and control
Combines qual + quant (ranked drivers + counts + verbatims) for decision credibility
Standardizes repeatable workflows (deep dives, comparisons, hypothesis validation)
Pushes results into execution—so insights become backlog items, actions, and updates
Meets enterprise privacy and compliance expectations across demanding markets
Leadership lessons from Bosch
Efficiency is removing work, not speeding it up: Automating synthesis frees experts to focus on decisions.
Shared truth beats local truth: When every team sees the same drivers, alignment accelerates.
Evidence reduces risk: Counts + verbatims turn “opinions” into decision-grade inputs.
Speed compounds: Shorter learning loops create faster iteration cycles and earlier market validation.
“The biggest win is decision velocity. When evidence is instant and accessible on-demand, teams move faster—with fewer misbets.”
– Bernd Wiesenauer, Director of User and Customer Experience
Looking ahead
As AI and agentic workflows become embedded in how teams operate, Bosch is well positioned to use NEXT AI as a customer intelligence layer that powers more automated, more efficient feedback-to-action loops—across business units, markets, and customer touchpoints.