How utilities can understand the business behind the meter

As utilities plan for the future, many are discovering that understanding future energy needs requires understanding the businesses creating that load growth.

For decades, utilities have built sophisticated intelligence about energy use: which buildings consume the most energy, which customer segments have the highest savings potential, and which technologies are most likely to deliver measurable results. That intelligence remains essential for infrastructure planning, customer programs, and regulatory objectives.

But it is no longer enough on its own. Many of the forces now shaping utility strategies begin long before a meter shows a change in usage or a customer submits a program application. A manufacturer may announce a new production line. A hospital may invest in resilience planning. A data center developer may begin assessing new locations. 

Utilities that recognize and connect these signals earlier will be better positioned to support customer needs, prioritize investments, and prepare for future demand. Increasingly, that means understanding not only buildings, equipment, and usage patterns, but also the business priorities, investment cycles, stakeholder dynamics, and relationship potential behind them.

In that sense, the business customer is becoming part of the grid edge.

When people talk about the grid edge, the conversation often centers on technology: solar, storage, electric vehicles, and distributed energy resources (DERs). But technology adoption does not happen in isolation. Businesses decide when to invest. They evaluate risk, weigh competing priorities, build internal support, and determine whether a utility offering aligns with broader operational or strategic objectives.

The decision to participate in an energy program can involve facilities, finance, operations, sustainability, and executive leadership, each viewing the same opportunity through a different lens. Budget cycles, capital planning, stakeholder alignment, operational constraints, and timing can all determine whether a project moves forward.

For utilities, the implication is clear: effective engagement requires understanding the customer’s business context well enough to reach the right people at the right time, with information that is actually useful.

The good news is that utilities are not starting from scratch.

Every day, business customers leave signals about what they care about, what challenges they are facing, and what opportunities they may be evaluating. Program participation, account manager conversations, digital engagement, market characterization research, customer surveys, and operational interactions all provide pieces of the picture.

The challenge is that those signals remain disconnected, separated by organizational structure. Planning teams understand future growth opportunities within a sector. Account managers know a customer’s priorities and concerns. Marketing teams see emerging patterns in customer engagement. Program teams understand participation history and technical potential.

Individually, those signals may not reveal much. Together, they provide context. The customer experiences a single relationship with the utility, whereas the utility often experiences a series of disconnected interactions.

That disconnect becomes more consequential as customer relationships become more strategic. Electrification, resilience, demand flexibility, DERs, and long-term account planning all require a deeper understanding of customer needs than traditional program participation alone. Most utilities already possess many of the ingredients required to build that understanding. What is missing is a framework for bringing those raw materials together, which is where business intelligence comes in.

A common mistake is assuming that any individual signal is highly predictive on its own. Most are not. For example, an email click does not necessarily indicate intent, a facility expansion does not automatically create a program opportunity, and previous participation does not guarantee future participation.

The value emerges when signals are viewed collectively. That is the essence of business intelligence: connecting customer, stakeholder, market, and engagement signals to create a more complete understanding of opportunity and decision-making at the account level.

In practice, this means looking beyond individual data points to understand what may be driving behavior. ICF’s work in market characterization, business analytics, and customer insights has shown that seemingly similar customers can represent very different opportunities once you look beyond a single source of data. Government customers, for instance, may combine substantial savings potential with some of the largest energy users in a territory, yet show relatively low participation. At first glance that looks like an awareness challenge. In reality, the barrier may be budget cycles, stakeholder alignment, approval processes, or messaging that does not reflect how that audience evaluates investment decisions. Understanding those dynamics can be more valuable than identifying another marketing opportunity.

The same principle becomes even more important at the account level, where the most important difference between two customers is often invisible in usage data. Two customers with comparable usage, eligibility, and geographies can represent entirely different opportunities if one operates a single site and the other is one facility in a national portfolio. In the second case, a single relationship may influence decisions across dozens of buildings.

Business intelligence is not about predicting every customer decision. It is about providing context, helping utilities ask better questions, identifying where additional conversations may be valuable, and prioritizing limited resources more effectively.

When many people hear the term account-based marketing, they think of highly targeted campaigns. Those capabilities have value, but the larger opportunity for utilities is broader: ABM provides a framework for organizing intelligence around the account itself.

Instead of organizing information around programs, organizing intelligence around the customer relationship changes the questions utility teams are able to ask:

• What do we know about this business across all of our interactions?
• Which people influence decisions?
• Which sites matter most?
• What business priorities appear most important?
• Where could coordinated engagement create value?

More than a marketing tactic, this approach becomes an organizing discipline for business intelligence, giving marketing, account management, analytics, planning, and program teams a shared framework for understanding the customer relationship rather than viewing customers through isolated functions.

Business intelligence also creates an opportunity to think differently about customer portfolios.

As business customer relationships become more important to utility strategy, there is significant benefit to considering relationship portfolios as well. Not every commercial customer creates value in the same way. Some represent significant energy efficiency potential. Others are major employers, economic development priorities, rapidly growing organizations, strategic community partners, or significant future load opportunities.

Relationship value is also dynamic: a customer that appears relatively unimportant today may become highly significant as it expands, electrifies, invests in new facilities, or changes its operating model. Another customer may be valuable not only because it is likely to complete a project this year, but because the relationship could create opportunities across multiple programs, sites, or years. The objective, then, becomes understanding which relationships will create value over time, and which accounts deserve greater strategic attention.

Understanding which relationships matter is only the first step. The next step lies in helping utilities engage more effectively, rather than building a better customer profile.

Most utilities can identify high-potential commercial accounts. Far fewer have a consistent way to determine what conversation is most useful next, and that distinction matters. Utilities often focus on which email to send, which offer to promote, and which account should receive outreach. Business customers are working through different questions, though: Is this investment worth pursuing? Is the timing right? How do we justify it internally? What risks need to be addressed? What information is missing?

The next era of utility engagement may therefore depend on identifying the next best conversation. What that conversation looks like depends on who is in it:

• A facility leader may need help developing an internal business case.
• A finance stakeholder may need greater cost certainty.
• A sustainability leader may want to connect utility programs to corporate goals.
• An operations team may need confidence that a project will not disrupt production or service.
• A large account may need one coordinated conversation spanning efficiency, electrification, resilience, and rates rather than separate outreach from separate teams.

These considerations form the difference between customer engagement as communication and customer engagement as decision support.

In a more account-centered model, marketing's role extends beyond generating participation.

While engagement data is not definitive evidence of customer intent, it provides valuable clues about topics customers are exploring and questions they are beginning to ask. This makes marketing an increasingly important source of business intelligence. Because marketing engages customers at scale and across different business groups, it often has the earliest visibility into emerging interests, concerns, and priorities. Patterns of engagement can reveal not only which topics are attracting attention, but also how interest is spreading across an organization. When multiple stakeholders from the same account consume related content over time, it can signal that an issue is moving from individual curiosity to organizational consideration.

Marketing helps shorten the distance between customer behavior and commercial action. Insights from content engagement, event participation, and digital interactions can help account teams identify emerging needs, anticipate future conversations, and tailor outreach around topics customers are already exploring. Marketing becomes not only a creator of demand, but also a strategic sensor for the organization, helping sales and client teams understand where customer priorities may be headed before those priorities are explicitly articulated.

Key account managers (KAM) remain essential because strong customer relationships depend on judgment, experience, and trust. As utilities generate more data through analytics and AI, business intelligence can give KAMs a more complete view of customer priorities, engagement, opportunities, and history in one place, helping them understand where customers are in their decision-making process. AI can identify patterns, connect information, and surface insights at scale, but it cannot fully interpret the organizational dynamics, competing priorities, and human factors that shape business decisions. The greatest value comes from combining AI-generated context with human judgment, enabling account managers to make better decisions and have more relevant customer conversations.

For years, utilities have asked which customers are most likely to participate. That remains an important question, but a broader one is emerging: Which business customers will shape our future, and how well do we understand them today?

Most utilities already possess many of the building blocks needed to answer it: customer data, account relationships, program histories, market insights, engagement signals, and operational knowledge. The opportunity is to connect those pieces into a more complete understanding of the business customer.

Utility leaders can start by asking:

• Do marketing, planning, account management, and program teams use different criteria to define a high-value commercial account?
• Does valuable customer intelligence still live primarily in the experience of individual account managers?
• Can teams explain what conversation is most useful next without consulting multiple systems and reports?
• Are strategic account priorities based solely on historical participation, or on a broader understanding of business relevance and growth potential?
• Do your most successful customer conversations occur through repeatable processes, or through individual efforts to connect disconnected information?

ICF’s Sightline® was designed to help utilities bring fragmented customer, market, and engagement signals into a more complete account view. The platform expands beyond a business intelligence foundation to connect planning, engagement, execution, and performance through capabilities, such as market characterization, predictive analytics, and performance analytics. Our application of these approaches has recently been recognized through both ANA Data Excellence and MarTech Breakthrough awards.

Rather than collecting more information, the next step for utilities is creating a clearer understanding of the information they already have. And then using that understanding to build stronger relationships, engage with greater context, and support better customer decisions.

Because the next era of utility strategy will not be defined only by what happens behind the meter. It will be defined by how well utilities understand the businesses behind the meter.