How does customer intelligence support modern marketing?


In my last blog post, I discussed the features of a customer intelligence solution that enable it to support more coherent marketing. In this post, I consider how customer intelligence can be used to support marketing, from conscious management and monitoring of strategic goals to planning and managing the experience of an individual brand.

There are three fundamental areas that I consider to be the pillars of the modern customer intelligence system.

  1. Supporting multichannel, multistage customer interactions

Customers can make contact with companies through a huge range of channels, including both traditional and digital. They range from visual advertising in traditional and digital media, to dedicated marketing and service channels. One of the main ways in which a customer intelligence solution can help is to deliver an appropriate level of unification of multistage customer contacts. This allows businesses to react appropriately to customers, making contact more effective and improving customer satisfaction.

Obvious benefits of this include better planning and visualisation of customer journeys and friendly, understandable and personalised messages.

  1. Prioritisation of analytics

The second pillar involves the use and, more crucially, integration of analytics. This means that companies are focused on achieving a better understanding of each customer, not only their value or willingness to purchase specific products or services. This understanding includes their preferred points of contact with the organisation, convenient times for contact and the typical sequence of steps leading to a purchase.

Modern marketingA marketer equipped with this knowledge will be able to divide the target group using specific criteria and therefore plan effective scenarios. Some customers, for example, will receive a link to a personalised offer in the online store by email, and others will receive a phone call offering a consultation at a convenient time. Compare this to the traditional scenario, when the target group is selected on the basis of a simple question: “Which customers do not yet have X product?”, and the telemarketing campaign is remunerated only on the basis of conversion rates. This type of campaign may have been profitable for the business, but deeper analyses show that they were not necessarily popular with clients, and often resulting in wasted marketing time for many clients.

Comprehensive analysis of customer behaviour significantly improves the ability to study typical customer journeys, improve interfaces, and modernise and enhance communication methods. These first two pillars are therefore closely related.

Prioritising analytics means democratising it. Businesses tend to have two groups of analytics users. First are the advanced data analysts or data scientists, who build forecasting models that determine the tendency to respond to offers, the product best suited to the customer’s individual preferences, and the willingness to purchase the product. They need the best tools available, including the most effective algorithms, to provide models that support optimal marketing decisions. The second group is marketers, who were traditionally consumers of analytical results. Their role was therefore limited to effective selection of the right offer and method of communication to previously defined target groups.

Modern customer intelligence tools, however, have opened up the role of this second group. They now have greater autonomy and creativity. It is now possible to detect previously unidentified segments, and increase the individualisation of offers or the way they are presented using traces left in the digital ecosystem or by A/B testing.

  1. Strategic planning

The third pillar is that the system must implement long-term key performance indicators (KPIs), which should be aligned with the tactical and operational goals of marketers or product managers, although this is not always the case. Top-down strategic planning often stops at a particular level of data granularity. After that, it goes through an arduous stage of verification to determine whether the plan can be delivered through the available marketing activities at their current level of effectiveness.

The precise decomposition of high-level business goals into a set of specific marketing activities is one of the greatest challenges of the organisation. Marketing is not an exact science, and the results achieved are the result of both innovation and the effects of a competitive environment. In a digital age, however, with such volumes of data available, systems enabling interactive tracking of the impact of individual campaigns on KPIs, and vice versa, has ceased to be a distant dream.

In my next blog post, I will discuss this issue of marketing system integration with the wider company’s goals, and also the ecosystem more generally.


About Author

Dariusz Jańczuk

Dariusz Jańczuk is a Senior Business Solution Manager at SAS Poland. The Master of Science obtained in Computer Science allows him to play a role of a bridge between typically separated worlds of business users and IT guys. For more than ten years he's been responsible for promoting and developing Customer Intelligence solutions. An active promoter of the latest trends in marketing communications including rapidly evolving digital space. Supporting customers from many different industries but his main area of focus are communications and banking.

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