Transforming Marketing Operations with AI

Innsyte has been at the forefront of AI transformation in marketing — well before the rise of ChatGPT. We’ve deeply explored how AI can elevate personalisation, automation, and content creation. However, integrating AI into daily processes poses challenges.

We help businesses identify impactful AI use cases, justify the investment, support AI integration and ensure required governance..

Common challenges in Marketing Operations

While implementing AI for marketing teams, we’ve identified several challenges:
  • Fragmented data systems: companies often juggle CRM platforms, ad services, and social media, creating silos that prevent a holistic view of marketing performance.
  • Overwhelming pace of tech change: rapid advancements in AI tools can leave teams feeling overwhelmed and struggling to stay competitive.
  • Difficulty in tracking metrics: without clear visibility, marketing ROI remains elusive, eroding trust and limiting budgets.
  • Unrealistic expectations: AI’s hype sometimes pressures teams to deliver impossible results.
  • Disconnect between AI and Marketing teams: without alignment, AI models may fail to integrate effectively, delaying outcomes.

Key areas of support

Boosting
productivity

We integrate Large Language Models (LLMs) to automate content generation, saving time and helping teams scale.

Driving growth with personalisation

Our custom AI models predict customer behavior and segment clients, improving accuracy and experience.

Performance insights and ROI

We create a 360° view of your marketing efforts, tracking campaigns across CRM, websites, and automation tools to demonstrate ROI.

Tailored use-cases for AI in Marketing Operations

At Innsyte, our AI experts specialise in mid-size to enterprise marketing transformations. Our journey started over a decade ago, well before tools like ChatGPT. Please consider that use-cases mentioned below were successfully delivered by Innsyte’s employees in their historical experience. Here’s how we help:

Scalable marketing content

Automation of products description

EU AI Act: Low or minimal risk
Automated generation of product descriptions enhances marketing efforts and reduces manual workload.
  • Problem: Marketing teams struggle to craft engaging product descriptions for large inventories, resulting in time-consuming manual efforts.
  • Solution: we implement AI-driven automation to generate compelling product descriptions across multiple languages.
  • Results: increased effectiveness, improved engagement, and reduced costs.
AI generates customised newsletters, improving open and conversion rates through personalisation.
  • Problem: teams find it hard to optimize newsletters to drive engagement.
  • Solution: AI models predict customer preferences for personalised newsletters.
  • Results: improved conversion rates and customer satisfaction.

Automated newsletter crafting

EU AI Act: Low or minimal risk

AI agents to generate marketing content across different platforms

AI-driven content creation across platforms saves time and ensures consistent messaging
  • Problem: marketing teams struggle to produce consistent, engaging content across various platforms, leading to time-consuming processes.
  • Solution: AI agents automatically generate tailored content for each platform, ensuring consistency and efficiency.
  • Results: significant time savings, consistent messaging across all channels, and a marketing team free to focus on strategic initiatives.

Marketing predictions

Product purchase propensity prediction

EU AI Act: Low or minimal risk
AI predicts the likelihood of a customer purchasing a product, enabling more targeted marketing efforts.
  • Problem: marketing teams struggle to reach relevant customers when launching new products, leading to wasted resources and impersonal marketing.
  • Solution: a propensity-to-buy algorithm identifies customers with the highest likelihood of purchasing, allowing for personalised marketing campaigns.
  • Results: this approach saves costs by focusing on relevant customers, improved customer relationships with tailored offers, and boosted marketing campaign effectiveness.
AI suggests optimal next steps in customer interactions, improving service quality and satisfaction.
  • Problem: businesses can need a way to enhance customer interactions and elevate service quality.
  • Solution: AI-driven recommendations guide teams toward actions that improve service and satisfaction during customer interactions.
  • Results: this solution can lead to more effective customer interactions, resulting in higher service quality and improved customer satisfaction.

Next best action

EU AI Act: Low or minimal risk

Personalised product recommendations

EU AI Act: Low or minimal risk
AI offers personalised recommendations based on purchase history and demographics, driving sales and customer satisfaction.
  • Problem: customers often struggle to find products that suit their preferences, leading to lower sales and missed opportunities.
  • Solution: an AI-based recommendation system uses purchase history and demographic data to suggest relevant products.
  • Results: this approach can significantly increase conversion rates and sales, as customers were more likely to purchase products that aligned with their interests.
AI segments customers based on behavior and preferences, enabling more targeted marketing strategies.
  • Problem: businesses lack insights into customer behavior, making it difficult to target marketing strategies effectively.
  • Solution: AI-driven segmentation groups customers based on preferences and behaviours, enabling tailored marketing.
  • Results: this solution can provide more precise marketing strategies, improved engagement, and higher conversion rates.

Customer segmentation

EU AI Act: Low or minimal risk

Customer sentiment analysis

EU AI Act: Low or minimal risk
AI analyses customer sentiments from online interactions, providing valuable insights to improve products and services.
  • Problem: marketing teams struggle to fully leverage web and mobile data to gain insights into customer behavior as digital interactions increased.
  • Solution: AI tools analyse web and mobile logs to map customer usage patterns and provide insights into behavior.
  • Results: the solution can enhance the company’s understanding of customer preferences and improved customer journey experiences.
AI predicts user interests for more targeted marketing, improving the effectiveness of campaigns.
  • Problem: a fashion retailer struggled to determine which brands to feature in newsletters to increase conversions.
  • Solution: a predictive model used customer transaction data to forecast which brands each customer would likely prefer, enabling personalised newsletter content.
  • Results: the solution can boost conversion rates and newsletter open rates by up to 10%, improving customer satisfaction and loyalty.

User interest prediction

EU AI Act: Low or minimal risk

Need help identifying your best AI use case?

Our experts provide clear, actionable advice on the best AI use case for your business.

Marketing performance management

Marketing 360 Performance View

EU AI Act: Low or minimal risk
AI enhances performance reporting by consolidating data across multiple units, improving decision-making and operational efficiency.
  • Problem: marketing teams face fragmented performance data, spread across different systems, leading to poor decision-making and inefficiency.
  • Solution: the system consolidates all performance data into a unified, real-time view, enabling comprehensive reporting and analysis.
  • Results: improved decision-making and operational efficiency, as teams can now access a holistic view of marketing performance, allowing for more informed and faster decisions.
Simplifies data retrieval and analysis for marketing teams, allowing them to access and analyse customer data without needing SQL expertise.
  • Problem: Marketing teams often struggle to retrieve and analyse customer data stored in relational databases due to a lack of technical skills.
  • Solution: an AI-powered assistant, using a Large Language Model (LLM), converts natural language queries into SQL commands, retrieving data through a simple chat interface.
  • Results: streamlined data retrieval, reduced dependency on technical skills, and faster, more informed data-driven decisions, improving overall marketing efficiency.

AI-powered decision making for Marketing

EU AI Act: Low or minimal risk

FAQ – most frequent questions to AI in Marketing Operations

Review our other Operational AI use-cases for specific departments

Performance management

Customer service

Sales
Operations

Finance Operations

HR
Operations

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