How AI + analytics are revolutionizing marketing performance

In an environment where every interaction matters, organizations applying artificial intelligence with an operational focus are making a measurable difference. And if there's a clear example of that, it's EXL.

As their Executive Vice President, Narasimha Kini, recently explained in an interview with the New York Post, EXL has increased marketing ROI by 60% and improved engagement by 35%, thanks to a strategy where AI is directly embedded into real commercial processes.

What matters isn’t just the data, but how it’s used: a direct integration between artificial intelligence, advanced analytics, and commercial execution.

AI in action: operational, predictive, and connected

EXL hasn’t limited itself to using AI as an assistant or peripheral tool. It has made it a structural part of how the business operates. Some of the most notable use cases include:

  • Insurance: in collaboration with Nvidia, they developed predictive models that anticipate purchase intent, customer churn, and the optimal timing for campaigns.
  • Retail and Sports: applying real-time analytics to adjust promotions, personalize messages, and redesign customer journeys on the fly.

The key lies in a solid integration: AI + data + processes. Not as a lab experiment, but as a true business operating system.

Implications for Marketing and CRM

This approach is fully applicable to organizations managing large volumes of data and customer relationships. The goal is to activate AI within the existing ecosystem, especially within CRM.

  • Embedding analytics inside the CRM: not as a dashboard, but as a decision-making engine.
  • Connecting AI across the funnel: from predictive acquisition to automated retention.
  • Closing the measurement loop: it’s not enough to report KPIs — you need to analyze, predict, and act on them in real time.

When applied correctly, AI doesn’t replace marketing — it enhances it. It makes it smarter, faster, and significantly more effective.

How to get started: The Hike&Foxter approach

Based on our experience implementing AI in CRM and commercial processes, we recommend the following roadmap.

  • Data audit: identify silos, redundancies, and automation opportunities.
  • Design of intelligent flows: connect your tech stack so data flows, learns, and acts.
  • Actionable predictive models: for real cases like lead scoring, churn prediction, or content recommendations.
  • Continuous, real-time measurement: tools that help you understand not only what happened, but what’s happening — and what might happen next.

Ready to take the first step?

If you're considering introducing AI and advanced analytics into your marketing and CRM workflows, Hike&Foxter can guide you throughout the entire process, from goal definition to technical implementation and results measurement.

Request a no-obligation diagnostic session and start exploring solutions tailored to your business.

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How to implement AI in Marketing to Achieve Real Results

Introduction: From Superficial Adoption to Smart Implementation

 

Artificial intelligence (AI) is already part of the daily life of marketing teams. Tools like ChatGPT or Gemini have become almost indispensable. However, many brands have yet to make the leap from occasional use to strategic integration of these technologies.

In this article from Hike & Foxter, we explore how to implement AI intelligently to improve processes, elevate personalization, and directly connect with business KPIs.

The Current Landscape: Are We Really Integrating AI? 

According to the report "The State of AI in Marketing" by Search Engine Journal, although 91% of marketers already use some AI tool, only a fraction have deeply integrated these solutions into their strategies. Most limit themselves to using tools like ChatGPT to generate ideas or draft content, without linking these efforts to business goals.

Integrating AI is not about using it as a magic solution for isolated tasks. It involves redesigning entire processes, transforming decision-making, and rethinking the customer experience from the first contact to conversion and retention.

Is ChatGPT Enough? What Widespread Adoption Reveals 

83% of surveyed marketers use ChatGPT as a central tool. However, the real impact is limited when not paired with other complementary solutions.

The key is tool literacy:

  • Understanding what each solution can (and can't) do

  • Knowing how they integrate with each other and platforms like CRM

  • Spotting opportunities to redesign processes, not just tasks

🔎 Useful fact: Teams with an integrated AI stack generate 3.2 times more personalized content than those who rely on a single tool.

kickstart-newsletter-sej-report

Recommended AI Stack: Tools by Objective

Objective Basic Tool Advanced Tool Success Metric
Content Generation ChatGPT Jasper + CRM CTR +25%
Personalization Static Templates Dynamic content + AI Conversion +40%
Predictive Analytics Google Analytics Machine Learning in CRM Lead scoring +60%

 

A solid AI stack should not only include a variety of tools but also be connected and centered around the CRM. Only then can real results be tracked.

Content Is Still King… But Needs Purpose
 

64.5% of respondents highlight content creation as the area most benefited by AI. But more content isn’t always better. The difference between noise and value lies in the strategy.

How to Create AI-Generated Content That Actually Works:

  1. Well-defined prompts: with clear intent and goal

  2. Business context: using CRM data, buying behaviors, and ideal customer profiles

  3. Clear editorial guidelines: with tone, voice, and consistent structure

Measurement: From Efficiency to Strategic Impact 

One of the most common pitfalls in AI integration is not measuring its real impact. While 87% measure operational metrics like speed or content volume, only 13% evaluate strategic indicators such as LTV or MQL to SQL conversion.

AI Metrics Pyramid

  1. Tactical: time saved, content volume

  2. Engagement: CTR, time on page

  3. Strategic: conversion rate, revenue attributed to AI

💡 Recommendation: connect all AI-generated content with real CRM data for comprehensive measurement.

Reputation and Quality Control: New Challenges 

As AI use intensifies in marketing, so do the risks: errors, misinformation, inconsistent tone. Poor implementation can damage brand reputation in minutes.

Basic Policies for Safe AI Use:

  • Mandatory human review before publishing AI-generated content

  • Clear labeling of AI-assisted content

  • Ongoing training in “prompt literacy” and emerging tools

Teams and Talent: Evolution, Not Replacement 

Only 4.5% of companies have reduced staff after adopting AI. Why? Because AI doesn’t eliminate roles—it redefines them. The most valued profiles today are:

  • Content strategists with technical skills

  • CRM managers who understand automation

  • Marketing ops with cross-functional vision

📘 AI requires new skills, not layoffs. Investing in trained talent is the best long-term strategy.

Immediate Future: SEO, Personalization, and Content Overload 

With more content circulating, the challenge is to stand out. Posting is no longer enough. The focus must be on:

  • Optimization for generative systems like Gemini or Perplexity

  • Structured, verifiable, and semantically clear content

  • An editorial strategy that’s also a data strategy

Conclusion: Smart AI Integration Is the New Competitive Advantage 

AI is no longer optional. But effective implementation requires more than testing tools. It demands strategic vision, connection to business data, and a human team capable of guiding the process.

Your next step: Evaluate your AI stack, identify gaps in CRM integration, and define new strategic KPIs.

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