Leverage AI to Fast Track Account Planning and ABM – Intent Data, Digital Initiatives, Tech Stack, Budgets, and more!
Account Based Marketing (ABM) has been transformative for B2B marketers, leading to faster 360-degree penetration of target account that further helps to drive revenue growth fast.
However, despite its potential, many marketers have struggled to execute ABM due to these three execution level nuances:
- It takes a lot of time to identify the right stakeholders within the target account. An individual identified as a key stakeholder might not have the decision-making influence, at times. It is a time and effort-intensive process to identify and map the right stakeholders to pitch your product offering.
- It takes time to connect with and engage the right stakeholders within prospect accounts – understand their business, learn about their business priorities and digital initiatives for the year. It involves multiple rounds of complex discussions, over weeks, months, at times quarters.
This indeed has been a challenge to pipeline and revenue owners over the years. - Manual deep analysis of the target account level data, compiled over a period of time, identification of the right patterns and triggering the correct messaging / campaigns mix is a complex process, at an execution level.
However, AI has transformed ABM workflows by unlocking and incorporating data-driven, deep actionable insights into the above processes and other ABM workflows.
AI is fast-tracking essential workflows and improving the accuracy of the insights for sales and marketing to focus on outreach and deal clothing. Let’s explore:
- Instant availability of target-account specific critical data like decision making panel, outsourcing trends, and high-priority digital initiatives to target specific accounts. It cuts down on your research and account analysis time of weeks or even months.
- Fast-tracking of data modeling/analysis: AI models automate and fast track data analysis and infer insights instantly, reducing the time needed for decision-making compared to traditional workflows.
- Fast-tracked workflows: AI streamlines workflows and data crunching and allows your sales and marketing members to focus more on outreach and deal closure with instant access to account priorities.
- Improves accuracy: As it is generated by a system and a model, the chances of errors are reduced. The chances of errors in analyzing the data with the right model is lower.
Fast-Track Account-Level Research by 80% Leveraging AI
In an ABM motion, each target enterprise account requires hyper-personalized pitches to improve the chances of faster account penetration and probabilities of closing deals, faster.
It involves tailoring outreach strategies and creating personalized messaging that resonates with the account-level pain points, goals, and buying behaviors of stakeholders.
This requires deep account-level research that typically consumes a lot of effort, resources, and time when done manually.
Traditional ABM motions typically involve pipeline/revenue-focused teams conducting deep research on the target accounts – and deriving market and account level insights for use in the ABM workflows.
The process is slow. It involves enterprise sales and marketing teams conducting:
- Manual discovery of target account related data/intelligence,
- Manual identification of market or account level data trends/patterns, and
- Manual correlation of data, multiple trends and patterns and ABM objectives – to tailor solutions for target accounts.
Hence, marketers looked for ways to cut down on research time. With AI-powered analytics and workflows, ABM teams can achieve:
AI helps enterprises scale the ABM process, real quick
AI enables AI-driven ABM process with these three elements – the data, the model, and insights extraction.
AI can evaluate massive amounts of unstructured data in real-time, allowing sales teams to effectively identify new industry trends and consumer preferences.
AI uses applied ML models tailored to certain use cases to optimize ABM.
These models extract insights from unstructured datasets and aid in discovering new insights to expand account planning efforts, generate sales pipelines, and grow wallet share.
This capacity to comprehend complex datasets and derive insights enables sales teams to match their strategy and product planning with the demands of prospects or customers.
Applying AI in your account-based marketing strategy definitely acts like an accelerator, accelerating the workflows and cutting manual, repetitive steps to target the key accounts.
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[Let AI do the data crunching, analysis and insight generation, freeing your ABM teams to focus on creativity, strategy, and personal connection.]
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[With AI, your ABM becomes more efficient and scalable. With AI, your ABM motion fast-tracks the compilation of consumer behavior patterns and buyer intent data.]
AI-powered ABM frameworks are better structured than traditional ABM processes
AI allows ABM teams to transition from anecdotal statements to data-driven evidence and help them develop a structured approach to their ABM strategy. AI-powered frameworks excel which is attributable to:
- Evidence-based decisions and enhanced account outreach – Manual research in traditional ABM is subjective due to time consumption due to manual research, selection bias, manual data interpretation. AI analyses and identifies ideal accounts instantly, leading to evidence-based decisions and improved outreach effectiveness.
- Large data processing – Traditional ABM struggles to handle large datasets. AI processes these datasets and uncovers patterns and trends that inform better targeting and personalization with an enhanced ICP.
- Consistency – Human decision-making can be susceptible to fatigue and bias, whereas AI-powered ABM ensures consistent application of rules and selection criteria through the ABM process, leading to reliable and predictable outcomes.
- Pattern recognition – AI algorithms detect patterns and trends that traditional processes run by humans may miss. These patterns can reveal valuable insights into account behavior and preferences, enabling marketers and ABM teams to:
- Discover opportunities to expand their wallet share.
- Tell a better brand and product story for prospects and customers.
- Identify the potential to engage and establish a pipeline, then grow and optimize account planning.
AI-powered account-based marketing frameworks combine these advantages to provide a more organized and data-driven approach to account-based marketing, which eventually yields better results.
AI-powered market analytics enables competitive benchmarking instantly, for efficient GTM planning
Benchmarking – the process of screening, selecting, and analyzing comparable companies is complex, multi-layered, and time intensive. Enterprise sales and marketing teams spend a lot of time and effort on competitive benchmarking, every year.
With the help of machine learning models and algorithms, AI transforms raw data into strategic intelligence about the competitive landscape which include:
- Your competitors’ global footprint and the work they perform across serviceable TAM.
- Their financial data through investor relation pages or financial statements aggregators.
- Their hiring trends and tech stack.
- Their go-to-market initiatives and partnerships.
Sales teams can compare this data with their own to determine how their business compares against competitors.
Data-driven insights guarantee that benchmarking is accurate and representative of the market trends, helping sales teams make better strategic alignment possible.
Draup empowers ABM teams with AI-driven insights – A case study
Consider the case of Persistent Systems, a leading IT services company, who looked to reduce their account planning research.
Draup for Sales, an AI-based Sales Intelligence platform, was leveraged by 150+ individuals across sales, marketing, and delivery teams, and reduced research time by 60%, fast-tracking their ABM initiatives.
They chose to utilize Draup for the following reasons:
- The client’s presales and internal teams would spend a lot of time gathering insights for each account.
- They had to sift through multiple databases and sources to derive account planning insights.
- It took them multiple hygiene checks to organize the data from secondary sources and derive insights manually.
Draup’s AI-based SaaS platform enabled Persistent’s GTM teams to leverage its Account Intelligence feature, examine the Digital Tech Stack across various accounts, and receive custom ‘Braindesk’ reports, helping them achieve the following:
- The single platform usage helped Persistent Systems to coordinate and integrate better.
- The team was able to reduce their research time by 60% with Draup’s actionable insight for target accounts.
- Less reliance on multiple databases and secondary research.
- Increased efficiency of research and internal teams for Industry Intelligence, Competitors, and Outsourcing Intelligence.
Draup delivers actionable insights through preferred consumption channels and enables ABM teams to learn about:
- The prospects’ likely budgets, technology purchases, outsourcing details, and
- The stakeholders’ contact coordinates to figure out the ideal way to conduct their ABM activities.
Draup’s cognitive engine built with state-of-the-art cloud architecture of advanced AI & ML models runs over 16 million data points about companies, decision makers, and industries, from over 8000+ data sources.
