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Customer Engagement Strategies For Gen Zs in Insurance

Indian market is a multi-headed Hydra that confounds in more ways than one. Being the world’s largest democracy and the most diverse country has resulted in a level of stratification that most countries would be unable to fathom. The tiered expectations and a shift in customer demographic are pushing insurers to rework the Customer Engagement Strategies For Gen Zs.

Tier 1 customers hold businesses to an extremely high standard, often on par with global companies operating out of mature ecosystems like the UK, USA, et al.

Tier 2 customers on the other hand are more rustic in their ways of seeing but actively seek the kind of novelty and flair that their Tier 1 counterparts crave. This cohort also strikes a fine balance between modernity and tradition when it comes to customer engagement expectations, e.g. would prefer talking to a live agent instead of a bot.

Tier 3 customers continue to operate on a major time lag, i.e. fully digital touchpoints do not work and software can be a catalyst for change only insofar as they remain invisible in the interactions that Tier 2 customers have with businesses.

Use Cases:

Given the democratized access to generative AI technologies, insurers would do well to incorporate them in each and every facet of the customer experience, right from purchase, all the way to fraud detection. That being said, regional differences could be accounted for in the following ways:

Tier 1: Metro cities require a comprehensive customer experience approach that never rests. Highly personalized chatbots that operate on context, slick user interfaces that are built to minimize friction in service, and proactive communication (via reminders, automated calls, etc.) are strategies that insurance providers could start using.

Tier 2: Given the relatively less frenzied environment in Tier 2 cities, it would make more sense to devote a sizable portion of the budget towards a digitally-enabled physical office. Incorporating the usual technologies to extend reach, while also maintaining a team in these geographies would give it that added human touch that Tier 2 residents usually appreciate.

Tier 3:

For Tier 3 cities, technology ought to recede into the background and do all the legwork that humans did earlier. A more committed implementation of predictive analytics would be needed as Tier 3 residents don’t have as much of a digital footprint as their Tier 1 and Tier 2 counterparts do. 

Phygital v. Digital

Ensuring stickiness and retention amongst Tier 1 GenZ customers will require a domineering digital play. Establishing multiple touchpoints across popular and emerging platforms would be a non-negotiable strategy. 

Tier 2 customers on the other hand would do well with a digital play with a slight mix of physical touchpoints which could include a singular office in the arena, primarily for servicing and support activities. Customer engagement would require a localization effort, in terms of language as well as distribution.

Tier 3 GenZ members would require a full-fledged phygital strategy where the role of digital engagement would purely be limited to the realm of convenience, by way of sharing documents, essential information, etc. Establishing reasonably spacious offices, coupled with outdoor advertising would be the only way to be ‘taken seriously’ in such geographies.

Next-gen Engagement Models

Both AdTech and MarTech are evolving at a rapid pace, to the point where the cost of implementing experiential engagement strategies is decreasing with each passing year. Audiences in Tier 1 areas will be more receptive to AR/VR engagement that can allow Insurers to integrate physical locations with a slick, digital experience. 

The current ecosystem could even allow for engagement strategies built on the metaverse. These, however, will need to be restricted to upscale commercial/residential areas for maximum effectiveness.

Tier 2 and Tier 3 geographies, on the other hand, are not yet primed for such innovations. The balance between physical engagement strategies, i.e. having a team on the ground, hosting events, and actively reaching out to younger customers in collegiate environments ought to be in favor of the physical, with digital-only being an enabler.

There can be no one size fits all customer engagement strategies. The only way forward would be to carefully select an engagement mix and deploy it dynamically to get the attention of GenZ customers.

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Smart Manufacturing Dashboards: A Real-Time Guide for Data-Driven Ops

Smart Manufacturing starts with real-time visibility.

Manufacturing companies today generate data by the second through sensors, machines, ERP systems, and MES platforms. But without real-time insights, even the most advanced production lines are essentially flying blind.

Manufacturers are implementing real-time dashboards that serve as control towers for their daily operations, enabling them to shift from reactive to proactive decision-making. These tools are essential to the evolution of Smart Manufacturing, where connected systems, automation, and intelligent analytics come together to drive measurable impact.

Data is available, but what’s missing is timely action.

For many plant leaders and COOs, one challenge persists: operational data is dispersed throughout systems, delayed, or hidden in spreadsheets. And this delay turns into a liability.

Real-time dashboards help uncover critical answers:

  • What caused downtime during last night’s shift?
  • Was there a delay in maintenance response?
  • Did a specific inventory threshold trigger a quality issue?

By converting raw inputs into real-time manufacturing analytics, dashboards make operational intelligence accessible to operators, supervisors, and leadership alike, enabling teams to anticipate problems rather than react to them.

1. Why Static Reports Fall Short

  • Reports often arrive late—after downtime, delays, or defects have occurred.
  • Disconnected data across ERP, MES, and sensors limits cross-functional insights.
  • Static formats lack embedded logic for proactive decision support.

2. What Real-Time Dashboards Enable

Line performance and downtime trends
Track OEE in real time and identify underperforming lines.

Predictive maintenance alerts
Utilize historical and sensor data to identify potential part failures in advance.

Inventory heat maps & reorder thresholds
Anticipate stockouts or overstocks based on dynamic reorder points.

Quality metrics linked to operator actions
Isolate shifts or procedures correlated with spikes in defects or rework.

These insights allow production teams to drive day-to-day operations in line with Smart Manufacturing principles.

3. Dashboards That Drive Action

Role-based dashboards
Dashboards can be configured for machine operators, shift supervisors, and plant managers, each with a tailored view of KPIs.

Embedded alerts and nudges
Real-time prompts, like “Line 4 below efficiency threshold for 15+ minutes,” reduce response times and minimize disruptions.

Cross-functional drill-downs
Teams can identify root causes more quickly because users can move from plant-wide overviews to detailed machine-level data in seconds.

4. What Powers These Dashboards

Data lakehouse integration
Unified access to ERP, MES, IoT sensor, and QA systems—ensuring reliable and timely manufacturing analytics.

ETL pipelines
Real-time data ingestion from high-frequency sources with minimal latency.

Visualization tools
Custom builds using Power BI, or customized solutions designed for frontline usability and operational impact.

Smart Manufacturing in Action: Reducing Market Response Time from 48 Hours to 30 Minutes

Mantra Labs partnered with a North American die-casting manufacturer to unify its operational data into a real-time dashboard. Fragmented data, manual reporting, delayed pricing decisions, and inconsistent data quality hindered operational efficiency and strategic decision-making.

Tech Enablement:

  • Centralized Data Hub with real-time access to critical business insights.
  • Automated report generation with data ingestion and processing.
  • Accurate price modeling with real-time visibility into metal price trends, cost impacts, and customer-specific pricing scenarios. 
  • Proactive market analysis with intuitive Power BI dashboards and reports.

Business Outcomes:

  • Faster response to machine alerts
  • Quality incidents traced to specific operator workflows
  • 4X faster access to insights led to improved inventory optimization.

As this case shows, real-time dashboards are not just operational tools—they’re strategic enablers. 

(Learn More: Powering the Future of Metal Manufacturing with Data Engineering)

Key Takeaways: Smart Manufacturing Dashboards at a Glance

AspectWhat You Should Know
1. Why Static Reports Fall ShortDelayed insights after issues occur
Disconnected systems (ERP, MES, sensors)
No real-time alerts or embedded decision logic
2. What Real-Time Dashboards EnableTrack OEE and downtime in real-time
Predictive maintenance using sensor data
Dynamic inventory heat maps
Quality linked to operators
3. Dashboards That Drive ActionRole-based views (operator to CEO)
Embedded alerts like “Line 4 down for 15+ mins”
Drilldowns from plant-level to machine-level
4. What Powers These DashboardsUnified Data Lakehouse (ERP + IoT + MES)
Real-time ETL pipelines
Power BI or custom dashboards built for frontline usability

Conclusion

Smart Manufacturing dashboards aren’t just analytics tools—they’re productivity engines. Dashboards that deliver real-time insight empower frontline teams to make faster, better decisions—whether it’s adjusting production schedules, triggering preventive maintenance, or responding to inventory fluctuations.

Explore how Mantra Labs can help you unlock operations intelligence that’s actually usable.

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