Ever since I was little, I've struggled with making decisions.

Well, not every decision.

But definitely decisions where I had a lot of choices.

All my other siblings could pick a flavor at Baskin Robbins before they even walked in. I, on the other hand, looked at every single flavor and when asked what I wanted, would get a surge of paralyzing indecision.

Even multiple-choice exams were hard for me. (I used my ACT scores instead to get into college lol)

And on top of it, after I made a decision, I would often voice my regrets.

Luckily, this hasn't been the case for important things in my life—mainly because those don't give you so many options and they were no-brainers! ☺️

• Decision to get married → 1 partner
• Decision to start CS2 → only could compare to my current job
• Decision to have kids → didn't know otherwise lol

As a leader, I've had plenty of self-reflection to know that making decisions faster (but informed) is better than slow and drawn out. So over time, I've become confident in my decisions.

But it's very clear when making decisions becomes hard: when you've already used a ton of brain power and energy to make many other ones.

Yes—this is called decision fatigue.

Popularized by Steve Jobs's reasoning for wearing the same thing every day. The more you can free up your brain from making choices on things that don't matter, or limit how many decisions need to be made, the more energy you have for the ones that are critical.

And you know what I think is going to plague GTM teams with this new rush of AI?

You guessed it - decision fatigue.

Because now, not only are we making decisions on WHAT to do—we're also forced to make decisions on HOW to do it.

With so many new AI tools coming out, new features being added to existing tools, and the GTM playbook changing so rapidly, the decision on how to do something feels daunting.

I even see companies not making decisions on certain tech purely out of wanting to wait to see what new and better tool will come out. And honestly? I don't blame them.

To really understand what I am saying, let's take an example of a GTM ops process and how the decision-making has changed.

The Task: Creating a Target Account list for sales

The Process Before

• Identify your company ICP and document the key firmographics (company size, industry, technologies used, region, etc.)
• Build a list of accounts with those firmographic filters from your data platform
• Export the list and dedupe it against your current Account list in CRM
• Prioritize accounts to flag as targets that have had engagement
• Task the sales team to also select targets from the list that match their territory
• Flag those accounts in CRM and revisit the same exercise the following quarter

Now, there were clearly things we knew that made this process not the best. But there were very few decisions to get this done. The GTM team used the tool they had and the data they had.

The Process Now (With New Questions)

But now, with the playbook changing, more intent data at our fingertips, and even more data sources available, the "how" we do this uncovers way more decisions to be made.

Identifying your company ICP:

• Should we leverage AI to analyze all our closed-won deals and see if there are other commonalities in those accounts that our data team isn't seeing?
• What tool should we use to do that?
• Is it secure with our PII data?

Building the list of accounts:

• Why only use our one data tool when we can leverage multiple?
• Should we use something like Clay, where we can leverage multiple sources and also use its integrations to get key data on those accounts that our AI analysis gave us and our current data platform doesn't?

Prioritizing accounts:

• What about the accounts that are showing intent? What do we do with that data?
• Do we cross-reference it from our existing accounts and make those instant targets?
• Do we also prioritize the list of new accounts we found with this intent data?

Prioritizing accounts with intent data:

• We have 3 tools that give us different types of intent data. Some of it is first-party intent from our website, some of it is signal data, which includes offsite activity, and some of it is a combination from another tool.
• Which source do we trust, or should we use all of it?

Finalizing the list of accounts:

• Should we let sales have a say in their targets? We just spent a lot of time and effort compiling this list of accounts, but what if the reps don't trust it because they didn't have a say?

Flagging the accounts in CRM:

• Should we continue to do this manually, or should we have an automated process that cycles out accounts based on new account signals/intent we see or if an account is already being worked?
• What tool should we use for this automation?

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Is your brain SPINNING?! 🤯

We've always been kind of building the plane as we fly it in GTM Ops, but holy smokes—it feels like we're also wondering if we should just stop building that plane and build a rocket ship instead during the process.

Each time the GTM team is positioned with these new decisions to be made, I feel like it will get even harder to make them.

My Current Advice (Still Figuring This Out)

I'm still working out the best advice on how to combat this ourselves at CS2, but here's what I've got so far:

1. Don't reinvent the wheel. If you have processes that work well and support the new marketing playbook and your current GTM strategy—leave them alone!

2. Look at adopting new features/functionality within tools you already have. Companies like HubSpot are already introducing innovative features, such as instant enrichment, intent tracking, and AI summaries. Really look to stretch your current tools first.

3. Don't make every decision a hard one because you want to use a cool new tool. I already see companies collecting tools, and this makes architecting solutions hard because you're just so unsure about what tool should be used for the job.

4. Don't have the mindset that everything should just be "automated." I don't think a lot of GTM in B2B is best suited for being run by autonomous agents. I also don't think good marketing can run on its own. And I don't think a ton of automation from a million tools is setting up any GTM team for success.

5. Above all else—try to approach problems with simple solutions. Simple doesn't always mean unsophisticated! But the more "what ifs" or "what about this" you hear in a conversation, the less likely you'll get anywhere close to a solution in a timely manner.

Have you been feeling some decision fatigue lately?