My biggest learnings from working at enterprise startups
My biggest learnings from working at enterprise startups
I've found these to be true for enterprise startups, regardless of industry.
As a serial early-stage startup employee and advisor, I've seen the ups and downs of this stage and still keep coming back because I love it. I've spent a lot of time reflecting on some of my biggest learnings for enterprise startups from Seed to Series B—across product, go-to-market (GTM) and company building. What surprised me most is how consistent these learnings are for enterprise startups, regardless of industry.
Mistakes are inevitable (even, desired) in the startup world. My goal isn't for founders to avoid these altogether, but to recognize signals early and quickly course-correct. I hope to help founders navigate the tensions at this stage, come out stronger on the other side, and make new mistakes.
Don’t try to sell an enterprise-ready product when you don’t have one
Enterprise sales cycles are long, > 6 months, and it's easy to fall into the trap of assuming you can build the necessary features during that time. Personally, I haven’t seen this approach work well.
Instead of “building the plane while flying it” for an enterprise-ready product, startups that believe enterprises are their best-fit ICP should invest in enterprise-readiness from day one as a true differentiator, not just to land deals.
What enterprises care about is fairly standard:
Data security and ownership of their data
Network security (run inside their VPC, use their buckets, etc.)
Access controls
Integrations & extensibility (aka API support)
Auditing (enterprises love auditing features)
Compliance
Rather than viewing these items as checkboxes to land enterprise deals, startups should build thoughtful features that demonstrate a deep understanding of enterprise challenges around reliability, performance, scale, and user experience.
Some examples of demonstrating enterprise as a differentiator could be :
Investing in “magic” alerts that can be triggered on certain thresholds—alerting fatigue is a key concern for enterprises.
Making audit logs structured and easy to query, as well as integrating with other observability tools.
Thinking through how “scale” shows up in all your features—this includes designing every aspect of your product to ensure tables paginate well and can manage hundreds or thousands of entities and alerts.
Another key learning about selling to enterprises is separating out engineering resources that support the sales team from those working on your main roadmap. You don’t want a false battle inside your company between focusing on core differentiation and making small customizations to land deals.
Lack of a clear differentiation thesis
We’ve all heard the platitudes: “competition is good, the market is validating the category,” “the market is big enough for multiple players.”
Yet in most markets, there is a winner—at least from a market perception perspective.
How the winner got there is a question of their company strategy, but why is clear: they were differentiated.
Most product visions are not differentiated, yet achieving them assumes market dominance (where differentiation is critical). For example, if I showed you just the vision statement of a company, you probably wouldn’t be able to guess who it is—many companies aim to “personalize customer experiences", or other similar broad statements.
In the space between where a startup is today and their future vision lies how they’re positioned at each step of the journey, and I believe too often “differentiation” gets lost along the way, and your competitors out-execute you.
A great diagram from April Dunford showing the relationship between Positioning, Strategy & Vision (Source)
I believe that in addition to their product vision, startups should clearly identify a differentiation thesis on how they’ll be different from everything else while achieving that product vision.
How you do that is a whole other post! But essentially, my advice is to invest early in positioning on order to define with conviction:
How you’re 10x better than any other product and can prove it.
Your startup's inherent advantages.
Build your product and GTM strategy on a strong foundation of differentiation and lean into your advantages. We can all agree it’s much easier to sell a differentiated product, but startups worry they will fall behind by not entering the market and try to “figure out” differentiation along the way. But here’s the catch: you can’t build differentiation by doing what everyone else is doing.
Not focusing on their best-fit customers
Good positioning isn’t just about defining who your product is for, but also who you’re not for. In the early stages, startups are very afraid to say “no” or disqualify a customer. This causes massive problems with focus in the company.
Just like when you build a feature, you’re not just signing up for the cost of building that feature, you’re signing up for a lifetime of maintaining it. The same is true for a customer. When you acquire a customer, you're not just spending time and money on their acquisition; it’s a long-term investment in retaining and growing their lifetime value (which means lots of support). Startups should build conviction on a positioning direction as soon as possible and stick to it by disqualifying companies that don’t fit. The outcome of a positioning statement isn’t just a document; it must be reflected in your GTM decisions.
Scaling the sales team too early
Most people use a “work backwards” methodology to grow a sales team. For example, to grow revenue by $2M, you need 4 salespeople with a $500K/year quota, taking 4-6 months to ramp up, so you need to hire 4 salespeople ASAP. It’s important to do both "work backwards" and “play forwards'' modeling. Achieving ambitious revenue goals often requires massive leaps, so it’s crucial to interrogate the assumptions behind these leaps. If you hire 4 salespeople, where will they get leads if no one is focused on enterprise demand generation? You need to de-risk your bets by ensuring your underlying assumptions are less risky, for example having 3x more pipeline for one salesperson is a good signal to hire a second.
A common trend with these decisions is that founders often only account for the time it takes to make the initial decision, not the ongoing focus and ‘maintenance’ cost. For example the hidden costs of hiring 4 salespeople means:
Massive investments in sales enablement and training
The need for a sales manager
A couple of meetings a week to align the sales team
Lots of randomization for the engineering team
Not anchoring on domain expertise for early sales hires
Related to scaling the sales team is who those early sales hires are. Enterprise customers are demanding more of a consultative sales process. They want added-value beyond your product in the form of advising them on best practices – most enterprises are paranoid they aren’t doing things the right way.
As a result your early sales hires should have some domain expertise and be excited to become experts on a topic. It’s going to lead to greater success in your sales motion and will save you a lot of resources on enablement.
I know what you’re thinking: how do you find developers who want to do sales? Lots of startups have proven success with hybrid roles partnering with sales like developer evangelists, Figma’s design advocates etc.
If marketing should think about building a 'media company,' I believe your sales team (or at least sales engineering team) should aim to build the most profitable consultancy in your field.
Not investing in demand generation early enough
That leads me to my next point. There are two parts to demand generation: capturing demand today (ensuring that people who are in-market for your solution find you) and creating demand (building trust and authority with your target persona so that when they’re in-market, they will think of you).
Creating demand is a much longer-term investment and, therefore, needs to be kicked off at the same time as capturing demand. At the beginning, startups are very focused on “getting leads now” and lose sight of the fact that every week they aren’t investing in the long-term strategy, they’re hurting their top of funnel (TOFU) for the future. Creating demand involves investing in brand, education, and high-quality, authentic content through “dark social.” That’s how you end up with 5 salespeople and very little pipeline, resulting in a lull of at least a year while you try to figure out how to build that pipeline.
Not investing in partnerships
I’ve come to see that partnerships are critical for enterprise products. I like to think of a partnership ecosystem kind of like a solar system. Some products are “sun” products – these are the sources of truth (or centers of gravity) for different kinds of data: customer data (CDP or Data Warehouse), employee data (AD), financial data (ERP), etc. Most startups are building products around these “suns,” and as a startup, it’s important to understand who your “sun” is, as well as how data flows in and out of your product. This understanding is crucial because enterprise products need to have strong integrations, which create great opportunities for partnerships.
I’m not an expert in partnerships, but the most successful strategy I've seen is hiring someone who has clout at one of your “sun” companies, as that will save you a lot of time and energy in building the relationship.
Raising too early
Why do startups scale their sales team too fast? Because they raise too early, without strong validating signals that the money can be used to fuel repeatable growth. Using an analogy from marketing, the common knowledge when scaling a marketing channel, like LinkedIn ads, is to start with a smaller budget, prove that the channel is viable, and only then scale it up. For example if you start with an initial budget of $5K and get 10 leads at $500/lead, you could assume that spending $50K (10x the initial budget) will get you 10x more leads. But that’s still only 100 leads for $50K. You haven’t proved the channel is viable.
What I’ve seen is startups raising sizable Series A’s with only $1M in revenue and investors telling them to spend that money to grow, but they didn’t have a viable plan in the first place.
I believe that getting to $1M ARR is no longer a reflection of strong market differentiation and PMF fundamentals for enterprise companies (where ACVs are higher). Instead, I believe $3M is a much better indicator of success. Now, I’m not necessarily advocating that startups wait until $3M ARR to raise a Series A; I’m merely saying startups should ensure their underlying “machine” assumptions are correct before adding more money to them. Otherwise, you’re just scaling something that isn’t working.
Compromising the hiring bar
This one is near and dear to my heart as I’m really passionate about building amazing teams. Under the pressures of trying to grow quickly, startups often compromise on their bar for hiring. I understand why it happens, yet I’ve never seen it work as desired. It always hurts growth and leads to more problems down the line.
The cliches here are all true (that’s how they became cliches), "A players hire A players and B players hire C players", “hire slow, fire fast”, so I’m not about to tell you to just do them. Perhaps the best reframe I’ve heard is to hire people who are excited about hiring people smarter than them.
Be especially careful when hiring executives, as they will set the quality bar for their team. Ideally, they’ve seen your stage and include experts on your hiring team, e.g. a successful VP of Sales who worked at a company at your stage with your business model, when hiring your VP of Sales.
Takeaways
If I think about some of the common threads from these learnings, they are:
Not focusing well
Not investing in something early enough
Scaling too fast
I realize there are inherent trade-offs in even implementing these learnings—focus on only this thing, but also remember to invest in this other thing now otherwise it will hurt you later.
Sigh, startups are hard. But I hope by sharing these learnings I can help accelerate your learning curve and help recognize patterns from mistakes I’ve seen before.
And ultimately, there's nothing more fun and fulfilling than tackling these challenges with an awesome team and making a real impact with large enterprise customers.