AI-Enhanced Marketing & Automation

Intelligent systems that optimize decisions, personalize journeys, and scale performance with minimal manual effort.

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Automate My Growth

Executive Summary

AI-driven marketing is no longer a “nice to have”—it’s the operating system behind the region’s fastest-growing brands.

Manual optimization, static segmentation, and batch campaigns are no longer competitive. Modern brands rely on predictive models, automated workflows, and real-time personalization to reduce CAC, increase ROAS, and unlock higher lifetime value. At IntelliVise.co, we build AI-driven systems that run 24/7 to orchestrate journeys, score users, personalize content, and optimize performance in ways that human teams cannot replicate manually.

Our automation frameworks plug directly into your stack—Shopify, HubSpot, Zoho, Klaviyo, BigQuery, GA4, or your custom backend—ensuring fast time-to-value, reduced operational overhead, and measurable uplift across acquisition, conversion, retention, and monetization.

Results? Lower costs, faster decision-making, more agile operations, and a fully automated growth engine that scales as your brand scales.

Problems We Solve

Acquisition Inefficiencies

  • Poor targeting and manual bid adjustments
  • Inconsistent optimization cycles
  • Budget leakage and inefficient ROAS

Conversion Gaps

  • No personalization across funnel stages
  • Limited user scoring and intent prediction
  • Underperforming landing and product experiences

Retention Challenges

  • High churn and weak lifecycle touchpoints
  • No predictive retention or winback strategies
  • One-size-fits-all CRM automation

Data Fragmentation

  • Disconnected analytics sources
  • Missing attribution signals
  • Unreliable forecasting and reporting

Operational Overload

  • Manual campaign management
  • Heavy content production workload
  • Slow experimentation cycles

Our AI Marketing Framework

A unified, enterprise-grade operating model for automated, intelligent growth.

1. Intelligence Layer (AI + Predictive Models)

Lead scoring, churn prediction, purchase intent, product affinity, and LTV forecasting models tailored to your category and data maturity.

2. Automation Layer (Journeys & Workflows)

Event-driven, lifecycle-based automations that trigger the right message, at the right time, for the right user.

3. Personalization Layer

Dynamic product suggestions, content personalization, behavior-triggered messaging, and user-specific experiences across web, app, email, SMS, and ads.

4. Experimentation Layer

Automated hypothesis creation, variant testing, statistical validation, and rollout—driving continuous incremental gains.

5. Creative Automation Layer

AI-powered ad copy, creative iteration, product-feed enrichment, and DCO pipelines to scale creative production.

6. Insights & Decision Layer

Real-time dashboards, anomaly detection, forecasting, and automated alerting to accelerate decision making.

Our Methodology

1. Discovery & Data Architecture

We map your existing events, CRM fields, workflows, and analytics stack to identify misalignments, missing signals, inefficiencies, and automation opportunities.

2. Predictive Modeling

We develop bespoke machine learning models using categorical signals, behavioral patterns, transactional data, and product interactions.

3. Automation & Lifecycle Engineering

We build automated, event-based lifecycle programs covering onboarding, activation, retention, reactivation, and upsell.

4. Real-Time Personalization

We integrate identity resolution, recommendations, and dynamic content to deliver contextual user experiences.

5. Creative Automation

AI-generated creative variants, automated copy testing, product feed optimization, and ad personalization pipelines.

6. Experimentation Ops

Continuous A/B and multivariate testing powered by automated frameworks that launch, validate, and scale winning variants.

7. Dashboards & Forecasting

Centralized dashboards for real-time visibility into revenue drivers, channel performance, cohort behavior, and anomaly detection.

8. Optimization & Governance

Ongoing refinement of models, workflows, content, and experiments, ensuring long-term impact and operational stability.

Deliverables

  • Predictive models (lead scoring, churn, LTV, intent)
  • Lifecycle workflows for acquisition, retention, and reactivation
  • AI-driven personalization engine
  • Dynamic content and product recommendation systems
  • Creative automation pipelines (copy + visual)
  • Experimentation framework and testing playbooks
  • Analytics dashboards in Looker, BigQuery, and GA4
  • Documentation + optimization roadmap

Case Studies

Case Study #1 — GCC Fashion Retailer

We deployed predictive models and a retention automation system for a retailer with 100K+ SKUs across GCC. Our system identified high-propensity shoppers, optimized discounting, and automated lifecycle journeys. Results: +22% AOV, +38% returning customers, 15% lower churn.

Case Study #2 — B2B SaaS Platform

We built AI lead scoring, automated nurturing workflows, and intent routing for a B2B SaaS client. Sales velocity increased by 41%, and pipeline predictability improved within weeks.

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Let’s design your AI-powered growth engine and accelerate performance.

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