Account-based marketing (ABM) is a strategic approach that focuses marketing efforts on targeted accounts rather than individual leads or contacts. The goal of ABM is to personalize messaging and engage key decision makers within strategic accounts to drive revenue. A key component of running effective ABM campaigns is choosing the right targeting strategy to identify and select the accounts to focus your efforts on. There are several types of targeting that can help you run ABM campaigns successfully:
Firmographic Targeting
Firmographic targeting involves selecting accounts based on firmographic attributes like company size, industry, revenue, number of employees, etc. Firmographic data helps you identify accounts that match your ideal customer profile (ICP). For example, if you sell an enterprise level solution, you would target large companies in industries that commonly use your type of solution. Some key firmographic criteria to consider for ABM targeting include:
- Company size – target by employee count or revenue
- Industry – target accounts in your relevant industries or verticals
- Technology used – target companies using solutions you integrate with
- Geography – target locally or in key regions
Firmographic targeting allows you to zero in on accounts that have a higher likelihood of needing your offering based on their profile. It is best paired with other types of targeting.
Behavioral Targeting
Behavioral targeting involves selecting accounts based on certain behaviors, interests, or intent signals. This allows you to identify accounts that are already demonstrating some level of interest in solutions like yours. Some behavioral signals to look for include:
- Website activity – pages viewed, content downloads, time on site
- Ad engagement – clicks, conversions, retargeting
- Search activity – keywords and queries used
- Tech stacks – use of related technologies
- Social media engagement – mentions, shares, follows
Behavioral targeting helps you focus on accounts more likely to buy since they are already researching or showing interest. You can track behavior through web analytics, intent data, or predictive intelligence solutions.
Technographic Targeting
Technographic targeting means selecting accounts based on the technology they currently use. Most ABM programs involve integrating with another technology solution. You can target accounts using tech that aligns with or complements your own. Some technographic targeting options:
- Stack targeting – target companies using specific tech stacks
- Integration targeting – target users of a solution you integrate with
- Data partner targeting – leverage data from tech partners to identify accounts
- Intent graph targeting – target accounts researching related tech topics
This allows you to go after accounts poised for your specific solution based on their tech environment. You can work with data partners, leverage intent graphs, or target by ads/content engagement.
Predictive Intelligence Targeting
Predictive intelligence uses AI and machine learning algorithms to analyze multiple attributes and predict which accounts have the highest propensity to buy. Predictive analytics solutions can ingest firmographic, technographic, and behavioral data to score accounts and identify lookalike profiles of your best customers. Key capabilities include:
- Lookalike modeling – find accounts similar to closed/won deals
- Propensity modeling – assess likelihood that accounts will convert
- Ideal customer profiling – define target account attributes
- Data enrichment – append attributes to fill profile gaps
Predictive targeting is highly accurate and scales account selection. It’s ideal for organizations with robust data that need help surfacing the most valuable accounts.
Intent Data Targeting
Intent data targeting leverages real-time insights into which accounts are demonstrating active research behavior related to products, solutions, or topics. There are two main types of intent data to leverage for ABM:
- First-party intent data – your own behavioral data on what accounts are engaging with your brand in some capacity. Signals they’re interested.
- Third-party intent data – anonymized insights into research behavior from ad networks, DMPs, search platforms, and other sources.
You can target accounts researching topics related to your offering, visiting pages on your site, clicking on ads, attending events, and more. This reveals accounts actively in-market for solutions like yours.
Comparing Different Targeting Approaches
Each type of targeting has its own advantages and disadvantages. Here is a comparison of the different options:
Firmographic Targeting
Pros:
- Scalable way to identify likely buyers based on profile
- Leverages common ICP attributes like industry, revenue, etc
- Data readily available on most accounts
Cons:
- Doesn’t confirm actual interest or intent to buy
- Higher risk of wasting effort on accounts that won’t convert
- Less accurate than behavior or intent-based targeting
Behavioral Targeting
Pros:
- Accounts are demonstrating some existing interest
- Scalable way to target high-potential accounts
- Can integrate data from multiple sources
Cons:
- Data collection and tracking can be complex
- Doesn’t always capture full buyer journey
- Behaviors don’t guarantee purchase intent
Technographic Targeting
Pros:
- Identifies accounts poised for solutions based on tech stack
- Allows for partnerships leveraging shared customer bases
- Accounts likely need integrated or complementary solutions
Cons:
- Not all accounts use the technologies you can target
- Must have accurate tech stack data sources
- Still need to confirm actual buyer intent
Predictive Intelligence Targeting
Pros:
- Analyzes multiple attributes with AI/ML for accuracy
- Continuously improves as algorithms ingest more data
- Scalable way to expand target account list
Cons:
- Requires extensive data inputs and complex modeling
- Quality depends on data quality and model design
- Ongoing vendor costs associated with software fees
Intent Data Targeting
Pros:
- Reveals accounts actively researching related topics
- Zeroes in on accounts demonstrating interest
- Includes both your first-party data and external signals
Cons:
- Requires tools to capture and analyze intent signals
- Data sourcing and modeling can be challenging
- Still need to rate quality of intent for sales follow up
Best Practices for Using Targeting in ABM
To leverage targeting most effectively for ABM, keep these best practices in mind:
Blend multiple targeting methods together
Using only one type of targeting gives an incomplete picture. Combine firmographic, behavioral, technographic, predictive, and intent data for the most accurate view of your total addressable market.
Continuously expand and refresh your target list
Account selection should be an ongoing process. Continuously add net new target accounts as company attributes and signals change over time.
Prioritize accounts with multiple positive attributes
Accounts matching multiple ideal attributes and demonstrating multiple strong intent signals should be highest priority for sales outreach.
Focus ad spend on targeted accounts
Use targeted ad campaigns and personalization to serve relevant messages to your target account list.
Rate accounts with tiered scoring models
Develop an ABM scoring system to objectively rate accounts based on fit, engagement, and buyer signals. Assign tiers so you can prioritize follow up appropriately.
Use data to inform your account-based messaging
Behavioral, technographic, and intent data reveals what messages will resonate most with specific accounts. Personalize campaigns accordingly.
Test and optimize your targeting over time
Evaluate campaign performance by targeted segments to determine what account attributes drive the most success. Refine your targeting accordingly.
Key Takeaways
Here are the key points to remember about leveraging targeting for account-based marketing:
- Utilize firmographic, behavioral, technographic, predictive and intent data for well-rounded targeting
- Blend multiple data types together for the most accurate view of accounts
- Continuously expand your target list with new, high-potential accounts
- Prioritize accounts with multiple positive attributes and buying signals
- Use data-driven targeting to personalize messaging and engage your ideal accounts
With the right blend of targeting data powering your ABM strategy, you can precisely engage the accounts most likely to drive revenue for your business. Advanced targeting enables you to scale your ABM efforts efficiently. By combining firmographic insights with behavioral, technographic and intent data, you can zero in on the highest potential accounts and personalize campaigns to capture their interest. Testing and optimizing your targeting over time ensures your ABM efforts stay on track.
Frequently Asked Questions
What are the main types of targeting for ABM?
The main targeting approaches for ABM include firmographic, behavioral, technographic, predictive intelligence, and intent data targeting. Using a blend of these methods gives the most well-rounded view.
How can you identify target accounts for ABM?
Key ways to identify target accounts include analyzing firmographic data to match your ICP, tracking behavioral signals like site activity, leveraging intent data and predictive scoring, and partnering with tech solutions used by your target personas.
What are some examples of attributes to target by?
Examples of targeting attributes include company size, industry, revenue, website behavior, ad clicks, technologies used, keywords researched, social media activity, lookalike profiling, buyer propensity scores, and real-time research behavior.
How many accounts should you target for ABM?
The ideal number of target accounts depends on your sales capacity and other factors. Many experts recommend starting with at least 300-500 accounts for a robust ABM program. Highly targeted campaigns may focus on a smaller list of 100 premier accounts.
How can you prioritize target accounts for outreach?
Ways to prioritize ABM accounts include scoring based on number of ideal attributes matched, profile completeness, multi-channel engagement, research behavior intensity, predictive lead scores, and technographic fit. Rank accounts into A, B, C tiers for follow up.
Conclusion
Leveraging the right blend of targeting is critical for running successful account-based marketing campaigns. While firmographic data provides a starting point, layering on behavioral, technographic, predictive, and intent signals gives the most accurate and prioritized view of your most valuable accounts. ABM targeting should be an ongoing process, not just a one-time effort. Continuously monitoring your accounts and integrating new targeting data will help you nurture and convert your highest-potential accounts over time. With the ability to measure your targeting ROI and optimize based on performance, ABM can deliver proven pipeline and revenue.