Chapter 3: Unlocking Customer Potential Through Data
Summary
Organisations are widely adopting advanced analytics, with a clear majority reporting moderate (56%) or extensive (44%) use of techniques such as machine learning, AI, and predictive analytics. Importantly, there were no reports of limited or no adoption of these technologies.
Ensuring data quality and consistency across disparate systems and sources remains a key challenge. Data security and privacy concerns (44%) are paramount, closely followed by the issue of data silos (37%).
Data governance issues (35%), along with concerns about data quality and data volume and variety (both 34%), also present significant obstacles. Data integration complexity (19%) and legacy systems (20%) are perceived as less of a hindrance.
Many organisations are actively leveraging data to gain valuable insights into consumer behaviour and preferences. This includes developing a deeper understanding of customer behaviours, enabling more effective segmentation, analysing purchasing patterns and digital behaviours, and utilising customer feedback and reviews.
These insights are then being applied to improve existing products and services, inform new product development, enhance product recommendations and inventory management, and optimise the overall customer experience through personalised and omnichannel strategies.
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Question 1: To what extent has your organisation adopted advanced analytics techniques?
Question 2: For those who selected AI, we asked them to explain their specific goals in their own words
Question 3: How are you leveraging data to gain deeper insights into customer behaviour and preferences?
To what extent has your organisation adopted advanced analytics techniques such as machine learning, artificial intelligence or predictive analysis?
Moderate (We have started to explore advanced analytics in specific areas)
Extensive (We have implemented advanced analytics across multiple business functions)
Limited (We have limited experience with and primarily rely on traditional reporting and analysis tools.
No adoption
To what extent has your organisation adopted advanced analytics techniques such as machine learning, artificial intelligence or predictive analysis?
Moderate (We have started to explore advanced analytics in specific areas)
Extensive (We have implemented advanced analytics across multiple business functions)
Limited (We have limited experience with and primarily rely on traditional reporting and analysis tools.
No adoption
What challenges does your organisation face in ensuring data quality and consistency across different systems and sources? (Respondents were asked to select three options)
Data security and privacy
Data silos
Data governance issues
Data quality issues
Data volume and variety
Data latency
Lack of data literacy
Real-time data integration
Legacy systems
Data integration complexity
