The Scattered Customer

Last year put enormous pressure on digital transformation processes, part due to the COVID-19 pandemic, part to the increasing need to be digital – This process cannot be limited to having digital channels, organizations need to be able to reach their customers and be to do it better that their competition – It is critical they have a detailed understanding of their customers.

Most organizations are working with an average of 15 to 20 customer data sources, with customer data scattered across multiple systems and formats. With so many data sources spread throughout the organization, and confined to functional and channel-specific silos, building a single view of the customer is a huge challenge.

This a result of a natural growth process, due to competing priorities within the organization - leading to customer data silos across multiple departments – making almost impossible for all the stakeholders to achieve their customer-related goals and preventing organizations from getting a clear understanding of the customer journey.

Gathering all the scattered pieces of customer data from multiple systems and building a cohesive view of the customer that can be analysed and used as input for the decision processes is complex, but unavoidable if using customer data to drive revenue growth is a business objective.

This siloed ecosystem has a deep effect on the quality of existing customer data:

• Duplicate customers – The existence of multiple systems leads to high degree of duplicated customers, i.e. the same physical customer will have multiple, unrelated, instances across multiple systems and lines of business.

• Lack of timely data – These systems are updated simultaneously, and these updates are usually not replicated to the other systems, either by lack of integration or because they cannot be easily related – leading to different data being used in different contexts.

• Redundant and inconsistent data – Customer data is collected across multiple channels, with different requirements and formats, to answer to different business needs.

• Rogue data sets – The inexistence of a reliable data source leads to data being extracted from arbitrary data sources to be used for multiple purposes outside any consistent framework or criteria.

In another perspective, as the business models changed, today customers have a numerous touch points connecting them to organizations, it is critical that these different touch points connect and develop a consistent customer experience.

This is impossible when data is not shared within the organization, incapacitating organizations from making the most informed decisions about their customers – Something that should be seamless.

All I described above shows how poorly we are managing customer data. This kind data management, or absence of data management, is done in autonomously, with inconsistent requirements, a process that is inefficient and expensive and results in the proliferation of multiple uncontrolled versions of data.

How to create a seamless customer journey when data is not shared within the organization?

Customer data management must focus on the best practices to collect, store and secure customer data for the purpose of improving an organization’s services, processes, and products. Enabling the creation of true value, translated into increased sales, improved customer retention, more effective marketing campaigns, stronger customer relationship, and more.

Creating a 360 view of the customer will help organizations to eliminate data duplication and improve security, allowing to deliver improved customer experience, improving sales effectiveness, and enabling a personalized customer engagement.

Additionally, breaking down these siloes to combine customer data with product and other data, can also reveal previously hidden relationships and connections and create a true 360-degree view of the customer, that can positively impact not only sales, but also other needs, for instance risk management.

This is not about buying and implementing the latest and greatest technical solution, this is about adapting the solution to the real business needs, and these solutions can range from a customer master data management to ca customer data platform. The important is to ground the option on specific and measurable business objectives, regarding the organization’s capabilities and its data strategy.

Starting small and focused is most frequently the best approach.

Creating initiatives where business and IT teams can fast-track high-value customer initiatives as organization build out their longer-term transformation.

Focusing on specific business cases and linking customer data across data silos, integrating relevant customer data, making it accessible across the business will reduce duplicate information, and manual data set, starting to address some of the issues mentioned above.