Making the transition from legacy systems to Customer Data Platforms

Data can be put to work in many contexts, providing multiple reads for businesses.However, with increasing data sources and use-cases, comes the problem of handling data complexity.

Businesses are no longer dealing with a finite number of tech systems. On the other hand,some businesses are limited by legacy systems, which do not keep up with the ever-increasing number of apps that collect, house, manage and mine data.

Businesses need a Customer Data Platform (CDP) that not only helps overcome customer data silos and unifies data from across the tech stack; but also ‘talks to’ the existing tech stack.

Here are 4 key starting points, when embarking on the journey to evaluate CDPs:

·        GOALS: Identifying a platform requires businesses to consider their current and future Analytics goals; and the data they require, to achieve such goals. Defining use-cases is a necessary first step, before embarking on the quest for a suitable platform.

·        AGILITY: For today’s rapidly changing business ecosystems,finding Future-proofed data platforms is a somewhat ambitious task. Instead,businesses must actively seek out agile platforms that offer flexibility to deal with newer data complexities as they arise.

·        PROTOCOLS: Established data protocols help reduce ambiguity around treatment of specific data formats. When evaluating platforms, businesses need to verify whether they can ingest, cleanse and transform data of all types, sizes and formats. A related check is –integrations and connectors. Businesses that use more than one MarTech platform need to confirm whether a new platform will work in tandem with the existing tech stack.

·        ENRICHMENT: Digital businesses operate in a connected world. For instance, in case of QSR, customers leave data trails on various social platforms. Thus, ability of a CDP to enrich customer profiles with first, second, third party data sources is an important criterion.

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