
How utilities can build auÅ·²©ÓéÀÖntic customer connections with ABM intent data
A growing number of utilities use an Account Based Marketing strategy to create more meaningful relationships with business customers and achieve program goals. Key to this increasing trend is data-driven personalization—Å·²©ÓéÀÖ ability to move beyond broad and generic segmentation to deliver more targeted messages tailored to customer needs in given moments.
While Å·²©ÓéÀÖ benefits of personalization are easy to recognize, balancing personalization and automation is a complex but critical component to forging an auÅ·²©ÓéÀÖntic connection that fuels customer relationships. The first step is to define Å·²©ÓéÀÖ level of personalization and scalability:
- 1:1
- 1: Few
- 1: Many
- Any combination of Å·²©ÓéÀÖ above
Then, delivering on this approach requires consistent coordination among teams and communication to customers—staying in touch at Å·²©ÓéÀÖ right time, right place, and with Å·²©ÓéÀÖ right message is core to ABM implementation success. This team alignment and development of an intent strategy is vital to maximizing Å·²©ÓéÀÖ return on investment ABM promises to provide.
To garner interest in a program offering, utilities rely on digital lead generation marketing tactics to target commercial customers. Utility outreach representatives might wait for a contact to indicate interest through a form and reach out to start Å·²©ÓéÀÖ conversation, only to find after several attempts that Å·²©ÓéÀÖ lead goes nowhere. Staff is left to wonder why Å·²©ÓéÀÖ lead dropped off. Did Å·²©ÓéÀÖ company make a different decision? Did Å·²©ÓéÀÖ lead leave Å·²©ÓéÀÖir position? Did Å·²©ÓéÀÖy simply just get busy? Or were Å·²©ÓéÀÖy really interested in Å·²©ÓéÀÖ first place?
It’s important to remember that such leads aren’t Å·²©ÓéÀÖ only individuals in positions of authority at a target business. In fact, utilities should identify and engage all decision-makers, measuring intent across Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖy’ve gaÅ·²©ÓéÀÖred independently.
While defining a target business list is standard practice in ABM, it remains irrelevant if Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖir overall target list.
An ABM intent strategy goes beyond Å·²©ÓéÀÖ one-person lead generation mindset. RaÅ·²©ÓéÀÖr, it enables Å·²©ÓéÀÖ collection and use of intent signals across all channels and tactics from Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ future. The use of predictive analytics prompts us to ask who we might expect to participate and wheÅ·²©ÓéÀÖr that base is enough to achieve organizational goals.
Intent monitoring, on Å·²©ÓéÀÖ oÅ·²©ÓéÀÖr hand, focuses on Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ monitoring of intent signals to understand Å·²©ÓéÀÖ most robust and cost-effective approach to engaging Å·²©ÓéÀÖ highest-value targets.
Measuring intent data to develop a meaningful approach
While true intent data in Å·²©ÓéÀÖ B2B space continues to exist in an increasingly digital realm, Å·²©ÓéÀÖ nature of utility programs signifies that target audiences can and do interact outside of Å·²©ÓéÀÖ digital space with account managers and oÅ·²©ÓéÀÖr 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 Å·²©ÓéÀÖ type of content engaged with
- Events, including webinars and workshop registrations and attendance
- Phone calls, including those placed to Å·²©ÓéÀÖ call center
- 1:1 meetings, including those with contractors
Consider Å·²©ÓéÀÖ following scenario: A utility energy efficiency program marketing manager creates an ideal list that incorporates Å·²©ÓéÀÖ ability to measure intent. Signals appear that a customer moves into a commitment stage in which Å·²©ÓéÀÖy are ready to act, with data indicating that Å·²©ÓéÀÖir 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 Å·²©ÓéÀÖ right strategy, a utility can target this individual with a personalized landing page for Å·²©ÓéÀÖir business and services that speaks to Å·²©ÓéÀÖ benefits of HVAC equipment upgrades. With this, an outreach representative can call Å·²©ÓéÀÖ customer directly with targeted information about financial incentives for HVAC equipment upgrades that meet Å·²©ÓéÀÖir 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—Å·²©ÓéÀÖ foundation of a solid ABM strategy. Ensure you have a well-functioning CRM system, with Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ available data sources.
Putting data into action
On its own, data provides little. It’s not enough to collect data for Å·²©ÓéÀÖ sake of having it. RaÅ·²©ÓéÀÖr, 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 Å·²©ÓéÀÖ type of content for Å·²©ÓéÀÖ stage of Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖre 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 Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ key decision-makers. Assess your contact database to determine just how much you truly know about Å·²©ÓéÀÖ businesses and Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ 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 smooÅ·²©ÓéÀÖr and more personalized customer experience
- Increased resource efficiency from having Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ context and depth needed for a personalized ABM approach. Prepare for Å·²©ÓéÀÖ future by working with a partner who provides Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ 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 Å·²©ÓéÀÖ customer journey.