Knowing when to scale (and how to prove that you can do it)

When you’re talking to investors about a Series B, Series C or later round, one of the questions that will inevitably come up is “What are your CACs?”. It sounds like a simple question, but from the question of what costs to include and the right way to account for organic traffic to the pandora box of multi-touch attribution, there are lots of devils in the details.

What's more, the real question is not "What are your CACs?" but "What will your CACs be if you invest $10-20 million in sales & marketing?". It’s hard enough to calculate historic CACs for different acquisition channels with a high degree of accuracy. It’s much harder to predict future CACs at bigger scale.

And yet it shouldn’t come as a surprise that later-stage investors are so focused on this question. When you’re raising a Series B or later round, you’ve achieved Product/Market Fit (which is hard to define, see me attempt here) and you’ve got what Jason M. Lemkin calls “Initial Traction” and “Initial Scale”. At that point, the biggest thing standing between you and building a $100M+ business is finding scalable and profitable customer acquisition channels. Obviously you still have to overcome lots of other challenges along the way, but if you’re at $5-10M in ARR and you are confident that you’ve found scalable sales and marketing channels you are in an excellent (and rare) spot.

So how do you know if your customer acquisition channels will scale, that is, if a 10x increase of your sales and marketing spend will lead to a 10x increase in new customers? Consumer Internet startups are sometimes in the fortunate position to have found a profitable customer acquisition channel that offers huge potential for expansion. If ads on TV, YouTube or Facebook work for you, you might be able to increase your spending by 10x (and maybe much more) because these platforms have such a gigantic reach. In the B2B SaaS world this is very rare. Mass-market advertising won’t work because there’s way too much ad wastage, and targeted ads usually don’t give you the volume to easily 10x your spend.

Without a careful keyword volume analysis, being able to profitably spend $10k a month on AdWords doesn’t mean much in regards to your ability to spend $100k a month. If you spend small amounts on AdWords you will by definition (AKA by algorithm) capture the lowest-hanging fruits. As you’re trying to spend more, prices will go up. You might be able to offset the price increase by optimizing your campaigns, landing pages, onboarding, etc, but don’t take it as a given.

The underlying problem is that the existing “hot demand” for your product – people who are actively looking for a solution – is usually quite limited. The good news is that the amount of “lukewarm demand” – companies that would benefit from your product but aren’t aware of it yet – is usually much larger. That’s why content marketing is so critical in SaaS: it allows you to capture leads at a much earlier stage of the discovery process. But scaling up your content marketing by 10x is not as straightforward as simply 10x-ing your ad budget.

So how do you know, in B2B SaaS, if you’ve found scalable acquisition channels?

Nothing is completely certain here, but one great sign that should give you a lot of confidence is if you can hire new salespeople and the new hires (once they’re ramped up) are hitting their quota. If you add two AEs, add another two, and then another two, and most of them are hitting quota it shows that you’re able to increase the amount of high-quality leads. If that wasn’t the case, your growing sales team would quickly start fighting for the best leads and some of your salespeople wouldn’t be able to hit their quota any longer. Equally important, it also shows that you’ve managed to industrialize the sales process to a certain extent. Firstly, it doesn’t take the founders or superstar salespeople to sell your product, it can be sold by “normal” people. And second, you’ve managed to attract the right people, to set up the right processes and infrastructure and to create the right incentive structure and culture that is required to make a sales team successful.

Besides a growing, successful sales team, there are a few other factors that you can look at when you’re trying to decide if it’s time to put the pedal to the metal:

1. Are you able to make outbound sales work?
Doing outbound at reasonable CACs is usually very hard because you’re dealing with lots of unqualified leads. It requires lots of persistence from every AE and your sales leader as well as a strong commitment from the founders, since a serious attempt to make outbound work can cost a lot of money and time. The beauty of outbound sales is that if it works for you, you may have found a highly scalable customer acquisition channel: emailing or calling every single target customer in the world will keep your sales team busy for a while. :)

2. Have you managed to increase your SEM budget consistently and significantly without negative effect on CACs? What is your impression share, and how large is the search volume that you can still tap into?
As mentioned above, past performance in scaling an SEM budget from A to B alone is not a reliable indicator of future performance to scale from B to C. But in combination with a thorough analysis of the relevant search volume it can be a relevant data point.

3. Have you built a content marketing “machine” that consistently generates more leads month-over-month? 
If you can consistently increase inbound/content leads for some time, it means that you’ve found your narrative, or “North Star”; started to build content distribution channels; and managed to attract the right marketing people and make them effective. (Check out this great post from my colleague Clément for much more about this.)

If there are other aspects that you’re looking at to decide if you’re ready to scale, I’d love to hear about them in the comments below!

Thank you Rodrigo and Janis for reviewing a draft of this post and the valuable feedback.

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!

The 7th DO for SaaS startups – Build a repeatable, profitable sales process

The last post in my series on DOs and DON'Ts for early-stage startups was about lead generation. The next logical step is sales, and so I want to write about what you can do to convert as many of those leads into paying customers.

7th DO for SaaS startups

Build a repeatable, profitable sales process

Sales is a very different animal depending on the stage of your company, the market segment you're going after and on whether we're talking about inbound sales or outbound sales. For all the differences, though, the goal is always to create a scalable process which allows you to acquire customers for a small fraction of their CLTV. As a rule of thumb, you should aspire a payback time of 6-9 months, meaning that you spend 6-9 months' worth of subscription revenue to acquire a customer. It really is just a rule of thumb though, since depending on the customer lifetime and various other factors, you may want to accept a significantly longer payback period.

To achieve a payback period in that neighborhood you have three options:

1. If your ARPA is around $20-50 per customer per month, you need to be able to generate a large amount of leads for little money and convert them with little to no human interaction (self-service with no/low touch sales)
2. In order to support an inside sales force you need customers who pay you around $100 per month, preferably significantly more (often called "transactional sales").
3. If you need a field sales force to sell your product, assume that your ARPA needs to be at least $3000 per customer per month if not higher (enterprise sales).

Most people would argue that you need much higher prices to make inside sales work (including Jason M. Lemkin, who says you need at least $300/m), but several of our portfolio companies have shown that due to a combination of high conversion rates, fast sales cycles and sales people in countries where salary levels are 50-80% lower compared to Silicon Valley, you can use inside sales people to profitably acquire customers at much lower price points.

So – take the specific numbers with a grain of salt as they are highly dependent on a variety of individual factors. The important message is that your customer lifetime value defines what you can spend on customer acquisition. If you don't keep that in mind you'll end up in what Joel York, who created a nice visualization of the different models, calls the "startup graveyard".

In line with the theme of this series I'm going to focus primarily on the self-service and transactional models and want to break down my tips & tricks into three parts based on the stage of your company. I'm going to call them "pre product/market fit", "pre scale" and "post scale" (being well aware that the transitions between these phases are gradual). I'll focus on inbound sales in this post and will follow up with one on outbound sales shortly.

Pre product/market fit

• In the beginning, while you're still trying to figure out product/market fit, spend as much time with potential customers as possible. Don't consider the time spent with customers a sales expense – it's an essential investment that you need to make in order to solve a real problem of real people.
• Don't worry about scalability yet. In this phase it's perfectly fine to do things that are completely unscalable. As I wrote before, a good "unscalable hack" for SaaS startups is to spend huge amounts of time with early users.
• Don't worry about processes or tools, don't even worry about metrics (if you know me a bit you know that you won't hear me say this often!). Be "obsessively focused on getting to product/market fit", as Marc Andreessen put it.

Post product/market fit, pre scale

When you've found product/market fit and start to get more and more signups every month, some of the things that you did in the previous phase start to not work any more. As long as you get 50 signups a month you can still talk to every trial customer. Once that number gets into the hundreds or thousands, you need to hire people and put some processes and tools in place.

So the goal of this phase is to maximize the conversion rate of a large and ever-increasing trial volume while keeping customer acquisition at an acceptable level and starting to get a sense for the scalability of various sales and marketing channels. With that in mind, here are some tips:

• Set up an automated lifecycle email program to welcome new users, reach out to inactive users and follow-up with users towards the end of their free trial. Solutions like userfox (a portfolio company of ours) or Intercom make it easy.
• Send personalized messages to as many trial users as possible. Use any piece of information that you can easily get e.g. by looking at the trial customer's website or the way he uses your software to add some personal touch. This job can be done by junior customer support or sales people. The idea is to make every trial customer feel important and show him that you care, but do it in a highly scalable way. 
• Segment your trial users based on factors like potential account size, activity and brand and use this information to prioritize the queue for your inside sales people. A lot of this can be automated e.g. by checking a trial customer's Alexa rank or Google Page Rank to get an indication of the company's size. Also take a look at Totango, which can help you identify your most valuable prospects. You can also use this information to assign different types of potential customers to different types of sales people (e.g. small businesses are assigned to junior customer care people, bigger ones are assigned to more senior Account Executives).
• Set up a lead nurturing program for trial users who are only moderately interested in your product or don't have an immediate need for your product yet. Send them a newsletter, offer webinars, organize events... The goal is to provide them with valuable content and stay top of mind, so that when they eventually need a solution they'll think of  you.
• Track everything and do lots and lots of tests. A/B test different messages, find out the best moments and triggers for your lifecycle emails, test in-app messaging... In short: Try lots of different things and measure what works best.
• Avoid SaaS Metrics Worst Practice #3, which is to attribute all conversions to your sales team. To calculate the effectiveness and the ROI of your sales team you have to measure the conversion uplift relative to your unaided baseline conversion.  
• You can still do things that you know won't scale, but you should know what these things are and leave this phase with an excellent understanding of your CACs at scale.

Post scale

In this phase you're going to double down on what you've found to be working in the previous phase. Sounds easy, but it of course comes with its own challenges: Hiring, onboarding and retaining the right people; continuing to fill the funnel with enough leads to keep your sales team busy; adapting processes  and tools for a much larger sales team. At this point it's primarily a management challenge, and if you've come this far without hiring a seasoned VP of Sales, now is the time to hire one. And since this series is geared towards early-stage SaaS startups I'll leave it with this. :)