How fragmented data sabotages personalisation and key ways to get it right

Written by Ian Nicholls, Explic8

Personalisation is more important than ever for businesses today, with the majority [81 per cent] of customers stating they prefer companies that offer a personalised experience according to Forbes.

Personalisation not only builds customer loyalty, but it also improves experiences and helps drive overall success.

With access to a wealth of customer data, businesses have the potential to create tailored interactions that make every customer feel valued. However, many companies struggle to meet expectations, and fragmented data is often to blame.

When customer information is scattered across disconnected systems and departments, it undermines a business’ personalisation efforts, often leading to inefficiencies, missed opportunities, and dissatisfied customers.

To address this challenge, it’s essential to understand how fragmented data undermines personalisation, and to explore effective strategies for leveraging data to deliver better outcomes.

Incomplete customer profiles

Fragmented data creates an incomplete view of the customer. Key pieces of information, such as purchase history, browsing behaviour, or previous interactions with customer service may be housed in different systems that don’t communicate with one another. As a result, businesses are left with a disconnected understanding of their customers.

This incomplete picture makes it difficult to predict customer needs or offer meaningful recommendations. For instance, a retail business might fail to suggest complementary products based on a past purchase because its e-commerce platform and in-store sales system aren’t integrated. The result is a generic customer experience that feels impersonal and disengaging.

Redundant or irrelevant messaging

When data is fragmented, customers often receive redundant or irrelevant messages. For example, a customer who has already purchased a product might be sent promotional emails encouraging them to buy the same item, or worse, they might receive offers that have no connection to their preferences or past behaviour.

This lack of coordination frustrates customers, who expect brands to remember their past interactions. It can also harm a business’ reputation by making personalisation efforts appear careless or superficial.

Inaccurate insights lead to poor decision-making
Data is the foundation of customer insights, but when it is fragmented, businesses can’t rely on the accuracy of the conclusions they draw. Disconnected data sources may provide conflicting or incomplete information, leading to flawed decision-making.

For instance, in a manufacturing context, one system might indicate that a client frequently orders high-volume standard parts, while another fails to capture their recent interest in custom, specialised components.

Without a unified view, personalisation efforts could focus on promoting irrelevant products, missing the opportunity to meet the client’s changing needs. This not only wastes resources but also risks alienating valuable customers by showing a lack of understanding of their priorities.

Increased costs and operational inefficiencies

Managing fragmented data is time-consuming and costly. Businesses have to dedicate significant resources to reconciling disparate datasets, often relying on manual processes to align records. This inefficiency slows down decision-making and creates bottlenecks that hinder responsiveness.

For example, a team tasked with resolving duplicate customer records might spend hours merging information from multiple systems. These efforts divert resources from more strategic initiatives like enhancing customer engagement or innovating new offerings.

Erosion of customer trust

Perhaps the most significant consequence of fragmented data is the erosion of trust.

Customers expect brands to use the data they provide to create seamless and relevant experiences. Therefore, when personalisation efforts fall short due to fragmented data, it sends a message that the business doesn’t truly understand or value its customers.

Trust is difficult to rebuild once lost. A single poorly timed or irrelevant message can undo years of relationship-building, making it critical for businesses to address data fragmentation before it undermines their reputation.

Key strategies to overcome fragmented data

Businesses can adopt several strategies to eliminate the problem of fragmented data and should start by consolidating their data into a single, unified system.

Customer Data Platforms [CDPs] and other integration tools allow companies to aggregate data from multiple sources into one comprehensive view. By breaking down silos, these platforms enable teams to access the same up-to-date information, ensuring consistency across all touchpoints.

Data quality is just as important as data integration, so businesses need to prioritise regular data hygiene practices to ensure accuracy and reliability. This includes removing duplicates, updating outdated records, and standardising formats across systems.

Clean data not only improves personalisation but also enhances the efficiency of marketing and sales efforts. Accurate information enables teams to focus their energy on meaningful interactions rather than resolving inconsistencies.

Artificial Intelligence [AI] and machine learning technologies can also play a pivotal role in overcoming the challenges of fragmented data. These tools can analyse vast amounts of information quickly, identify patterns and predict customer behaviour with remarkable precision.

For example, AI-driven recommendations can suggest products based on a customer’s browsing history, purchase behaviour, and even the time of day they typically shop. This level of personalisation helps businesses connect with customers on a deeper level, encouraging loyalty and increasing conversion rates.

Cross-department collaboration and a customer-centric approach

Fragmented data often stems from organisational silos. Marketing, sales, and customer service teams frequently work with separate datasets, creating inconsistencies that hinder personalisation, and breaking down these silos is essential for creating a unified customer experience.

Collaboration can be built through putting shared goals and systems in place that allow all teams to access the same customer data. When everyone’s work is aligned, it’s easier to join up messaging and deliver seamless interactions.

Businesses must also adopt a customer-centric approach that prioritises understanding and meeting individual needs. This cultural shift ensures data integration and personalisation efforts are driven by the goal of creating value for the customer.

For example, companies that actively seek customer feedback and incorporate it into their strategies are better positioned to offer personalised experiences that truly resonate with their target audience.

Final thoughts

Fragmented data presents significant challenges to effective personalisation, making it difficult for businesses to gain a comprehensive understanding of their customers.

But, by recognising the complexities of data fragmentation and implementing the right strategies, businesses can transform this obstacle into a valuable opportunity.

The key is to invest in robust data integration tools, adopt advanced analytics and create a seamless data flow across platforms. By doing so, businesses can achieve a holistic view of customer preferences and behaviours, enabling more precise targeting and enhanced customer experiences.

About the author

Ian Nicholls is CEO of Explic8