Online Word-of-Mouth and Other Information Influences Consumer Preferences
We live in an era when we can easily purchase all kinds of things—including clothes, bags, books, foods, and sweets—not only at stores but online too. We often start our shopping off by gathering information. For example, we read guides online to products, search for customer comments on social media, install official store apps on our smartphones, or subscribe to email newsletters.
What people are looking for has dramatically diversified. Many companies use various types of data for detailed analysis of consumer lifestyles and preferences. They hope to use the obtained data in marketing activities targeting individual consumers and in product development.
Discovering Purchase Intentions
Fujitsu has released a consumer preference analysis solution to analyze consumer preferences for marketing purposes. It uses a product attribute addition model developed by Fujitsu to visualize consumer lifestyles and preferences, and output them as analysis reports.
For example, by using text-mining technology it extracts useful information from descriptions of food products. It then automatically adds tags to product characteristics or USPs such as "homemade" and "healthy." It combines these tags with information on products and purchasers, and visualizes the results. The obtained data facilitates the planning of sales promotions that match target user preferences or needs. The data can also be combined with weather information or social media-based information.
The analysis of a combination of product attributes, survey results, and purchase history allows consumer preferences to be estimated based on their purchase history. Analysis results can be used in creating higher-level marketing plans. Companies can develop products that meet consumers’ needs and encourage them to visit stores or make purchases in an effective way.
Finding a New Type of Preference to Increase Sales
An e-book company that has chosen our solution added tags describing product characteristics to all of its e-books. An analysis of these tags combined with member purchase history led them to discover a new type of preference, which is something they could not have discovered with traditional book categories. The new type of preference is somewhere that goes beyond the traditional "non-fiction" or "historical drama" categories; the newly discovered preference is for the true story genre. Customers liked books based on scandals and investigative reports. The company sent email newsletters including book recommendations to those who had this preference. As a result, links to products were clicked on 3.2 times more frequently and products were purchased 3.1 times more often compared to regular email newsletters.
This solution was recognized as a solution for carrying out business in a consumer/customer orientated way. It received the CRM Best Practice Award from the CRM Association Japan in November 2015. Based on our understanding of data usage and consumers, Fujitsu, as our customers' business partner, will continue to further help solve management and operational challenges.