Data-Driven Case Study : Barnes & Noble

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Barnes & Noble's beginnings can be traced to 1873


Today's post is inspired by an article I read about the recent resurgence of Barnes & Noble, the iconic American bookstore chain.

As a bookworm, I found the story especially appealing. Back in secondary school, I used to imagine working in a bookstore or a library during summer vacation, surrounded by shelves of book.

It seemed like a dream job.

Barnes & Noble originally set itself apart with vast, well-stocked stores and an enormous selection of titles. This approach attracted a steady stream of customers and fueled the company’s rapid expansion. But then Amazon arrived, making it possible to order a book with a few clicks and have it delivered to your doorstep. The shift to online shopping left many of Barnes & Noble's stores eerily empty.

Enter James Daunt, the managing director of Waterstones, the largest bookseller in the United Kingdom. Tasked with turning Barnes & Noble around, he brought a fresh perspective—and hope—to the company’s future.

When he stepped in as CEO in 2019, Barnes & Noble was on the brink of collapse, having closed over 150 stores in the previous decade due to declining sales. At the time, the company's revenue was down to approximately $3.5 billion—a stark contrast to its peak in 2006 when it earned over $5.1 billion.

So what exactly did Daunt do to revive this beloved bookstore giant? Let's find out!

1. Analyzing Sales and Customer Behavior by Location

Data Observed: Sales data from each Barnes & Noble location, identifying which books and products performed well in different regions.

Decision: Allowed local store managers to curate their inventory based on regional preferences, moving away from a centralized, uniform inventory model.

Outcome: This customization increased foot traffic and sales in individual stores, with some locations reporting double-digit sales growth.


2. Measuring Customer Satisfaction and In-Store Experience

Data Observed: Customer satisfaction scores, surveys, and in-store traffic patterns.

Decision: Redesigned store layouts to make browsing easier, created comfortable seating areas, and focused on displays featuring staff recommendations and seasonal themes.

Outcome: Stores that adopted these changes saw a 7-10% increase in foot traffic and a 15% boost in customer satisfaction scores within a year.


3. Evaluating the Product Mix and Revenue Composition

Data Observed: Sales data showing revenue breakdown between books and non-book items like toys, games, and stationery.

Decision: Reduced emphasis on non-book items and made books the primary focus, with other products as complementary offerings.

Outcome: By 2022, book sales made up 85% of in-store revenue (up from 72%), helping Barnes & Noble regain its identity as a bookstore and attract loyal readers.


4. Monitoring Financial Stability and Profit Margins

Data Observed: Financial reports on operating costs, profitability, and overall revenue trends.

Decision: Reduced operating costs by streamlining store operations, adjusting inventory, and focusing on profitable, community-driven store models.

Outcome: Stabilized the company’s financial position, with revenue approaching $4 billion by 2023, reversing a decade-long decline and paving the way for new store openings.


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