Trevor Gordon, Director and Principal Consultant, Redshank Consulting Limited

Trevor is a digital, commercial, and customer leader who consistently delivers results through innovative use of customer insight, data, and technology to drive growth and improvement in complex, global organisations. His experience has been gained in a wide variety of sectors and high-profile brands on both client and consultancy sides, including most recently at Diageo as Global Transformation Director – Customer. Recent focus has seen Trevor delivering top and bottom-line growth by developing new experiences, operations, strategies, propositions, products, services, and business models for the digital age. Trevor regularly speaks at leading global conferences, podcasts, and online seminars, delivering keynotes on digital transformation, customer experience, continuous improvement, and omnichannel strategy. Let’s read his recent article, where he talked about AI and Machine Learning in Customer Experience Transformation.


In an era of digital transformation, increasing competition from disruptive brands, new business models, and ever-changing consumer behavior; consumer-facing organizations are constantly seeking innovative ways to enhance their customer experience (CX) and stand out from the competition.  While Omnichannel has become much more common as a strategy for most consumer-facing organizations, the increasing importance of integrated Physical/Digital Commerce and the rapid progression of new technologies means that a lot of organizations are constantly updating their CX strategy, roadmap, and investment plans.  Increasingly important for organizations who are looking at CX transformation is the use of both Artificial Intelligence (AI) and Machine Learning (ML).  While technologies/platforms using both AI and ML in terms of managing CX/Customer Engagement have been around for over a decade, a lot of organizations are just starting to adopt the use of AI and ML in their CX transformation, this article will set out some considerations in beginning their journey.

Care of Customers & Employees

While AI and ML can look to optimize and drive efficiencies and gains through customer and employee experience, increased and continued focus on the care of customers and employees is essential.  In starting out it is important that an organization should make “community” a priority while staying true to your company’s purpose.  This is particularly important in terms of the use of data privacy and security, customer consent & control, and transparency.  Some specific areas to consider:

  • Data privacy: As a standard, organizations must prioritize the protection of customer data and adhere to evolving regulations like GDPR. Effective processes and procedures regarding data collection and usage are essential, and ensuring effective cyber security resilience and measures are in place to safeguard this information.
  • Customer Control: Customers need to own and control their experiences, and they will do this by stating their permissions and preferences regarding how they are contacted, when they are contacted, and through what channel. Respect for customer autonomy is key to creating positive experiences and building longer-term customer engagement.
  • Transparency: Consumer-facing organizations should strive for transparency in the use of any AI or ML regarding their CX and Customer Engagement. Many organizations are now establishing customer panels to help with feedback and validation where customers can better understand the reasoning behind things like product recommendations or a “next best action”. This not only builds trust but also aids in regulatory compliance.

Understanding your customer strategy and expected business outcomes

As part of any organization’s Customer Strategy, they need to have a clear understanding of the objectives they hope to achieve by their use of AI and ML, and the return on investment (ROI) they expect in the use of these new technologies.  Some things to think about:

  • Measuring ROI: Any organization starting to use AI and ML needs to understand the impact on your customer experience digital transformation. Establishing and tracking simple key performance indicators (KPIs) related to areas like customer satisfaction, operational efficiency, and revenue generation.  Understanding the ROI of your investments is essential for strategic decision-making, and your future CX and technology roadmap.
  • Futureproofing your technology stack: The adoption of the use of AI and ML should seamlessly integrate into existing technologies and the wider customer digital ecosystem. This needs to be considered for both digital and physical touchpoints (e.g., chatbots, virtual assistants, data-driven insights), so there is an integrated omnichannel end-to-end experience.  As well you need to think of wider areas like scalability and reliability, ensuring your infrastructure can support increased usage and maintain high availability to prevent disruptions in customer service.
  • How much personalization: While hyper-personalization for their customers is usually the desired endpoint, balancing personalization with customer privacy is a delicate art.  No business wants to appear to be crossing this line, and being perceived as overly obtrusive or just plain “creepy”!  Striking this balance ensures that customers feel valued without feeling like their privacy is being invaded.

Ears to the ground & effectively managing customer operations

When an organization first starts using AI and ML in their customer experience transformation, it will be important to understand quickly what is working, and not working. Utilize your customers and colleagues for “ears to the ground” insights, to adapt and move quickly as needed.  As well as ensuring that robust customer operations, governance, and controls are in place to effectively manage this.  Some additional considerations:

  • Customer Feedback Loop: While we have mentioned the use of customer panels, in addition, it is worth providing an instantaneous customer feedback loop that allows customers to provide input on their experiences, communications, and interactions. This should be continually monitored, updated, and reviewed.
  • Training and skills development: Digital Transformation of your CX through AI and ML requires the right skill set and experience in your workforce.  The processes and procedures in the use of AI and ML need to be integrated into an organization’s overall marketing operations and customer operations. This is particularly important with the huge advances in the use of AI by tech companies building CRM (Customer Relationship Management), CDP (Customer Data Platforms), Customer Experience platforms, and other technologies.


AI and Machine Learning can present many new opportunities for consumer-facing organizations to accelerate their customer experience digital transformation. Success is dependent on considering many factors beyond what I have highlighted in this article, and while there is a lot to consider it should not become over daunting for an organization, and the best advice in starting is to keep it simple and to get started with some experimentation.  By addressing these considerations thoughtfully, organizations can harness the full potential of AI while ensuring a positive and trust-enhancing customer journey in the digital age.  This will be crucial for businesses to both retain their existing customers, but also looking to differentiate and grow their business in a profitable way.


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