Tackle customer strategy through data: 7 key steps to drive growth

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In APAC’s competitive landscape, customer analytics and customer centricity are vital for driving growth and enhancing memorable experiences. Yet, many brands limit analytics to marketing or email campaigns, missing broader opportunities.

By leveraging customer lifetime value (LTV) and focusing on data-driven strategies, brands can move beyond narrow metrics to make impactful decisions. This paper presents a step-by-step approach to embedding analytics into business strategy, unlocking sustainable growth through actionable insights and optimized customer experiences.

1. Dive into your customer data…

…to begin your customer understanding. This is the first step to building your customer analytics maturity and allows you to start making sense of who your customers are – e.g., where and how they shop, what makes them loyal, or not.  For example, Pet Lovers Centre in Singapore uses AI-powered agents to manage high volumes of customer queries, providing quick resolutions and analyzing customer feedback to identify emerging trends [1].  This is a use case where data maturity and governance are both quite advanced.

To start this journey, brands can build an initial actionable segmentation using existing known attributes to differentiate between customer segments. A simple and effective method is RFM analysis (Recency, Frequency, Monetary value), which helps identify distinct groups based on purchasing behavior. This allows brands to tailor marketing strategies to engage specific segments, enhancing customer relationships and driving conversions.

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2. Identify and prioritize your use cases…

…to drive the strategy forward. Involve vertical experts and cross-functional teams to consider use cases along the customer journey from awareness to acquisition, retention to advocacy.  Analyzing this journey allows you to design a program to implement a customer-centric approach.  OCBC Bank in Singapore utilizes its AI-powered chatbot, Emma, to enhance customer experience by providing personalized financial services. Emma offers tailored financial planning based on individual customer profiles and their current journey Emma suggests suitable investment opportunities by analyzing market trends and customer risk profiles and provides 24/7 support for banking queries. These AI-driven services lead to improved customer satisfaction and loyalty through timely and relevant financial advice with each customer in mind [1].

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3. Design customer strategies…

…aligned to your brand promise and the opportunities identified through your data. Ask yourself, ‘what type of customer should I be acquiring?’ ‘What brand experience should I give customers throughout their journey?’ ‘What perception do I want to leave them with?’

An Ekimetrics’s luxury client in Hong Kong and Macau sought to enhance CRM analytics to better identify and engage high-value customers. They faced challenges such as limited analytics resources and inefficient manual processes. By implementing segment analysis, a boutique scorecard, and product path analysis, Ekimetrics was able to help automate performance monitoring and identify key drivers for customer transitions into high-value segments. Now, the client can customize its customer strategy based on the identified high-value customer segments and improve the efficiency on engaging customers.

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4. Set the data foundations…

…to facilitate the deployment of analytics capabilities and strategic use cases. Think about data capture, structure, and governance; building up these capabilities in a way which supports your long-term vision is essential. To fast-track this process, make use of tech accelerators. One example is how FedEx APAC modernized its customer lifecycle strategy by leveraging data to engage customers from initial acquisition to long-term retention [2].  FedEx created automated and personalized customer lifecycle campaigns for different segments in 14 APAC markets, boosting customer growth and revenue.  This approach cut campaign setup time by 60-80%, enabling the team to focus on strategic priorities.

5. Advance your customer intelligence…

…to enable optimized and anticipatory outreach. Long-term thinking to build on the potential of your client base is essential to the deployment of next-best experience. For example, propensity and behavioral scoring models can be used to understand and predict a customer’s likelihood of buying a product, returning a product, leaving to competition, basket size, and more.  Shopee, a leading e-commerce platform in Southeast Asia, uses AI to predict customer churn.  By analyzing user engagement metrics, purchase frequency, and customer service interactions, Shopee can identify customers who are likely to stop using the platform and implement retention strategies [3].

6. Industrialize your approach…

…with live and dynamic model outputs. By moving to always-on scoring and optimization, with data visualization to bring customer data to life, you can both automate and animate customer analytics. With the sheer quantity of data in play, advanced analytics and machine learning can support automation. Grab and GoJek have pioneered the super-app model, integrating various services into a single platform to meet customer demands for convenience. Users enjoy access to multiple services through a single app, leading to increased usage and loyalty. Both Grab and Gojek use AI and machine learning to analyze user behavior and preferences. This allows them to provide personalized recommendations for services such as ride-hailing, food delivery, and financial products. For example, Grab’s AI algorithms suggest restaurants based on a user’s past orders and browsing history. [4]

7. Democratize insights

It’s essential to onboard all teams, from the concept of customer centricity to sharing the insights that are relevant to winning. Gain their trust through transparency in how the models are built and the value of the resulting actionable analysis in driving high-level strategies. Dashboards will help to standardize and make accessible the basis for decisions from finance, supply chain, marketing, and analytics. Ekimetrics helped a leader in luxury beauty and fragrance in Hong Kong and Macao enhance customer analytics by developing brand-specific segmentation models, creating more than 20 Tableau dashboards for CRM reporting, and conducting training to upskill teams within 9 brands. These efforts enabled data-driven decisions, improved reporting by 40%, and ongoing adaptability, supporting the client for over 8 years.

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Discover how to unlock the full potential of customer analytics and drive growth. Explore our expertise here: Customer Analytic Solutions.

Sources :

1.       https://www.ocbc.com/group/media/release/2017/home-and-renovation-loan-specialist-ai-emma.page

2.       https://marketech-apac.com/from-acquisition-to-retention-how-fedex-modernised-its-customer-lifecycle-strategy-to-boost-engagement/

3.       https://e27.co/how-shopee-builds-its-marketing-strategy-to-suit-user-behaviour-in-the-time-of-crisis-20200820/

4.       https://www.cxnetwork.com/cx-experience/articles/6-customer-behaviors-influencing-cx-strategy-in-apac