Account-based marketing, or ABM, is a term that dominates modern marketing strategy conversations. Actually, managing an ABM program can be as short and sweet as a buzzy acronym. It begins with creating a clear, understandable ABM dashboard. What is an ABM dashboard? Who provides input in an ABM dashboard? You probably have questions, but Mighty & True spells it out here to get you creating your very own ABM dashboard.

Step 1: Define the Audience for Your ABM Dashboard

Your ABM dashboard will have to accommodate various co-worker needs, so designing your reporting and dashboards requires some sleuthing. Interview a range of key stakeholders from CXO level to operational and sales roles to document preferences, priorities and KPIs that map into your dashboard project. You’ll want to capture information on report format, timing, frequency of refresh and preferred delivery to ensure you can deliver the right info in the right way.

Step 2: Build a Plan around the Data

With your newfound reporting requirements in hand, you can begin to map the stakeholder requests with the available data from your current source systems to create perfect dashboards by viewer type. If you have all the data, congrats! However, it’s likely you’ll need to create unique views and/or derived fields from multiple data attributes to fully accomplish reporting plan glory.

Breath easy, because most database administrators can combine, manipulate and create new attributes from various data sources. Come prepared with the data you want and how it will affect the output you’re shooting for. Also, it’s good to consider any filters you’d like on the dashboards, like accounts, date ranges, sources or campaigns. These will affect what data you’ll need to create the filters.

Step 3: Mock up a Low Fidelity Prototype

Taking all the knowledge collected thus far, it’s time for some artistry! Using the audience needs and data available in your ABM plan, bring the project to life by creating a series of dashboard sketches. Whether you do this in design software, whiteboarding or old-fashion pen and paper, gallery-quality looks aren’t the goal here.  We’re really just trying to give the development team a blueprint with ideas and direction on what they will be building.

Always remember to consider the needs of the users and the views they may want to see as well as the data available to create the dashboards. As a final step in prototype development, make sure that you note where each reporting data point originates. This includes column names and/or individual field name examples. This will help the development team know where to look for the data they’ll need to create your dashboard design masterpieces.

Step 4: Select Technology and Start Development

Now it’s time to kick off the development phase by reviewing the requirements, data plan and low-fidelity prototypes with your development team. Using your information as an input, they can help you select the right technology to align with the data and the requirements provided by the various user types. You might already have an in-house BI tool in mind, and that’s okay. You can always tweak the requirements to align with the capabilities of the selected technology. We recommend starting with a sandbox environment where you can stage all the new reports and related data until the primary stakeholders sign off. Once you have their blessing, move the dashboards to production and follow up with users. We advise, at minimum, a follow up at launch followed by a one-month check-in after initial launch to tweak things as needed.

There you have it, a handy plan that will have you analyzing ABM results simply, smarter, and more importantly, sooner. For an interesting take on types of ABM reporting frameworks Mighty & True recommend, check out this blog.

Still struggling on ABM?  Contact us, we’d love to help!

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Mighty & True’s Hall of Awesome is our place to write about all the things that our clients and community care the most about. We’ll try to keep things focused on B2B Marketing, Marketing Technology, Creative Best Practices and all things digital. Let us know what you think.



Intent data in B2B marketing is becoming more than just a nice-to-have. Your target customers and accounts are already in market well before you’ll figure it out, so purchase intent data is worth the wait. It allows companies to evaluate buying intentions so you can strike at accounts and prospects while the iron is hot.

Some companies we work with still view intent data as something they buy from third-party providers, a route with limited options.  As grim as that sounds, there are a few overlooked places B2B marketers can go for buying intention data: owned, third-party and modeled intent. The way we see it, these three options allow B2B marketers to understand purchase intentions of both known and unknown targets.

Let’s break these options down.

Owned Purchase Intent

This includes the intent data you already own based on an individual’s or account’s interactions within your own customer experience ecosystem. This may include engagement with specific types of content, visits to various web pages (product, customer service, order pages, community site, etc.), and/or your earned media channels. Acquiring a visitor’s intention by using your own assets allows you to build content plans that include capturing intent-based signals that you’d otherwise have to pay for.

Third-Party Purchase Intent

Third-Party purchase intent includes account-based intent data that can be bought or rented directly from intent data providers like Bombora, Big Willow, (now Aberdeen), Tech Target Priority Engine. You can also integrate this data with your current sales or marketing platform with a provider like DiscoverOrg.com. This type of intent data can help scale your ability to evaluate intent at specific accounts beyond your own website. These tools also allow you to integrate intent data directly into your marketing workflow and automation tools, so you can use it across channels and sales tools.

Modeled Purchase Intent

Various engagement and intent signals, coupled with third-party data, go into creating modeled intent data. Modeled intent creates a derived intent “score” in order to quickly evaluate an account’s opportunity and receive more targeted marketing and/or sales outreach. Like third-party intent data, modeled data can be an easy way to expand and scale your intent intelligence with resources that you might already have in place. Modeled intent providers include companies like Lattice Engines, Mintigo and Everstring.

Smart B2B companies don’t just settle for a single intent data source. They expand their understanding of a prospect’s or account’s buying intentions by combining all three purchase intent types in order to create a trifecta of success for their account-based marketing strategy.

All this strategy still has you stumped? Contact us!

About Our Blog

Mighty & True’s Hall of Awesome is our place to write about all the things that our clients and community care the most about. We’ll try to keep things focused on B2B Marketing, Marketing Technology, Creative Best Practices and all things digital. Let us know what you think.