Generating Highly Qualified Leads: Maximising Success with Account-Based Lead Scoring

Account-Based Marketing (ABM) has redefined how businesses engage with high-value accounts through a targeted and personalised approach. A critical component of successful ABM is account scoring, which involves evaluating and prioritising accounts based on their potential to convert and generate revenue. This article explores ABM scoring, its steps, opportunities, the role of AI in scoring, and why it is advantageous for businesses.

What is ABM Scoring?

ABM scoring is a strategic process used to evaluate and prioritise target accounts based on specific criteria that indicate their potential value to the business. Unlike traditional lead scoring, which focuses on individual leads, ABM scoring considers the entire account, encompassing multiple stakeholders and their interactions with the company. This holistic approach ensures that marketing and sales efforts are concentrated on the most promising accounts, enhancing the efficiency and effectiveness of campaigns​​.

Steps in ABM Scoring

• Identify Ideal Customer Profile (ICP): The first step is to define the characteristics of accounts that are most likely to benefit from your products or services. This includes factors such as industry, company size, revenue, geographic location, and specific pain points​​.
• Data Collection and Integration: Gather data from various sources, including CRM systems, marketing automation tools, social media, and third-party data providers. This data should cover firmographics, technographics, engagement metrics, and intent data​​.
• Define Scoring Criteria: Establish the criteria for scoring accounts. This can include engagement data (e.g., website visits, email opens), firmographic data (e.g., company size, industry), technographic data (e.g., technology stack)​ and intent data (e.g., buying signals).
• Score Accounts: Use the defined criteria to assign scores to accounts. This can be done manually or through automated systems that aggregate and analyse the data. The scoring should reflect the account’s potential value and likelihood to convert​.

To effectively score accounts, it is crucial to weight each criterion based on its significance, ensuring the total weight adds up to 100%. Once the weighting is determined, create a scoring scale, such as from 1 to 100. Each criterion will receive a specific number of points, which are then adjusted by the assigned weight.

For instance, consider intent data. Assign points based on the level of buying signals:

• Little or no buying signals: 10 points
• Weak buying signals: 40 points
• Medium buying signals: 70 points
• Strong buying signals: 100 points

Given that intent data is highly relevant, you might weight this criterion at 30%. If an account scores 100 points for strong buying signals, multiply by the 30% weight, resulting in 30 points towards the overall score. This method ensures each account is evaluated comprehensively, with emphasis on the most critical factors.

• Prioritise and Segment Accounts: Based on the scores, prioritise the accounts and segment them into tiers (e.g., high, medium, low priority). This helps in allocating resources and tailoring marketing and sales efforts accordingly​​. Remember, we should allocate the most resources to the accounts that are most likely to make high-value purchases from our products or services.
• Continuous Monitoring and Adjustment: Regularly review and update the scoring model to reflect changes in the market, customer behaviour, and business objectives. This ensures that the scoring remains accurate and relevant over time​​.

Opportunities with ABM Scoring

1. Improved Resource Allocation: By identifying high-value accounts, businesses can allocate their resources more efficiently, focusing on accounts that are most likely to generate revenue​. In other words, the sales and marketing teams will avoid wasting valuable time on accounts that are unlikely to yield a return.
2. Enhanced Customer Engagement: ABM scoring allows for personalised and targeted engagement strategies, which can lead to higher levels of interaction and conversion rates​​. Let's be honest, everyone appreciates being engaged through topics they find interesting.
3. Better Sales and Marketing Alignment: ABM scoring fosters collaboration between sales and marketing teams, ensuring that both are working towards common goals and targeting the same high-value accounts​​.
4. Increased Revenue and Growth: By focusing on the most promising accounts, businesses can drive higher revenue and growth, maximising the return on investment for their marketing efforts​.

The Role of AI in ABM Scoring

Artificial Intelligence (AI) and machine learning have significantly enhanced the capabilities of ABM scoring by automating data collection, analysis, and scoring processes. AI-driven tools can analyse vast amounts of data in real-time, identify patterns, and provide predictive insights that improve the accuracy of scoring models​​. Innovative ABM platforms such as 6sense, HubSpot, Apollo, and Demandbase now offer advanced capabilities that leverage AI to automate account scoring. These platforms provide powerful tools for identifying and prioritising high-value accounts, significantly enhancing the efficiency of sales and marketing teams (we will explore these platforms in detail in another article).

1. Predictive Analytics: AI can predict which accounts are most likely to convert based on historical data and current engagement metrics. This helps in prioritising efforts towards the most promising accounts​​.
2. Real-Time Insights: AI tools provide real-time insights and alerts, enabling sales and marketing teams to engage with accounts at the right moment, increasing the chances of conversion​.
3. Enhanced Personalisation: AI can analyse individual preferences and behaviours within an account, allowing for highly personalised engagement strategies that resonate with each stakeholder​​.

Why ABM Scoring is Beneficial

1. Higher ROI: ABM scoring ensures that marketing and sales efforts are focused on high-value accounts, leading to higher conversion rates and a better return on investment​​.
2. Efficient Use of Resources: By prioritising accounts based on their potential value, businesses can use their resources more efficiently, avoiding wasted efforts on low-potential leads​​.
3. Stronger Customer Relationships: Targeted and personalised engagement strategies foster stronger relationships with key accounts, leading to higher customer satisfaction and loyalty​​.
4. Improved Sales Performance: With a clear focus on high-priority accounts, sales teams can perform more effectively, closing deals faster and increasing overall sales performance​​.

Conclusion

Account Based Marketing scoring is a powerful approach that enables businesses to strategically target and engage with high-value accounts. By leveraging AI and data-driven insights, companies can enhance their ABM strategies, improve resource allocation, and drive significant growth. As the business landscape continues to evolve, adopting ABM scoring will be crucial for organisations looking to stay competitive and achieve their sales and marketing goals.