Blurring lines in enterprise SaaS; the race to own customer data

I’ve written before about the competitive nature of SaaS and the amount of entrants in every category.

Lately after every conversation, I feel like the world is being divided into two camps and there is a massive battle going on in terms of who is going to own them and how. To oversimplify, I’ll call it pre-customer and post-customer domination. And there are companies looking to blur both of those categories as well.

It’s pretty hard to create a new system of record these days as Salesforce, Marketo, Gainsight and the like are building tighter lock-in around their products. That’s not to say it can’t be done as those companies have larger fish to fry, mainly huge enterprise customers and $1mm + deals. Opportunities abound in the SME (small, medium enterprise), and we’ve seeded a number of founders going after that space.

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Thoughts from Mulesoft and AppDynamics IPO Filings

I finally had a chance to take a quick read of the respective S1 filings for AppDynamics and Mulesoft. While the growth for each company is quite amazing, two thoughts jumped out at me.

As we move to a cloud-only world with instant-on capabilities and low friction in onboarding customers, why does professional services revenue keep increasing year over year for these enterprise cloud businesses. Secondly, as the world continues to move to the cloud, why does on-prem software exist any more?

Looking at both S1 filings, it’s clear that AppDynamics and Mulesoft have caught on to what Salesforce already knows – if you want to be a massive business you also need to sell professional services. As these tech companies get larger and larger, their target customer also increases in size as these vendors look to move from 6 to 7 figure deals. In order to support continued ARR growth upstream, some of the best companies successfully use professional services as a weapon and make implementation, support and training part of the sale. See Jeff Leventhal’s post (boldstart venture partner and Workrails cofounder/CEO) on why services continue to matter for cloud vendors.

Same goes for why on-prem. In both S1s, we can see Mulesoft and AppDynamics discussing the need for multiple delivery models as many larger customers have regulatory and compliance needs, esp. in banking, insurance, and health care. On-premise and hybrid cloud deployments are not going away despite the continued adoption of the cloud. There is a whole world of what being enterprise ready from a product perspective looks like, and how SaaS companies can use new technology like Docker to have the best of both worlds, SaaS and on-prem without multiple code bases. If interested, take a look at EnterpriseReady.io curated by Replicated (full disclosure: boldstart is an investor).

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Building AI on CXOTalk cutting through AI hype, "applied AI" to enterprise

I had a great time participating on CXOTalk by Michael Krigsman with boldstart portfolio co founders, Sean Chou from Catalytic and Keith Brisson from Init.ai

When you get down to it, AI is going to be huge in the enterprise but you need to make sure to focus on solving real business problems. Watch to learn more on our discussion about “applied AI.”


Here are some nuggets of wisdom:

Companies are removing #data silos. This will enhance usage of applied #AI

@keithbrisson @edsim  on #CxOTalk

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Enterprise Collaboration Wars Lessons for SaaS startups

It’s going to be fun to watch the enterprise collaboration wars and how each company is approaching the market! In my mind it is a microcosm of many battles being played out with startups versus incumbents. Do large enterprises go for “best of breed” providers or the “one throat to choke” model? How does the bottom-up model work versus the traditional top-down enterprise sales model? As for collaboration, here is a view of some of the players:

  1. Slack – bottom up, adding enterprise features, but not on-prem yet, many early adopter enterprises but can they bridge gap to more traditional
  2. Microsoft – Teams, product not as fleshed out but starting with bases of thousands of enterprise clients due to enterprise company licenses, does that mean adoption?
  3. Box/Dropbox – coming at it from a technically commodity base layer of file sharing and storage, trying to add stickiness on top with Paper by Dropbox and Notes from Box
  4. Google – has Gsuite for Google Cloud – do they add a collaboration layer or do they just buy someone else?
  5. Salesforce – has Quip, do they keep adding layers on top?

and many others…

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Developer love vs revenue Going from Seed to Series A

Great blog post by CockroachDB on open source business models and their plans to make money:

If you’re serious about building a company around open source software, you must walk a narrow path: introduce paid features too soon, and risk curtailing adoption. Introduce paid features too late, and risk encouraging economic free riders. Stray too far in either direction, and your efforts will ultimately continue only as unpaid open source contributions.

I would say same goes for any developer-focused company whether OSS or some other hybrid free/premium model. It is truly an art form when it comes to striking that steady balance between developer and community love versus generating revenue and potentially alienating those who supported you.

This is also an important question as it relates to fundraising for dev-focused startups. Introduce your pricing page too soon and that is the metric that Series A investors will track religiously. Bet the farm on developer love and metrics only and you may never get enough traction to get to that next round.

From what I have seen in our portfolio, goal #1 is always to build an amazing community, focus on developer love and track the metrics and tweak. Without the developers, you have no customers.

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Thoughts on SaaS in 2017

When we started boldstart in 2010, a core thesis of ours was to invest in next-gen SaaS which we called SaaS 2.0 at the time and best highlighted in our end of 2015 review:

SaaS 2.0, reinventing for the mobile first workforce will continue to remain robust. We also see older school SaaS companies being rebuilt with more flexible back-end technologies like microservices and reimagined with a more responsive and beautiful UI.

While we continue to be excited about opportunities in SaaS startups, it is clear that the game has changed substantially since 2010. Despite the amazing productivity gains from open source, AWS, microservices and other new technologies, we have seen the time to launch extending and the cost of getting a minimally viable product (MVP) out the door increasing. So why is this the case?

  1. Most SaaS categories have multiple players and to build a transformative SaaS app means the bar to what a “minimally viable product” is much higher than it was 5 years ago. In other words, a MVP of 5–6 core features may now need 8–10 core. This takes more time, money, and resources. Founders need to make tough decisions on what their definition of feature parity is and what that one unique product angle will be to rise above the noise (more to come in a follow up post).
  2. The competition for talent has and continues to be fierce so as tech costs go down, human capital costs continue to increase.
  3. Cost of getting message to market has increased due to the noise from the many competitors in a particular space.

So what can a founder and investor do in this changing world?

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boldstart in 2016, enterprise tech in 2017 year in review, outlook for enterprise tech in 2017

2016 was a banner year for boldstart, and we could not have achieved any of this without the amazing support of our boldstart family and the founders who have given us the opportunity to invest in and partner with them.

Before diving into the standard year-end predictions on the enterprise, I thought I would share some data on our firm and our founding teams from 2016:

  1. we welcomed 9 new enterprise founding teams to the portfolio including Workrails (started by venture partner Jeff Leventhal), BigID, Hypr, Init.ai, and 5 stealth companies
  2. Thematically our new investments include 5 infrastructure/dev platforms, 3 security, and 2 SaaS; 4 are using some form of AI or machine learning; geographically 4 are in NYC, 3 Bay Area, 1 Canada, 1 Chicago
  3. 8 of our portfolio companies raised follow on Series A rounds with > $70mm raised and an average size of almost $9mm — announced rounds include Kustomer, Robin, Emissary, Replicated and Front — geographically 2 in NYC, 3 Bay Area, 1 Canada, 1 LA, 1 Chicago
  4. 4 of our portfolio companies raised Series B financings with close to $70mm raised and an average financing size greater than $17mm — announced rounds include security scorecard, handshake, and wevr — geographically 2 in NYC, 1 LA, 1 Canada
  5. fund iii had an oversubscribed closing of $47mm

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our journey to an oversubscribed fund iii for first check enterprise boldstart closes $47mm fund iii for first check, enterprise founders

 

This is a story about starting an enterprise seed fund called Boldstart in 2010 and our journey in enterprise since 1996. Despite our firm being a little over 6 years old, our individual stories go further back. We each independently fell in love with enterprise software 20+ years ago as seed investors (cos like gotomeeting/Citrix, greenplum/EMC, livperson/IPO LPSN) and founders (workmarket, onforce/Adecco, spinback/buddymedia/salesf0rce) and are now benefiting from the ecosystems, knowledge and network that we’ve collectively developed.

What seemed like a big bet in early 2010 was only us pursuing our passion. Our goal was to be the best first check partner for enterprise founders, bringing the value add of a VC firm while moving with the speed and conviction of an angel investor. We set out to build boldstart at the height of mobile app mania and viral growth and were faced with questions about our focus on enterprise and NYC. At the time there were only a handful of micro-VCs in existence, and despite going against the tide, we felt that the opportunity to build the first and best enterprise seed fund was a dream worth pursuing.

Today, we are super excited to announce our final close of $47mm for fund iii. This was oversubscribed from our initial target of $30mm

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The 4 Kinds of Series A Rounds in Enterprise roadmap for understanding how to go from seed to Series A

A wise VC once told me when dinner is served, you eat. When it comes to fundraising, I’ve learned that if someone is trying to invest now, you should strike while the iron is hot. Given that the headwinds are getting stronger, we at boldstart have been advising all of our portfolio companies to raise as much as they can as soon as they can and to make sure that every dollar spent has a real ROI.

Related to this, the question I am often asked is “what metrics do I need to hit” to get that next round. While super important, I always like to understand where the business is in its lifecycle before answering. Having spent the last week in several meetings with startups going from seed to A, I thought I would break down the various types of A rounds and the major ??? to success:

The 4 kinds of A rounds:

  1. No A round. Sucks. — self explanatory
  2. Vision A round, super hard — raise on the promise and pre-launch, on the vision, huge market with the killer team that can build and scale. sometimes easier to raise on the promise and the expectations of amazing success than after the launch
  3. Metrics A round, easier — killer metrics, repeatable growth and predictable sales model, used to be $80–$100k MRR/$1mm ARR, the bar is raising…
  4. Hybrid A, toughest — this is where you are between 2 and 3 and the hardest to get done.

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First enterprise customers – revenue or user engagement? need to optimize for engagement first, revenue comes after

Since we are seed investors in enterprise technology, I am often asked this question. The answer on the surface seems quite obvious — generate as much revenue as you can to prove that customers find value and are willing to pay. My answer is the less obvious one — focus first on user engagement and the revenue and bookings will follow.

Wait, isn’t user engagement more of a consumer metric? It is, but it is equally as important to focus on this metric in the enterprise. No matter what business you are in, you need to ensure that your ultimate customer (the end user) is happy and absolutely loves using your product. I have seen countless situations where a startup extracts initial dollars top-down from an enterprise but ultimately cannot get traction because the end users don’t love the product. Without love of product there is no user engagement, and without user engagement, there is no long-term customer.

This is especially important in the age of SaaS as switching costs are quite low for substitute solutions. This is also the reason why next to VP of Sales, I would argue a VP of Customer Happiness/Success is a crucial hire. One is for generating new revenue and the other is for expanding existing customers and reducing churn. It is also why a number of companies have been created to help understand and monitor user engagement in the enterprise to proactively determine issues before they happen (totango, gainsight, and preact — full disclosure, my fund is an investor)

What is user engagement in the enterprise? When understanding initial customer traction, we like to understand how a product/solution can/will become a daily habit for the user. It is pretty clear that the more an end user interacts with the product the more important it becomes and ultimately the more value it provides. Another important metric to optimize for would be expansion of users within an existing account. In other words, how do you sell into one user and create viral loops (sharing dashboards, etc) and expand the active user base for the product. Once again, this sounds like a consumer metric but quite an important one —the more people that use it the more it becomes part of the ingrained workflow creating more value.

The challenge sometimes is that many enterprise tech companies are designed to work in the background, invisibly to automate tasks or aggregate data to reduce noise. If your tech is seamlessly analyzing data in the background, you need to find ways to show the user how awesome your product is by either sending alerts or creating some other eye candy to remind the user that your product is working and important. I have seen a few of our portfolio companies implement some simple changes regarding this and see their usage increase significantly.

So to recap, revenue matters but the path starts with optimizing for the end user in the enterprise and focusing on engagement. Once you create happy end users who love your product, the revenue will follow.