Energy companies are under pressure to contain customer churn in the wake of deregulation and growing competition. Along with this, the rise of new energy sources, increasing demand for green energy for personal use, and evolving customer needs are compelling energy providers to devise ways to attract and retain customers.
The energy sector has come a long way from its avatar as an investor-owned, vertically integrated monopoly utility (IOU) that provided generation, transmission, local distribution, and billing/collections. The challenge now is to deliver an Amazon or Uber-like experience for demanding customers. There’s a race underway to win new customers but these companies also realize the need to retain customers. Fortunately, these companies can leverage the power of data to prevent churn and attract new customers.
Data and energy companies
Data and energy companies are old friends. However, earlier, managing data meant simply processing analog meter readings and customer billing information. Today, the energy company has to address growing volumes of data being acquired at increasing velocity and representing a far greater variety of data points. This opens up the need to build increased capabilities to mine, store, and analyze data. The promise is, that will allow these energy companies to build customer acquisition, boost stickiness, and prevent churn.
Enhance customer experience
We are in the customer experience age. The customer now wants all experiences to mimic the retail experience they have become used to. Amazon, for example, became the benchmark of customer experience by making it incredibly easy for the online shopper to find new products, know all about them, and complete the purchase, even for needs they didn’t know they had! Amazon did this by leveraging data and tracking consumer behavior to capture valuable information regarding their attitudes, purchase history, and drivers of purchase decisions.
There’s no denying the energy sector is vastly different from the retail sector so energy companies need to identify the data points that matter to their personalization initiatives to create relevant and contextual moments of delight for their customers. Identifying potentially environmentally conscious customers and offering them photovoltaic installations or energy saving plans, for example, can be driven by data.
Data analytics presents the unique opportunity to identify new opportunities by examining trends, market shifts, changing customer behaviors. Energy companies can identify the gap between customer experience and expectation by understanding consumption patterns with analytics and create offers that drive value.
With contextual data-driven personalization, energy companies can offer experiences aligned to the moments that matter in the customer journey. These experiences positively impact customer experience and help in reducing customer churn, increasing retention, and drive customer advocacy.
Lower customer acquisition cost
With data, energy companies can create clearer brand differentiation and drive strategies that lower the customer acquisition cost. Whether it is reducing customer price sensitivity, setting pricing premiums, or identifying factors that drive customer interest, satisfaction, and advocacy, data is a valuable weapon for energy companies.
Data gives energy companies the power to conduct clustering and affinity analysis to identify cross-selling and upselling opportunities. It helps these companies identify the characteristics of profitable customer segments to drive their customer acquisition strategies through better-placed media and ad buys. This becomes a valuable capability as it helps companies augment online customer acquisition efforts and reduce their dependence on face-to-face strategies as COVID-19 mandates demand the move to online channels.
Try price-adjustment campaigns and reduce the cost to serve
Energy companies also need to improve their capabilities to set the right prices for their consumers and drive price adjustment campaigns to drive customer retention. These decisions, however, have to be deeply rooted in data to drive customer satisfaction and enhance customer retention.
Using advanced data analysis, energy companies can drive successful customer segmentation and run appropriate price adjustment campaigns. They can also identify opportunities for differentiated pricing based on the customers’ ability to pay and usage patterns.
Data can also highlight the likelihood of defaults, identify at-risk customers and motivate these customers to prepay. This translates into reduced cost and better service through payment reminder messages sanitized to fit the specific circumstances of the consumer.
Drive operational efficiency
Data helps energy companies drive operational efficiency in a deregulated market. This can translate to higher customer acquisition and customer retention, along with delivering major cost savings.
Research suggests that the annual cost of weather-related power outages to the U.S. economy ranges between $18 – $33 billion. By leveraging the power of data analytics, energy companies can proactively identify operational remedies for preventable outages and substantially improve uptimes.
They can also make customer communication more proactive, employ digital solutions to invest in systems and technologies such as fault isolation systems, and enable automated switching in the distribution system to reduce sustained outages, thereby improving performance and directly driving customer satisfaction.
Optimize demand response management
Customers are leaning towards green energy and want to use energy efficiently. Energy management thus becomes important in customer retention and acquisition. Successful energy management creates a balance between demand and supply and avoids the challenges caused by both high and low demand rates.
Data analytics can help energy companies fine-tune and optimize their demand response management by studying and mapping energy use and patterns. With these insights, companies can educate customers on how to use energy best, what kind of energy model or pricing plan meets their needs accurately, or shift customers to different pricing programs. This helps energy companies achieve a balance in energy provisioning while meeting customer expectations.
In Conclusion
There is tremendous potential for data in the energy sector to drive efficiencies, add customers, and improve profitability by driving customer satisfaction. With data, we can get a comprehensive 360-degree view of the customer, transparently view transactions, and identify powerful means to create relationships that drive customer preference in a value-driven, multi-dimensional energy market.
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