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One of the companies that spearheaded the use of big data in sales started out as a book store. Now, from tiny homes to groceries, there are few things you won’t be able to find on Amazon. Even when you’re not looking, Amazon makes timely recommendations that are spot on. How can book sellers learn from Amazon’s strategy and build their own success?
According to Inc., collaboration is one of the most common ways that brands involve customers in product development. Authors do this through beta readers. When working with beta readers, an author completes a first or second draft of work and shares this with readers from his or her target demographic. The author then uses the feedback to make adjustments while working his or her way up to the final draft.
In most cases, receiving feedback from beta readers is informal. Collect better data by using surveys, checklists or special forms for readers. For book stores, following Amazon’s model of using big data is even easier. By combining sales data with consumer information, companies can better predict and recommend the types of books readers may want to delve into next. According to Entrepreneur, Amazon uses three data points to accomplish this:
- The ratings customers provide for purchases
- Items customers with similar interests buy next
- When customers make their purchases
Customize Marketing Tactics
Customer data is also useful for marketing strategies. It provides valuable information that the marketing team can use to better understand not just the market they want to target, but the demographics of the people actually buying specific books. By building a persona of the various ideal customers, book sellers can better tailor ads to suit them. This leads to more effective marketing, highly engaged readers and bigger profits.
Do you need help energizing relationships with readers so you can boost sales? From editing to distribution, Amnet can help. Email us at email@example.com for more information