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Quantzig’s Customer Lifetime Value Helps a Leading Retail Industry Client Improve Customer Loyalty

The client: Retail industry client

Area of engagement: Customer lifetime value

The retail industry accounts for 31% of the world’s GDP and employs millions of people throughout the globe. Supermarkets and hypermarkets account for 35% of the retail sector’s direct sales, with China and USA at the forefront. Since e-commerce is another sector that is exhibiting a rapid growth rate, it has a direct influence on the retail industry, which is expected to rise to US$ 28 trillion by 2019. To sustain themselves amidst the rising competition in this market space, leading retailers are focusing on understanding the art and science of catering to the customers.

Moreover, the changing retail trends have also impacted the growth of this industry. The exponential growth of technologies has brought about several transformative possibilities, both in the store and beyond. As a growing number of customers seek new products and experiences, retailers have been forced to find new ways to delight their customers and improve loyalty. Now, let’s take a look at some of the major trends and their potential impact on the retail industry:

  • Deflation: Inflation remains dormant, despite the unusually aggressive monetary policies in leading developed countries. The failure to revive inflation can be attributed to several factors, including the temporary effect of declining commodity prices and weak demand. However, inflation is likely to remain low in most of the developed economies. For retailers, this means a reduction in pricing power, price competition, and the necessity of explicitly differentiating themselves from competitors to regain pricing power.
  • The backlash against globalization: In leading countries, there is a growing aversion to free cross-border migration and trade. QZ- Request free proposalThis is a primary concern for firms operating in the retail industry space since retailers benefited from expansions in trade that helped them reduce prices and improve customer spending power.    

The Business Challenge

The retail industry is an experiential motley that is currently going through a robust transformation, by employing new technologies, exploring new store formats, and revamping business strategies to creating personal experiences.

The client, a leading player in the retail industry with several business units spread globally, wanted to perform an in-depth customer lifetime value analysis to segment the customers based on their profitability. The client also wanted to gain a detailed understanding of what drives high customer lifetime value. Additionally, the retailer also wanted to develop personalized strategies to improve customer loyalty and brand recognition.

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The Solution and the Business Impact:

The customer lifetime value study offered actionable insights that helped the client in identifying and analyzing customer behavior over a period of time.  The solution offered by our team of experts also helped them in predicting future customer behavior to improve loyalty. Moreover, our customer lifetime value solution assisted the client in predicting churn and enabled the design of new programs to reduce customer attrition levels.

Customer Lifetime Value Insights:

Since retaining and organically growing customers is a far more cost-effective task than acquiring new customers, leading organizations have started realizing the importance of calculating customer lifetime value. Customer lifetime value also considers the financial value of each customer and helps in building strategic customer relationships. It also helps in developing optimal strategies for customer engagement, which, in turn, aids retailers in delivering tailored services to profitable customers and retain them for more extended periods.


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Retail Revolution and the Power of AI

The use of AI and machine learning in the retail industry is growing at an exponential rate. Retailers have been able to see the results delivered by artificial intelligence systems instantly. AI is expected to become pervasive across customer journeys, merchandising, marketing, and supply networks as it can provide detailed insights to optimize the retail operations. Big data and machine learning have been successfully used by several retailers to achieve substantial increase in their operating margins. Such technologies can enable retailers to deliver personalizedFree demo experiences to the customer in order to increase loyalty and spending. There are various use cases for AI in retail industry that can change the way this sector operates.

Uses of AI in retail industry

Sales and CRM applications

In 2010, Japan’s SoftBank telecom developed a humanoid robot, Pepper, which can interact with customers and perceive human emotions. The robot was used as a customer service greeter and representative in over 140 stores. The company later reported up to 70% increase in footfall in multiple stores. Additionally, an American company developed AI-powered sales-assistant software, Conversica, which identifies and converses with internet leads to enhance sales. The customized sales assistant software is also used for cross-selling and re-engaging existing leads.

Customer Recommendation

Product recommendation tools are adding significant revenues to e-commerce businesses. IBM Watson is one of the most advanced AI systems that exhibits order management and customer engagement capabilities. IBM Watson uses personality insights taking into account users personal information, browsing history, past transaction data, and other dynamic data including weather, location, time, and items in cart to develop its recommendation engine. By calculating respective personality profile, IBM Watson can accurately suggest brands and products users are most likely to buy. For instance, North Face has used IBM Watson’s cognitive computing technology to suggest jackets for the customers based on variables like gender and location.

Manufacturing

Long after automation revolutionized the manufacturing industry, AI is set to be next wave of change in this sector. AI can help companies keep inventories lean and reduce the cost. For instance, GE’s Brilliant Manufacturing software enables manufacturers to predict, adapt, and react more effectively by incorporating SCADA, MES, and analytics. It empowers decision makers with deep operational intelligence and real-time visibility to reduce unplanned downtime and inventory.

Logistics and delivery

Domino’s Robotic Unit (DRU) has developed a prototype delivery robot that can keep food and drinks at an appropriate temperature. Its sensor also helps the device to navigate the best travel path for delivery. Alongside DRU, Amazon’s Prime Air is expected to be the future of delivery systems. Such drones can deliver parcels up to five pounds in weight in less than 30 minutes. The autonomous delivery of goods can significantly improve the performance of the retail industry and increase customer satisfaction.

Payment services

With a view to reign in the retail industry, Amazon introduced its brick-and-mortar store, Amazon Go which enables check-out free technology that allows customers to shop and leave. Their check-out free shopping experience uses the same kind of AI technology used in autonomous cars including computer vision, sensor fusion, and deep learning. It automatically detects when the products are taken from or returned to shelf keeping track of it in a virtual cart. When customers are done with their shopping, they simply check out of the store, and Amazon will deduct the amount from their Amazon account. With regards to payment services, AI is also showing its potential in payments fraud. Payment fraud is a matter of concern in the e-commerce space, where fraudsters are using stolen accounts to make purchases. AI technologies can study thousands of purchase patterns to differentiate between payment made by the genuine user and a fraudster.

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Customer Analytics and Business Intelligence Solutions – Understanding the Dynamic Consumer Demographics in the Retail Industry

Quantzig’s recent study on customer analytics and business intelligence solutions for a global retail leader guarantees 12% increase in sales including many other benefits.

How does customer analytics work?

Customer analytics process includes techniques such as data visualization, information management, and predictive analytics to offer insights on the market. The solutions offered through these market analytics helps revolutionize the approach organizations take to identify customer needs and behavior. These solutions help large retail companies to compare products, prices, brand, and competitive offerings to gain a deeper understanding of customers’ buying habits and lifestyle preferences. Industries such as retail and CPG, banking, insurance, and telecommunications benefit the most from these business solutions.

Predictive analytics is trending in the business intelligence solutions market, helping enterprises to draw accurate predictions about the future consumer buying preferences. Various models used in predictive analysis are primarily designed to serve existing customers better, prevent attrition, and build stronger relationships. These business solutions collate historical and current data to offer insights on risk assessment and alternative strategic resolutions. Organizations are benefiting from these models and are extensively using them to prepare, blend, and analyze all customer data from various channels and systems.

Exploring the future growth opportunities

Market analytics experts at Quantzig help businesses to understand the dynamic demands of different customer demographics based on the in-store customer experience. Tackling issues such as stagnant revenues and declining customer satisfaction levels can play an important role in determining the growth or decline of any organization. To overcome these roadblocks in businesses, retailers need to analyze real-time, the in-store behavior of customers based on their demographics, purchasing history, marketing promotions,  response time, and dwell time data to optimize their experience, shopper traffic, and sales.
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Evaluating purchasing power and store design

Customer analytics engagements help organizations offer better customer service by studying purchasing behavior and evaluating how the store format impacts product sale. The identification of potential areas of improvement for store design will significantly increase consumer attraction and sales. The development of various business intelligence solutions that analyze and target customers based on in-store activity improves customer footfall and optimizes offers and discounts to boost sales.

Outcomes, insights, and solutions offered to a leading retailer

With hands-on expertise in customer analytics, Quantzig provided objective elucidations that resolved the issues pertaining to the changing consumer demographics and helped a leading retail company to maximize revenue and sales. Some of the solutions offered are as follows:

  • Insights on product location, sales, and associated customer behavior, such as footfall, the length of stay, visit frequency or loyalty, and purchase volume thereby, increasing sales volume by almost 12%
  • Develop a complete picture of user interactions based on demographic and purchase behavior to accurately identify customer needs and interests. This strategy improved consumer footfalls by around 7%
  • Identify product assortment issues in terms of average transaction volume or amount to improve space productivity
  • Improve cross-selling and up-selling based on targeted offers by almost 10%
  • Recognize the departments that the customers visit and gain insights into customer flow analysis, store penetration, and the time spent in each department
  • Provide sales forecasts at category and product level for better business planning
  • Improve product bundles and price modifications based on customer feedback and product reviews

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The complete case study on customer analytics and business intelligence solutions for a leading retail chain is now available on the website.

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