AI & The Evolution Of The Modern Revenue Stack

The GTM Newsletter

Sep 02, 2023

Happy Saturday GTM’ers.

Hopefully you’re not in your inbox right now and you’re out enjoying the long weekend.

But lots to cover this week, whenever you read this, so let’s get right into it.

We’re officially running a GTMfund Summer Giveaway: Share your favourite piece of our content (Newsletter or Podcast) on either LinkedIn / Twitter, tag us, and you’ll be entered to win a pair of exclusive GTMfund Airpod Pro’s.

Alright, AI continues to be the biggest talking point of 2023 (are we sick of talking about it yet?) - with every SaaS company on the face of the earth looking to experiment with some kind of AI integration into their software; It’s become quite apparent that less is more in today’s world.

And with this, business’ want a consolidated rev tech stack with deeper capabilities infused with AI. So that has many of us questioning which direction we should be heading toward in our modern day revenue tech stack?

What are today’s must-haves and what are the nice-to-haves?

Which AI tools are going to make revenue operators’ lives immensely easier?

Our RevTech stacks used to be much simpler… today we have an overwhelming amount of tooling and it can be hard to keep up.

With annual revenue declines in the last couple years, headcount decline and advancement in AI, organizations are prioritizing the ‘must-have’s’ and getting rid of any ‘nice to have’s’

This is what the RevTech landscape looks like (and this is from late 2022…there’s likely 100+ more start-ups added since then):

According to an article written earlier this year by Gartner on The Market Guide for Revenue Intelligence Platforms there are 5 must-have qualities that your RevTech stack should have in 2023:

Activity intelligence: Detects buyer interactions in other systems and turns this information into insight for the seller and manager.
AI-guided selling: Drives seller effectiveness and efficiency by delivering feedback on deal-related efforts and prescriptive guidance on what actions to take next, based on AI analysis.
Opportunity health assessment: Uses activity information, combined with other deal attributes, to provide insight on overall deal health.
Pipeline analytics: Offers sales managers a view of their teams’ pipelines that goes beyond what’s available in their native SFA applications. Incorporates outcomes of activity intelligence and opportunity health assessment to illustrate risks and opportunities down to the deal level.
Forecast prediction: Uses augmented analytics to offer insight on deals in the pipeline that sellers expect to close in a given period through an AI-driven predictive forecast recommendation at multiple levels of the sales hierarchy.

We asked a few of our GTM revenue leaders to weigh in on the subject:

What are still the must-haves in 2023?

—-

Robert Simmons - VP of Sales

I have lots of Sales Tech I love, but here’s my must must haves:

Salesforce, LeanData (Matching & Routing within SFDC), a quality data provider (LeadIQ, Seamless, Apollo, ZI), Clearbit (enrichment), Slack, LinkedIn Sales Nav, Outreach (sales engagement), and call recording (Gong, Avoma or Chorus).

Next highest priorities would be intent data (prefer 6Ssense), forecasting (Clari, Outreach, Gong), and content repository (Highspot).

Kyle Norton - SVP

My main RevTech stack isn’t too complex. Here’s what we use: CRM (SFDC), Sales Acceleration (SalesLoft), Forecasting (SalesLoft), Conversation Intelligence (Gong), Data (custom in-house), Automation (Momentum).

Brian Weinberger - SVP of Sales

CRM (Salesforce preference)

Quoting connected to Salesforce (We use Tyso - it’s very effective)
Email/Prospecting/Outbound - Outreach
Call Recording - We use Chorus (Gong is higher end)
Data Enrichment (If you get a lot of inbound) we use Clearbit
G-Suite
Slack
Docusign: eSig
Zoominfo
LinkedIn
ChiliPiper: Routing
Workramp: Enablement
Paerflight moving to Seismic: Content
COMPANY Tech We Use: 15Five (1:1s and OKRs)
Cube - Sales Planning & Analysis

Have you consolidated spend as platforms start to get closer to feature/functionality parity? Why or why not?

—-

Robert Simmons - VP of Sales

No, we’ve actually done the opposite and couldn’t be happier. Moved from one consolidated vendor for a lot of stuff to having a best in breed tech stack of all purpose built solutions and it’s great.

Kyle Norton - SVP of Sales

Yes, we’ve recently started consolidating, we got rid of calendaring tool and adopted the same functionally from one of our current providers and it has definitely brought some positive value from us!

Have you re-negotiated current contracts given the market?

—-

Robert Simmons - VP of Sales

Yes, at time of renewal we’ve negotiated and came to mutually beneficial terms.

Kyle Norton - SVP of Sales

Yes, with almost every vendor.

Brian Weinberger - SVP of Sales

We have re-negotiated contracts as the renewals come in.

What are you currently experimenting with? (AI tools?)

—-

Robert Simmons - VP of Sales

AI around outbound email personalization with LeadIQ.

Kyle Norton - SVP of Sales

Replayz.com for AI powered call scoring
Momentum.io for AI based automation
Chat GPT frequently

How much are you spending per/rep? Has this gone up or down over the past year?

—-

Robert Simmons - VP of Sales

Same per rep as last year. We got rid of some nice to have tools but also moved away from a consolidated vendor to best in breed solutions and thus the cost went up in some areas.

Kyle Norton - SVP of Sales

$250/user/month. It’s gone up slightly but nothing significant.

Where do you think revenue technology is heading?

—-

Robert Simmons - VP of Sales

A lot more automation and AI. Tools can largely do prospecting and emailing nowadays. Sellers need to focus on, and master, all of the human to human interactions in the buying journey, everything from cold calling to complex negotiations. AI and automation can replace most everything else.

Kyle Norton - SVP of Sales

This is really hard to answer because we seem to be bundling and unbundling at the same time. There are a number of AI-powered point solutions entering the market for specific use cases while many major vendors are consolidating more pieces of the revenue stack. If I was to make an educated guess, most organizations will consolidate around 1 primary tool and drop the point solutions that they’re using today to reduce cost and complexity but add some AI tools for specific purposes.

Brian Weinberger - SVP of Sales

I do not see a world where sales teams do not have the tools above…however when I list this out, it’s pretty nuts how much our small team does use

Let’s hear from the VP of GTM Strategy & Operations at Udemy , Noah Marks

I feel like a lot of room for disruption - particularly where AI can provide better insights, or build better models. I am super unimpressed with the current Go-to-market tech stack options…If I found the right team to start a company to take out all of them I would. A couple of big challenges & trends.

1) Data/insights often lack. I can see AI filling that hole, and I'll take 70% of functionally if I can get better insights on what to improve, what to double down on, etc.

2) Every tool is disparate - too much so. To this, I think M&A should heat up - or at least I'm willing to engage vendors that can combine multiple items. So that market dynamic is interesting. Not only is data disjointed but rep engagement is disjointed too. eg - a rep finds the right people on sales nav, then goes to ZI to download the contacts, then loads to Salesloft/Outreach, then that data in SFDC gets loaded to Marketo - even the bad data, so you pay for extra records and have to cleanup all the time. So like Apollo - combine salesloft and zi, then store the data outside SFDC until a contact is validated, then load to Salesforce/Marketo. That makes perfect sense.

3) If you don't own the exec dashboard, you are expendable. So Clari/Boostup have a unique spot where they are the place where teams/execs can go to monitor pipeline/sales. Boostup has the raw ability and then couldn't deliver (for us) but they fundamentally had a better foundation than Clari (ability to snapshot data so you can use Boostup for historical trend reporting) - something Clari cannot do b/c it just leverages SFDC data, which is constantly in flux.

4) AI for modeling. That applies to prediction models - all vendors are bad at this, and lead scoring - everything I've seen via AI for lead scoring is better than any vendor out there (b/c lead scoring is just snake oil), it's all manual yet people think there is some magic behind it.

Lastly wanted to share our GP, Max Altschuler’s recent take on the broader AI landscape:

There’s a lot to be excited about in the world of AI. Nvidia and the chip companies are getting hammered with massive orders sending their stocks soaring. Reports of OpenAI doing a billion in revenue just came out this week. AI companies like Hugging Face, Mosaic, and more are garnering multi-billion dollar valuations and rapid growth.

But the space isn’t something you can look at with broad strokes. It’s complex. Companies come across our desk every day that are small features or nice-to-haves. They have design partners or minuscule revenue from other tech companies that scream false positives for product-market fit. Starting as a feature is fine when it’s a wedge to something bigger, but all too often, we’re not seeing what that bigger vision is or why they would need more capital in the first place.

When a new groundbreaking piece of technology like OpenAI comes out (previous: mobile, social, etc), it usually breeds a new wave of startups that can be more agile and take advantage of new markets being created, faster than the incumbents.

This time, however, AI technology helps the larger incumbents more than it helps the startups because any LLMs plugged into the larger companies will already have built-in workflows with massive data sets to train on.

So there are many areas of opportunity, but not everything branded with AI is worth a look. You still need a moat and a real, scalable market opportunity.

We’ve put ourselves in a prime position to invest in AI infrastructure, Enterprise AI, and Vertical AI companies and we have been since our inception in 2021. One of our very first checks as a fund was into Simplified’s pre-seed round.

Over 70% of our recent portfolio companies now have some variation of AI infused in their software already.

You look at companies like, Writer, one of our fastest-growing companies, and you can see that the market is ready to adopt Enterprise-level AI.

Another thing we’ve been looking at is how AI is used in public tech company’s earnings calls to make those companies run with better efficiency. You can easily spot that this is not just a trend but a core pillar of any modern software/hardware infrastructure.

What we’re finding is that the startup world still knows so little about AI, but what we do know is that it is here to stay for the foreseeable future. It’s impact on life as we know has just begun - but there is still so much to learn and even more to build.

👀 More for your eyeballs:

One of my favs, Udi Ledergor, goes deeper on this topic below.