A disciplined approach to the capture, integration and analysis of customer data is needed to identify and leverage customer relationships and opportunities to their fullest. This emerging space, called marketing automation, forms the core of the knowledge engine which drives customer relationship management (CRM). In this column, we'll look at the defining characteristics and technologies to enable the marketing automation process.

Marketing automation is characterized by several key attributes.

Back-Office Alignment

Marketing automation provides alignment of cross-functional customer relationship decisions in the back office.

  • Marketing: Decisioning and opportunity identification based on customer needs, behaviors and value.
  • Campaign Management: Leverage of targeted segmentation, offer design and customer behavior information into the structure of the delivery campaigns.
  • Marketing Finance: Leverage of customer financial and modeled behavior sensitivities into business development for targeted complex investments.
  • Marketing Sciences: The ability to incorporate primary research design and findings, and third-party overlay data into segmentation, predictive and descriptive modeling analytics.
  • New Product Development: Leverage of customer learnings regarding behavior sensitivities, mind-set research and offer performance into new offer design and valuation.

Front-Office Integration

Marketing automation also drives customer-centric activities in the front office, effectively "close looping" the enterprise CRM process. It pushes the analytics and offer/promotion data out to front-office enablers such as call center automation and sales force automation technology. In return, the marketing automation process receives and integrates the customer experience information captured from the various customer access channels.

Rationalizes Resource Allocation

Enterprise-wide alignment of data and decisions is imperative to delivering a consistent customer experience and allocating the appropriate enterprise resources. Airlines, for example, are busy trying to integrate and align decisions across various enterprise functions such as reservations, customer care, Web sites and airport operations. They are doing this to fulfill customer needs in a way consistent with the customer experience proscribed ­ don't under serve or over serve.

Measurement Alignment

Many companies struggle with classic measurement dichotomies. For example, marketing's desire is for customer service representatives to spend call time on up-sale, re- promotion and customer data gathering while call center operations is incented to lower its cost by reducing talk time and increasing agent call volume. Performance measures must be aligned across the organization to effectively operationalize enterprise customer relationship decisioning.

Integrated Technology Solution Set

Achieving enterprise CRM is best served by implementing an architected solution set rather than taking a piece-meal "select and assemble" approach. The technology infrastructure for supporting marketing automation is represented by five major component areas.

  • Extract, Transformation and Load (ETL) Environment ­ addresses the data synchronization, cleansing and transformation needed to effectively utilize data in decision making. Merge/purge technologies such as Trillium and Vality can be employed to address customer identification, householding and name/address scrubbing. Service bureaus can provide overlay data for customer records (e.g., census block data).
  • Data Warehouse ­ an atomic store of customer data that transcends any one subject area. A consistent, logical representation of key customer data is essential to cross- enterprise decisioning. Given the growing volume of customer information, data warehouse designs must easily scale to the multi-terabyte realm.
  • Marketing Data Mart ­ provides analysis and reporting of marketing-specific customer financials, behaviors and performance measures for managing customer franchise value. Companies are employing various online analytical processing (OLAP) technologies. There is a strong focus on relational OLAP (ROLAP) technologies such as MicroStrategy and Sterling's MyEureka Suite to manage the volume and granularity.
  • Campaign Management (CM) ­ provides advanced tools for planning, managing and evaluating the delivery of offers to customers over time. CM tools from companies such as Exchange Applications and Prime Response are being implemented as a critical part of companies' CRM strategies. Real-time CM engines are gaining traction in the Internet age of high-velocity campaign cycles measured in terms of days and hours instead of months.
  • Modeling Platform ­ provides the environment to develop descriptive and predictive models for use in targeting offers, understanding customer behaviors and proactively managing the customer. Technologies such as SAS Institute's Enterprise Miner are being successfully employed by companies with a focus on tightening the integration with other parts of the knowledge infrastructure.

There are dozens of other technologies which address marketing automation, including capability delivered by "holistic" CRM players such as Siebel and E.piphany, and emerging solutions from traditional ERP vendors such as Oracle and SAP. An effective marketing automation process enables: 1) a continuous, closed-looped customer learning environment, 2) a knowledge engine that drives consistency and ensures leverage between front- office and back-office operations, and 3) effective measurement and understanding of the effectiveness of a cross-enterprise CRM strategy. Your marketing automation solution should allow your company to truly differentiate customer experience and drive customer portfolio profitability.

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