What is behind the term ‘customer analytics’, and what benefits are gained by focusing on communication with existing customers?
This article originally appeared on our German site, and as such cites a number of German sources and references. To maintain the article’s integrity, we have left in these references in this translated version.
What is customer analytics?
Customer analytics describes technologies and processes that are used to systematically research customer data. They help to improve the understanding of factors such as the behaviour, status, and needs of existing customers. The necessary data can be acquired from all sorts of channels, e.g. from transactions, the CRM system, social media channels or newsletters to name a few.
Data is consolidated in a large database so that it can be analysed. This type of database is often called a Customer Data Platform (CDP) or 360° customer view. An appropriate software solution is then used to analyse the data in detail.
In the next step, the findings generated are used to communicate offerings that are relevant, in terms of time and content, to individual customers.
The resulting improved customer dialogue has a crucial impact on a positive customer experience, which, in turn, is the key to successful customer relationships and a high degree of customer loyalty.
Customer analytics vs. web analytics
The terms web analytics and customer analytics are often used interchangeably. Though both expressions focus on data analysis, there are differences.
Web analytics deals with evaluating activities on a company’s own website, and is primarily used to evaluate the performance of the site and marketing activities. So the basic data for web analytics usually comes from only one source, whereas a number of different data sources are used in customer analytics. As data from web analytics is used for customer analytics, web analytics is also done earlier on.
Web analytics is also anonymous. It’s true that the tools often provide some demographic data, such as the location, gender, and age group of visitors, which enable a rough assessment of the relevant target group. They do not, however, lead back to any specific person.
Customer analytics, on the other hand, is personal: all activities can be assigned to a particular person. It is only this personalised view that enables customer communications to be actually shaped to suit the individual and optimised over the long term (Pinuts, 2019).
Benefits of data-based communication with existing customers via customer analytics
Many companies focus their marketing communications on acquiring new customers. According to Deutsche Post’s 2019 Dialogue Marketing Monitor, German companies tend to be reticent when it comes to communicating with existing customers. On average, only one in three companies deploys targeted communication with current customers. In the retail and services sector that figure is 40%, while in companies with annual revenues of over 25 million euros it jumps to 60%.
However focusing on existing customers can bring some vital benefits. Firstly, acquiring new customers is associated with far greater workloads and spending than supporting and nurturing loyalty in an existing customer. As a rule of thumb, you can assume this costs five times more (W&V, 2019). It has also been noted that existing customers add more value because they buy more frequently and opt for higher value products. They are also often more price-sensitive, so they improve planning reliability.
Another key issue is the fact that existing customers who are satisfied are more likely to recommend a product to others, e.g. on social media or amongst people around them, so they provide a sort of free sales support service. Moreover, in terms of compliance with data protection regulations, communicating with existing customers is simpler than addressing potential new customers (W&V, 2019).
Recent studies show that adding greater value based on optimising customer communications with customer analytics is not just theoretical.
According to McKinsey & Company (2016), businesses that deploy customer analytics widely see a substantial improvement in key figures such as profits, turnover, growth, and return on investment.
A study published recently by Harvard Business Review Analytic Services (2019) confirms this. 58% of the 560 companies surveyed state that using customer analytics has improved customer loyalty. In 44% of businesses, this led to significant increases in growth and revenue.
For which businesses is customer analytics relevant?
In principle, any company that has a lot of customer data can benefit from customer analytics, whether they are a corporate group or a medium-sized company. In many cases, deploying an appropriate software solution becomes worthwhile when the number of customer records reaches a few hundred thousand (for B2C; fewer in the B2B sector).
In terms of the industries in which customer analytics is relevant, some are more obvious than others. Due to the abundance of transaction data they accumulate, retail companies are ideal for deploying customer analytics. Charitable organisations, financial services providers, and insurance companies also have a large volume of customer data.
But at second glance, many other sectors also have a lot of data that they can use to analyse and personalise their communications. For example, energy and power companies have consumption data, car dealers have information about wear and tear in installed components, and media and publishing companies have data on how much time their subscribers spend with them.
Which requirements must be satisfied for customer analytics to be deployed?
An inevitable requirement for using customer analytics is access to all customer data, consolidated in a database. A company’s own IT department can often help create this. For any that are unable to implement it themselves, there are specialised service providers who can help.
A piece of analytics software that sits on top of the database is also needed. This type of application enables the data to be analysed and displayed, which generates new findings so that specific target groups can be selected for campaigns.
Having a corporate culture that puts analytical findings at the heart of its decision-making is also crucial for deploying customer analytics successfully.
Would you like to find out more about how customer analytics can create added value for your business? We would be happy to answer your questions and give you a demo to show you what is possible.