Search results for "täsmämarkkinointi"
showing 3 items of 3 documents
Serendipity in recommender systems
2018
The number of goods and services (such as accommodation or music streaming) offered by e-commerce websites does not allow users to examine all the available options in a reasonable amount of time. Recommender systems are auxiliary systems designed to help users find interesting goods or services (items) on a website when the number of available items is overwhelming. Traditionally, recommender systems have been optimized for accuracy, which indicates how often a user consumed the items recommended by system. To increase accuracy, recommender systems often suggest items that are popular and suitably similar to items these users have consumed in the past. As a result, users often lose interest…
Using AI to personalise emotionally appealing advertisement
2019
Personal data and information collected online by companies can be used to design and personalise advisements. This chapter extends existing research into the online behavioural advertising by proposing a model that incorporates artificial intelligence and machine learning into developing emotionally appealing advertisements. It is proposed that big data and consumer analytics collected through AI from different sources will be aggregated to have a better understanding of consumers as individuals. Personalised emotionally appealing advertisements will be created with this information and shared digitally using pragmatic advertising strategies. Theoretically, this chapter contributes towards…
‘Interesting but scary’ : Customers' perceived value of MyData
2022
Digitalisation has facilitated saving data in various warehouses. While Big Data is a new form of capital that is often considered an asset for organisations, the potential value of data to customers has seldom been addressed. This chapter discusses MyData (personified and personalised data) and aims to increase our understanding of its benefits and the value created when customers use their own data. The empirical data for this paper were collected from customers of a large retail organisation that adopted the practice of sharing data with customers. This study has found that value accruing from customer’s shopping data is multifaceted and can be either positive (creating value) or negativ…