Psychological data: interests and opinions
Posted: Mon Dec 23, 2024 3:53 am
To build a strong scoring system, you should include all types of data, such as:
Socio-demographic data: age, sex, marital status, and profession
Behavioural data: purchase history, date of last purchase, purchase frequency, website behaviour, number of customer service complaints, email response rate, etc.
You can source all of this data cp number philippines from various areas. For example, behavioural data can usually be sourced from your CRM and socio-demographic information is often provided by the customer when they make a purchase. The more information you have about your customers, the more data you can generate and the more accurate your scoring system will be. If you’re short on data, then you can run customer surveys to enhance your data pool.
Once you’ve gathered all the relevant information about your customers and decided on the objectives of your business, you need to build a formula or a set of rules that can be used to calculate scores for your customers and identify the ideal target group.
There are a wide range of customer scoring techniques you can use for this and the right method will depend on your goals. If you use a piece of data analysis software like Apteco FastStats®, you’ll find scoring methods are included with the software. Alternatively, if you’re working manually, you can try techniques like RFM scoring (recency, frequency and monetary value). This will determine customer purchase probability based on three criteria: the date of their last purchase, their purchase frequency and the monetary value of the purchases they’ve made.
You need to make sure that the customer scoring techniques you use accurately evaluate the key characteristics of your customers. By providing your chosen model with this information, it can then predict likely prospects by seeing if they share these key characteristics.
Socio-demographic data: age, sex, marital status, and profession
Behavioural data: purchase history, date of last purchase, purchase frequency, website behaviour, number of customer service complaints, email response rate, etc.
You can source all of this data cp number philippines from various areas. For example, behavioural data can usually be sourced from your CRM and socio-demographic information is often provided by the customer when they make a purchase. The more information you have about your customers, the more data you can generate and the more accurate your scoring system will be. If you’re short on data, then you can run customer surveys to enhance your data pool.
Once you’ve gathered all the relevant information about your customers and decided on the objectives of your business, you need to build a formula or a set of rules that can be used to calculate scores for your customers and identify the ideal target group.
There are a wide range of customer scoring techniques you can use for this and the right method will depend on your goals. If you use a piece of data analysis software like Apteco FastStats®, you’ll find scoring methods are included with the software. Alternatively, if you’re working manually, you can try techniques like RFM scoring (recency, frequency and monetary value). This will determine customer purchase probability based on three criteria: the date of their last purchase, their purchase frequency and the monetary value of the purchases they’ve made.
You need to make sure that the customer scoring techniques you use accurately evaluate the key characteristics of your customers. By providing your chosen model with this information, it can then predict likely prospects by seeing if they share these key characteristics.