In the context of this blog post customers are the users - the consumers of information. Customer intimacy uses customer information to tailor solutions that satisfy unique or highly-targeted customer needs. It is based on a continuous learning relationship with customers, which means that the organisation has to initiate dialogues with them, capture information about their behaviours and preferences, and use the information to further customize content to these preferences.
At the front end, the focus of the process is on customer needs and value creation. At the back end, the focus is on putting together a solution that efficiently fulfils that customer’s needs. In both cases, the process model development calls for extensive human judgment, combining experience and creativity. Experience management platforms such as Sitecore have evolved to address this premise.
Tailoring solutions at the front end involves gathering information recorded during each customer interaction and service request. Continual improvement leads to superior back-end processes and operational excellence. Thus, operational excellence is not about efficiency; the relationship needs to be front end to back end coordination to enhance the performance of the experience and deliver greater value. The goal of operational excellence in this model is to maximise relevancy.
A customer intimacy agent tracks the customer’s preferences and represents them in the choice process. You could say these agents are the things responsible for data driven personalisation. These agents belong to new process models and specialize in identifying customers’ current and future preferences and in helping customers to choose among alternative solutions by automatically presenting applicable content. Essentially this means serving relevant content across all digital channels. Information value analysis will match supply and demand automatically configuring solutions that use existing content.
The process should also suggest the creation of new information based on the data gathered about customer preferences and behaviours. Traditionally customers have had to explicitly state their preferences; however the new processes should trigger a solution search which will be managed by the agent on their behalf. Mass customization allows organisations to combine the benefits of customization to create customer-responsive experiences and disseminate them broadly at first with the intention of refinement.
This amounts to a subversive delegation of choice – the final presented content is based on analytics and on an agent’s ability to consistently find the best information for a given customer, or customer segment. Information value can be further assessed at any point. This is more than an automated matching of demand and supply, as mentioned it should result in the commissioning of new information based on the data from customers.
The customer intimacy agents also represent potential customer’s preferences and when merged with existing behaviours can suggest even more potential new information, to further match preferences, create even more value-added content and ultimately result in the creation of unique custom experiences. When setup properly this automates key parts of the customisation process and the iterations of more and more relevant content should be a natural process.
This can also be considered an electronic form of ideation because the system can test each information configuration via A/B Testing (or Split Testing) and can aggregate demand and preference data from the customer intimacy agents by comparing potential outcomes. Other than highly relevant experiences, one outcome would be the agents being able to determine and suggest what new forms of data might be valuable to capture.
The combined effect of technology with customer intimacy agents will sharpen the structure of future process models for customer engagement. Customer intimacy agents will be customers’ digital representatives in the communication process. They will use data to find and solicit information, while value analysis will match supply and demand and assemble customized experiences. This can be understood as automated data-driven customer innovation.
With all of these data driven experiences traditional forms of innovation and the ability to engage in more traditional customer-driven innovation may be a strong differentiator for the most successful information creators. While electronic customer-driven innovation can work well for experiences that are natural extensions of customer’s expectations, there will always be breakthrough experiences whose success cannot be inferred from the available data. The underlying process models will require all types of continuous innovation from real people with real insights and ideas. Developments in IT will make customer intimacy one of the central building blocks of how the organisation of the future communicates but it will need the right people and tools and the right commitment to be successful.