Customer Strategy

🎓 Definition

A customer strategy refers to a Retailer's plan of action aimed at attracting, retaining, and growing its customer base.

It includes identifying:

• Target customer segments
• Understanding their needs and preferences
• Developing offerings and experiences that meet those needs.

A well-designed customer strategy takes into account the New customer onboarding journey, marketing and sales tactics, customer service, and support. The goal of a customer strategy is to create a positive customer experience and build customer loyalty, leading to increased revenue and long-term success for the Retailer.

🧪 Example of Customer Strategy

A Retailer can identify customer segments by analyzing the specific day and hour customers visit their stores.

For example, there could be 3 customer segments:

1. After-work Shoppers: These customers visit the stores mostly on weekdays between 5:30 PM and 8:00 PM, seeking convenient shopping experiences after finishing their workday. The Retailer can ensure that their stores remain well-stocked during the evenings, and they might introduce loyalty programs with after-work discounts to encourage repeat visits.
2. Weekend Shoppers: This segment consists of enthusiastic shoppers who visit on Saturdays and Sundays between 11:00 AM and 3:00 PM, making their weekend outings to explore the latest trends and styles. To cater to this segment the Retailer can host special activities on weekends, showcasing the latest products or free samplings.
3. Early-Bird Shoppers: These customers prefer visiting the stores on weekday mornings between 9:00 AM and 11:00 AM. They are often looking for a calm and less crowded shopping environment. The Retailer can tailor their strategy to provide early bird discounts or exclusive promotions for new products to attract customers during the quieter hours.

An example of how a Retailer can understand customer needs and preferences can be:

• A Retailer analyzes its Wellness category and finds out that the sales are growing strongly, which could indicate shoppers are more health conscious. This could lead Retailer to create a dedicated "Health Corner" featuring organic, gluten-free, and health-oriented products.

❓What is Customer Strategy used for

Effective Customers segmentation

Customer Segmentation allows Retailers to attract the “best customer” as they simultaneously adapt their strategies according to their needs. Retailers need to examine Customers' Lifetime Value. This is why a customer who spends a little but frequently possesses a higher value to a company than a client who spends more but shops less often.

"Research from the Center for Retail Management at Northwestern University shows that 15% of a company’s loyal customers are responsible for 60% of its total sales."

Increase in retention rates

Customer retention plays a significant role in Customer Strategy. This refers back to the consumer’s lifespan. The more time is spent on a customer and the longer attention is paid to them, the more they will listen to Retailer suggestions and purchase the recommended products.

Creating a Unique Experience

Consumers have numerous options for purchasing goods, so creating a unique, high-quality shopping experience can be just as important for getting customers to come back as the products themselves. This is an area in which Retailers can have an advantage over larger competitors. Because small Retails have fewer customers than large ones, they can spend more time giving personalized assistance and creating strong relationships.

How can a retailer measure the effectiveness of their customer strategy over time?

Measuring the effectiveness of a customer strategy requires tracking specific key performance indicators (KPIs) that align with the retailer's objectives. One common KPI is Customer Lifetime Value (CLV), which helps retailers understand the long-term value of their customers. By analyzing CLV, retailers can determine if their strategies are attracting and retaining high-value customers. Additionally, monitoring customer retention rates, customer satisfaction scores, and sales growth can provide valuable insights into the success of the customer strategy. Regularly reviewing these metrics and comparing them over time allows retailers to identify trends, areas for improvement, and make data-driven decisions to optimize their customer strategy.

What challenges might retailers face when implementing a customer strategy, and how can they overcome them?

Implementing a customer strategy can come with various challenges, such as accurately identifying target customer segments, adapting to changing consumer preferences, and integrating the strategy across different channels and touchpoints. Another common challenge is ensuring consistent and personalized customer experiences across all interactions. To overcome these challenges, retailers should invest in market research and data analytics to gain deeper insights into their customers' needs and behavior. Collaborating cross-functionally within the organization can also help align different departments and ensure a cohesive approach to customer strategy implementation. Embracing agile methodologies and being open to iterative testing and optimization can enable retailers to adapt quickly to market changes and continuously enhance their customer strategy.

How can technology and data analytics support the development and execution of a customer strategy?

Technology and data analytics play a pivotal role in shaping a retailer's customer strategy by providing actionable insights, enhancing customer segmentation, and personalizing the shopping experience. Advanced analytics tools can analyze large volumes of customer data to identify patterns, trends, and preferences, enabling retailers to make informed decisions and tailor their offerings to meet customer needs effectively. Customer Intelligence systems can help retailers track customer interactions, manage relationships, and deliver personalized marketing messages and promotions. Additionally, leveraging artificial intelligence (AI) and machine learning algorithms can automate and optimize various aspects of the customer strategy, from product recommendations to pricing strategies, ultimately driving customer engagement, loyalty, and business growth.