Some would argue to find the needle in the haystack is not only difficult, but even impossible, but that’s exactly the day-to-day duty of marketing managers. In the course of automation and digitization, the purchasing behavior of a customer changes and leads to an enormous increase in data. Consequently, marketing managers use more and more tools to manage the flood of data.

The variety of data sources and data structures are the biggest challenges in big data marketing and to gain an overview of all data that is stored within all marketing activities and applications, individual tools need to get connected.
If you now ask yourself, how to manage to keep track of the many different marketing tools, the solution is simple: A place is needed where data from different sources and formats can merge.

This is where the Marketing Data Lake approach comes into operation. Unlike in a data warehouse, where data is stored within files or folders, Data Lakes are a kind of flat storage container that collects a large amount of raw data and, if necessary, provides that data in its original form again for processing.

That way, e.g. important data from Adobe Analytics, Marketo and Salesforce, regardless of their size or structure, are always available and can be used quickly to respond to the individual needs of customers in real time. Instead of looking for the needle in the haystack, market experts gain a comprehensive and quick overview. ‘Data Lakes’ allow marketers to use more and more digital channels and to address messages individually to target groups, which in the long term pays off for a companies’ success.

Another advantage is that context-related metadata, stored at the same time, records all information about the data flow and can be assigned to all findings related to customers or products.

Of course, where there is sensitive data, security can’t be neglected. Data lake solutions apply various security levels, such as access controls, data masks and encryption, to protect personal information from customers from third parties.

Like a powerful search engine, data lakes help to optimize the data orientation and companies get a business-centric view of all unstructured and structured data.

A successful integration of the company's software environment offers great opportunities, especially because the focus is steered to important individual areas that influence the customer experience and thus optimize the following areas:

• The intelligent segmentation of potential new customers;
• An efficient and effective customer approach;
• The personalization of any interaction during the entire Customer Journey.

The next step: Customer Data Lakes

The critical part of a marketing data lake is the data itself, as for many marketers, data is rather an abstract concept. What they do not consider is that core data is collected from the capture of customer requirements, since the focus is not only on the sales figures of the last products, but also on the interests or preferences of customers – even what they do not prefer. This means that wherever individual business units are in contact with customers, different departments, such as sales or marketing, need to have a common pool of data so they can share their knowledge.

That way, each member of a team can contribute knowledge about one and the same person and link it to the available data. This not only avoids errors, such as outdated addresses or incorrect email addresses, but offers at the same time the possibility to meet all its requirements with a comprehensive knowledge of the customer. Therefore, it is also imperative that administrators and developers work together to form clusters optimally.

With so-called Customer Data Lakes, a unified view of the customer experience can be created that helps the entire company to implement new business models which will benefit both the customer and the company in the long term.

By Daniela La Marca