If you’re just starting out with account-based marketing, you may not yet be using any sophisticated methods for segmenting and targeting your ideal customers. Maybe you’ve built out your TAM and ICP and you’ve identified the “big fish” you want to pursue.
But as you run your first few ABM pilot programs, you’ll want to start looking to scale your program from two perspectives: one that looks at how many accounts you want to target, and one that looks at the types of account data you are (or will be) using.
To do this you‘ll need to gather new types of account intelligence – but that’s just half the battle. Having the data at your disposal doesn’t necessarily mean it will work for you, you’ve got to take the steps necessary to start crafting account-based marketing efforts around the data you do have on your target accounts (and if you don’t have a certain data set that would be useful, it’s probably time to get your hands on it.)
It’s also critical to have a process outlined for ingesting the data and making it actionable. We’ll show you how to do that, but first, let’s look at the different types of account intelligence you can use.
What Types of Account Data Are Available?
Fit data, which includes firmographics such as industry and company size, are the basics of an account-based strategy. While having this may give you an edge over many of your competitors, some of your competition is probably using more advanced fit data – so you should, too, if you want to gain the upper hand.
Incorporating advanced data attributes into your account-based targeting, including some of the characteristics outlined below, enables you to get hyper-targeted with your marketing and sales campaigns. Common advanced data attributes include:
- Technology used
- Recent funding
- Number of employees in a specific department
How would you discover if your accounts are interested in what your company is selling? It starts with monitoring third-party websites — not your own websites — for signals that accounts are searching for services or products similar to yours, or are researching topics relevant to your company.
Here’s an example: imagine you sell a SaaS product for physical therapists. Based on your ICP and the research history of your current customers, you know your prospective customers are likely searching for content about cloud-based electronic medical records, streamlining documentation, and billing and outcomes tracking among other concerns a clinic director might face. Intent data would let you know when people from a target account are going to third-party sites about cloud-based electronic medical records, streamlining documentation, and billing and outcomes tracking.
Intent data arms your team with early intelligence that an account is interested in a solution or topic relevant to your company. With this intelligence, you can trigger campaigns targeting these accounts with more personalized messaging before your competition even has them on their radar.
By analyzing the email and calendar patterns of all your employees, relationship insights identify and quantify the entire network of relationships that exist between your team and decision influencers in target accounts.
Relationship data gives marketers true insight into the quality of relationships and engagement within target accounts while also allowing you to segment these relationships by location or other customizable segments.
Let’s say you’re planning a direct mail campaign for opportunity acceleration. You could use relationship data to segment out a list of opportunities that have the most two-way communication with your team and filter out the opportunities with weak or nonexistent communication.
While intent is all about identifying interest and catching it early to help inform your sales and marketing teams’ strategies, engagement insights demonstrate the ways in which accounts are currently interacting with your brand, online and off.
With engagement insights, you’ll know which accounts are engaging the most with your website, events, emails, and content — all signaling a high level of interest. And, you will know it before anyone from the account has filled out a form.
How Do You Get Advanced Account Data?
It’s time for a moment of truth: to get access to advanced account data, you’re probably going to have to buy most of it. While it is possible to gather fit, relationship, and engagement data yourself, it would be a very manual process, you would end up with a lot of gaps and errors in your intelligence, and it would not be scalable.
Below is a chart of account- based data providers.
How Should You Manage Account Data?
As we said earlier, getting that data is just half the battle. Your process for ingesting the data and making it actionable is the hard part.
To do this, you need to build a centralized account intelligence center, or more simply, an account hub. Your account hub is a place where you can see all the F.I.R.E data in a single view, prioritize accounts, and build your lists.
Account Data Management Options
Ideally, you want an account-based platform such as Terminus to manage your account data, but if you are earlier in your account-based journey, you may have to rely on spreadsheets as traditional lead-based CRM and marketing automation tools are designed to manage contacts, not accounts.
First, you will want to identify the firmographic, intent, relationship, and engagement data you want to track at an account level. For example:
- Company Size
- Medical Record Management
- Medical Documentation
- Medical Billing
- Campaign Responses
- **Last Engagement Spike
* Sigstr provides a score from their relationship algorithm. ** An engagement spike is a meaningful increase in the number of visitors
You’ll then want to build an account hub spreadsheet. Based on the criteria above, your spreadsheet would look like this:
Now that you have an account hub spreadsheet, you need to fill it out. To do this you need to first export a CSV file from each of your account data tools. So, if you are using Datafox for advanced firmographics and Bombora for intent, you will need to go into both, select your accounts, and download a CSV file.
Clean up and consolidate the data. To do this, you’ll typically use a VLookup to match the account domain when consolidating data across multiple sources. But, different tools have different ways of writing the domain. Some include a forward slash at the end and some don’t. Some tools use HTTP, while others use www. You will need to go through the list and make sure all the URLs are uniform.
This is what our Marketing Ops team used to refer to as “Spreadsheet Island.”
Finally, you will be ready to consolidate all the data into the account hub spreadsheet.
Once your data is centralized into your hub, you can begin to create account segments and lists for specific campaigns based on fit, intent, relationship, and engagement. For example, you may want to run digital ads for a group of accounts showing intent and send direct mail to a group of accounts showing engagement.
Get the Terminus Account-Based Platform’s Account Hub, so you never have to do that much manual reporting again (kidding!).
All jokes aside, as you prove the value of your ABM program and begin scaling it, you will have to find opportunities to streamline your workflow, reduce manual effort, and manage more accounts. At some point, it will become critical to be able to automatically see your account intelligence signals in real-time.
The Terminus Account Hub provides a single view of all your fit, intent, relationship, and engagement data. The data is automatically updated in real-time and you can prioritize and build lists with a click of a button. This streamlined approach to account intelligence allows you to focus more time and energy on identifying ways to engage and convert those accounts into opportunities.
But, if you aren’t ready to implement a comprehensive ABM platform, following the above steps will help you to centralize your data, which will enable you to ingest and take action on it that much quicker.