In today’s world, digital transformation forces companies of all sizes and industries to constantly re-evaluate their ongoing operations and adapt to new market realities. “The customer is king” has long been a popular mantra in marketing and sales departments, and industry leaders as well as academic experts are constantly preaching customer centricity. It is no longer a well kept secret that customer demographics and behaviors have radically changed within the last decade. Companies have to adapt their marketing and sales strategy to meet these evolving customer needs. On the one hand, the customers’ time is scarce and they want goods on demand, making them prime targets for a wellcrafted relationship strategy. On the other hand, as their technological skills and product knowledge continue to increase, customers gain more leverage over companies.

As customer behaviors and expectations change, companies experiment with new business models to create new revenue streams. Well known examples are various Freemium business models (e.g. Spotify), pay-per-use models with costs occurring only if the service is used or revenue models through relatively low monthly subscriptions (e.g. Netflix). In each of these models, continuous customer engagement is key to generating sustainable revenue streams, reaching profitability and turning recent adopters into loyal long term customers. If a company’s approach does not live up to the consumer’s expectations, they are very likely to abandon the company ecosystem entirely without generating enough revenue for the company to be lucrative or break even on acquisition costs. Building long lasting relationships with customers is therefore a crucial success factor for these new business models.

Lack of overview & responsibilities

In our observations, we found that functional groups are often unable to take astep back and consider the bigger picture of the journey they are a part of. They neglect how codependent the different touch points are and focus instead on optimizing each touch point individually. By contrast, customers focus on the cumulative product/service and brand experience across multiple touch points and channels. This becomes particularly important when looking at the various new interaction points available new channels, devices, applications, and more. And when new ecosystem partners are included, it takes the complexity of the game to the next level. That is why it is so important to manage the journey as a whole instead of individual touch points.

Enable individual interactions matching context, channel and customer segment

Once a company understands customer needs and visualizes potential touch points, it can start designing detailed interactions. An interaction plan can help to structure the relevant factors e.g. target group, occasion, channel. It is important at this juncture to differentiate between two kinds of interactions planned and unplanned interactions. Planned interactions can be derived and designed based on customer needs and predicted touch points. Using high quality customer insights and accurate context data, they can be personalized and context based to guide the customer along his journey and build relationships specifically.

Unplanned interactions are difficult to foresee and are characterized by a very individual context, in which the customer initiates the interaction. Although these interactions are complex to manage and difficult to integrate into an interaction plan, they often have a very high impact on the relationship between a company and its customers. Therefore companies might find it useful to define principles that ensure consistency in unplanned customer interactions

Balancing the right amount of interaction

Strong customer relationships promise loyalty and retention but their strength is influenced by various parameters such as contact frequency, relationship duration and customer preferences among others. Today, analytics provides an array of tools to help organizations engage with their customers at the right moment with the right content. For example, customer behavior analysis gives insights not only by collecting customer data but also by clustering customers into segments in order to approach them in a standardized yet personalized manner. Furthermore, natural language processing allows you to review past conversations to gather insights into customers’ levels of satisfaction. These can be used in the future to address them with their preferred content and style.

To create meaningful customer interactions, companies should focus on the value they can deliver to their customers through interactions instead of fixating on the financial value they might extract from a customer relationship through mere contact. If customers cannot see the value in engaging with a firm, the firm might lose their share of engagement. Also, if the contact is too frequent, CRM resources will not be used efficiently and customers may become dissatisfied and annoyed.