Customer analytics is the analysis of customer data and behavior, monitoring dynamics, and developing solutions based on the results obtained. That is, customer analytics is not a one-time action, but a systematic approach.

The goal of analytics is to identify, attract, retain, and grow the target audience. It is important to note that the level and success of analytics directly depend on the tools used.

Approach vs. Tool in Customer Analytics

According to the insights provided by Noltic, a popular Salesforce solutions provider, it is important to separate the concepts of the “analytical approach” and the “tool that simplifies the use of this approach.” It’s vital to distinguish between what we want to do and how exactly we are going to do it.

The first includes segmenting the client base and identifying a customer portrait, calculating the accumulated LTV (Customer Lifetime Value) and predicting further behavior, identifying a pool of effective campaigns based on pilots, etc.

The second includes BI systems (Business Intelligence) for data visualization, marketing and customer communications automation systems, business model optimization systems, etc.

Modern Customer Analytics Tools – What Are They?

Depending on the size of the company and the maturity of analytics, one can define simple to more complex and even industrial analytical solutions. Nevertheless, all of them can be divided into groups, depending on the purpose:

  • collection, storage, and accumulation of customer data – from small databases to full-fledged analytical solutions;
  • customer and lead relationship management (CRM, or operational CRM systems) – this includes both cloud-based solutions suitable for small businesses (e.g., Salesforce) and enterprise options for large businesses;
  • analytics of clients and their transactions, and selection of segments based on aggregated data – known as analytical CRM (examples include SAS, Teradata, SAP, and HCL);
  • predictive models – forecasting changes in client behavior based on the history of relationships with the client (from their transactions to responses to promotions and communication);
  • automation and data visualization (mainly BI, or business intelligence systems) – there are many options to suit every taste and budget, e.g., Power BI, Tableau, Qlik, Oracle BI, SAP BO.

While the realm of customer analytics is vast, tackling it incrementally, starting with readily available resources, is key.

Keep in mind that the primary aim of analytics is to deliver value, achieved through an ongoing process encompassing data collection, analysis, experimentation, automation, and iterative refinement. This systematic approach is essential for effectively managing your client base and avoiding reliance on intuition alone.

Final Remarks

Before deciding on implementing a particular customer analytics tool, it will be a good idea to assess your marketing maturity level accurately. Investing in advanced tools without sufficient data, knowledge, or capabilities is futile.

A CRM system, for instance, isn’t a magical solution; it requires skilled operation to yield results. Just as a spaceship needs a competent pilot, analytical systems rely on adept users. With the right expertise, any analytical tool can evolve into a valuable ally in customer data management.

Customer analytics is too important and useful for any business to neglect. For the first results, you can start small. The main thing is not to be afraid to experiment, look for details, and, as in any analysis, look critically at the first conclusions obtained.