Ping Identity, a leader in identity and access management (IAM), has embraced a sophisticated, AI-powered approach to one-to-many account-based marketing (ABM). This strategy, underpinned by AI-driven insights and automation, has enabled the company to scale demand generation while maintaining a high level of personalization.
By blending AI with predictive analytics, intent data, and automation, Ping Identity efficiently targets its ideal customer profile (ICP) and tailors content to individual needs, addressing the inherent challenges of engaging prospects in a crowded and complex B2B environment.
Business needs
The decision to adopt a one-to-many ABM model emerged from Ping Identity’s need to engage large target accounts in a cost-effective and scalable manner. With a focus on identity and access management, the company sought to nurture a large audience while maintaining a personalized, outcome-driven approach to customer engagement.
As Emanuela Mafteiu, Senior Digital Marketing Manager, Ping Identity, explains, Ping Identity has always employed a one-to-many ABM model, driven by clear criteria such as annual revenue and potential spend on IAM solutions.
“We have a specific target account list. We’ve always used a one-to-many ABM approach for anything related to digital and demand generation. Internally, we refer to them as ‘big bets’. The way we arrive at these accounts is quite a scientific process within our company. We work closely with the sales team to identify these big accounts, which are based on factors like annual revenue, identity and access management needs, potential spend, and so on. So, the criteria are very clear.”
However, as only 3-5% of the market is actively researching or switching vendors at any given time, the company needed to enhance its strategy to effectively engage the remaining 95% through brand awareness and nurturing campaigns.
Integrating AI into one-to-many ABM
AI has become central to Ping Identity’s ability to scale its one-to-many ABM strategy while maintaining high personalization standards. The company uses a customized version of ChatGPT, referred to internally as “Pinglet,” to accelerate and optimize campaign creation. By feeding the AI with insights, such as brand voice and outcome-focused messaging, Pinglet assists with a variety of tasks, including copywriting, design optimization, and campaign ideation.
Ping Identity uses AI to:
- Generate campaign ideas: Pinglet helps create outcome-driven campaign strategies and suggests variants of content, significantly speeding up campaign development.
- Conduct competitor research: The AI can quickly analyze competitor landing pages and suggest improvements or new approaches.
- Optimize copy and design: AI-driven A/B testing allows the team to identify high-performing subject lines and design elements (such as color schemes), driving higher engagement rates.
By positioning AI as a research and ideation tool, Ping Identity ensures that marketing teams receive fresh perspectives and insights quickly, allowing for faster decision-making and campaign execution.
Overcoming challenges in data quality and scalability
While AI has enhanced Ping Identity’s ability to personalize at scale, challenges around data quality, particularly intent signals, persist. According to Emanuela, intent data often varies by region, with stronger signals in markets like North America compared to EMEA.
“The biggest issue with data quality is obtaining accurate intent information. We are using 6Sense to track where prospects are in their journey, leveraging both predictive and behavioral analytics. We analyze all of these factors. However, from my experience, it’s challenging to pinpoint the exact intent of accounts. It’s difficult to determine if they’re researching a specific theme, as intent signals can vary significantly. For example, intent signals may be stronger in the Americas but not necessarily as strong in EMEA. This inconsistency is the main data quality issue I’m facing right now.”
This poses a challenge for segmenting and personalizing outreach across geographies. AI aids in segmenting accounts based on verticals, allowing Ping Identity to tailor content more effectively by focusing on specific industries (e.g., financial services, insurance) and their unique pain points. This verticalization helps the company deliver relevant messaging, improving personalization across a broader audience while maintaining scalability.
“True personalization happens when you tailor your messaging per vertical and specific problems rather than trying to personalize everything. This is where you can really hone in on key challenges in sectors like financial services or insurance, for example. By doing this, you still work with a one-to-many target account list but with verticalized messaging, establishing yourself as a thought leader in each industry.”
AI as an internal ally, not a threat
Despite the evident benefits, Ping Identity faced initial resistance to adopting AI, particularly among sales and business development representatives (BDRs). Concerns about AI “taking over jobs” were common. To mitigate these concerns, the marketing team engaged in transparent discussions with stakeholders, explaining that AI was intended to support, not replace, human efforts.
AI’s role was to enhance efficiency, reduce time-to-market for campaigns, and ultimately free up time for BDRs and sales teams to focus on higher-value activities. By demonstrating tangible results, such as faster campaign launches, higher engagement rates, and more effective targeting, Ping Identity was able to secure internal buy-in.
“Once we had those conversations internally, our stakeholders were convinced and open to moving forward. The best advice I can give is to start small: run pilot programs. People appreciate trials, and you can then go back to your stakeholders with clear communication, showing the results, and ensure everyone is aligned.”
Automation & AI-driven insights
Automation and AI-powered insights play a crucial role in Ping Identity’s ABM strategy, particularly in streamlining account segmentation and content personalization. Using 6sense, the team automates the segmentation process, identifying and prioritizing accounts based on predictive analytics and intent data. This significantly reduces the manual effort involved in traditional segmentation methods, allowing Ping Identity to move more quickly from segmentation to execution.
“I would say predictive analytics and intent data are incredibly powerful, but my personal favorite is persona mapping. By using personalization, you can build your buyer committee within a specific vertical. This allows you to hone in on the exact keywords or themes that prospects are interested in, making your approach highly granular. Today’s buyer committees often include eight or more people from different departments, so it’s important to ensure you’re engaging with each of them.”
Emanuela suggests connecting your CRM to AI-powered tools to track engagements, like how many emails they’ve opened or how many internal campaigns, both outbound and inbound, have reached them. This gives a comprehensive view of their journey and helps understand the pain points of different personas and deliver content that addresses those challenges.
Results and success metrics
Ping Identity tracks a range of KPIs to measure the success of its one-to-many ABM initiatives. The primary focus is on pipeline growth and influenced pipeline, with specific KPIs varying by channel.
“I would say it really depends on the channel because we use different KPIs for each one, but overall, we are all responsible for pipeline growth. In the one-to-many ABM initiatives that I manage, they are more focused on the top of the funnel. I tend to rely on pipeline influence reports to demonstrate how we’re contributing to pipeline growth. We are constantly learning quarter over quarter, assessing what worked, what could be improved, and if there are ways to boost conversion rates — especially from digital and one-to-many ABM initiatives.”
Emanuela adds that the buyer’s journey is becoming more complex, B2B buying cycles are getting longer – often lasting two, three, or even four years – and buyer committees are growing larger. All of these factors make KPIs critical for evaluating success across different channels. AI has been particularly effective in improving soft metrics such as click-through rates, as well as more concrete outcomes like conversion rates and pipeline velocity.
Conclusion
Ping Identity’s AI-driven approach to one-to-many ABM has enabled the company to scale demand generation while maintaining personalized, relevant content for a broad audience. By leveraging AI-powered insights, predictive analytics, and persona mapping, Ping Identity enhances campaign optimization and empowers its teams to focus on higher-value tasks, improving alignment across marketing and sales.
Despite challenges like data quality and regional variations in intent signals, AI helps Ping Identity segment and tailor messaging by industry. This strategy has led to improved engagement, better pipeline growth, and higher conversion rates, showcasing how AI can drive personalization at scale and long-term success in a complex B2B environment.
