Customer data has gained a new relevance in recent years. The collection of this data through various customer touchpoints is an essential method to create an accurate and reliable customer profile that can be used to establish efficient, effective customer-brand relationships. Customer are demanding to be the centre of the world of retail, and this can only be achieved through building correct profiles.
What does data collection mean?
Although not a new topic, there is a still an element of mystery surrounding data collection. This is understandable as it is a complex field. Furthermore, data collection cannot only relate to the collection of information, but rather than collection and measuring of information that has been collected.
This data collection also contains information from various sources. There are many forms of data collection through multiple touchpoints, such as customer loyalty cards and in-store questionnaires, but arguably the most efficient way of collecting customer data is through an online store or app, enabling the creation of a digital footprint.
Why is data collection important?
There are many advantages to collecting customer data correctly, and the importance of this customer data cannot be overstated.
Data collection and accurate data analysis is essential in improving the quality of customer experience, building customer loyalty, creating successful marketing strategies and great customer experience. All of these factors are key to attracting, engaging and retaining customers, and overall creating value for the business.
What is the process for collecting data?
As previously stated, the way to collect customer and buyer information can take many forms, from in-person interviews, to building digital profiles through analysing a customer’s digital journey.
Importantly, the different methods for collecting customer information also result in different types of data. There are also a variety of different stages of data collection, and once the data is collected it must be analysed.
What type of data to collect?
The primary types of data are qualitative and quantitative data, and there are key differences between these two.
Quantitative data is data that can be counted or measured in numerical values, for example, customer footfall throughout the day, or customer age.
Qualitative data is data which describes qualities or characteristics and is therefore much more difficult to analyse. It is collected using questionnaires, interviews, or observation, and frequently appears in narrative form.
Crucially, it is imperative to collect a mixture of qualitative and quantitative data. This is the most effective way to build accurate customer profiles, which enables the data collection to be of most use.
There are also four main sub-types of data:
- Basic or Identity Data – A type of quantitative data such as age.
- Engagement Data – Quantitative data of the interactions that form a client-company relationship.
- Behavioural Data – Quantitative data that provides information about a customer’s interaction with your business.
- Attitudinal Data – Qualitative data that contains information about customer feelings, motivations, and opinions toward a product, brand, or customer experience.
Data is key to attracting, engaging, and retaining customers and to building great customer experience. Through small steps and ensuring the right type of data is collect it is possible to build accurate customer profiles. These profiles are essential in all types of retail, but especially so in the DIY and home improvement sector as customer preferences change. To attract new customers, continue to engage them and market to them successfully it is essential to know what type of customer you are building a customer-brand relationship with.
