Going beyond "individual productivity" in GTM AI
Dissecting a recent GTM AI report and its findings.
This past week, Scale Venture Partners released their State of GTM AI report, and it’s quickly become one of the best reports that I’ve seen lately.
(Kudos to Charlie, who sent it to me as a must-read.)
According to Scale, they teamed up with Benchmarkit to survey 278 GTM leaders and interview dozens more about their GTM AI adoption and use cases.
And the results were interesting.
Mainly because they confirmed some of the beliefs and findings we’ve had here at CS2. But also because, according to the results, 80% of GTM teams are using AI! A higher number than I expected.
And they noted the main reason the other 20% are not is because they don’t have people with the skills to use it.
Some of you might be thinking, “80%? Really?”
When you dig down further, you’ll find that a majority of those teams are still in what Scale (smartly) calls “Phase 1,” which primarily focuses on use cases that support individual productivity.
And the team that is adopting at the highest rate? Marketing.
Not a shocker, right?
SDR and sales are just behind them.
In Phase 1, GTM teams’ top use cases are creating content, drafting messaging, conducting research/scoring, and enriching prospect and customer data.
When done well, these are all great at boosting productivity—from time savings, but also through better prioritization for sales.
The results are still good. More time, better targeting—of course you’ll see some gains.
However, in my opinion, effectiveness in GTM needs to go beyond productivity and efficiency gains.
Unless the output of everything (including messaging, targeting, etc.) is great, then it doesn’t matter how fast or at what higher volume you’re doing it.
And that’s why I was stoked when I saw this quote in the article: The next phase (Phase 2) is about doing better, not more.
This means a focus on quality and use cases that will benefit the goals of the full GTM team (i.e., increased pipeline, velocity, and conversion rate to closed-won business).
This is key.
We want to go beyond individual productivity/efficiency to full department (GTM team) metrics. (aka pipeline and revenue!)
So how do we get there?
I was stoked to see Scale’s thoughts align with what both Charlie and I have been talking about together recently.
Here are the highlights on how to move to “Phase 2”:
Ops needs to be driving the initiatives (not just leadership).
In fact, GTM/Rev Ops-led AI initiatives were 20% more likely to have positive outcomes.Hire GTM engineer(s)
I see both 1 & 2 as related. In my opinion, the wise thing to do for companies would be to have a separate group or even just one person who is really driving these initiatives. A lot of the operations will still need to run as it usually does, but having someone or a team solely dedicated to researching and testing out AI initiatives will see better results because it will actually get done. If you don’t have the people-power, hire an agency!You need to identify the top use cases internally through your own auditing and research.
Ops folks do this all the time for their projects, so this is just another reason why ops should lead the initiatives. The easiest places to start are by interviewing sales/SDRs and looking at important parts of the customer journey and operations foundation that can be best improved with AI.Empower functional teams to experiment by using tiger teams and setting up AI Hackathons.
I somewhat agree with this. However, I think that GTM teams need to work together to ensure that anything they are using or building supports a cohesive and better (not worse) buyer journey and sales process.Adopt a “buy and build” strategy and use your GTM engineer talent to build internal capabilities and complement them with best-in-class vendors.
Love this advice! I want to emphasize that stockpiling tools without a strategy will not get you anywhere. Your team can get so much out of a few tools plus the ones the GTM team is already using! (i.e., n8n & Clay paired with SFDC, HubSpot, Gong).
Well, there is my own summary (not AI generated! lol) and analysis of the report!
What do you think? And are you in Phase 0, 1, or 2? Would love to know.
Watch on YouTube 🎥
Let’s be honest. AI is “smart.” But some things can really trip it up. Including your data.
Here are 5 GTM data issues that can confuse AI.
What We are Cookin' Up (for real)
Are you a Fall food lover like me?
Pumpkin is cool - but you won’t catch me with a SBucks PSL at any moment during this season.
In fact, I have been straying away from most things pumpkin spice flavored unless it’s a loaf of homemade pumpkin bread or some pumpkin butter.
Fall has so much more to offer when it comes to flavors, produce, and cozy dishes.
Especially the fruit! My faves are the apples, pears, and cranberries.
Apples and pears are meant to be savored right now! And whether they are fresh or cooked up in a baked good - they pair so well with spices like cinnamon and clove.
And cranberries should get more shining moments beyond the Thanksgiving table.
And one delicious thing I have been prepping as part of my morning breakfast is chai spiced stewed fruit.
I put it on top of skyr (Icelandic-style greek yogurt) and top it off with homemade granola or Catalina Crunch cereal. It’s literally like eating dessert for breakfast.
I pair with 2 eggs as my “sweet” side with a boost of even more protein.
Here is my “recipe.” You can always leave out cranberries and create a thicker/chunkier mixture of apples and pears, which is equally delightful. Just make sure to reduce the water.
Chai Spiced Stewed Fruit
Ingredients:
1 tablespoon Chai Masala spice blend
1 teaspoon extra ground cinnamon
1-2 apples diced
1 large asian pear or 2 bosc pears diced
1 bag whole cranberries
1 to 4 tablespoons maple syrup (varied based on your sweetness level)
1 teaspoon salt
2 cups water (only 1 if you leave out cranberries)
Directions:
- Pour all ingredients into a pot with a lid
- Cook on medium heat covered for about 25-30 minutes (or less if you decide to leave out the cranberries).
- Take off lid and reduce down more if it’s too “liquidy.”
- Cool down the mixture and store in a Tupperware in your fridge for about a week (or longer if tightly sealed).
Enjoy over yogurt or cottage cheese for a quick morning treat or afternoon snack!
Links We’re Liking on LinkedIn
“Marketing Ops is the glue for AI and GTM.” Agree (but also GTM Ops! hehe)
How the VP of Marketing at Vector did her pitch to her CEO and COO to secure her marketing budget.
“Wife Swap”, but for CROs and CMOs. Genius!
The current state of AI reliability. 🫠
A great example of individual productivity increases thanks to AI.
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