From Customer to Fan

The pandemic has greatly changed the way in which we interact with our environment. As physical points of contact have disappeared, customers often expect that companies can be reached through multiple channels 24 hours a day, seven days a week. At the same time, customers do not want ‘one size fits all’ solutions but rather look for personalized recommendations to help them make quick purchase decisions. These decisions are often based on recommendations and reviews from other people, or the customer's identification with his or her company / brand. For companies, the first challenge is to identify these different expectations, needs, and behavioral patterns at an early stage and respond to them individually. At the same time, ever shorter product life cycles, rapid technological developments, and new players in the market (with sometimes similar products and services) also increase the competitive pressure.  

Data-based customer experience management that uses micro-segmenting can help companies create an optimized customer journey as well as tailored and personalized contents that surpass those offered by competitors, resulting in a competitive advantage. Unique experiences increase customer satisfaction, which leads to increased customer loyalty and, therefore, secures the company's long-term success. And consumers are often willing to pay more for an excellent customer experience.  

On its own, this approach is not really new, but it is considered the supreme discipline when it comes to marketing and sales. The systematic collection, aggregation, and analysis of all available customer information from a variety of data sources represents an important foundation for customer experience management, because it is used to synchronize the company's services with the needs of customers. But usually, it is quite challenging to generate an improved quality of experience from the existing data: For example, what instruments are used to measure the concrete effect of a specific marketing measure? And how can different measures be combined across different touch points to create excitement among customers and raise customer satisfaction and loyalty over the long term? 

In this article, we discuss which core elements must be considered for the development of a customer-centric marketing and sales approach - and why.

Already, the analysis of data is one of the most important levers for improving growth, efficiency, and the responsiveness of marketing and sales measures, and it will only become more important in the future. But such efforts are often hindered by historically grown data modeling systems, which do not enable real-time analysis or offer a sufficiently granular representation of customer requirements. These legacy systems are usually based on an outdated one-size-fits-all approach, without the capacity for personalization. Moreover, they only analyze customer interactions separately for different marketing and distribution channels, and, therefore, do not allow for real-time analyses to assess the effectiveness of customer experience measures. 

Cutting-edge technologies, on the other hand, provide companies with an integrated view of their customers and make it possible to develop a valid assessment of the financial benefit of each marketing and sales activity: Based on the intelligent real-time integration of all relevant data from the different external and internal channels, contents and customer approaches can be quickly personalized across channels. Companies are also in a position to quickly react to changing customer requirements and to further optimize the experience quality of the customer journey in an iterative process consisting of analysis and action. 

In implementing this vision, companies encounter a number of very different challenges: In many places, conventional systems make it impossible to exploit the advantages that are offered by data-driven customer experience measures. Often, data and key indicators are not linked, therefore, the impact of customer experience initiatives remains invisible, and conclusions for strategic decisions cannot be drawn. Added to the above are problems with data quality and availability. That is a lot of challenges - but what is the best starting point for building a data-driven customer experience management system? 

Campana & Schott outlines eight points that must be considered when introducing and optimizing a data-driven customer experience.

With an optimum technologically- and organizationally-supported customer experience, companies can identify patterns of behavior, better understand customer needs, and increase the value contribution of their digital contact channels along with use frequency. In addition, they can also identify satisfaction and growth drivers. The greatest reward: long-term growing customer trust in the company and enormous customer loyalty. 

Customers, on the other hand, enjoy real-time support and tailored products/services that actually meet their needs. Both have an effect on the brand experience and strengthen customer loyalty. Hence, good reasons for using smart data to build a customer-centric company. At the same time, it is important to keep in mind that the added value from personalization must be so great that customers are willing to share their data.  

Therefore, companies must invest more in sales and marketing to leverage the positive effects of customer experience management, so that the relevance of the company's customer-centric direction becomes visible.