In the age of data-driven marketing, poor customer data isn’t just an inconvenience – it’s a liability. Customers expect brands to anticipate their requirements and respond instantly, making clean, unified data essential for delivering the “next best experience” that resonates with individual emotions and preferences.
To understand the customers you serve, consider investing in a Customer Data Platform (CDP) that unveils the power of customer data, drives loyalty, and elevates customer experience. Before we get into CDP in data management, we’ll see how collecting and cleaning customer data impacts the customer experience and why real-time customer data is essential to achieving this transformation.
Understanding customer data quality
Data quality, consisting of clean, accurate, and actionable data has never been more important in an era where data-driven systems and strategies dominate decision-making. As companies strive to enhance everything from recruitment to product development, getting clean and relevant data becomes more complex as information increases. Unfortunately, poor-quality data diminishes economic value, with Gartner estimating that it costs organisations an average of $15 million annually. The scenario gets much more difficult for organisations operating across numerous regions, business units, and consumer segments.
Clean data: Data that is free from errors like typos, inconsistencies like conflicting entries, and duplications that waste storage space, etc. it is meticulously formatted, adhering to established standards and conventions. The means data is organised in a structured and predictable manner, making it easily understandable and usable by humans and machines alike. For instance, customer email addresses in clean data are correctly formatted, devoid of typos or invalid characters, enabling seamless communication and efficient operations. Ultimately, clean data empowers informed decision-making, drives innovation, and enhances the overall effectiveness of any organisation that relies on data.
Accurate data: Accurate data mirrors reality, providing a true reflection of the world. The data is not only up-to-date and reliable but also devoid of any inaccuracies, like errors, inconsistencies, or outdated information. For instance, accurate customer data ensures that contact information like phone numbers and addresses are current, enabling effective communication and personalised experiences. In essence, accurate data empowers informed decisions, fosters trust, and drives meaningful outcomes.
Actionable data: The data is not just raw information; it’s data that is meaningful, timely, and presented in a format that empowers action. This means it’s relevant to the specific business questions at hand and delivered promptly enough to influence decisions that can still be made. Moreover, actionable data provides clear and concise insights that translate directly into specific actions or strategies. For instance, a report highlighting customers who abandoned their online shopping carts in the past day allows the marketing team to immediately launch targeted email campaigns to encourage them to complete their purchases, potentially resulting in a significant increase in sales. In essence, actionable data bridges the gap between raw information and impactful outcomes, driving successful business decisions and achieving desired objectives.
Poor data quality can have several consequences for a business, including:
Financial losses: Poor data quality may lead to revenue loss, higher expenditures, and wasted resources. For instance, inaccurate inventory data might cause stockouts and delays in processing customer orders.
Operational inefficiencies: Poor data quality can interrupt operations and reduce operational efficiency. For instance, promoting a marketing campaign targeting the wrong demographic could end in wasted resources.
Damaged customer interactions: Inaccurate or inadequate consumer data can result in poor experiences, dissatisfaction, and, eventually, loss of loyalty.
Regulatory obstacles: Noncompliance with data privacy standards can result in significant fines and reputational harm.
Loss of customer trust: Customers may lose control over their data and become skeptical of trusting businesses.
A customer data platform can address these challenges. It can reduce manual effort and ensure data integrity by automating tasks like
Profiling: Analysing data to understand its characteristics, including data types, formats, distribution, and potential issues.
Cleansing: Correcting errors, inconsistencies, and missing values to improve data quality.
Matching: Identifying and linking records representing the same entity across different datasets.
Deduplication: Removing duplicate records to ensure data accuracy and consistency.
CDPs unify data across touchpoints, automate quality tasks, and enable real-time, personalised engagement with a comprehensive 360 customer view.
The role of CDP in data management
A CDP collects data from all touchpoints where customers interact with your company, including websites, applications, social media, and offline sources. It compiles this data into a unified profile for each user, collecting real-time behavioural data from each interaction with the product. The notion enables businesses to segment data in various ways, creating highly targeted marketing campaigns for specific audience objectives.
Real-time customer data allows businesses a comprehensive 360-degree customer view by capturing and unifying data from multiple sources.
Here are the capabilities that enable this:
Data consolidation
CDPs aggregate customer data across diverse channels – social media, email, websites, mobile apps, and existing systems like CRM platforms – to provide a holistic view. This enables businesses to connect fragmented data and gain deeper insights into customer behaviour.
A complete picture of the customer typically includes data from first, second, and third-party sources.
First-party data: Information is collected directly from interactions with a business. This includes user behaviour data captured in real-time from websites and mobile apps, like clickstream or event data. The data tracks the customer’s digital journey, detailing actions across platforms and devices. CDPs are designed to collect and unify first-party customer data from multiple digital sources, creating a single source of truth that eliminates data silos and enhances data accessibility.
Second-party data: Often obtained from trusted partners like ad platforms or shipping and delivery systems, enhances customer profiles by adding transactional and logistical context.
Third-party data: Purchased from external vendors, this data provides valuable insights into customer browsing habits, intent, and demographic or firmographic details.
Data unification
Once all relevant customer data is collected in a data warehouse, the next important step is unifying it to create a comprehensive 360-degree customer view. The process involves resolving multiple customer identities to form a cohesive profile. The integration process, also known as identity resolution or data unification, ensures that fragmented data from numerous sources is consolidated into a single customer profile, removing discrepancies.
Identity resolution links all unique identifiers associated with a customer across various systems and channels. For instance, a customer might use an email address for one purchase, a phone number for another, or engage with your brand through multiple touchpoints. The disparate identifiers are seamlessly connected to form a unified customer profile, eliminating duplicates and fragmentation. The process assigns a canonical identifier to each customer, consolidating all interactions, purchases, and behaviours under one unified profile. Data is validated, cleaned, and deduplicated during this unification to ensure accuracy and consistency.
Customer classification and segmentation
Once identity resolution is completed, a real-time customer data platform processes the unified data into actionable insights, creating detailed customer traits and audience segments. The platform classifies customers into segments through real-time analysis based on key demographics like purchase history, preferences, behaviour, pain points, location, age, gender, and more.
Businesses can use this data across multiple platforms to launch highly personalised marketing campaigns aligning with customers’ unique behaviour and preferences. As new or updated customer data is continuously acquired, it is processed in real-time to ensure that all customer interactions remain relevant, contextual, and up to date.
Benefits of having a clean customer data
Clean customer data, managed effectively through a data management platform, is the foundation of outstanding customer experiences, allowing businesses to personalise interactions to meet individual requirements and preferences. According to PWC, 73% of customers consider the experience an important factor in purchase decisions, after price and product quality. customers are eager to invest in better experiences, with 43% paying more for increased convenience and 42% valuing friendly and welcoming experiences. Clean data helps businesses to exceed such expectations, resulting in increased satisfaction.
Clean data enhances customer interactions in multiple ways, including:
Personalisation and relevance
Businesses may use precise and consistent data to identify segments and audiences, allowing marketing, sales, and customer support teams to create a message that connects effectively to their target audiences. A customer data platform simplifies intricate information by processing it in real-time from first, second, and third-party sources.
The capability enables teams to provide tailored experiences across numerous touchpoints, including email campaigns, website interactions, and social media engagements. Businesses can use data analytics insights to develop customised marketing messages, promote adequate products, and create content for customer preferences. CDPs enable marketers to respond to real-time customer interactions, ensuring that offers and suggestions are relevant and engaging.
Improved customer interactions
A real-time customer data platform enhances customer service by delivering a comprehensive picture of each customer’s interactions with the business. Customer support teams can react to requests more efficiently with a consolidated view of information, which encloses everything from purchase histories to recent chat or call discussions. Clean data eliminates inconsistencies and redundancies, enabling agents to respond precisely and avoid repetitive requests for the same information. For instance, access to up-to-date customer profiles allows support agents to offer tailored solutions and proactive assistance. By streamlining interactions, a CDP ensures that every customer engagement is impactful.
Better prediction through AI
Using clean data through predictive analytics empowers businesses to anticipate customer needs and behaviours precisely. The process relies on four key components:
Data collection: This accumulates information from different sources, like customer discussions, purchase history, and demographic details.
Data cleaning: This would ensure the acquired data is accurate, complete, and error-free. It then becomes the foundation for reliable analysis.
Data modeling: It employs predictive techniques like regression analysis, decision trees, and neural network modeling for discovering trends and predicting future behaviours.
Data validation: It ensures the correctness and reliability of predictive models to produce actionable and trustworthy insights.
Data transparency
Clean and transparent data is fundamental to an exceptional customer experience. It empowers businesses to accurately comprehend their customers’ behaviours, preferences, and needs. Transparency is paramount throughout the data lifecycle. This includes clear and concise communication about what data is being collected, obtaining explicit consent from individuals, and adhering to strict data privacy regulations regarding data storage and processing. data should only be used for the specific purposes for which it was collected, ensuring that customer trust is maintained. By using accurate and transparently gathered data, businesses can create highly personalised experiences, like targeted marketing campaigns, customised product suggestions, and tailored communication. The focus on data integrity and transparency fosters stronger customer relationships and cultivates long-term loyalty.
Best practices for maintaining clean customer data
Maintaining clean data is essential, but it’s not easy given the rapidly growing data volumes and complexity.
Here are some best practices to help you effectively manage clean, reliable data:
Regular data audits
Conducting routine data quality checks reduces the risk of discrepancies and fortifies a culture of high-quality data across the organisation. This also eliminates the need for your team to clean the data every time they interact with a dataset.
Data entry protocols
Establishing data entry protocols minimises errors from the start. Use standardised data field formats, validate real-time inputs, and implement automation tools to reduce manual entry mistakes. The ensure consistency across data touchpoints and create a solid foundation for clean data management.
Employee training
Educating all team members who interact with customer data is vital to maintaining clean and accurate data. Start by establishing and communicating the organisation’s core data hygiene values. Conduct regular training sessions to underline the importance of precise data handling and its impact on business outcomes. Provide step-by-step guidelines for data management processes, ensuring new employees can quickly learn and adhere to best practices. Employees should be encouraged to keep data clean and maintain data accuracy.
Key trends for customer data platforms
Customer data platforms are developing at an unprecedented pace. From AI-powered personalisation to composable CDP, these key trends are driving the future of customer engagement.
Composable CDP: Businesses are shifting to the composable CDP for greater control, flexibility, and cost efficiency. With modular architecture, it integrates seamlessly with existing data systems, extending their lifespan, enhancing functionality, and enabling instant data activation without delays and disruptions.
Real-time data processing: CDPs enable businesses to respond instantly, using real-time insights to implement strategies like Next Best Action. This ensures that every touchpoint is an opportunity to deepen the relationship and drive conversion.
Hyper-personalisation: Businesses can predict customer requirements by analysing behaviour across multiple channels. CDPs use AI-powered predictive and generative analytics to provide smooth, personalised interactions. The enhanced data orchestration improves hyper-personalisation and maximises the impact of every customer engagement.
Multi-channel integrations: Marketers frequently deal with fragmented customer interactions across channels. A CDP consolidates these interactions, whether by WhatsApp, email, or direct conversation, into a 360-degree view. This enables businesses to provide resonant, tailored messaging that addresses individual requirements.
Conclusion
Businesses often struggle to harness customer data scattered across multiple channels and silos. A customer data platform transforms these obstacles into opportunities by integrating clean data and unleashing the full potential of the marketing technology stack. Businesses can use a CDP to create, unify, and activate data in real-time, empowering organisations to deliver personalised, multichannel experiences and customer journeys. From predictive analytics, easy integrations with advertising, mobile applications, chatbots, and marketing automation to improve customer service interactions, the benefits of clean data are far-reaching, making it an indispensable tool for increasing customer engagement.
Ready to kickstart your CDP implementation? Schedule your customer data platform demo now for actionable insights on selecting the right platform and maximising ROI.
