Advanced Customer Analytics: Developing Customer Journey Accelerator Strategies

There is a lot of excitement over big data, predictive analytics, and data science. These buzzwords have business leaders scrambling to develop their analytical offerings, which may not fit in their broader strategy. Without a simple and focused direction, advanced analytics can unfortunately be viewed as flashy and non-substantive. West Monroe believes an action-oriented strategy leads in to the implementation of analytical solutions. For customer analytics, keeping strategy focused on the customer journey map, and assessing the maturity of the ability to transform raw data into a means to effortlessly convert customers for each touch-point, provides comprehensive direction for developing a solid analytics capability.

Analytics Maturity Framework – The Traditional Strategy Tool
When it comes to analytics vendors, the maturity framework is table-stakes. How the enterprise matures in its analytics practice from describing trends, to predicting outcomes, to prescribing the right actions is not a new concept to most firms. The maturity framework is important to understand and leverage, but it is far too general to develop fully articulated strategies.

Analytics Maturity Framework

Journey Map – The Customer-Centric Strategy Tool
The customer journey map provides a strategic look at where the key ‘moments of truth’ lie in a firm’s interaction with its customers. Each key touch-point has a desired outcome, from acquiring a customer, to preventing customer churn. Each desired outcome has a unique way data can be used to help drive the desired outcome. Applying the maturity framework to each one of these touch-points is a more meaningful and direct application. Each touch-point should have plans to solve one simple question: How can data help my customer interactions each step of the way?

Example maturity model by key touch-points

For example, an organization may have a suite of dashboards around online conversions, this would put the organization in the ‘descriptive’ stage for this touch-point. A strategy to develop how to predict conversions within each session through real-time analytics would be the next stage of analytical evolution. Developing personalized content through multivariate testing and predicting what messages to use would evolve that touch-point into the prescriptive stage.

By leveraging the customer journey map, a clear and concise analytics solution inventory can be established for each touchpoint: Are there recommender systems in place for each upsell opportunity? Are we personalizing all of our direct mail and email? Is there a clear ROI on marketing spend? After prioritizing these opportunities with ROI assessments and voice-of-customer tools, a full-fledged analytics strategy is constructed. This approach seems intuitive, but it is still common to see tool driven strategies in companies of all sizes. Investments in advanced analytics technologies like SAS, Hadoop, and Tableau often are treated as silver bullets resulting in limited ROI due to the lack of a fully articulated analytics strategy.

Another benefit of this type of planning provides an opportunity to develop non-customer analytics solutions, as adjacent opportunities become apparent. Customer opportunities open other analytical opportunities in supply chain, finance, quality, and product development.

The possibilities of analytics applications are versatile and endless, and the ability to focus on key pain points is a critical success factor for analytics initiatives. By focusing on key points in the customer lifecycle, a solid analytics foundation can be developed quickly and practically.

To learn more information, please visit our Advanced Analytics page or reach out to Matt Rager or Greg Layok

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