Tag Archives: Recurring Revenue

A Practical View of Your Customers

7 Oct

A few months ago I wrote a post about customer segmentation titled All Customers Are Equal, But Some Are More Equal Than Others.  I graphically represented the concept of customer segments with a pyramid, because it was a simple and straightforward representation of the concept.  When it comes down to actually segmenting your own customer base, though, and making decisions about how to service them, I’ve found the best way to do that is to use a Pareto Chart.

Pareto1

Figure 1: Pareto Chart of 2000 Hypothetical B2B Customers

The Chart Described

If you aren’t familiar with the concept, a Pareto Chart is great way to visualize how your revenue is distributed across your customer base and how much your largest customers contribute to your overall revenue.

The chart above came from a hypothetical set of 2,000 customers I created from data that I made-up to represent a typical B2B customer distribution curve. The grey portion of the Pareto Chart is actually a bar graph made up of 2000 data points in descending order. Each (very thin) bar represents a customer’s Monthly Recurring Revenue (MRR) and maps to the axis on the left – in MRR dollars.

The blue line shows the cumulative percentage of revenue represented by the customer base as it moves along the X axis and maps to the axis on the right – in percentage of total revenue.

Creating Your First Segment

The Pareto chart quickly shows you a couple of things:

  1. How your customers are distributed
  2. How many customers fall into each bucket so that you can efficiently allocate resources to manage a large percentage of your revenue base.

The image below takes this hypothetical (but not uncommon) B2B case and creates a first segment of customers. This segment happens to consist of approximately 10% of the customer base (It’s 200 grey “bars” wide, representing 10% of the 2000 bars in the graph) and approximately 45% of the revenue (the right edge of the green area intersects the blue “% of revenue” line at about 45%). You’ll also see that the MRR value at the right edge of the green area is approximately $5,000 – which represents the minimum MRR for a “Tier 1” customer.  Again, these numbers are examples. The process for creating customer segments requires a little art to go with this science and is going to take some iterations to get right; however 10% of your customer base is a reasonable baseline number for a high-touch CSM organization.  You may choose to make it larger or smaller for a number of reasons (which I’ll cover in a future post), but this framework is a good way to illustrate it and justify whether you’re covering a reasonable amount of your revenue base.

Figure 2: The First Segment

Figure 2: The First Segment

The Second Segment

Now that you’ve created a high-revenue customer segment that can justify a high-touch CSM, you might want to see whether it makes sense to cover another relatively small number of customers that still might represent significant revenue with a somewhat lower touch, but still personal, approach.  Based on this customer distribution, you can see that a second segment can be created that consists of twice as many customers as the first segment, and in combination with the first segment gives you coverage for approximately 75% of monthly revenue.

Figure 3: The Second Segment

Figure 3: The Second Segment

Pareto Charts can illustrate pretty clearly how much revenue is represented by each segment of customer as well as show the baseline MRR that can be used to define the “floor” of each segment.  Figure 3 shows that in this hypothetical situation, 75% of the revenue is represented by approximately 30% of the customer base, with an MRR of $1,700 and above.

So Now What?

Now that you have a framework for segmenting your customers, you can optimize your investment in your CSM function.  In this example, the first segment of customers represents significant revenue that can justify high-touch named CSMs who can engage with customers in a personal, frequent, and customized manner. The second segment consists of roughly twice as many customers and a little over half the overall revenue of the first segment, so the amount of engagement per customer that can be justified for each CSM is significantly lower. The third segment represents approximately 3/4 of total customers yet only 1/4 of total revenue and can be effectively managed with Customer Success Automation and Marketing Automation. I’ll discuss how to address these three very different customer segments in more detail, and how Customer Success Automation applies across all three in a future post.

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The Waterfall Model: Not Just for Startups and VCs

5 Aug

Brian Ascher, a partner at Venrock, wrote a great blog post a while back about how the waterfall model may be the “single best financial reporting tool ever”. That might actually have been an understatement.  I highly recommend reading his post, by the way, if you aren’t familiar with a waterfall model and want a good primer as well as the example spreadsheet below.

Waterfall2

In a nutshell, a waterfall model allows you to lay out your projections over a period of time (monthly numbers over a one year period; weekly numbers over a year, or daily numbers over a month, for example) and at the end of every period, compare your actuals to your projections then revise your estimates for the periods moving forward based on what you’ve learned. The waterfall model doesn’t provide you with all the answers; however, it gives you a good idea of how you’re doing with respect to your original and revised plans and as a result, figure out what additional questions you need to ask yourself to understand why. It’s an incredibly powerful tool given its relative simplicity.

VCs and Startup CEOs/CFOs have been using waterfall models for decades to measure progress against plan and to help validate assumptions about growth, cash balance, user adoption, and a number of other important business metrics. Outside of the VC/startup/board community, however, waterfall models seem to be underutilized. Maybe it’s because startups need to move quickly. They’re constantly making assumptions, learning, understanding which assumptions were good and which ones weren’t, then revising their plan of attack quickly as they continue to move forward …and a waterfall model helps them understand that and react quickly. There are a few reasons that waterfalls can be particularly helpful in the area of Customer Success as well, given a similar need to move quickly in order to proactively manage recurring revenue:

Reason 1: You need a plan, and you need to know how you’re tracking according to the plan

A waterfall model enforces management to a plan. The interim checkpoints, by nature, hold you accountable to that plan, and if there is a variance, force you to do three things: 1) Acknowledge the variance.  If you set up your waterfall model correctly, the interim periods you define should be frequent enough to allow you to take action while there is time to impact the outcome; 2) Ask why there is a variance; and 3) Re-plan the future periods given what you now know.

Reason 2: Your assumptions aren’t always right

Planning, or more precisely, getting a plan right, is an ongoing process. People make plans based on assumptions. Managing an existing customer base can be tricky, and having frequent enough visibility into key metrics in order to take meaningful action allows you to challenge your assumptions with enough time to take meaningful action. One important point to clarify here: This isn’t an opportunity to make excuses for why you didn’t hit your numbers.  This is an opportunity for you to understand what you need to do differently to improve your performance (while there’s still time) and create more accurate plans and forecasts in the future.  If you do need to re-plan, the waterfall still allows you to measure against your original plan and your revised plan.

Reason 3: Trends are interesting, but without a comparison to your original plan, trends don’t give you the entire picture

Growth is great. Improvements in key metrics are great. In order to run a business and plan/manage it successfully, though, you also need some predictability. Waterfalls provide you with a historical snapshot of how well you did delivering to plan.  You always have historical information on your original plan, your re-plan, and your actual performance for each measurable period – in one table.  It’s a simple, yet very effective visual tool.  If you ended up growing up-sell revenue 25% quarter over quarter is that good? What if your original plan was to grow at 30% QoQ?

So, with all that justification behind us, here’s an example of where and how I’ve used a waterfall model in Customer Success:

Planning and Forecasting Retention and Churn:

I recently blogged about the many Customer Success Automation solutions coming to market to help companies manage a SaaS customer base more effectively. Whether you’re using one of these products or whether you’re just starting to get your head around managing your customer base, it’s very valuable to understand which of the data elements and assumptions you’re using to identify “healthy/reference customers” or “at risk customers” are accurate, and which ones require you to go back and think again.

A team of mine once needed to forecast churn risk from the existing customer base and had very little valid historical information from which we could create projections.  We started by looking at customers using broad-stroke definitions of various health levels.  We assigned customers a “health status” of Red, Orange, Yellow, and Green, then based on their contract renewal month, assigned a probability of renewal based on that health status. We eventually began adding criteria to more clearly define health status, including usage metrics (not just frequency of logins, but how effectively were they using the system), customer responsiveness, and other indicators of risk associated with their business and usage model. We looked at our first months data and saw where we were off, then went back to our assumptions and looked at where we might possibly have miscategorized customers. We also looked at whether our percentage ratios by health status were accurate (for example, did x% of our “orange” customers actually cancel).  We gradually increased our sophistication level as we gathered more data and continued to refine our assumptions in our waterfall model. By the end of our first full year of deploying the model, we were within 5% accuracy forecasting revenue retention and churn.

In addition to forecasting retention and churn, a waterfall model can be useful in other areas of customer success, including:

  • Planning and forecasting up-sells
  • Modeling the rate at which you plan on improving service levels and/or resultant customer feedback scores
  • Planning and forecasting adoption of certain strategic product features across your user base

Pretty much any key metric you want to track and measure against can be managed using a waterfall model. You may want to start with a couple of the ones above, then determine if tracking others will be useful. Just be ready to dig into the underlying data to ask “why” the variances are occurring… and keep asking “why?” until you see patterns emerge. Then act.

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When the Funnel Stops Working

30 Jun

The funnel has been used for decades to model the journey a customer takes during the sales cycle.  While it is still very effective as a forecasting tool, it falls short as an effective model of the overall customer journey, especially in the context of recurring revenue customers.

The cultivation process for identifying and processing new leads, then moving them through the steps to an initial commitment to your product is still best modeled by a funnel, and most of the common sales methodologies to date only support a funnel metaphor.  I get it.  Going though the qualification process and filtering a bunch of unqualified leads to qualified leads to qualified suspects and so on through the process is best illustrated and managed as if all these were going through a funnel with an expected conversion rate at each stage of x%, y%, and z%.  In a world centered around new customer acquisition, this seems like a pretty good metaphor and it also helps provide forward visibility and predictability into new revenue for somewhat mature organizations; however when it comes to: A) capturing the journey once someone becomes a customer, especially one with multiple transactions; and B) predicting recurring revenue from an existing customer base, the funnel metaphor doesn’t work.

New Business is Only the Beginning

There is a strong tendency, even in the world of SaaS, to look at all revenue  the same way.  With any recurring revenue model, the focus needs to shift from a sales-centric perspective to a customer-centric perspective.  Again, I’m not trying to minimize the importance of sales and new customers, or the predictability and management of that revenue stream.  New customers and new revenue are vital to the growth and success of any organization.  They just aren’t the end game of a sustainable recurring revenue business.  They’re only the beginning.

So if the funnel isn’t the right metaphor for ongoing customers, what is?  Some great minds have spent considerable time and effort on this problem and have come up with some good alternatives as a starting point.

Earlier this year Brian Solis wrote a blog post detailing a concept from his two most recent books about how the funnel no longer represents the customer journey, and especially from a digital marketer’s perspective, he isn’t alone.  He cites work done by McKinsey four years ago based on research of 20,000 consumers identifying the customer decision journey as circular, with an outer loop representing “active exploration” and an inner “loyalty loop”. Both of these works, as well as Google’s Winning the Zero Moment of Truth highlight the recurring nature of the customer journey.  They also key in on the important concept that the experience of your existing customer base will influence the purchase decisions of your future prospects.  Brian Solis and The Altimeter Group’s model maps the following steps into a recurring elliptical path:

  1. Awareness
  2. Consideration
  3. Evaluation
  4. Purchase
  5. Experience
  6. Loyalty
  7. Advocacy

The Funnel Has Revenue All Backwards

A funnel implies that significantly less revenue comes “out” of the funnel than entered the funnel in the form of leads – as shown in the image below.  Again, this is a good assumption when managing and forecasting new business.

Sales

However, for an existing customer base in a healthy growing business with a good “land and expand” strategy and execution, the revenue that comes out of every cycle through the ellipse for the overall customer base should actually increases as a result of up-sells and cross-sells – as shown in the next figure.

Customers

Yes, some customers will (gulp) churn; however with a healthy business model and a good upsell/growth model and “land and expand” strategy, this net revenue should increase for your installed base of customers.  Seth Godin, in his ebook Flipping the Funnel, as well as Joseph Jaffe, in his book Flip the Funnel, both discuss how you can use your existing customer base as advocates to market to additional prospects.

Are Rumors of the Funnel’s Death Greatly Exaggerated?

I don’t believe the funnel is dead.  I think it still serves a purpose for predicting revenue and conversions, especially for new business.  From a marketer’s perspective, however, and when trying to manage an existing customer base, the metaphor falls way short.  The continuous elliptical path provides a much more realistic model for the customer journey and influence path.  The next step is in applying metrics to the elliptical path in order to forecast recurring revenue so that it can be as effective as the funnel as a forecasting tool.  Hmmm… I bet that would make a good topic for a blog post.

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All Customers Are Equal, But Some Are More Equal Than Others

14 Jun

With all the Orwellian quotes from 1984 being tossed around as a result of PRISM, I thought I’d use one from his other book to describe the paradox of customer service for those of us who have ever supported a large and diverse B2B customer base.  How do you provide a *great* experience for all of your customers in a scalable manner while creating something truly exceptional for your high value customers?

Well, first, you need to understand your customers – and while it’s actually not that uncommon for many startups in the SaaS space to have very good aggregate metrics such as CAC (Customer Acquisition Cost), Conversion Rates, etc., many companies don’t necessarily have individual customers very well segmented into logical groupings of actual and strategic value to the organization.  It’s ugly, but it’s true, and it’s because a number of startups have gone through a growth process that looks something like this:

1) Invest in product and build it;

2) Invest in sales and grow the customer base;

3) Realize that the growing customer base is now large enough that it needs to be proactively managed and scramble like crazy to get the recurring revenue base under control.

Customer Segments

If you’re at this stage, getting things under control and categorized can actually be pretty straightforward.  It just takes some thought, focus, and basic analysis.  I’ve blogged about some of the technologies that are emerging in the space of revenue renewal management or Customer Success Automation.  The reality, though, is that most SaaS companies, especially early stage ones, don’t yet have an analytics or Customer Success Automation solution to provide them with good insight into their customer base using real data-driven scoring and early warning systems across all customers.  This post focuses  on how to segment customers in the short term using basic data that you already have on your existing customer base (MRR, ACV, CLV, plus some other identifier for “strategic” accounts) …and it starts with the 80/20 rule.

Cust_Segments

The Top Tier: The “Most Equal”

While it may not be exactly 80/20, the reality is that in the vast majority of B2B SaaS companies, some small percentage of customers will represent a very large percentage of their revenue.  Those customers are very high value and need to be treated as such.  Create executive relationships and multiple touch points.  Invest in them.  Meet them face to face.  Get to know them.  Involve them in your business.  Provide detailed monthly or quarterly business reviews that give them an indication of progress against stated objectives that you’ve worked out with them in advance.  Determine the set of services you should be providing to this tier of customer and identify the amount of time it will take on an ongoing basis for your CSMs to provide those services to a model customer, then understand how many customers you can reasonably and consistently service given that time requirement… Congratulations, the laws of time and space just helped you create your first cut at your top customer segment.

Until you add more trained, senior, CSMs to your team or modify the level of service, you shouldn’t try to service more customers than you can at this level.  If you over-commit, you risk missing on delivery expectations and you’ll leave your customers, er, less than satisfied.  That may sound obvious, but getting from today’s reality to tomorrow’s desired state needs to be carefully managed.  Next, determine how many customers you would like to see getting that level of service and either staff up your CSM team or pare back your service offering slightly (or some combination of both) in order for your needs and reality to align.  Whatever number you come up with, you will need to justify it financially and take it into consideration when calculating your cost of services.  A good initial target to shoot for if you’re a B2B SaaS company is to get 40% of  your revenue into this bucket.  In many cases it will be represented by fewer than 10% of your customers.  Your mileage may vary, of course; however a reasonable range seems to be 1/3 to 1/2 of revenues represented by this customer tier for B2B SaaS companies.

The Second Tier: “The Most Leveraged”

While a high touch model works for that small percentage of customers who represent between 1/3 to 1/2 of your revenue, the law of diminishing returns takes over quickly and that model won’t scale to service the rest of your customer base.  In this next tier, each CSM will handle significantly more customers (sometimes up to 10x more) than their “Top Tier” counterparts and they will need automation in order to be effective.

Try to identify useful data that you can extract from your systems, and automate its delivery to your customers via Customer Marketing and drip campaigns that are “signed” by the CSM.  Compare that customer’s data against relevant benchmarks or aggregate data from the rest of your customer base.  The more you can automate the heavy lifting and position your CSM as the expert who can provide some context, insight, and recommendations around the data presented, the more you’ll position your Customer Success Managers for success.

The Third Tier: “The Most Scalable”

Some percentage of customers, (in many companies this group might represent the majority of them) are not going to generate revenue sufficient enough to justify the cost of a high-touch relationship – especially with respect to proactive communication with customers.  In order to support this tier of customers, a company needs to build out great self-service tools, including a self-service portal and an excellent customer marketing program… and they need to have a product offering for this tier that is intuitive and continuously improved as a result of customer feedback.  Companies like MailChimp and ZenDesk are poster children in this space for what to do and how to do it.  They provide great content.  They also understand that many of their existing customers interact with their company primarily online, so they focus on creating a powerful, bonding, consistent online experience for their customers.  Philosophically, they don’t see a “low touch” model as “low service”.  They see it as a way to create a consistent, powerful, engaged relationship with their customer base – at scale.  Understanding the importance of getting the product experience right, they also constantly listen to customer input, concerns, and challenges and respond by continuously making their product easier to use, more prescriptive, and less support-intensive.

While every company’s distribution of customers across these segments will vary with respect to percentage and number, and while your specific circumstances might require one more (or fewer) segment; understanding and segmenting your customers will help you focus on taking the right steps to provide the right level of service to each of them and create a great experience across all of them.

How have you segmented your customer base and what challenges have you faced in the process?

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