Sunday, June 26, 2016

A better way to visualize pipeline development? (WIP)

When founders show me their sales pipeline, the data is typically visualized in some variations of one of these formats:






When I see charts like this, I often find it hard to quickly wrap my head around the data and draw meaningful conclusions. Sometimes, important numbers are missing altogether. In other cases, they are there but are shown on another page or in another report.

I then find myself wonder about questions such as:

  • The pipeline is growing nicely, but how much are they actually closing?
  • How long does it take them to move leads through the funnel?
  • Are they purging their pipeline or are they accumulating a lot of "dead" pipeline value?

With this in mind I tried to come up with a new way for high-level pipeline development visualization, one that makes it easier to quickly get to the key take-aways. If you're interested in the (preliminary) result only, check out this mockup. If you'd like to learn more about my thought process and some additional details, read on.

The key problem that I have with the standard ways of looking at pipeline development is that it's hard to follow how deals move through the funnel. I've always thought that pipeline development charts should work a bit more like a cohort analysis that allows you to follow a customer cohort's development over time, and so I mocked up this:



The "pipes" give you a better understanding of what happened to the leads in a certain stage and month. For example, you can see that of the $1.6M that was in "prospect" stage in January:

  • $750k (47%) stayed in "prospect" stage
  • $500k (31%) were moved to the next stage ("demo/trial")
  • $350k (22%) were lost/purged

The next step was to add a few additional months to the mockup:



This unfortunately made things a little messy, and people will probably feel overwhelmed by the amount of numbers. One solution, if someone decides to build a little application like a Salesforce.com add-on, could be to hide all of the pipe numbers by default and show them on-hover (maybe with an option to show them all at once):



What's still missing are some aggregated key metrics ...



... and a better way to quickly grasp how these numbers have changed month over month:



Here's one mockup with all three elements on it:



What you can quickly see in this example is that this imaginary startup is adding an increasing dollar amount of prospects to the pipeline and keeps closing deals, but the rate at which it moves leads to the bottom of the funnel is declining. At the same time, the percentage of lost deals has been growing slowly, while the percentage of deals that remained in the same stage has increased sharply, indicating an increase in sales cycle and/or a poor job of pipeline purging. This has already led to a shrinking bottom-of-the-funnel pipeline, and if the company can't figure out and fix the cause of that development, it will soon close less and less deals.

All of this is something that you can immediately see by looking at these charts and numbers and which I think is usually harder to see by looking at traditional pipeline charts. What do you think? Looking forward to your comments!






















Friday, June 03, 2016

SaaS Funding Napkin, the mobile-friendly edition

My "SaaS Funding Napkin", published a few days ago, got lots of love on Facebook, Twitter, etc. Thanks everybody! Some people (rightfully) mentioned, though, that the image is hard to read on mobile devices. So if a napkin has a good format for a desktop or laptop screen, which real-world-analogy could be a fit for mobile screens?

You guessed right.

Here you go (please scroll down or click here).


Tuesday, May 31, 2016

What does it take to raise capital, in SaaS, in 2016?

When we invest in a SaaS startup, which almost always happens at the seed stage, the next big milestone on the company’s roadmap is usually a Series A. If you carry this thought further and assume that the biggest goal after the Series A is to get to the Series B (and so on, you get the idea) it sounds like turtles all the way down. But financing rounds are obviously not a goal in itself. They are a means to a bigger goal. Some SaaS companies got big without raising a lot of capital – Atlassian, Basecamp and Veeva are probably the most famous examples. But they are exceptions, not the rule. According to this analysis of Tomasz Tunguz, the median SaaS company raises $88M before IPO.

So what does it take to raise money for a SaaS company in 2016? With constantly rising table stakes and a fundraising environment that looks quite a bit less favorable than last year’s, I believe the bar is higher than in the last 18-24 months (although raising money is still much easier than it was in “Silicon Valley’s nuclear winter” in 2008).

Below is my back of a (slightly bigger) napkin answer to this question.

A few important notes:

  • The assumption of the information in the table is that the founding team is relatively “unproven”. Founding teams with previous large exits under their belts can raise large seed rounds at very high valuations on the back of their track records and a Powerpoint Keynote presentation.
  • Some of the information is tailored to enterprise-y SaaS companies. If you have a viral product (like Typeform or infogram), some of the “rules” don’t apply.
  • If you have virality and a proven founder team, you’re Slack and no rules whatsoever apply. :)


(click here for a larger version)

PS: Thanks to Jason M. LemkinTomasz Tunguz, Nicolas Wittenborn and my colleagues at Point Nine for reviewing a draft of this post!

[Update 1: Here's a mobile-friendly version of the napkin.]

[Update 2: And here is a Google Sheet version for better readability. :) ]



Monday, April 11, 2016

Introducing the French Cloudscape

For some reason we keep finding great early-stage SaaS startups in France, and it's not because of my command of the French language. In the last few years we've invested in four awesome SaaS companies from France: Algolia, Front, Mention and Critizr. We recently did #5, which hasn't been announced yet, and are in advanced talks with a potential #6. Besides our SaaS investments, we're also proud investors in StarOfService, an online marketplace to hire a wide range of professionals. Something is clearly going on in France, and we like it.

Our good connection to the French startup ecosystem was one of the reasons why we picked France as the first country for our "European SaaS Landscape" project. Another reason was that Clément not only speaks French, he IS French, and knows the market very well.

Without further ado, here it is: an industry map of the most important SaaS startups founded in France.



To learn more about our methodology and some of the insights we got while doing the research, check out Clément's post on Medium. If you have any questions, comments or suggestions, give us a shout!




Wednesday, April 06, 2016

Truffle pig reloaded – Point Nine is looking for an Associate

About three years ago, we were looking for an Associate to join Point Nine and put up this landing page:




We called the position "truffle pig", because just like a truffle pig is digging up the best truffles from the ground, we as an early-stage VC try to find the best startups among a large number of potential investments. I have to give full credit for the truffle pig analogy to Mathias Schilling and Thomas Gieselmann of e.ventures, by the way. "Truffle pigs" is what they (young VC Associates at that time) called themselves when they approached my co-founder and me back in 1997 after having stumbled on this website. Fast-forward almost 20 years and we still haven't found a better way to describe the role. :)

Anyway, our search three years ago led to two fantastic truffle pigs, Rodrigo and Mathias, both of whom got promoted to Principals at Point Nine in the meantime. And today we're excited to kick-off the search for a new Associate. Here are all the details.

This is an incredible opportunity for a young, super-smart, super-driven person with outstanding analytical skills and a solid user interface. I'm pretty sure that it took me more than 10 years to get the expertise and network which you'll get during three years in this job. 

If you're interested, please take a look at our job ad. If you know somebody who could be great fit, please pass on the link. Thanks!


Tuesday, March 29, 2016

SaaS Financial Plan 2.0 - bug fixes

Since I published v2 of my SaaS Financial Plan a few days ago, two alert readers have kindly pointed out two formula errors in the Excel sheet. Sorry about that.

Here's a corrected version. The Excel sheet that was linked from the original post has been corrected as well.

In case you've started to modify the template already and want to keep working with the previous version, here are the two bugs that you need to correct:

1) Cell U124 on the Costs tab, i.e. the costs for external recruiters in December 2016, contained:

=(W87-U87)*$E$124+X96

The +X96 part has been added accidentally and needs to be removed. So the correct version is:

=(W87-U87)*$E$124

2) Row 55 on the Revenues tab, i.e. the CACs for the Pro plan, is completely wrong. It should be, for column I (with the other columns following analogously):

=0,5*(Costs!J62+Costs!J96+Costs!J104+Costs!J112+Costs!J122)/I49

Once again, apologies for the inconvenience. If I or somebody else finds any other bugs, I will fix them ASAP and update the change log here.

PS: Before you ask – yes, I'm aware that it's ironic that I have to post an on-premise software style bug patch to a SaaS financial planning template. Ironic in an Alanis Morissette kind of way, that is, because "ironic" actually means something completely different. Google it if you don't believe me.

[Update  06/30/2016: I've fixed two further small issues that were reported by two kind readers in the comments below.]

Wednesday, March 23, 2016

SaaS Financial Plan 2.0

Almost exactly four years ago I published a financial plan template for SaaS startups based on a model that I had created for Zendesk a few years earlier. I received a lot of great feedback on the template and the original post remains one of the most viewed posts on this blog up to this day.

In the last few weeks I've finally found some time to create a "v2" of the template ... just in time for a little Easter gift to the SaaS community. ;-) I'd recommend that you read this post first since it includes some important notes, but if you prefer to check out the template right away click here to download the Excel sheet.

The original v1 model was a very simple plan for early-stage SaaS startups with a low-touch sales model. As I wrote in the original post:

It's a simple plan for an early-stage SaaS startup with a low-touch sales model – a company which markets a SaaS solution via its website, offers a 30 day free trial, gets most of its trial users organically and through online marketing and converts them into paying customer with very little human interaction. Therefore the key drivers of my imaginary startup are organic growth rate, marketing budget and customer acquisition costs, conversion rate, ARPU and churn rate. If you have a SaaS startup with a higher-touch sales model where revenue growth is largely driven by sales headcount, the plan needs to be modified accordingly.

The new version comes with a number of improvements:
  • Support for multiple pricing tiers
  • Support for annual contracts with annual pre-payments
  • Much more solid headcount planning
  • Better visibility into "MRR movements"
  • Better cash-flow planning
  • Charts galore :-)

The downside of these improvements is that the spreadsheet has become significantly larger and more complex, but I tried my best to find the right balance. Also, the vast majority of the numbers in the sheet are calculated and the number of input cells is fairly limited.

The spreadsheet should be pretty self-explanatory but I've included a number of comments in the spreadsheet. Make sure to check them out - some of them are important in order to understand the model (in case you're not familiar with that Excel feature, hover over the little red triangles).

Here are a some additional notes:

1) General comments
  • The sheet is hot off the press and given the large amount of formulas I can't rule out that there are bugs. If you find one, please email me at and I'll fix it ASAP.
  • Blue numbers indicate data-entry cells. Black and grey numbers are computed.
  • The model contains a lot of simplifications. Don't expect that it will perfectly fit your specific business - consider it a starting point.

2.) "Summary" tab
  • The "Summary" tab contains only two types of input cells: Your starting bank balance and cash injections from financings. Everything else is calculated, mostly using data from subsequent tabs.
  • As with all input cells in the model, consider the values that I've put in to be dummy data. Fill those cells with your own data and assumptions.
  • The model doesn't take into account interest or taxes (except for payroll taxes).
  • The "Revenues" line shows your end-of-month MRR for the respective month. This is not compliant with the US GAAP definition of "revenues", which uses different revenue recognition rules, but since SaaS companies live and breathe MRR I think it's the right approach for a SaaS financial model.

3.) "Revenues" tab
  • The model assumes that you have three pricing tiers. I've called them "Basic", "Pro" and "Enterprise". If you have more or fewer pricing plans you can of course adjust the model accordingly (with some effort). It is further assumed that all Basic and Pro customers are on monthly plans and that all Enterprise customers are on annual plans.
  • The model assumes that you're getting signups organically and via paid marketing and that you're converting a percentage of them into Basic customers and Pro customers. You can change the key assumptions such as your organic growth rate and your conversion rates in the grey area on the left.
  • The Enterprise customer segment follows a different logic, based on the assumption that Enterprise customer acquisition is sales-driven as opposed to the marketing-driven low-touch sales model for Basic and Pro customers. The key drivers in the Enterprise segment of the model are your revenue targets, sales team quotas and your assumptions for churn and upsells.
  • The spreadsheet shows the impact of e.g. Basic customers who upgrade to Pro and Pro customers who upgrade to Enterprise, but to keep things simple it doesn't support each and every possible movement between plans. For example, I didn't include the option for Basic customers to upgrade to Enterprise straight away or for Enterprise customers to downgrade. If this is a relevant factor in your business, you can of course accommodate for that by adding a few extra rows.
  • For Basic and Pro customers, the model allows you to project ARPA development using a given ARPA at the beginning of the planning period along with assumptions on monthly ARPA increases. For Enterprise customers, the model assumes pricing increases at the time of renewal but not during the term of the subscription. Depending on your specific pricing model you'll have to modify that, e.g. to allow for Enterprise customers to add more seats continuously.
  • In order to be able to calculate churn for Enterprise customers in the 1st year of the plan, it is assumed that existing Enterprise customers have been acquired over the course of the previous 12 months. This is of course a somewhat theoretical assumption and you need to adjust the model to include your actual numbers.
  • As you can see in one of the charts below the numbers, the model allows you to calculate your "MRR movements". It's worth pointing out that the model currently doesn't show "Expansion MRR" and "Contraction MRR" separately but only the delta of the two, which I've called "Net Expansion MRR". In order to calculate Expansion MRR and Contraction MRR separately I'd have to add a couple of additional rows. To avoid making things too complicated, I decided against doing that for now. Fortunately ChartMogul (a Point Nine portfolio company, sorry for the plug) makes it super easy to drill down into all of your MRR movements.
  • Please note that the CAC data and "CAC payback time" calculation are based on pretty crude simplifications. A solid planning of CAC payback times, CAC/LTV ratios etc. would require a lot of additional input data.
  • The rows with the "Thereof bonuses..." label contain matrix formulas. Handle with care. :)

4.) "Costs" tab
  • In order to adjust headcount planning in the G&A, R&D and marketing departments, change the assumptions for start date, base salary and bonus in the grey "Assumptions" area. You can remove, change or add roles in column H.
  • With the exception of the VP of Sales role, sales staff headcount planning is done on the separate "Sales Team Hiring Plan" tab (re-using a model that I've built for this post). It calculates the number of sales people that you need based on the growth targets for your Enterprise customer segment, the quota of your sales people and a few other variables.
  • Headcount planning for the Customer Success team is (again with the exception of the VP) done formulaically as well, based on assumptions on how many customers a customer success team member can handle.
  • It is assumed that there's only one team, which I've called Customer Success, which does both customer support and customer success. Many SaaS companies have different teams for the two functions; if you're one of them you can adjust the plan accordingly. 
  • The costs for the Customer Success team are attributed to CoGS. This is debatable – if your Customer Success team plays an important role in converting signups or upselling customers you should consider allocating at least a portion of these costs to S&M and include those costs in your CACs. Please note that changing the "cost type" in column I will not automatically move the costs to a different category on the "Summary" tab so you'll have to do that manually.
  • The model assumes that payroll tax is the same for all employees. This may have to be adjusted, e.g. if you have people in different countries.
  • Regarding the cash impact of expenses, the model assumes that:
    • payroll taxes are paid monthly
    • bonuses are paid yearly (except for the sales team)
    • sales team bonuses are paid quarterly (since bonuses/commissions play a much stronger role in sales compared to other departments)
  • The model (somewhat simplistically) assumes that there are no capital expenditures. If you make investments into things like servers, computers or office furniture you should add these expenses accordingly.

If you've made it this far and haven't downloaded the Excel sheet yet: Here it is.

If you have any questions, comments or suggestions, let me know in the comments or email me. And if you like the model, tweet it out. :)

Finally, big thanks to Chris Amani, Sr. Finance Director at Humanity, as well as to Pawel and Dominik of Point Nine, for reviewing drafts of the model and for providing valuable feedback.