top of page
  • Raj Varma

Challenges of Automation & AI in Marketing and Customer Lifecycle Optimization (CLO)

-Matt Hasan, Ph.D.


Automation in the marketing and customer lifecycle optimization (CLO) areas,

particularly when powered by AI, leads to increased accuracy & precision as well as

decreased time in

(1) gathering, consolidating, structuring, cleansing and scrubbing vast

amounts of diverse customer data,

(2) analyzing the data using classical methodologies

as well as neural networks, and

(3) making instantaneous decisions and taking action.

The obvious benefits are higher revenue, lower costs and improved ROI. However, there

are significant challenges as well. Some of those are discussed below.

Data Quality and Integration

Data Accuracy : Automation relies crucially on data. If the data used for automation is

inaccurate, outdated or compromised in any way, it can lead to ineffective actions and

undesirable results.

Integration Issues: Marketing and customer lifecycle optimization automation/AI tools

need seamless integration among marketing, CRM and analytics platforms. Ensuring

seamless integration can be a challenge, especially when dealing with different data

formats and structures.

Personalization and Targeting

Reliance on Algorithms : While algorithms can help in personalization, they may not fully understand the nuance of human behavior. Striking the right balance between

automation and human touch is crucial.

Limited Creativity: Automation may excel in repetitive tasks but can struggle with creative aspects. Crafting compelling and creative content often requires a human touch.

Automated Content Creation: While automation can help in content distribution, creating high-quality, engaging content often requires a level of creativity and understanding that machines may struggle to achieve. This is likely to improve over time.

Costs and ROI

Initial Investment : Implementing automation systems can have a high upfront cost, and calculating the return on investment (ROI) can be challenging, especially when considering the complexity of attribution in multichannel campaigns.

Continuous Testing & Optimization: Automated processes need continuous testing and optimization. Failing to adapt and refine automation strategies can result in suboptimal performance.

Change Management

Rapid Technology Evolution: The marketing & customer lifecycle optimization technology landscape is constantly evolving.

Marketers and customer lifecycle optimization specialists need to adapt quickly to new tools, algorithms, and channels, making it challenging to keep automation strategies up to date.

Resistance to Change : Employees may resist automation due to fear of job loss or

discomfort with new technologies. Training and change management are crucial to

overcome this challenge.

Data Security & Regulatory Compliance

Data Security: The automation of marketing processes involves the handling of sensitive customer data. Ensuring the security of this data from potential breaches is a critical concern.

Data Privacy Concerns : With increasing emphasis on data privacy regulations like GDPR, marketers need to ensure that their automated processes comply with these regulations, and that the data collected and used is done so legally and ethically.

Customer Trust and Relationship

Loss of Human Touch: Reliance on automation can lead to a loss of the personal touch in customer interactions. Building and maintaining trust often requires a more human approach, especially in delicate situations.

To summarize, while automation/AI provides substantial benefit in the short as well as

longer term, its challenges and shortcomings have to be acknowledged and addressed.

The key is to strike the proper balance between automation/AI and human involvement. This is a very nuanced task and can only be fine tuned over time with practice.

Contact aiRESULTS Team for ai solutions that deliver RESULTS.


bottom of page