CDP are replacing CRM's in the customer-centric world

‍…and the first thing brands should know is that CDP is not the same as CRM

‍CRM (Customer relationship management) organises and manages Customer-facing interactions with your team

‍Vs

‍CDP (Customer data platform) collects data about a customer's behaviour in interacting with your product or service

And today, we’ll understand more about how ‍Marketers brace for reduced Customer Loyalty.

Basically, CDPs provide a big picture of how all customers and platforms interact with your brand, while CRMs note interactions between a specific account and your brand.

‍CRM manages interactions with existing, past, and potential clients. It uses data of clients history with a company to improve business relationships, specifically focusing on client retention and driving sales growth.

‍CDP allows transforming raw into actionable data to deliver the best possible holistic Customer Experience by using their preferred communication channels and tactics that work.

‍Building customer loyalty and trust with a CDP

What is the Difference Between Customer Loyalty and Customer Retention?

While customer loyalty and customer retention are closely related, they refer to different concepts in business, particularly for Direct-to-Consumer (D2C) brands:

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• Customer Retention: This refers to a brand's ability to keep customers over a specific period of time. It's typically measured by the rate at which customers continue to purchase from the brand, renew subscriptions, or remain engaged with the brand's products and services. Customer retention is often focused on reducing churn, which is the loss of customers over time. Metrics like customer retention rate, churn rate, or repeat purchase rate are used to track it.

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• Customer Loyalty: This concept goes beyond just retaining customers. It describes a customer's deep-rooted emotional connection to a brand, often leading to repeat purchases, advocacy, and a willingness to try new products from the same brand. Loyal customers are less likely to switch to competitors and are more likely to recommend the brand to others. Customer loyalty can be measured by metrics like Net Promoter Score (NPS), customer satisfaction, and customer lifetime value.

Why is Customer Loyalty So Important for Brands?

• Reduced Marketing Costs: Loyal customers are more likely to make repeat purchases, reducing the need for costly customer acquisition campaigns. They might also recommend the brand to others, acting as informal brand ambassadors, thus generating word-of-mouth referrals.
• Higher Customer Lifetime Value (CLV): Loyal customers tend to buy more frequently and are more willing to try new products. This increases their overall lifetime value to the brand, which can lead to greater profitability.
• Resilience to Competition: In a crowded market, loyal customers are less likely to switch to competitors, providing a more stable customer base. This can be especially crucial for D2C brands, which often face fierce competition from both established brands and new entrants.
• Valuable Feedback and Co-Creation: Loyal customers are more likely to provide constructive feedback, helping D2C brands improve their products and services. They might also engage in co-creation, where they suggest new product ideas or participate in beta tests.
• Emotional Connection and Brand Advocacy: Loyalty creates a strong emotional bond between the customer and the brand. Loyal customers become brand advocates, promoting the brand on social media, writing positive reviews, and influencing others to try the brand's products.

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Benefits of CDP

1. Implementing customer segmentation
2. Employing automation processes
3. Collecting, managing, and activating customer data
4. Improving recommendations aka personalisation
5. Increasing customer loyalty

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How does CDP do this?

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1. Data Fragmentation:
   
   Many businesses collect customer data from various sources, such as websites, mobile apps, social media, and offline interactions. This data is often scattered across different systems and databases, leading to data fragmentation. A CDP centralises and integrates customer data from multiple sources, creating a unified and comprehensive view of each customer.
   
   According to a survey by Forrester, 40% of businesses reported that their customer data is scattered across multiple databases and systems, making it difficult to get a complete view of their customers.
2. Data Silos:
   
   In large organisations, different departments or teams may have their own databases and systems, resulting in data silos. These silos inhibit data sharing and collaboration, making it challenging to gain a holistic view of the customer. A CDP breaks down these data silos, allowing data to be shared and accessed across the organisation.
3. Real-time Data Access:
   
   Traditional data management systems may not provide real-time access to customer data, leading to delays in decision-making and marketing efforts. A CDP offers real-time data processing and updates, enabling businesses to respond quickly to customer interactions and deliver timely and relevant messages.
4. Customer Segmentation and Personalisation:
   
   Analysing customer data and creating meaningful customer segments manually can be time-consuming and complex. A CDP automates the process of customer segmentation based on various attributes and behaviours, allowing businesses to deliver personalised experiences and targeted marketing campaigns efficiently.
   
   According to a survey by MemSQL, 71% of businesses consider real-time data access to be a top priority for their data strategy.
5. Data Privacy and Compliance:
   
   With increasing data privacy regulations (e.g., GDPR, CCPA), businesses need to ensure that customer data is handled responsibly and securely. A CDP provides robust data privacy features, allowing businesses to manage customer consent, enforce data access controls, and comply with relevant data protection laws.
6. Multi-channel Orchestration:
   
   Customers interact with businesses through multiple channels, such as websites, mobile apps, email, social media, and offline stores. Coordinating marketing efforts and customer communications across these channels can be challenging. A CDP enables multi-channel orchestration, ensuring consistent and personalised messaging across all touchpoints.
7. Customer Journey Optimisation: Understanding the customer journey and identifying pain points or areas for improvement can be complex without a comprehensive view of customer interactions. A CDP helps businesses analyse the customer journey, identify key touchpoints, and optimise the customer experience to increase customer satisfaction and loyalty.
8. Data Analytics and Insights:
   
   Extracting valuable insights from large volumes of customer data can be overwhelming. A CDP comes with built-in analytics capabilities and reporting tools, allowing businesses to derive actionable insights and make data-driven decisions to improve marketing strategies and overall business performance.

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• CRMs are mainly designed for customer-facing roles, like salespeople and customer success representatives
  
  Whereas CDPs are complex and help marketing, products, or service, not just sales.

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• CRM manages only registered customer data and uses predefined first-party data
  
  Whereas CDP handles them all as the table suggests.

How a CDP Helps Execute Highly Relevant Customer Loyalty Campaigns

‍360-degree Customer Profiling

Utilise the potential of zero, first, and third-party data to establish a comprehensive customer profile, gaining genuine insights into their requirements.

‍Unified database‍

Combine structured and unstructured data gathered from various sources into a cohesive and enduring customer database, using a single customer identifier for a unified view.

‍Actionable data‍

Leverage the collected data to make informed decisions and enhance your brand's marketing processes.

‍Packaged System‍

Implement a user-friendly set of features within a marketer-managed system that enables effective communication, segmentation, and optimization of the customer journey using customer data.

‍Predictive Analytics‍

Discover the best course of action with a consumer to meet their requirements, enhance engagement, and maximise their lifetime value by predicting their likelihood to make a purchase or the risk of churning.

Data-driven offer personalisation‍

Examine the behavioural and transactional activity patterns of your customers and provide personalised 1-to-1 product recommendations for cross-selling and upselling opportunities.

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How does CDP help in supply chain optimisation

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To find the optimum next move with a client and satisfy their needs while increasing engagement and lifetime value, you can use predictive analytics and data-driven strategies.

Here's a step-by-step approach:

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1. Data Collection:
   
   Gather relevant data about the client, including their past interactions, purchase history, engagement with marketing campaigns, customer support inquiries, and any other relevant touchpoints.
   
   This data can be obtained from various sources, such as CRM systems, transaction records, website analytics, and customer surveys.
2. Data Analysis:
   
   Utilise predictive analytics and machine learning algorithms to analyse the collected data. Predictive models can be used to forecast the likelihood of a client making a purchase (purchase probability) or the risk of churning (churn probability).
   
   These models can identify patterns and trends in the data, allowing you to understand customer behaviour better.
3. Customer Segmentation:
   
   Divide your client base into distinct segments based on their characteristics and behaviour.
   
   For example, segment clients based on their purchase frequency, average spending, or engagement levels. This segmentation will help tailor marketing strategies and offers to each group's specific needs and preferences.
4. Personalisation:
   
   Use the predictive models and customer segmentation to deliver personalised experiences and offers to each client. Tailor marketing messages, promotions, and product recommendations to align with their predicted likelihood to buy or risk of churning.
   
   Personalisation enhances engagement and increases the chances of satisfying their needs.
5. Engagement Strategies:
   
   Implement targeted engagement strategies for clients at different stages of the customer journey. For clients with a high probability of purchasing, focus on conversion-oriented campaigns and offers.
   
   For clients at risk of churning, deploy retention-focused initiatives, such as personalised incentives, exclusive offers, or customer support outreach.
6. Customer Journey Optimisation:
   
   Continuously monitor and analyse the client's journey across various touchpoints. Identify areas where clients may be experiencing friction or disengagement.
   
   Optimise the customer journey by removing obstacles, enhancing user experience, and providing seamless interactions to increase satisfaction and lifetime value.
7. Feedback and Iteration:
   
   Collect feedback from clients to understand their experience and gather insights for improvement.
   
   Use this feedback to refine your predictive models, segmentation, and engagement strategies iteratively.
8. Measure and Evaluate:
   
   Regularly measure the impact of your strategies on customer satisfaction, engagement, and lifetime value. Monitor key performance indicators (KPIs) such as customer retention rate, repeat purchase rate, and customer lifetime value.
   
   Analyse the results to determine the effectiveness of your decisions and adjust your approach accordingly.

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By leveraging predictive analytics and data-driven strategies, you can proactively address client needs, increase engagement, and enhance their lifetime value, leading to more satisfied and loyal customers.

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Influence of CDP on Supply Chain Management

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A Customer Data Platform (CDP) can have a significant influence on the supply chain of Direct-to-Consumer (D2C) e-commerce companies in India, because it provide the following:

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1. Enhanced Customer Insights:
   
   A CDP centralises and integrates customer data from various sources, including online and offline interactions. This comprehensive view of customer behaviour, preferences, and purchase history allows D2C e-commerce companies to better understand their customers and anticipate demand patterns.
   
   By analysing this data, they can make more informed decisions regarding inventory management, production, and order fulfilment, leading to improved supply chain efficiency.
2. Demand Forecasting and Inventory Management:
   
   With access to real-time and historical customer data, a CDP can help D2C e-commerce companies accurately forecast demand.
   
   This allows them to optimise inventory levels and reduce the risk of overstocking or stockouts. By aligning their inventory with actual customer demand, companies can lower carrying costs, minimise wastage, and improve overall supply chain performance.
3. Personalised Product Recommendations:
   
   A CDP enables D2C e-commerce companies to deliver personalised product recommendations to customers based on their preferences and previous purchases.
   
   By leveraging this capability, companies can drive cross-selling and upselling opportunities, leading to increased order values and customer retention.
4. Seamless Customer Experience:
   
   A CDP ensures that customer data is accessible across various touchpoints, allowing for a seamless and consistent customer experience.
   
   For instance, if a customer interacts with the company through multiple channels (e.g., website, mobile app, social media), the CDP can provide a unified view of that customer's journey.
   
   This ensures that the supply chain processes, such as order processing and delivery, are aligned with the customer's preferences and expectations.
5. Personalised Offers and Promotions:
   
   Using customer data from the CDP, D2C e-commerce companies can create targeted marketing campaigns with personalised offers and promotions.
   
   By tailoring discounts or promotions to specific customer segments, companies can incentivize repeat purchases and encourage customer loyalty.
6. Customer Segmentation:
   
   A CDP allows D2C e-commerce companies to segment their customer base based on various attributes such as demographics, purchase behaviour, and engagement levels.
   
   This segmentation enables companies to design supply chain strategies that cater to the unique needs and preferences of different customer segments, optimising their supply chain resources and improving customer satisfaction.
7. Post-Purchase Engagement and Support:
   
   After the purchase is made, a CDP can help facilitate post-purchase engagement and customer support.
   
   By analysing post-purchase data, such as order tracking and customer feedback, companies can proactively address any issues and ensure a positive post-purchase experience. This can lead to increased customer satisfaction, repeat business, and positive word-of-mouth.

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In conclusion, a Customer Data Platform can greatly impact the supply chain of D2C e-commerce companies in India by providing valuable customer insights, enabling demand forecasting, improving inventory management, enhancing customer experience, and optimising marketing strategies for cross-selling and upselling.

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To Wrap it Up

• 73% of marketers believe a Customer Data Platform will be critical to their Customer Experience efforts
• 44% of organisations found CDP helping in driving Customer loyalty (Forbes)
• In the last 5 years, the overall volume of events that customers have tracked through Customer Data Platform increased by 60%

‍Meaning, investing in CDP is investing in customer experience. 

Pragma’s products are specifically meant to boost profits for D2C brand. So if you’re working towards building your sales funnel, connect with the experts at Pragma and learn how you can win customer loyalty.

FAQs

1. What is a Customer Data Platform (CDP) and how can it improve customer retention?

A Customer Data Platform (CDP) is a software solution that aggregates and organizes customer data from various sources into a unified, accessible platform. It provides a comprehensive view of each customer, enabling marketers to understand customer behaviors and preferences better. CDPs can improve customer retention by allowing marketers to deliver personalized experiences, targeted communications, and timely offers, which enhance customer satisfaction and loyalty. By using a CDP, businesses can better predict churn and take proactive measures to retain customers.

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2. How to use CDP for loyalty marketing?

CDP for loyalty marketing proves to be a valuable tool as it helps in providing insights into customer behaviors, preferences, and purchase history. With this information, marketers can create highly personalized loyalty programs, tailor reward structures, and design targeted campaigns that resonate with individual customers. CDPs allow for segmentation based on customer activity, enabling brands to identify and target their most loyal customers with specific offers or exclusive content. By leveraging a CDP, marketers can build stronger relationships with customers and encourage repeat business, thus enhancing customer loyalty.

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3. What are some common challenges in using a CDP for customer retention?

Some common challenges in using a CDP for customer retention include:

• Data Integration: Integrating data from various sources into a single platform can be complex. Ensuring data accuracy and consistency is critical.
• Data Privacy and Compliance: CDPs must comply with data protection regulations, which require careful handling of customer data to maintain privacy and trust.
• Data Analysis and Actionability: Merely having customer data is not enough. The challenge is in analyzing the data and taking meaningful actions to improve retention.
• Organizational Alignment: Teams across the organization must align on how to use CDP insights to drive retention strategies effectively.

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4. What metrics should be tracked when using a CDP to assess customer loyalty?

Key metrics to track when using a CDP to assess customer loyalty include:

• Repeat Purchase Rate: Measures how often customers make additional purchases over time.
• Customer Lifetime Value (CLV): The estimated revenue a customer will generate throughout their relationship with the brand.
• Net Promoter Score (NPS): Assesses customer loyalty by asking how likely customers are to recommend the brand to others.
• Churn Rate: Tracks the rate at which customers stop doing business with the brand.
• Customer Engagement: Measures interactions with the brand, such as website visits, email opens, and social media activity.

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5. How can a CDP help brands adapt to a trend of reduced customer loyalty?

A CDP can help brands adapt to reduced customer loyalty by providing a detailed understanding of customer behavior and preferences. This allows brands to:

• Identify At-Risk Customers: By analyzing customer engagement and purchase patterns, brands can spot signs of potential churn and take action to prevent it.
• Deliver Personalized Experiences: With a comprehensive view of customers, brands can create tailored experiences that enhance loyalty and retention.
• Segment and Target Effectively: CDPs allow for granular segmentation, enabling brands to target specific customer groups with relevant content and offers.
• Develop Effective Loyalty Programs: By understanding what motivates customers, brands can design loyalty programs that encourage repeat business and long-term relationships.
• Measure and Optimize Campaigns: CDPs provide real-time data and insights, allowing marketers to track the effectiveness of loyalty campaigns and make adjustments as needed.

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