Account Research for ABM: Scaling with AI & Behavioral Insight

The success of your Account-Based Marketing depends on the quality of your research, but traditional methods take hours of work and data often becomes outdated before you can act on it.

The solution? AI tools that research and analyze data from multiple sources automatically, helping you launch personalized campaigns that move target accounts through the funnel faster.

In this guide, we’ll cover everything you need to know to get started with AI-powered account research for your ABM strategies.

What Is Account Research?

Account research is the process of gathering, analyzing, and organizing intelligence about the companies in your target account list. The goal is simple: collect the data that will help you scale personalized engagement with the right contacts.

Unlike contact-level research, which focuses on individual buyer personas, account research zooms out to understand an entire organization.

For example, contact-level research might reveal that your contact is a VP of Marketing interested in demand generation. Account research goes deeper to uncover that the company just raised Series B funding, recently hired a new CMO, and is expanding into three new markets.

When done well, account research gives your go-to-market team a detailed understanding of each target account. Sales knows which pain points to emphasize, marketing knows which messages will resonate, and customer success can anticipate future needs.

Mutiny’s Account Studio will give you deep account insights. For example, in the image below, it shows each account’s main competitors.

Source: https://help.mutinyhq.com/hc/en-us/articles/39115544155931-AI-Research-and-Data-Enrichment-in-Account-Studio

How Account Research Drives Better Targeting & Personalization

Deep account-level insights turn stale outbounds into strategic conversations. By using the research data in personalized messaging, you enhance the effectiveness of your ABM strategies.

During account research, your first objective is to align your Ideal Customer Profile (ICP) with your account data. The intersection between the two is where the magic happens. Those are the accounts you should target with personalized experiences like 1:1 landing pages and tailored LinkedIn ads.

To get there, segment your target account list strategically:

Start in your account overview and begin creating broad segments, using firmographic and technographic data such as industry, company size, and tech stack. Then, get granular with intent signals, pain points, company culture, and more unique differentiators that set high-priority accounts apart.

For example, in Mutiny’s Expansion Playbook, Celeste, an Account Executive, used three specific criteria to identify upsell opportunities:

• Account Tier: To prioritize high-value customers

• Current Package: To identify expansion opportunities

• Upcoming Renewal Dates: To time conversations for maximum impact

Using these insights, she worked with the ABM team to create personalized 1:1 landing pages showcasing how specific teams within each organization were already winning with Mutiny. They also launched hyper-targeted LinkedIn ads directing stakeholders to these experiences.

Their approach led to 100% of target accounts receiving personalized outreach, a 5x increase in engagement from existing customers, and 30% of target accounts engaging in expansion conversations.

Source: https://help.mutinyhq.com/hc/en-us/articles/39115544155931-AI-Research-and-Data-Enrichment-in-Account-Studio

Common Challenges in Manual Account Research

Traditional research approaches will not help you scale. Here’s why.

• Manual research eats up strategic time. According to the H2 2024 State of B2B Pipeline Growth, 65% of marketers still spend more than 5 hours per week just ensuring data quality. That’s time that could be spent on strategy, creative development, and campaign optimization.

• Data fragmentation creates blind spots. When you’re pulling information from multiple platforms manually, it’s easy to miss critical context or fall into subjective traps. For example, one team member might research an account on LinkedIn while another pulls data from a CRM. The results might be duplicated or even contradictory.

• Information becomes stale quickly. Companies are changing constantly. Leadership shifts, priorities evolve, and new initiatives launch. By the time you’ve manually compiled research on 100 accounts, the first few might already be outdated.

• Scaling is nearly impossible. You can research 10 accounts thoroughly by hand. Maybe even 20. But what happens when you need insights on 100+ accounts? A manual process simply can’t keep pace with the demands of enterprise ABM.

The difference between manual and AI-powered research matters more than ever. According to recent industry data, 97% of marketers report that ABM delivers higher ROI than other marketing strategies. And with the global ABM market projected to reach $1.6 billion by 2027, organizations are investing heavily in ABM strategies and expect results that manual processes can’t deliver.

Source: https://www.mutinyhq.com/blog/account-studio-ai-research

What Modern Account Research Should Include

Modern account research steers away from time-consuming manual data gathering. AI now helps you find patterns faster and build segments in seconds instead of days.

Here’s what your research should include:

Firmographic and Technographic Data

Start with the company’s fundamental data, including industry type, annual revenue, team size, and office locations. This foundation helps you understand an account’s basic profile and compatibility with your solution.

Don’t stop there, though. Dig into their tech stack to understand what tools they’re already using. Are they on Salesforce or HubSpot? What automation platform do they use? This intel will help you position your solution as a natural fit within their existing ecosystem and identify potential integration opportunities.

Tech stack data also reveals buying signals. If a company recently adopted a new tool, they’re likely in growth mode and open to new (and better) solutions. If they’re using outdated technology within your category, they might be prime candidates for an upgrade.

Organizational Context

Real-time account intelligence gives you relevant communication angles. Recent funding rounds, leadership changes, expansion plans, and market challenges all signal shifts in priorities and budget availability inside a company.

For instance, if a startup has just completed a Series A funding round, it likely has fresh capital to invest in growth initiatives. A CMO might bring in new ideas and fresh approaches.

An expansion into a different region can create urgency to find solutions that enable global operations.

To gather this data, use the AI-powered research feature in Account Studio to write detailed prompts that will scour news sources, press releases, and social media to find exactly the information you need.

Pain Points and Strategic Priorities

Other types of data Mutiny can help you find are company pain points and strategic priorities. This insight will help you shape personalized messaging and determine whether you’re addressing a nice-to-have or a must-have problem.

For example, what initiatives is your target account investing in? What challenges are they publicly discussing? Ask Mutiny’s AI to look through annual reports, investor presentations, and executive interviews to reveal strategic direction. When a CEO mentions “improving customer retention” or “accelerating time-to-market” in an annual report introduction, that’s a good indicator of what they wish to improve.

You can also analyze job postings on their sites or on LinkedIn to understand strategic focus. A company hiring five Account Executives is clearly growing. If another account is building a data science team, it is probably betting on analytics and AI.

Engagement Timelines and Intent Signals

Timing is everything in ABM. Tools that track page views, content engagement, and conversation data help you spot buying signals quickly.

Mutiny’s Account Intelligence automatically tracks when accounts visit your website, the 1:1 landing pages you created for them, plus how long they engage and which content resonates the most. If you’ve successfully connected to your Salesforce, Mutiny will also show each account’s opportunity stage.

When multiple people from the same account visit your pricing page in the same week, that’s a signal. When they download case studies specific to their industry, that’s another signal. Layer enough signals together, and you’ve identified an account actively researching solutions like yours.

Source: https://help.mutinyhq.com/hc/en-us/articles/29092716399131-Account-Intelligence-for-Target-Accounts

Best Practices for Account Research at Scale

Scaling your account research without losing valuable account depth depends on three best practices. Let’s discuss each one below.

1. Master Prompt Engineering for Account-Level Questions

Generic prompts return generic results. So, when using AI for your research process, specificity matters. Improving your prompts will help you build granular segments while also giving you a deeper understanding of the individual accounts on your target list.

Avoid bad prompts like, “Are these companies growing?” And do this instead: "Which companies have raised funding in the last 6 months?"

Here are a few examples of great account research prompts:

• "Have they raised funding in the last 6 months?"

• "What was their most recent funding round size?"

• "Do they use Salesforce as their CRM?"

• "What marketing automation platform do they use?"

• "Who are their main competitors?"

• "What market segment do they serve (SMB, Mid-Market, Enterprise)?"

Using these types of detailed prompts with Mutiny’s Account Intelligence will help you identify patterns you might miss with manual research. Like, for example, accounts that share specific tech stacks, face similar regulatory challenges, or operate in high-growth markets.

2. Use Segmentation, Filters, and Automation Strategically

As we’ve already discussed, Mutiny’s Account Studio and its AI-powered account research feature help you segment your account list to whichever level of detail you need. But, doing it strategically involves going deep into what makes your accounts unique and targetable.

Follow this process: segment > filter > get specific insights > automate.

Step 1: Segment into meaningful groups

Create broad segments based on shared characteristics. For example, if you’re targeting mid-market companies, break it out by vertical:

• Financial services

• Healthcare

• SaaS

Step 2: Filter for the highest priority

• Within financial services, apply additional filters to find accounts most likely to convert:

• Using Salesforce or HubSpot? (tech compatibility)

• Visited pricing page in the last 30 days (intent signal)

• Marketing team of 10+ people (budget indicator)

• Operating in North America? (product compatibility)

• This narrows 200 financial accounts down to 25 high-priority targets.

Step 3: Prompt AI for account-specific insights

Now use AI Research to analyze each account:

Prompt: “For each financial services account, identify their biggest compliance challenges based on recent news and job postings, competitors they likely use based on their tech stack, and any communication around digital transformation.”

Your insights could be:

• Company X recently hired a CCO and posted about GDPR challenges on LinkedIn.

• Company Y uses legacy systems, and the CTO mentioned modernizing their data infrastructure in the latest news articles.

• Company Z expanded to EU and is hiring for data privacy roles.

Step 4: Automate personalized experiences

From inside your Account Studio, use these insights to generate 1:1 landing pages automatically for each account. Based on the results in step 3, Company X would see compliance messaging, Company Y would see modernization content, and Company Z would get global scalability features.

Direct the company’s leadership team and decision-makers towards their landing pages, by automating targeted LinkedIn Ads.

3. Align With Sales Using Content and Timely Insights

Your account research should flow directly to the sales team by sharing information and valuable insights. When an account shows high intent or engagement, both the ABM and sales should see it simultaneously.

Shab Jahan, Senior Enterprise ABM Manager at Amplitude shares "The web extension is one of tools that the sales team is constantly telling me they absolutely love."

This is where regular collaboration sessions with sales become critical. Get together and review target account engagement and impact. Run feedback loops and assign action items to both sales and ABM teams based on what’s working.

Use Mutiny’s Sales Extension to give sales representatives instant access to account research, behavioral insights, and personalized assets they can use to customize outreach.

Here’s a video that explains how the extension works and help your teams

Turn Account Research Into Revenue with Mutiny

Account research is a vital step of your ABM strategy, without it your team will lack direction and personalization takes forever. Thankfully, there’s a better way.

With the right approach and AI platform, you can gather data, analyze it, surface actionable insights and integrate it all with your existing tech stack. Then, make the data flow to the teams that need it and turn account research into your competitive advantage

Ready to see what AI-powered account research can do for your business? Check out Mutiny’s Account Intelligence and start communicating personally with your target accounts.