From Zero to One: Account-based GTM Powered by Intent Data for Inside Sales
This article examines how intent data transforms inside sales by powering account-based GTM strategies. It covers the fundamentals of ABM, the value of intent signals, practical use cases, technology integration, and actionable best practices. Learn how to identify, engage, and convert high-value accounts for predictable growth.
Introduction: The Evolution of Inside Sales and Account-Based GTM
Inside sales has rapidly transformed over the last decade. Gone are the days when sales teams would rely solely on cold calls and generic outreach. The modern B2B environment demands precision, personalization, and data-driven strategies. In this context, the intersection of account-based go-to-market (GTM) approaches and intent data represents a significant leap—from zero to one—in sales effectiveness. This article explores how organizations can harness the power of intent data to supercharge account-based GTM strategies, elevate inside sales performance, and drive predictable growth.
Understanding Account-Based GTM: A Strategic Overview
Account-based GTM is a strategic approach that aligns marketing, sales, and customer success to focus on high-value accounts rather than casting a wide net. Instead of treating each lead equally, ABM prioritizes accounts based on fit and potential value, tailoring outreach to their specific needs and pain points. This strategy is particularly effective in complex B2B sales cycles where buying committees and multi-step decision processes are the norms.
Alignment: ABM requires tight coordination between marketing and sales teams to create a unified message.
Personalization: Outreach and engagement are tailored to each account, increasing relevance and resonance.
Efficiency: Resources are focused on accounts with the highest likelihood of conversion and expansion.
However, even the most carefully selected account lists can fall short without signals that indicate which accounts are actually in-market or actively researching solutions like yours.
The Role of Intent Data in Modern Sales
Intent data is information that signals an organization’s interest in a particular topic, product, or solution. This can include online behaviors such as web searches, content downloads, page visits, and engagement with industry content. By capturing and analyzing these digital footprints, intent data providers can surface accounts showing early buying signals, empowering sales teams to prioritize outreach with precision.
First-party intent data: Derived from your own digital properties, such as website visits, content downloads, or email engagement.
Third-party intent data: Collected from external sources—such as industry publications or review sites—where prospects show interest in topics relevant to your solution.
The Business Case for Intent-Driven ABM in Inside Sales
Why do so many ABM programs struggle to achieve true scale and impact? The answer is often a lack of actionable insights about which accounts are ready to engage. Intent data bridges this gap, enabling inside sales teams to:
Identify in-market accounts earlier: Engage accounts before competitors do, shortening sales cycles and increasing win rates.
Personalize outreach at scale: Craft messaging that speaks directly to the topics and pain points prospects are researching.
Optimize resource allocation: Focus sales and marketing efforts on accounts that show real buying intent, reducing wasted activity.
Improve forecasting accuracy: Better understand pipeline health and forecast revenue based on real-time buying signals.
Ultimately, intent-driven ABM empowers inside sales teams to move from reactive selling to proactive, data-driven engagement.
Key Components of an Account-Based GTM Framework Powered by Intent Data
Defining the Ideal Customer Profile (ICP): Begin by identifying the firmographic, technographic, and behavioral characteristics of your best-fit accounts. This provides a foundation for both account selection and messaging.
Account Selection and Tiering: Use intent data to refine your target account list, segmenting accounts into tiers based on their fit and level of buying intent. For example, Tier 1 accounts might be both high-fit and exhibiting strong intent signals.
Data Integration and Enrichment: Integrate intent data with your CRM, marketing automation, and sales engagement tools. Enrich account profiles with real-time signals, allowing reps to see which topics are trending within each account.
Orchestrated Engagement: Develop coordinated campaigns across email, social, phone, and digital ads. Use intent topics to inform content and outreach cadences.
Measurement and Optimization: Track engagement, pipeline creation, and revenue outcomes at the account level. Continuously refine targeting and messaging based on what’s working.
Intent Data in Action: Practical Use Cases for Inside Sales
1. Prioritizing Outbound Outreach
Intent data helps inside sales reps break through the noise by focusing their outreach on accounts showing active interest. For example, if a target account is researching “sales engagement platforms,” your team can reach out with tailored messaging and relevant case studies, greatly increasing the likelihood of a response.
2. Personalizing Messaging and Content
Generic emails are less effective in today’s market. With intent data, reps gain insights into the specific challenges and interests of each account. This allows for hyper-personalized emails, calls, and follow-ups that directly address what matters most to the buyer.
3. Triggering Timely Campaigns
Intent data enables the creation of trigger-based campaigns that activate when an account crosses a threshold of activity. For instance, if a prospect downloads multiple whitepapers on a relevant topic, the inside sales team can initiate a tailored sequence focused on that particular pain point.
4. Accelerating Pipeline and Reducing Churn
By tracking intent signals post-sale, customer success and expansion teams can identify upsell and cross-sell opportunities, as well as accounts at risk of churn. Proactive engagement based on these signals leads to stronger customer relationships and higher lifetime value.
Building a Tech Stack for Intent-Driven ABM
To execute an intent-powered GTM strategy, organizations need a tightly integrated tech stack that brings together data, automation, and analytics. Key components include:
Intent Data Providers: Platforms like Bombora, 6sense, and Demandbase aggregate and analyze intent signals across the web.
CRM and Marketing Automation: Systems such as Salesforce and HubSpot serve as the command center for account data and engagement workflows.
Sales Engagement Platforms: Tools like Outreach and Salesloft enable scalable, personalized outreach based on real-time account insights.
Analytics and Reporting: Dashboards and analytics tools provide visibility into account engagement, pipeline progression, and campaign ROI.
Seamless integration is critical—intent data must flow into the systems where salespeople work, surfaced in a way that’s actionable and easy to use.
Best Practices for Operationalizing Intent Data in Inside Sales
Train Sales Teams on Intent Signals: Educate reps on how to interpret intent data and use it to inform their outreach strategies.
Align Messaging Across Teams: Ensure marketing, sales, and customer success are using consistent messaging and leveraging the same intent insights.
Test and Iterate: Continuously run experiments to determine which intent signals and outreach tactics yield the best results.
Measure What Matters: Track critical metrics such as response rates, meeting creation, pipeline velocity, and closed-won rates by account segment and intent level.
Respect Privacy and Compliance: Use intent data ethically and in compliance with regulations such as GDPR and CCPA.
Challenges and Pitfalls to Avoid
While intent data is powerful, its effectiveness hinges on thoughtful execution. Common challenges include:
Data Overload: Too many signals without a clear action plan can overwhelm sales teams.
Poor Integration: Siloed data and disconnected systems reduce the impact of intent signals.
Misinterpreting Signals: Not all intent data is created equal—focus on high-fidelity signals that align with your ICP.
Lack of Follow-Through: Intent insights are only as valuable as the action they drive. Ensure there’s a process for timely outreach and follow-up.
Case Study: Scaling Inside Sales with Intent-Driven ABM
Consider a SaaS company targeting enterprise IT leaders. By integrating Bombora intent data into Salesforce, the company identified a subset of Fortune 500 accounts researching “cloud security.” The inside sales team coordinated with marketing to launch a targeted campaign featuring webinars, personalized emails, and executive briefings. As a result, engagement rates doubled and pipeline value increased by 45% within a single quarter. This example underscores the potential of intent-powered ABM when executed with discipline and cross-team alignment.
The Future of Account-Based GTM: AI and Predictive Analytics
The next frontier for ABM is AI-powered intent analysis and predictive engagement. Machine learning models can analyze vast quantities of intent data, uncover hidden buying patterns, and recommend next-best actions for sales teams. By layering AI on top of intent-driven GTM, organizations can further increase efficiency, surface high-potential accounts earlier, and automate much of the personalization that once required manual effort.
Emerging Trends to Watch
Deeper buyer journey mapping: Combining first- and third-party intent data to create a comprehensive picture of account activity.
Omnichannel orchestration: Coordinating outreach across email, ads, chat, and social channels based on intent triggers.
Automated playbooks: Using AI-driven recommendations to launch targeted sequences as soon as intent thresholds are met.
Conclusion: From Zero to One—Realizing the Full Potential of Intent-Driven ABM
Moving from zero to one in inside sales effectiveness means embracing the power of intent data and account-based strategies. By aligning teams, investing in the right technology, and operationalizing data-driven processes, organizations can create predictable, scalable revenue engines. The future belongs to those who act on signals—not just data—and who continuously refine their approach to stay ahead of buyer expectations.
Summary and Next Steps
Implementing an account-based GTM strategy powered by intent data requires vision, discipline, and the right technology foundation. Start by defining your ICP, integrating intent data into your workflows, and testing personalized outreach at scale. With ongoing measurement and optimization, your inside sales team can achieve new heights of productivity and impact—setting the stage for sustainable growth in a rapidly changing market.
Introduction: The Evolution of Inside Sales and Account-Based GTM
Inside sales has rapidly transformed over the last decade. Gone are the days when sales teams would rely solely on cold calls and generic outreach. The modern B2B environment demands precision, personalization, and data-driven strategies. In this context, the intersection of account-based go-to-market (GTM) approaches and intent data represents a significant leap—from zero to one—in sales effectiveness. This article explores how organizations can harness the power of intent data to supercharge account-based GTM strategies, elevate inside sales performance, and drive predictable growth.
Understanding Account-Based GTM: A Strategic Overview
Account-based GTM is a strategic approach that aligns marketing, sales, and customer success to focus on high-value accounts rather than casting a wide net. Instead of treating each lead equally, ABM prioritizes accounts based on fit and potential value, tailoring outreach to their specific needs and pain points. This strategy is particularly effective in complex B2B sales cycles where buying committees and multi-step decision processes are the norms.
Alignment: ABM requires tight coordination between marketing and sales teams to create a unified message.
Personalization: Outreach and engagement are tailored to each account, increasing relevance and resonance.
Efficiency: Resources are focused on accounts with the highest likelihood of conversion and expansion.
However, even the most carefully selected account lists can fall short without signals that indicate which accounts are actually in-market or actively researching solutions like yours.
The Role of Intent Data in Modern Sales
Intent data is information that signals an organization’s interest in a particular topic, product, or solution. This can include online behaviors such as web searches, content downloads, page visits, and engagement with industry content. By capturing and analyzing these digital footprints, intent data providers can surface accounts showing early buying signals, empowering sales teams to prioritize outreach with precision.
First-party intent data: Derived from your own digital properties, such as website visits, content downloads, or email engagement.
Third-party intent data: Collected from external sources—such as industry publications or review sites—where prospects show interest in topics relevant to your solution.
The Business Case for Intent-Driven ABM in Inside Sales
Why do so many ABM programs struggle to achieve true scale and impact? The answer is often a lack of actionable insights about which accounts are ready to engage. Intent data bridges this gap, enabling inside sales teams to:
Identify in-market accounts earlier: Engage accounts before competitors do, shortening sales cycles and increasing win rates.
Personalize outreach at scale: Craft messaging that speaks directly to the topics and pain points prospects are researching.
Optimize resource allocation: Focus sales and marketing efforts on accounts that show real buying intent, reducing wasted activity.
Improve forecasting accuracy: Better understand pipeline health and forecast revenue based on real-time buying signals.
Ultimately, intent-driven ABM empowers inside sales teams to move from reactive selling to proactive, data-driven engagement.
Key Components of an Account-Based GTM Framework Powered by Intent Data
Defining the Ideal Customer Profile (ICP): Begin by identifying the firmographic, technographic, and behavioral characteristics of your best-fit accounts. This provides a foundation for both account selection and messaging.
Account Selection and Tiering: Use intent data to refine your target account list, segmenting accounts into tiers based on their fit and level of buying intent. For example, Tier 1 accounts might be both high-fit and exhibiting strong intent signals.
Data Integration and Enrichment: Integrate intent data with your CRM, marketing automation, and sales engagement tools. Enrich account profiles with real-time signals, allowing reps to see which topics are trending within each account.
Orchestrated Engagement: Develop coordinated campaigns across email, social, phone, and digital ads. Use intent topics to inform content and outreach cadences.
Measurement and Optimization: Track engagement, pipeline creation, and revenue outcomes at the account level. Continuously refine targeting and messaging based on what’s working.
Intent Data in Action: Practical Use Cases for Inside Sales
1. Prioritizing Outbound Outreach
Intent data helps inside sales reps break through the noise by focusing their outreach on accounts showing active interest. For example, if a target account is researching “sales engagement platforms,” your team can reach out with tailored messaging and relevant case studies, greatly increasing the likelihood of a response.
2. Personalizing Messaging and Content
Generic emails are less effective in today’s market. With intent data, reps gain insights into the specific challenges and interests of each account. This allows for hyper-personalized emails, calls, and follow-ups that directly address what matters most to the buyer.
3. Triggering Timely Campaigns
Intent data enables the creation of trigger-based campaigns that activate when an account crosses a threshold of activity. For instance, if a prospect downloads multiple whitepapers on a relevant topic, the inside sales team can initiate a tailored sequence focused on that particular pain point.
4. Accelerating Pipeline and Reducing Churn
By tracking intent signals post-sale, customer success and expansion teams can identify upsell and cross-sell opportunities, as well as accounts at risk of churn. Proactive engagement based on these signals leads to stronger customer relationships and higher lifetime value.
Building a Tech Stack for Intent-Driven ABM
To execute an intent-powered GTM strategy, organizations need a tightly integrated tech stack that brings together data, automation, and analytics. Key components include:
Intent Data Providers: Platforms like Bombora, 6sense, and Demandbase aggregate and analyze intent signals across the web.
CRM and Marketing Automation: Systems such as Salesforce and HubSpot serve as the command center for account data and engagement workflows.
Sales Engagement Platforms: Tools like Outreach and Salesloft enable scalable, personalized outreach based on real-time account insights.
Analytics and Reporting: Dashboards and analytics tools provide visibility into account engagement, pipeline progression, and campaign ROI.
Seamless integration is critical—intent data must flow into the systems where salespeople work, surfaced in a way that’s actionable and easy to use.
Best Practices for Operationalizing Intent Data in Inside Sales
Train Sales Teams on Intent Signals: Educate reps on how to interpret intent data and use it to inform their outreach strategies.
Align Messaging Across Teams: Ensure marketing, sales, and customer success are using consistent messaging and leveraging the same intent insights.
Test and Iterate: Continuously run experiments to determine which intent signals and outreach tactics yield the best results.
Measure What Matters: Track critical metrics such as response rates, meeting creation, pipeline velocity, and closed-won rates by account segment and intent level.
Respect Privacy and Compliance: Use intent data ethically and in compliance with regulations such as GDPR and CCPA.
Challenges and Pitfalls to Avoid
While intent data is powerful, its effectiveness hinges on thoughtful execution. Common challenges include:
Data Overload: Too many signals without a clear action plan can overwhelm sales teams.
Poor Integration: Siloed data and disconnected systems reduce the impact of intent signals.
Misinterpreting Signals: Not all intent data is created equal—focus on high-fidelity signals that align with your ICP.
Lack of Follow-Through: Intent insights are only as valuable as the action they drive. Ensure there’s a process for timely outreach and follow-up.
Case Study: Scaling Inside Sales with Intent-Driven ABM
Consider a SaaS company targeting enterprise IT leaders. By integrating Bombora intent data into Salesforce, the company identified a subset of Fortune 500 accounts researching “cloud security.” The inside sales team coordinated with marketing to launch a targeted campaign featuring webinars, personalized emails, and executive briefings. As a result, engagement rates doubled and pipeline value increased by 45% within a single quarter. This example underscores the potential of intent-powered ABM when executed with discipline and cross-team alignment.
The Future of Account-Based GTM: AI and Predictive Analytics
The next frontier for ABM is AI-powered intent analysis and predictive engagement. Machine learning models can analyze vast quantities of intent data, uncover hidden buying patterns, and recommend next-best actions for sales teams. By layering AI on top of intent-driven GTM, organizations can further increase efficiency, surface high-potential accounts earlier, and automate much of the personalization that once required manual effort.
Emerging Trends to Watch
Deeper buyer journey mapping: Combining first- and third-party intent data to create a comprehensive picture of account activity.
Omnichannel orchestration: Coordinating outreach across email, ads, chat, and social channels based on intent triggers.
Automated playbooks: Using AI-driven recommendations to launch targeted sequences as soon as intent thresholds are met.
Conclusion: From Zero to One—Realizing the Full Potential of Intent-Driven ABM
Moving from zero to one in inside sales effectiveness means embracing the power of intent data and account-based strategies. By aligning teams, investing in the right technology, and operationalizing data-driven processes, organizations can create predictable, scalable revenue engines. The future belongs to those who act on signals—not just data—and who continuously refine their approach to stay ahead of buyer expectations.
Summary and Next Steps
Implementing an account-based GTM strategy powered by intent data requires vision, discipline, and the right technology foundation. Start by defining your ICP, integrating intent data into your workflows, and testing personalized outreach at scale. With ongoing measurement and optimization, your inside sales team can achieve new heights of productivity and impact—setting the stage for sustainable growth in a rapidly changing market.
Introduction: The Evolution of Inside Sales and Account-Based GTM
Inside sales has rapidly transformed over the last decade. Gone are the days when sales teams would rely solely on cold calls and generic outreach. The modern B2B environment demands precision, personalization, and data-driven strategies. In this context, the intersection of account-based go-to-market (GTM) approaches and intent data represents a significant leap—from zero to one—in sales effectiveness. This article explores how organizations can harness the power of intent data to supercharge account-based GTM strategies, elevate inside sales performance, and drive predictable growth.
Understanding Account-Based GTM: A Strategic Overview
Account-based GTM is a strategic approach that aligns marketing, sales, and customer success to focus on high-value accounts rather than casting a wide net. Instead of treating each lead equally, ABM prioritizes accounts based on fit and potential value, tailoring outreach to their specific needs and pain points. This strategy is particularly effective in complex B2B sales cycles where buying committees and multi-step decision processes are the norms.
Alignment: ABM requires tight coordination between marketing and sales teams to create a unified message.
Personalization: Outreach and engagement are tailored to each account, increasing relevance and resonance.
Efficiency: Resources are focused on accounts with the highest likelihood of conversion and expansion.
However, even the most carefully selected account lists can fall short without signals that indicate which accounts are actually in-market or actively researching solutions like yours.
The Role of Intent Data in Modern Sales
Intent data is information that signals an organization’s interest in a particular topic, product, or solution. This can include online behaviors such as web searches, content downloads, page visits, and engagement with industry content. By capturing and analyzing these digital footprints, intent data providers can surface accounts showing early buying signals, empowering sales teams to prioritize outreach with precision.
First-party intent data: Derived from your own digital properties, such as website visits, content downloads, or email engagement.
Third-party intent data: Collected from external sources—such as industry publications or review sites—where prospects show interest in topics relevant to your solution.
The Business Case for Intent-Driven ABM in Inside Sales
Why do so many ABM programs struggle to achieve true scale and impact? The answer is often a lack of actionable insights about which accounts are ready to engage. Intent data bridges this gap, enabling inside sales teams to:
Identify in-market accounts earlier: Engage accounts before competitors do, shortening sales cycles and increasing win rates.
Personalize outreach at scale: Craft messaging that speaks directly to the topics and pain points prospects are researching.
Optimize resource allocation: Focus sales and marketing efforts on accounts that show real buying intent, reducing wasted activity.
Improve forecasting accuracy: Better understand pipeline health and forecast revenue based on real-time buying signals.
Ultimately, intent-driven ABM empowers inside sales teams to move from reactive selling to proactive, data-driven engagement.
Key Components of an Account-Based GTM Framework Powered by Intent Data
Defining the Ideal Customer Profile (ICP): Begin by identifying the firmographic, technographic, and behavioral characteristics of your best-fit accounts. This provides a foundation for both account selection and messaging.
Account Selection and Tiering: Use intent data to refine your target account list, segmenting accounts into tiers based on their fit and level of buying intent. For example, Tier 1 accounts might be both high-fit and exhibiting strong intent signals.
Data Integration and Enrichment: Integrate intent data with your CRM, marketing automation, and sales engagement tools. Enrich account profiles with real-time signals, allowing reps to see which topics are trending within each account.
Orchestrated Engagement: Develop coordinated campaigns across email, social, phone, and digital ads. Use intent topics to inform content and outreach cadences.
Measurement and Optimization: Track engagement, pipeline creation, and revenue outcomes at the account level. Continuously refine targeting and messaging based on what’s working.
Intent Data in Action: Practical Use Cases for Inside Sales
1. Prioritizing Outbound Outreach
Intent data helps inside sales reps break through the noise by focusing their outreach on accounts showing active interest. For example, if a target account is researching “sales engagement platforms,” your team can reach out with tailored messaging and relevant case studies, greatly increasing the likelihood of a response.
2. Personalizing Messaging and Content
Generic emails are less effective in today’s market. With intent data, reps gain insights into the specific challenges and interests of each account. This allows for hyper-personalized emails, calls, and follow-ups that directly address what matters most to the buyer.
3. Triggering Timely Campaigns
Intent data enables the creation of trigger-based campaigns that activate when an account crosses a threshold of activity. For instance, if a prospect downloads multiple whitepapers on a relevant topic, the inside sales team can initiate a tailored sequence focused on that particular pain point.
4. Accelerating Pipeline and Reducing Churn
By tracking intent signals post-sale, customer success and expansion teams can identify upsell and cross-sell opportunities, as well as accounts at risk of churn. Proactive engagement based on these signals leads to stronger customer relationships and higher lifetime value.
Building a Tech Stack for Intent-Driven ABM
To execute an intent-powered GTM strategy, organizations need a tightly integrated tech stack that brings together data, automation, and analytics. Key components include:
Intent Data Providers: Platforms like Bombora, 6sense, and Demandbase aggregate and analyze intent signals across the web.
CRM and Marketing Automation: Systems such as Salesforce and HubSpot serve as the command center for account data and engagement workflows.
Sales Engagement Platforms: Tools like Outreach and Salesloft enable scalable, personalized outreach based on real-time account insights.
Analytics and Reporting: Dashboards and analytics tools provide visibility into account engagement, pipeline progression, and campaign ROI.
Seamless integration is critical—intent data must flow into the systems where salespeople work, surfaced in a way that’s actionable and easy to use.
Best Practices for Operationalizing Intent Data in Inside Sales
Train Sales Teams on Intent Signals: Educate reps on how to interpret intent data and use it to inform their outreach strategies.
Align Messaging Across Teams: Ensure marketing, sales, and customer success are using consistent messaging and leveraging the same intent insights.
Test and Iterate: Continuously run experiments to determine which intent signals and outreach tactics yield the best results.
Measure What Matters: Track critical metrics such as response rates, meeting creation, pipeline velocity, and closed-won rates by account segment and intent level.
Respect Privacy and Compliance: Use intent data ethically and in compliance with regulations such as GDPR and CCPA.
Challenges and Pitfalls to Avoid
While intent data is powerful, its effectiveness hinges on thoughtful execution. Common challenges include:
Data Overload: Too many signals without a clear action plan can overwhelm sales teams.
Poor Integration: Siloed data and disconnected systems reduce the impact of intent signals.
Misinterpreting Signals: Not all intent data is created equal—focus on high-fidelity signals that align with your ICP.
Lack of Follow-Through: Intent insights are only as valuable as the action they drive. Ensure there’s a process for timely outreach and follow-up.
Case Study: Scaling Inside Sales with Intent-Driven ABM
Consider a SaaS company targeting enterprise IT leaders. By integrating Bombora intent data into Salesforce, the company identified a subset of Fortune 500 accounts researching “cloud security.” The inside sales team coordinated with marketing to launch a targeted campaign featuring webinars, personalized emails, and executive briefings. As a result, engagement rates doubled and pipeline value increased by 45% within a single quarter. This example underscores the potential of intent-powered ABM when executed with discipline and cross-team alignment.
The Future of Account-Based GTM: AI and Predictive Analytics
The next frontier for ABM is AI-powered intent analysis and predictive engagement. Machine learning models can analyze vast quantities of intent data, uncover hidden buying patterns, and recommend next-best actions for sales teams. By layering AI on top of intent-driven GTM, organizations can further increase efficiency, surface high-potential accounts earlier, and automate much of the personalization that once required manual effort.
Emerging Trends to Watch
Deeper buyer journey mapping: Combining first- and third-party intent data to create a comprehensive picture of account activity.
Omnichannel orchestration: Coordinating outreach across email, ads, chat, and social channels based on intent triggers.
Automated playbooks: Using AI-driven recommendations to launch targeted sequences as soon as intent thresholds are met.
Conclusion: From Zero to One—Realizing the Full Potential of Intent-Driven ABM
Moving from zero to one in inside sales effectiveness means embracing the power of intent data and account-based strategies. By aligning teams, investing in the right technology, and operationalizing data-driven processes, organizations can create predictable, scalable revenue engines. The future belongs to those who act on signals—not just data—and who continuously refine their approach to stay ahead of buyer expectations.
Summary and Next Steps
Implementing an account-based GTM strategy powered by intent data requires vision, discipline, and the right technology foundation. Start by defining your ICP, integrating intent data into your workflows, and testing personalized outreach at scale. With ongoing measurement and optimization, your inside sales team can achieve new heights of productivity and impact—setting the stage for sustainable growth in a rapidly changing market.
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