How utilities can build authentic customer connections with ABM intent data

It’s important to remember that such leads aren’t the only individuals in positions of authority at a target business. In fact, utilities should identify and engage all decision-makers, measuring intent across the entire deciding committee. After all, we know that a business can have between six to 10 decision-makers, each armed with four to five pieces of information that they’ve gathered independently. 

While defining a target business list is standard practice in ABM, it remains irrelevant if the decision-making committee at a company lacks interest. How many tries are attempted? How much time is allowed to lapse? What continued resources are invested? In such cases, utilities must be ready to reprioritize and re-evaluate their overall target list.

An ABM intent strategy goes beyond the one-person lead generation mindset. Rather, it enables the collection and use of intent signals across all channels and tactics from the many decision-makers at a business.

But it’s not just about collecting or measuring intent. A utility needs to be able to act—in real time—when interest is shown. To get started, let’s define what we mean by “intent.”

What do we mean by intent?

It’s important to note that intent is not the same as predictive analytics.

Predictive analytics play a crucial role in any utility’s ability to develop its ideal customer profiles (ICPs) and key target lists. They inform who makes a good fit and provide a guide for historical success, using those indicators to anticipate what is ideal for the future. The use of predictive analytics prompts us to ask who we might expect to participate and whether that base is enough to achieve organizational goals.

Intent monitoring, on the other hand, focuses on the current behaviors of a target audience to anticipate future interests and needs. This could mean monitoring business customers new to your target list or those existing business customers who are primed for cross- or upselling opportunities. An ABM intent strategy should layer predictive analytics models with the monitoring of intent signals to understand the most robust and cost-effective approach to engaging the highest-value targets.

Measuring intent data to develop a meaningful approach

While true intent data in the B2B space continues to exist in an increasingly digital realm, the nature of utility programs signifies that target audiences can and do interact outside of the digital space with account managers and other influencers including contractors, distributors, and manufacturers. Because of this, non-digital environmental factors need to be taken into consideration. When it comes to measuring intent data, it’s important for utilities to consider all channels, including:

• Paid media, including search
• Websites and landing pages, including form fills, file downloads, sign-ins, and specific page views
• Emails, including opens and clicks and evaluated based on the type of content engaged with
• Events, including webinars and workshop registrations and attendance
• Phone calls, including those placed to the call center
• 1:1 meetings, including those with contractors

Consider the following scenario: A utility energy efficiency program marketing manager creates an ideal list that incorporates the ability to measure intent. Signals appear that a customer moves into a commitment stage in which they are ready to act, with data indicating that their strongest interest is in HVAC equipment. We know this by measuring intent related to keyword searches. In this case, we can ascertain that someone who searches for “energy efficiency” is not as likely to act as someone who searches for “HVAC equipment savings.” With the right strategy, a utility can target this individual with a personalized landing page for their business and services that speaks to the benefits of HVAC equipment upgrades. With this, an outreach representative can call the customer directly with targeted information about financial incentives for HVAC equipment upgrades that meet their specified needs.

Such a scenario is closer to actualization than many realize. It only requires a few necessities.

The first is a high-performing customer relationship management (CRM) system—the foundation of a solid ABM strategy. Ensure you have a well-functioning CRM system, with the proper data flow, training, and dashboard visualizations in place to make efficient and effective use of intent signals. To start, you’ll need to know who you are trying to target.

To build a contact list and measure intent related to those contacts, you’ll need to consider the available data sources.

Putting data into action

On its own, data provides little. It’s not enough to collect data for the sake of having it. Rather, utilities should know how to use this vital information. Beyond measuring and monitoring intent data, it’s important to establish processes to understand when to act on data at each stage of a customer’s journey. And that will undoubtedly require you to build a deep content library.

Insights, for example, can inform strategies such as the type of content for the stage of the journey a customer is in. By merging firmographics and psychographics with behavior, you can introduce intent scoring and assign weights and prioritization for outreach and marketing teams. This process involves layering an ideal customer profile with decider personas to include a measurement and score of implicit factors. While there are many implicit and explicit measures worth measuring, only a few are needed to create actionable insight.

Explicit factors: These are hard facts. Set parameters around ICPs and personas like firmographics to include things like job function, company size, and business sector type.

Implicit factors: These are the behaviors documented by your target customers. This includes downloads of papers, email open- and click-through rates, and webinar attendance.

To get started, consider your ideal business targets and define the key decision-makers. Assess your contact database to determine just how much you truly know about the businesses and the decision-makers.

• Identify no more than five criteria with which to begin.
• Ensure at least 65% of your database has consistently identified fields that you want to weigh.
• Establish your desired evaluation time frame for each criterion (i.e., month, week, year).
• Be selective in the interaction and piece of content—don’t evaluate every interaction and select no more than 15 to start.

The benefits of implementing a robust ABM intent data strategy

By properly harnessing an ABM approach, utilities can make strategic and data-driven decisions that improve efficiencies, increase customer confidence, and achieve—and often exceed—goals. The benefits of an intent strategy include:

• More accurate pipelines and forecasts
• Greater satisfaction and trust due to a smoother and more personalized customer experience
• Increased resource efficiency from having the entire team work on larger and more accurate intelligence
• Ability to monitor markets and understand customers on a new and more meaningful plane

Intent data provides the context and depth needed for a personalized ABM approach. Prepare for the future by working with a partner who provides the right technology to accurately create target lists and develop a deep content library. Partners with proven deep-bench experience in research can help utilities craft the best value propositions for a wide array of business types and business decision-makers. Utilities that build trusting relationships with B2B customers benefit from continued growth and customer loyalty as the energy landscape rapidly evolves. Working with a partner that can help to properly leverage intent data will ensure that you have working and meaningful insight at every stage of the customer journey.