Leveraging Data to Drive Personalized Marketing

Marketing efforts are no longer about pitching products; there is a major shift toward adding value through relevant, personalized marketing initiatives. As the role of the CMO continues to expand and companies recognize the value of targeted campaigns and increasingly personal customer relations as the keys to success in today's new marketing reality, marketers need to be more strategic in leveraging data that resides across the company. Customer data has quickly become the marketing department lifeblood, and, quite simply, siloed CRM and digital marketing systems can no longer suffice.

The next big thing in digital marketing is data integration—connecting financial, CRM, marketing, and other business applications to get a 360-degree of the customer. But while the future of digital marketing lies with integration, companies must first overcome these core data obstacles:

  1. Divergent Data Models: There are a lot of dissimilarities when it comes to database structures between various customer systems. For instance, vertical markets such as insurance have incredibly complex CRM models, whereas their marketing automation systems are usually designed for high-volume processing and real-time execution and are much less complex. Reconciling these differences can be daunting.
  2. Data Quality: Bad (incomplete or inaccurate) data can spread like a virus once systems are integrated, permeating various applications and cracking your data foundation at its core. Even something as seemingly innocuous as duplicate data (actually one of the biggest quality killers) can detract from customer experiences and increase implementation costs.
  3. Data Relevance: More data doesn't equal better data. Dive into the data and identify the meaningful data that will help drive personalized communication so you can strip out the noise and only share the data that is needed by each of your applications.
  4. Performance: Data-driven marketing initiatives demand real-time integration with rapid response times. Data integration efforts need to be ready to automatically scale to meet changing needs and run at the same pace as your business.
  5. Rate of Change: Things change fast in today's business environment, so data integration flexibility and control are key. In addition, avoiding an overdependence on IT is critical, as most IT departments are overextended and data integration priorities may become lost in the shuffle.

Now that you understand these obstacles, how can you overcome them and effectively integrate customer data across applications? Here's a snapshot of smart data integration tactics:

Start by identifying key database differences and logically map everything from the onset. Use a data sample from each application to understand issues before integrating the data so you can build automatic assessment and correction rules into the process. Be sure to continually clean and standardize data in all systems to maintain data health, just like you schedule annual checkups for your own well-being. Make sure integration solutions are iterative—growing and expanding with changing needs without disrupting the business. And, most importantly, keep the end objective in mind at all times and focus on the data that is going to drive action within each application.

The availability of information any time, anywhere has changed the game—customers are in control and companies are scrambling to deal with this new reality. As consumers increasingly engage companies later in the buying cycle, it is more critical than ever to leverage a data-driven marketing strategy and deliver relevant, personalized content and interactions.

Integrated smart data can provide powerful insights that will improve business outcomes across sales, marketing, customer service, and finance. You can cultivate better information sharing, create a unified view of each customer, and drive better business decisions. Don't let anything get in the way of data integration success.

Peter Chase is the founder of Scribe Software.

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