Common ABM Targeting Issues and Solutions Guide

Key Takeaways:

Choose the right accounts: Build an Ideal Customer Profile (ICP) and use intent data to prioritise high-value targets.
Fix data problems: Regularly clean and maintain your database to ensure accuracy.
Segment accounts effectively: Use tiering systems and AI tools for precise targeting.
Align teams: Improve collaboration between sales and marketing for a 38% boost in win rates.
Track results: Measure engagement, revenue impact, and campaign efficiency to refine your approach.

ABM works - 84% of marketers see better client retention and relationships. Follow these steps to target smarter and achieve stronger results.

ABM: How To Get It Right

How to Select Target Accounts

Choosing the right accounts is crucial for ABM success. Here's how to identify and prioritise the best targets for your strategy.

Building Your Ideal Customer Profile

An Ideal Customer Profile (ICP) helps you zero in on the companies that are the best fit for your solution. As Terminus explains, "An ideal customer profile is a description of the company - not the individual buyer or end user - that's a perfect fit for your solution".

To create your ICP, consider key company traits such as:

Industry and vertical
Annual revenue (minimum ~£16 million)
Employee headcount
Geographic location
Technology stack
Organisational maturity
Budget allocation

For instance, a B2B help desk software provider might focus on:

Region: UK and EU markets
Revenue: ~£16+ million ARR (around $20 million)
Team size: 10+ customer service employees
Customer type: SME-focused businesses
Technical needs: Significant hands-on training requirements

Once your ICP is defined, use behavioural data to fine-tune your target account list.

Using Intent Data for Selection

Intent data plays a big role in ABM targeting, with 42% of B2B marketers relying on it for their strategies.

"When you treat all 'in market' accounts the same and just create buyer journeys based on what prospects are searching for, you work off general assumptions about the organization's needs and pain points. This is the same information that your competitors are responding to, so there is no real differentiation from others using intent data platforms." - Kristina Jaramillo, Personal ABM

To make the most of intent data, validate your targets by analysing account performance and engagement. Group accounts into three tiers based on their intent signals:

Tier 1 – High Intent: Actively researching with multiple engagements.
Tier 2 – Moderate Intent: Matches your ICP with occasional engagement.
Tier 3 – Low Intent: Fits your ICP but shows limited activity.

Tailor your content strategy to address the specific challenges and interests revealed by these intent signals.

Account Selection Tools

ABM platforms simplify the selection process by bringing all your data together. Look for tools with features like:

Intent signal tracking
Account scoring
Multi-channel engagement tracking
Consolidated reporting
Website personalisation

These tools can help you focus your efforts on the accounts most likely to convert.

Fixing Data Quality Problems

Accurate data is the backbone of effective ABM. Without it, even the best account selection strategies can fail. Poor data quality can severely impact ABM efforts, with up to 25% of B2B database contacts containing critical errors and 62% of organisations relying on marketing data that's up to 40% inaccurate.

Data Quality Issues

Some common data quality challenges include:

Inaccurate Information: Outdated or incorrect company details, contact information, and firmographic data.
Incomplete Records: Missing key fields such as revenue or employee count.
Duplicate Entries: Multiple records for the same account or contact.
Information Decay: Around 30% of customer data becomes outdated every year.
Inconsistent Formatting: Differences in data formats across systems, complicating analysis.

These issues aren't just inconvenient - they can directly impact revenue, with poor data quality affecting as much as 25% of revenue.

Data Cleaning Methods

To address these challenges, establish a solid data cleaning process:

Regular Database Maintenance

Review your database every 3–6 months to check for accuracy, completeness, and relevance.
Use automated validation checks to spot formatting issues, missing fields, and duplicates.
Implement real-time data verification at the point of entry to catch errors early.

"You sometimes have to accept it's never going to be perfect. There's no such thing as 'perfect' data, and as soon as it becomes perfect, normally it's outdated and stale."
Sid Kumar, AVP of Revenue Operations, GTM Strategy & Planning at Databricks

One example is Tide, a UK-based digital bank, which reduced its 50-day manual data verification process to just hours by using automated validation rules and bulk processing through Atlan Playbooks.

These practices set the stage for reliable data management rules that keep your database in good shape.

Data Management Rules

Rule Category	Key Actions	Expected Outcome
Data Entry	Standardise formats, use dropdown menus, require essential fields	Consistent data capture
Data Updates	Schedule regular reviews, automate enrichment	Up-to-date information
Quality Control	Run automated validations, monitor error rates	Fewer inaccuracies

"RevOps serves as a single source of truth; it should govern your GTM motion, and your GTM notion needs to impact your revenue. Data-driven insights and decision-making underpin these three notions."
Jeff Ignacio, Head of GTM Operations and Growth at Regrow Agriculture

Key steps include:

Setting clear data collection standards.
Establishing regular cleaning schedules.
Assigning team responsibilities.
Monitoring quality consistently.
Defining procedures for updates.

While perfect data is unrealistic, maintaining 70–80% accuracy is enough to make informed ABM decisions. Reliable data not only improves account targeting but also enhances segmentation and campaign tracking, which will be discussed further later.

Better Account Segmentation

Effective segmentation is key to achieving accurate ABM targeting. By segmenting accounts properly, organisations can target more effectively and improve their campaign outcomes.

Account Tier System

Divide accounts into three tiers based on their value and strategic importance.

Tier Level	Characteristics	Approach
Tier 1 (Strategic)	High-value accounts with complex needs	One-to-one personalised strategies
Tier 2 (Growth)	Medium-sized accounts with growth potential	One-to-few targeted campaigns
Tier 3 (Scale)	Smaller accounts with standardised needs	One-to-many programmatic strategies

"Effective account tiering strategically allocates resources, focusing disproportionately on your highest-value accounts... ABM is about proper resource allocation in a world where B2B marketers are being asked to accomplish more with less." - Jennifer Hughes, Principle Digital Expert, Demandbase

Research indicates that focused targeting through account tiering can cut unproductive sales time by 50% while boosting revenue by over 200%. After categorising accounts, tailor your messaging to address the specific needs and roles within each organisation.

Buyer Role Segments

Understanding the roles within a buying committee is essential for crafting targeted messages. Each role requires a unique approach.

Key roles to consider:

Decision Makers: Have the final say on purchases.
End Users: Use the solution daily and influence its adoption.
Budget Holders: Manage the financial resources.
Champions: Advocate for your solution internally.
Blockers: May resist or challenge the purchase decision.

"Marketing is always trying to walk a fine line between helpful and creepy when it comes to highly segmented targeting." - Isaac Ware, Director of Demand Generation at UserGems

To implement this, map out the full buying committee and understand how each member influences the decision. Then, use AI tools to refine these segments for dynamic and precise targeting.

AI-Powered Segmentation

AI takes traditional segmentation to the next level by analysing real-time behavioural data. Machine learning identifies patterns across large datasets, such as website activity, social media interactions, purchase history, and firmographic or technographic details.

For example, ChatSpot uses AI to analyse customer interactions in real time, offering personalised recommendations that enhance engagement and boost conversion rates.

Steps for effective AI-powered segmentation:

Maintain high-quality, up-to-date data.
Set up validation processes to ensure accuracy.
Regularly review and adjust segmentation criteria.
Continuously monitor segment performance.

With 84% of marketers identifying ABM as crucial for improving customer relationships, precise segmentation plays a critical role in achieving long-term success.

Tracking and Improving Results

Use data-focused KPIs to measure how well your ABM targeting is working.

Key Success Metrics

Metric Category	Key Indicators	Measurement
Account Engagement	Account engagement score, penetration rate	Interaction quality and reach within target accounts
Revenue Impact	Customer lifetime value, average deal size	Financial outcomes and ROI
Pipeline Health	Sales cycle length, pipeline velocity	Speed and efficiency of deal progression
Campaign Efficiency	Customer acquisition cost, deal conversion rate	Resource use and targeting effectiveness

"Success metrics help marketers blaze to ultimate marketing triumphs, revealing the worth of their investments and overcoming the pitfalls of measuring campaign performances." - machintel.com

To measure account engagement effectively, track multiple touchpoints like website visits, downloads, email interactions, and event participation. This gives a clear picture of which accounts are responding best to your efforts.

The next step? Test your campaigns to refine your strategy.

Testing Target Campaigns

Systematic testing is essential to improve targeting accuracy and campaign results. With 81% of marketers reporting better ROI from ABM compared to traditional marketing methods, tweaking campaign elements is a must.

Focus your testing on these areas:

Content Personalisation: Experiment with varying levels of account-specific messaging to see what resonates.
Channel Mix: Compare the effectiveness of different communication platforms.
Timing and Frequency: Identify the best times and intervals for reaching out.
Call-to-Action Variations: Test different CTAs to find the most effective ones.

"The key is to develop messages that directly address the specific concerns, goals, and needs of each decision-maker. A good approach grabs their attention, proves your expertise in their industry, and distinguishes you from competitors." - inboxinsight.com

Use these insights to keep your target lists sharp and relevant.

Updating Target Lists

Keep your target account lists up to date by analysing performance data and market changes. Pay attention to these factors:

Engagement Patterns: Track website visits, content downloads, and email responses to identify active accounts and adjust priorities accordingly.
Sales Cycle Analysis: Look at sales cycle lengths within different segments; shorter cycles often indicate more effective targeting and messaging.
Contract Value Trends: Monitor contract values by segment. If values stagnate, revisit your technographic and firmographic data to pinpoint areas for improvement.

Conclusion

Using structured methods can solve many common challenges in ABM targeting. This guide has provided practical steps to improve targeting precision and campaign results.

Problem-Solution Overview

Here’s a quick look at the main challenges and their fixes:

Challenge	Solution	Impact
Poor Account Selection	Develop a data-driven Ideal Customer Profile and use intent signals	92% of companies with advanced ABM strategies report better ROI
Data Quality Issues	Conduct regular data audits and focus on key metrics	30% faster 'time to opportunity'
Skills Gap	Offer targeted training and recruit specialists	Tackles a major issue for 34% of UK marketers
Marketing-Sales Misalignment	Set shared goals and hold regular strategy discussions	Improves collaboration and team alignment

Action Plan

The steps below summarise the guide’s key recommendations into a practical plan:

Refine Target Account StrategyFocus on selecting accounts backed by data and intent signals.
Strengthen Data ManagementRegularly audit your data to ensure it stays accurate and relevant.
Enhance Team SkillsClose skill gaps with structured training. According to Demand Metric, ABM-specific training over a year can increase revenue growth by 30%.
Track and AdjustMonitor engagement metrics and financial outcomes, paying attention to account-level interactions that show buying interest.