- Houck's Newsletter
- The Founder Journey: Anis Bennaceur
The Founder Journey: Anis Bennaceur
And why you're probably closing fewer deals than you could
Who’s your startup’s biggest competitor? Would you ever join forces with that founder on a new idea?
After moving on from their previous startups, they met up for coffee and realized they’d both hit a similar pain point:
How to make their sales motion close more deals without needing to invest in coaching.
Fast-forward 9 months and Attention is rapidly growing and already signing big enterprise deals.
I caught up with Anis this week and our conversation hit on a few good insights I wanted to pass along:
What most founders miss about increasing win rates
Why hiring engineers is different than other roles
Why “land and expand” works for AI startups in particular
Why you should sell to startups first
The Founder Journey: Anis Bennaceur
What Most Founders Miss About Increasing Win Rates
As a sales team grows one of the biggest problems it faces is consistency — of messaging, framing, talk tracks, cadences, etc.
Managers can’t be expected to be on every call with every member of the team.
So if you’re serious about sales then chances are you now use one of the call recording software players that have emerged in the last few years. These notetakers will show you recap notes, but lack the broader business context of the conversation.
The other issue with these tools is that, while they do a good job of showing you the conversation recordings and some surface-level aggregate information, they lack the proactive and generalized insights, rep analysis, and self-coaching capabilities to progress a deal that a tool built from the ground up with LLMs like Attention provides.
Imagine for example that you want to stack rank why you’re losing deals to your competitors. Attention makes it simple (and you can specify this to specific competitors, reps on your team, deal sizes, etc):
The teams that maintain high win rates in this new AI-powered era will be the ones that embrace proactive insights that can be as specific or, critically, generalized, as needed — and Anis believes this is something most founders and leaders are currently missing.
Hiring Engineers is Different
When you think about the engineering culture at startups the first thing that probably comes to mind is Facebook’s famous motto “move fast and break things.”
That mindset became ubiquitous with startup engineering over the last 15+ years and, while nothing’s perfect, a power-law-driven approach to solving technical problems has helped create many massive companies ever since.
So if “move fast and break things” leads to good results more often than not, the critical question becomes who you actually want to be doing the moving and the breaking. Who can you trust to go fast and not break too many things or the wrong things?
Anis brought this up in our chat — at Attention he’s exclusively looked to hire engineers with 15 or 20 years or experience.
But more experience isn’t inherently better — no, the engineers have to still be actively coding. Ideally, they’ve recently been an early engineer at another startup. They still have the itch, rather than taking a cushy gig at a big company.
However, Anis made the case that this is only true for engineers. “For other roles like growth or sales, 5 years of experience is best:
Why Land and Expand Works for AI Startups
The land and expand strategy is a classic way for startups to get big companies to become customers.
In short, rather than trying to sell your product to the entire company you instead sell it as a POC to a segment of the team, including one director or manager. As they use it, they talk about and recommend it to their coworkers and you start expanding to the rest of the org. Once enough people or teams at the company are using it, you can approach them about a full rollout.
It’s basically product-led sales 101. And it’s rising in popularity once again amongst enterprise AI startups.
Understanding why is simple. ChatGPT was the fastest consumer product ever to hit 100 million users until Threads (and it’s had considerably more staying power…). AI is sending shockwaves throughout the world and the novelty factor of seeing LLMs in new places is still quite high.
In B2B software the same thing is true. If someone at a company is able to do their job 10x faster or better because of an AI tool, chances are word will get out to the rest of the company (whether they want it to or not). End users simply want to try out and integrate LLMs into their workflows.
Anis’s company, Attention, has executed this over the last 9 months — growing at an impressive clip that he asked me not to share (it’s that good!) by getting in front of individual sales reps and managers. It doesn’t take long for a director, VP, or head of sales at the same company to reach out after seeing the insights and win rate improvements Attention is able to generate for their reps.
Sell to Startups First
Accelerators, and even Y Combinator, are arguably inherently better for B2B startups because you get connected to your potential customers within your batch.
And even as markets settle after the ZIRP era which led to a huge influx of venture funding immediately following the pandemic (see below), there’s an advantage to selling to other startups.
Anis argues that a few factors make startups attractive customers:
They have quick buying cycles with few decision makers and red tape
They can buy with large ACVs
They help you iterate way faster and optimize for your own PMF
Since their teams will grow, the upsell and expansion opportunities emerge naturally
While some startups will inevitably shut down and stop paying you, the ones that succeed will grow so large so quickly that you’ll net out well. It’s actually the same mindset VCs need to have, except you’re not making bets — you’re just selling product.
Of course, you need to build something those startups actually want to pay for and then deliver, but once you do you’ll be in a great position to grow alongside your customers and move upmarket.
Anis went deeper into the differences between the early stage when you’re selling to startups, and the later stage when you move upmarket here.