Let’s talk about the role of account selection in dynamic books.
When we talk about dynamic books, we make a few assumptions about the kind of sales team this model works for. First, dynamic books requires an account-based GTM motion.
And for your books to be truly dynamic, you need to know who your ICP is. That means the account selection part of your GTM strategy is super duper critical. If you don’t know what kind of accounts make high priority prospects, then it’s going to be really hard to dynamically distribute high-potential accounts to reps. (There's a twist to this in a minute, though. Keep reading.)
You've got to nail your team's account selection.
That's why sales teams spend so much time figuring out who they should go after.
Think about the time your team spends on ICP and intent scoring, territory planning, qualifying and disqualifying accounts, account mapping, finding the right personas, titles and their accurate contact information, and so on. It's a LOT.
For larger or more mature teams, you’ve probably already got all the accounts you could possibly need in your CRM. You just need to figure out which ones to focus on.
And for smaller or younger teams, you may not have your full market identified and in your CRM already, so you end up spending your time finding new accounts.
Either way, the act of simply figuring out who you should call is time consuming, expensive, complicated, and almost impossible to get right.
In the before times (back in the ZIRP era), we could throw bodies at this problem. Got too many accounts? No problem - hire an army of SDRs to research those accounts.
But that’s not a realistic solution for most of us anymore, even if we have the funds to support it. Ultimately, it’s wasteful to use humans to do something computers can do faster, cheaper and more accurately. (And don’t worry, we still have plenty of other work for those SDRs and other sales humans to do.)
Account selection is important in the dynamic books process for another reason too.
With dynamic books, accounts are continuously cycling through the assignment loop. A rep gets a new account, works it, and either creates an opportunity or returns the account to the pool to get another in its place. When they create an opportunity, we learn something.
When they return that account, we learn even more.
In dynamic books, account returns are an incredibly valuable source of feedback for revops. When a rep returns an account, they need to include a reason for that return. Was the account too small to sell to? Has the company gone out of business? Are they under contract with a competitor? Was the contact data bad?
This information helps us learn about what kind of account is a good - or bad - fit for our solution. If we can get some information about an account, then we haven’t wasted our time contacting a company that turned out not being a good fit. Maybe we got info about when to reach out in the future (we call this a “Get Back to Me” or GBTM), or maybe we found out that a particular account needs some data cleanup before being reassigned.
And when we collect return data in the aggregate, we learn more about our ICP. Are we targeting the right kinds of accounts? Are there fit criteria we might not have considered? What can we uncover that helps us re(de)fine our idea customer?
And that’s the cool thing about dynamic books. Any little thing you learn about what makes a good customer (or a bad one!) impacts the accounts you distribute next time. You’ve got an amazingly effective feedback loop that lets you learn about who to call, and helps you clean up your database at the same time.
And reps are happy because not only are they continually getting new and better accounts, but they’re empowered because they have input into the account selection process by including return reasons to help improve future distributions.
It’s a win-win-win.
