In this two-part series I'll address the use cases for monetizing data, how organizations should approach the challenge and realize the potential benefits. 

Today, let's explore the use cases for monetizing data in the Utility space.  

Like many industries, utility companies find themselves at an unprecedented junction. What should they do with all of the data available from customers? Some research reports estimate that there are more than 3 billion data points served up daily among U.S. utility companies. Options for monetizing data include a variety of internal and external use cases that collectively have the potential to radically improve sales and profit margins.

Internal use cases for monetizing data include:

  • Personalization: Personalize marketing across the customer lifecycle from acquisition to retention to win-back to drive superior customer and sales growth
  • Triggered Consumer Alerts: Use smart device and smart meter data to trigger contextual messages that help consumers manage their energy usage. This will result in driving profitability through customer advocacy, customer stickiness after end of contract, and better referral volume
  • Customer Service: Provide better customer service through real time omnichannel insights provisioned across live and digital touch points that lower customer frustrations, improve employee productivity, reduce servicing call minutes and improve profit margins
  • Operational Efficiencies: Improve operations by mining voice of the customer and voice of the employee data to pinpoint lower performing functions and focus on micro operating improvements
  • Offer Optimization: Reduce offer costs by improving promotional offers required to stimulate incremental purchases and reducing unnecessary retention offers which often dilute utility revenues. The combined effect is to improve top line sales.
  • Product Optimization: Improve product reliability and performance by pin pointing delivery gaps and faults that result in substandard energy delivery to customers.

The internal use cases above are in addition to productivity improvements gained by simply becoming more efficient from better using Interactive Voice Response (IVR), automated chat/voice technology, and related digital improvements. The internal use cases are also in addition to simply being a more efficient digital marketer, which by definition will improve profits as media allocation gets optimized over time. This involves shifting budget allocation from broadcast media, outbound direct mail, and telemarketing solicitations to targeted digital media to drive efficiencies and free up funds for smarter and harder working marketing activities.

External use cases for monetizing data include:

  • Consumer Insights: Sell consumer data based on household behavioral and interaction attributes. This is akin to what Allstate did in the insurance industry with its 2016 launch of Arity. An advanced analytics team can create consumer household propensities for things like pool ownership, energy conservation, smart tech adopter, etc. This is of value to third-party companies interested in gaining a deeper understanding of their own customers’ behaviors and preferences
  • R&D purposes: Companies will pay for insights that inform their design and go to market approach for new energy-related products and services
  • Segmentation: Companies are looking for data-driven insights on prospects and customers to drive segmentation and feature messaging

 Going from concept to executing flawlessly is a challenging endeavor. Organizations often lack guidance from the C-suite to fully embrace these concepts and put in motion plans to realize their potential benefits.

Many companies that see the possible benefit of these changes don’t respond to the opportunity, taking on only incremental enhancements instead of developing a holistic strategy with a north star vision and plan to reach that vision. In contrast, industry leaders have a long term strategy and the resources lined up to execute on it.

If your organization has been struggling to capitalize on the potential for monetizing consumer data, here are some areas to consider:

  • Goals and Investments: What’s the use case that you want to pursue? What is aligned with your vision, goals and practical strengths? What’s the investment justification and business value available for taking?
  • Capabilities to Build: What capabilities will you need to realize the intended use cases? What analytics and sciences capabilities will you need? What org structure is required across business, marketing, IT, and data sciences? What data strategy and marketing technology is required to centralize and act on data for profitable effect?
  • Organizational Alignment: Which business units and stakeholders will be needed for success? What are the barriers to alignment? Will your culture support the change? What change management is needed?
  • Regulatory and Privacy: What are the laws and regulations that should be considered? How will you manage consumer opt-ins and the data rights afforded consumers in your operating area? What will be your retention, disclosure, deletion abilities and policies?

At Epsilon we help our clients create data-driven business and marketing strategies as a matter of course, regardless of where they fall on the data maturity continuum.

For those organizations who are starting this process fresh, there is opportunity to take a broad and all-encompassing view toward your consumer data goals and objectives.

Stay tuned for my second post on this topic where we discuss the best ways to approach this challenge and realize the potential benefit from monetizing data.

Topics: Customer Experience, Data

Join the discussion...