Agentic Workflows for Enterprise Automation

Executive Summary

Picture this: You have AI Agents crawling and analysing thousands of data points in real-time to assess current brand perception and sentiment, empowering you to quickly adapt and make informed decisions based on real-time customer feedback and market trends.

These Agents are no longer just tools. In fact, they've become indispensable members of your Marketing team and are capable of executing - with the right guardrails in place - data driven marketing and operational decisions. This includes autonomously creating branded digital assets and making real-time adjustment and optimisation of campaign strategies and messaging.

In today's digital environment, periodic customer surveys and passive feedback are no longer fit-for-purpose - they are lagging indicators that deliver delayed insights. The ability to measure and act on customer feedback and sentiment in real time is fast becoming a key competitive advantage. Together with optimisation of back office processes, this is what will ultimately drive brand equity, enhance customer acquisition and accelerate revenue growth.

The Strategic Importance of Real-Time Brand Monitoring

The core responsibility of any CMO is to plan and execute marketing strategies to build and protect brand equity, with the ultimate goal of attracting and retaining customers. In today's digitally connected world, real-time online brand monitoring, especially across social media, is no longer optional. Only by understanding how customers are perceiving and discussing a brand can we make data-driven decisions to adjust both our tactical and strategic marketing strategies.

There's no better way to gauge brand perception and sentiment than through authentic, unsolicited feedback across multiple channels. On social media, this often takes the form of genuine, immediate reactions from customers. Rather than relying solely on structured or controlled surveys, real-time brand monitoring offers a unique and unfiltered perspective on customer feedback and sentiment.

How do AI Agents Change the Game?

Traditionally, tools have existed to crawl and capture data while providing basic keyword and sentiment matching capabilities. However, these are often rigid, lack understanding of human emotions and require very specific instructions and datasets.

Modern AI technologies and LLMs incorporate Natural Language Processing and Machine Learning, enabling them to more effectively understand and interpret customer feedback, emotional tone and sentiment. Further, AI Agents can process unstructured and complex data sets from various channels, providing a truly holistic perspective.

The most impactful use cases arise from autonomous decision-making and execution by AI Agents. With the right workflows, integrations and guardrails, these agents can autonomously analyse data, execute marketing strategies in real-time and communicate with other agents - transforming how Marketing teams operate and collaborate.

A Practical Example and PoC - Airline Co.

Take for example, an airline company. The journey of an airline customer can be broken down into three distinct phases: Pre-Flight (bookings, lounges, boarding), In-Flight (onboard experience) and Post-Flight (disembarkation, post-flight customer support).

There are many online and offline data points for an airline CMO to measure brand perception, but let's focus on social media as it is a critical channel.

For this PoC, we designed and built an Agent to extract, categorise and analyse hundreds of social media comments from customers of a global airline to determine overall feedback and sentiment across the three phases of the customer journey.

(Disclaimer: This data and analysis is for educational purposes only).

Designing the Agent:

• Real-time crawling of social media data (e.g. mentions, comments, posts, etc.)
• Analysis of raw data:
  • Filter in relevant comments only
  • Categorise into different phases of the customer journey
  • Analyse feedback to determine tone and sentiment
  • Identify any serious safety or operational risks that needs to dealt with urgently
• Provide a summary and recommendation to the team, together with detailed feedback for deep dive if required

Building a Proof of Concept

In this PoC, we utilised n8n and OpenAI's GPT-4o LLM.

Output to the User:

The example output in the PoC is a summarised report that provides invaluable insights to the team on current customer sentiment and feedback. Note: This is very high level and can be tweaked to provide additional level of detail as required.

The more powerful use cases will come from how this data and insight can be utilised to enable data-driven, autonomous decision-making and execution across internal and third-party systems.

Conclusion: Why should CMOs be paying attention?

AI Agents are completely redefining how Marketing teams work and collaborate. For CMOs, the value propositions of uses cases are clear and compelling:

• Analyse and adjust live campaigns in real time to match current feedback, sentiment and trends
• Iterate quickly and reduce spend on ineffective and underperforming campaigns
• Assess the ROI of marketing and loyalty partnerships in real time
• Autonomously create branded, tailored digital assets
• Understand and capitalise on travel trends
• Gain deeper insights into competitors to enable stronger benchmarking

Ultimately, organisations will be able to better understand customer feedback, leading to improved customer journeys and higher satisfaction.

There's no better time than now to start designing, building and incorporating AI Agents into your organisation's workflows and processes. With rapid technological advancements and growing standardisation in this space such as Model Context Protocol (MCP) - the phrase "iterate, then innovate" has never been more true in the agentic age. Every organisation is unique and by starting small, then iterating, will be the key to unlocking transformative value and staying ahead of your competitors.

Note: This article contains personal views only and do not necessarily represent the views of our employer.