|By Joel York||
|April 23, 2014 09:00 AM EDT||
Over the past few years, the SaaS community has gained a solid understanding of SaaS financial metrics, as well as many of the operational principles required to achieve them. However, there has always been an obvious gap between what happens on the top line and what happens on the ground. It’s one thing to claim that a 50% reduction in churn will result in a 2X increase in recurring revenue, but it’s quite another thing to make it happen. Achieving that 50% reduction in churn is usually a tedious and unreliable process of trial and error. This is about to change. As the SaaS industry matures, we are witnessing the evolution of SaaS metrics beyond simple, historical financial measures toward sophisticated operational measures in the form of new SaaS customer success metrics and predictive analytics.
We are witnessing the evolution of SaaS metrics beyond simple, historical financial measures
toward sophisticated SaaS customer success metrics and predictive analytics.
This is the second post in a series inspired by my ongoing collaboration with Bluenose Analytics that explores the new Metrics-driven SaaS Business and its foundation of emerging best practices in customer success metrics. [Attention SaaS CFO's and VP's of Customer Success! Please see the exclusive invitation at the end of this post if you like this series and would like to explore more in person.] The first post discussed the unique qualities of SaaS that enable the Metrics-driven SaaS business to apply a more analytic approach to management than traditional licensed software. This second post drills down on the promise of customer success metrics to bring greater rigor to the processes of churn reduction, upselling and customer success management for increased recurring revenue and decreased recurring costs of service.
An Ocean of Customer Success Data
The promise of customer success metrics is immense. Unfortunately, so is the challenge of developing them. From the initial capture of a prospect’s email address to the final cancellation of a churning customer account, the Metrics-driven SaaS Business collects and analyzes customer data. At the very beginning of a SaaS customer’s lifetime, a cookie is dropped and the usage clock starts ticking as web visits turn into trial accounts. That initial email is complemented with profile information captured on sign-up forms and augmented by third-party databases. Sales and marketing kick in and engagement activities are recorded in CRMs and marketing automation systems. Finally, a purchase is made and the ecommerce engine captures the transaction and forwards it to the financial systems for future billing. Then, the real action starts. Customers log in to the product again and again. Every important click is recorded and every customer success activity is logged.
The SaaS customer success metrics challenge is a big data problem,
requiring powerful data collection engines and sophisticated statistical models.
Collecting the data, unfortunately, is not even half of the battle. The Metrics-driven SaaS Business must make good use of it, turning data into information and information into action. Compared to the SaaS metrics challenge of previous years where all we had to do was master a relatively short list of SaaS financial metrics, the SaaS customer success metrics challenge is truly daunting–a bona fide big data problem. There is just no way to make sense of these volumes of data without powerful data collection engines and sophisticated descriptive and predictive statistical models. Simply defining the relevant customer success metrics is a difficult problem onto itself. But for the very first time, we have the law of large numbers tilting in our favor and the benefit it offers for reducing churn and accelerating customer acquisition far outweigh the costs.
Driving SaaS Customer Success with Metrics
The SaaS profit equation from the previous post and repeated below shows the five key financial levers of SaaS businesses, the two volume drivers: current customers and new customers, and the three units of value: recurring revenue per customer, recurring service cost per customer, and acquisition cost per customer.
SaaS profit =
current customers x ( avg recurring revenue – avg recurring cost )
– new customers x avg acquisition cost
[ Note: For the accountants in the audience,
this should look a lot like activity-based costing. Because it is. ]
As SaaS executives, our financial goals are very simple: make business decisions that push these financial levers in the right directions to increase revenue and reduce costs. The challenge of maximizing SaaS profit is easily divided between the ‘current customer’ half of the calculation and the ‘new customer, half. SaaS business organizations and operating plans are often similarly divided into servicing current customers and acquiring new customers.
This second post in The Metrics-driven SaaS Business series focuses on the ‘current customers’ half. The next post in the series will focus on the ‘new customer’ half. As mentioned earlier though, pushing these financial levers is much easier said than done. Planning to increase revenue by increasing current customers with a 30% reduction in churn is easy. Reducing churn by 30% is hard. The following sections take a look at the first three financial levers: current customers (churn), average cost of service (customer success efficiency) and average recurring revenue per customer (upsells) and the principal role of SaaS customer success metrics in creating and executing operating plans that actually push them.
Leveraging Root Cause Analysis to Reduce SaaS Churn
By far the lowest hanging fruit of SaaS customer success metrics is their use in SaaS churn reduction. For a SaaS business of any reasonable size, churn uniformly represents the largest financial drain on SaaS growth and profit. Its simple math, ‘current customers’ is almost always the largest number in our SaaS profit equation above. SaaS churn is also a great place to start our exploration of SaaS customer success metrics, because at its heart, SaaS churn is a statistical concept, so modeling it operationally is fundamentally a statistical problem.
[Note: If you tweeted the quote above, CONGRATULATIONS!
Welcome to the club of true SaaS metrics geeks! ]
SaaS churn represents the probability that a customer will cancel in a given period. That probability is determined by a number of factors: the value the customer sees in your SaaS product, the customer’s reliance on your SaaS product, the potential value of competitor offerings, and the internal priorities and politics within the customer’s organization. The Metrics-driven SaaS Business gathers and analyzes information on all of these predictors. Customer profiles in CRMs and accounting systems combined with direct product usage data go a very long way in describing the first two, whereas the less visible ones can be tackled through customer success surveys and expert ratings by executives, sales reps, support reps, and customer success reps.
With an ocean of customer success data and the law of large numbers on our side,
we can apply well known statistical methods to identify the root causes of churn
Once we have collected the relevant information, we can apply well known statistical methods to identify the root causes of churn. There are a number of descriptive statistical methods that apply from simple cross tabulation of churn cohorts to more advanced methods like logistic regression and survival analysis. Statistics aside, we expect to find insights, such as customers in healthcare are more likely to churn than customers in financial services. If a customer has not logged in in the last 30 days, it is at severe risk of churn. Customers that use our reporting module frequently are our best advocates, and so forth. With the right data and the right analytics, root causes of churn can consistently be identified and addressed, a significant improvement over simply reducing churn from 15% to 10% in our financial forecast without having a clue as to how it will be achieved.
Predictive Analytics with SaaS Customer Success Metrics
Once we have a better understanding of why past customers churn, we can create models that predict the risk that a specific current customer will churn in the future. With sound predictions, the customer success organization can take action to prevent SaaS churn before it happens. At their heart, most of these statistical methods are simply scoring systems that estimate the probability of a given event, in the case of churn it is the probability that a customer will cancel. The predictors in our models and the models themselves can therefore be used to create key performance indicators (KPIs) for customer success that are tracked on a regular basis for each and every customer. For example, we may find that customers that stop using our product for a two week period are at a higher risk of churn, and that the risk increases the longer they do not use the system. This metric and the regression that produced it can both be used to create KPIs.
SaaS Customer Success Metrics and Product Use
Customer success metrics based on product usage data is the secret sauce within the Metrics-driven SaaS Business. In a sense, churn is simply the opposite of use. The more a customer uses your SaaS product, the less likely the customer is to churn. Not only does use indicate how much the customer values your product, prolonged use correlates strongly with switching costs. Customer success metrics that track inadequate use are key indicators of churn, while those that track deep and frequent use are strong indicators of customer advocacy. One of the smartest applications of customer success metrics based on product use is driving product use itself. By identifying customers that are struggling with your product, you can uncover opportunities to improve the user experience, offer help and education, and of course reduce churn.
Product usage data is the secret sauce within the Metrics-driven SaaS Business.
In a sense, churn is simply the opposite of use.
Improving SaaS Customer Success Efficiency through Metrics
The same KPIs that we use for churn reduction can be applied to improve the efficiency of the customer success organization and thereby lower cost of service. They key is to go beyond simply monitoring and modeling customer success metrics to embedding them in the daily workflow of customer success reps. From the preceding example, if we know that customers that have stop using our product for two weeks are in need of immediate attention, then we can use this information to create dashboards and alerts for customer success reps. The primary goal is to direct the attention of customer success reps to customers where the reps can have the greatest impact on financial results. Conversely, the secondary goal is to not waste time on customer success activities that have no influence on the success of a customer.
The beauty of SaaS customer success metrics over SaaS financial metrics is that they apply at the individual customer level. Moreover, they can be rolled up along any dimension, such as time, customer type, product module, customer success rep, etc. to create a detailed picture of our customer success operation. At the individual account level, they can be used to create a scorecard or health index for every single account to help customer success reps monitor and manage their territories. At the aggregate level, they can be used to design the customer success territories themselves, so that customer success reps are deployed to customer accounts in the right numbers and with the right mix of skills. Customer success managers are usually familiar with a straightforward small, medium and large account approach to territory design, however, it might just be that your large accounts have the least risk of churn and the least potential for upsell! SaaS customer success metrics provide much stronger guidance and many more dimensions from which to choose for territory design.
Driving Upsells with SaaS Customer Success Metrics
SaaS customer Success metrics can also improve upselling to increase average recurring revenue per customer, the next financial lever in our SaaS profit equation. By applying the same types of statistical models we used in churn reduction to analyze past upsell purchases across customer demographics, product usage data, and so forth, we can develop predictive models and scores for upselling. Again, we can embed these models and KPIs into the daily activities of customer success reps or account managers to direct them to the accounts with the greatest upsell potential at any given time. Finally, we can use the predictive models within the product itself to automatically trigger communications with high potential customers and facilitate purchase.
Attention SaaS CFOs and VPs of Customer Success!
I will be speaking at an exclusive CFO only dinner sponsored by Bluenose Analytics this coming Tuesday, April 29 in San Francisco. Please email me directly at joelyork [at] chaotic-flow.com if you are interested in attending. This event is part of a larger, ongoing series designed to create an intimate setting for SaaS industry leaders (10-15 at a time at a nice restaurant) where they can discuss and evolve SaaS business best practices for finance and customer success. There are only a few spots left for next Tuesday, however, if there is sufficient demand, we will likely repeat it. There are also upcoming dinners focused on Customer Success operational best practices for VP’s Customer Success. If you are interested in these, please email me and I will send you the agenda. Bluenose is also considering expanding these dinners to multiple cities, so let me know even if you are not in the Bay Area.
Thanks again for following Chaotic Flow!
PS Dinner is free!
Adding public cloud resources to an existing application can be a daunting process. The tools that you currently use to manage the software and hardware outside the cloud aren’t always the best tools to efficiently grow into the cloud. All of the major configuration management tools have cloud orchestration plugins that can be leveraged, but there are also cloud-native tools that can dramatically improve the efficiency of managing your application lifecycle. In his session at 18th Cloud Expo, ...
Jan. 21, 2017 02:30 AM EST Reads: 6,096
The pace of innovation, vendor lock-in, production sustainability, cost-effectiveness, and managing risk… In his session at 18th Cloud Expo, Dan Choquette, Founder of RackN, discussed how CIOs are challenged finding the balance of finding the right tools, technology and operational model that serves the business the best. He also discussed how clouds, open source software and infrastructure solutions have benefits but also drawbacks and how workload and operational portability between vendors an...
Jan. 21, 2017 02:30 AM EST Reads: 5,039
With the proliferation of both SQL and NoSQL databases, organizations can now target specific fit-for-purpose database tools for their different application needs regarding scalability, ease of use, ACID support, etc. Platform as a Service offerings make this even easier now, enabling developers to roll out their own database infrastructure in minutes with minimal management overhead. However, this same amount of flexibility also comes with the challenges of picking the right tool, on the right ...
Jan. 21, 2017 02:15 AM EST Reads: 5,353
"Tintri was started in 2008 with the express purpose of building a storage appliance that is ideal for virtualized environments. We support a lot of different hypervisor platforms from VMware to OpenStack to Hyper-V," explained Dan Florea, Director of Product Management at Tintri, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jan. 21, 2017 01:15 AM EST Reads: 4,892
There will be new vendors providing applications, middleware, and connected devices to support the thriving IoT ecosystem. This essentially means that electronic device manufacturers will also be in the software business. Many will be new to building embedded software or robust software. This creates an increased importance on software quality, particularly within the Industrial Internet of Things where business-critical applications are becoming dependent on products controlled by software. Qua...
Jan. 21, 2017 01:15 AM EST Reads: 5,041
The speed of software changes in growing and large scale rapid-paced DevOps environments presents a challenge for continuous testing. Many organizations struggle to get this right. Practices that work for small scale continuous testing may not be sufficient as the requirements grow. In his session at DevOps Summit, Marc Hornbeek, Sr. Solutions Architect of DevOps continuous test solutions at Spirent Communications, explained the best practices of continuous testing at high scale, which is rele...
Jan. 21, 2017 12:30 AM EST Reads: 4,546
A critical component of any IoT project is what to do with all the data being generated. This data needs to be captured, processed, structured, and stored in a way to facilitate different kinds of queries. Traditional data warehouse and analytical systems are mature technologies that can be used to handle certain kinds of queries, but they are not always well suited to many problems, particularly when there is a need for real-time insights.
Jan. 21, 2017 12:15 AM EST Reads: 6,374
Containers have changed the mind of IT in DevOps. They enable developers to work with dev, test, stage and production environments identically. Containers provide the right abstraction for microservices and many cloud platforms have integrated them into deployment pipelines. DevOps and Containers together help companies to achieve their business goals faster and more effectively. In his session at DevOps Summit, Ruslan Synytsky, CEO and Co-founder of Jelastic, reviewed the current landscape of D...
Jan. 21, 2017 12:00 AM EST Reads: 5,101
In his General Session at 16th Cloud Expo, David Shacochis, host of The Hybrid IT Files podcast and Vice President at CenturyLink, investigated three key trends of the “gigabit economy" though the story of a Fortune 500 communications company in transformation. Narrating how multi-modal hybrid IT, service automation, and agile delivery all intersect, he will cover the role of storytelling and empathy in achieving strategic alignment between the enterprise and its information technology.
Jan. 21, 2017 12:00 AM EST Reads: 4,704
IoT is at the core or many Digital Transformation initiatives with the goal of re-inventing a company's business model. We all agree that collecting relevant IoT data will result in massive amounts of data needing to be stored. However, with the rapid development of IoT devices and ongoing business model transformation, we are not able to predict the volume and growth of IoT data. And with the lack of IoT history, traditional methods of IT and infrastructure planning based on the past do not app...
Jan. 20, 2017 10:45 PM EST Reads: 917
WebRTC is bringing significant change to the communications landscape that will bridge the worlds of web and telephony, making the Internet the new standard for communications. Cloud9 took the road less traveled and used WebRTC to create a downloadable enterprise-grade communications platform that is changing the communication dynamic in the financial sector. In his session at @ThingsExpo, Leo Papadopoulos, CTO of Cloud9, discussed the importance of WebRTC and how it enables companies to focus o...
Jan. 20, 2017 08:45 PM EST Reads: 4,383
"We're bringing out a new application monitoring system to the DevOps space. It manages large enterprise applications that are distributed throughout a node in many enterprises and we manage them as one collective," explained Kevin Barnes, President of eCube Systems, in this SYS-CON.tv interview at DevOps at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jan. 20, 2017 06:30 PM EST Reads: 5,463
The Internet of Things can drive efficiency for airlines and airports. In their session at @ThingsExpo, Shyam Varan Nath, Principal Architect with GE, and Sudip Majumder, senior director of development at Oracle, discussed the technical details of the connected airline baggage and related social media solutions. These IoT applications will enhance travelers' journey experience and drive efficiency for the airlines and the airports.
Jan. 20, 2017 05:45 PM EST Reads: 2,102
With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo 2016 in New York. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be! Internet of @ThingsExpo, taking place June 6-8, 2017, at the Javits Center in New York City, New York, is co-located with 20th Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry p...
Jan. 20, 2017 05:15 PM EST Reads: 3,825
@DevOpsSummit at Cloud taking place June 6-8, 2017, at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to wait for long developm...
Jan. 20, 2017 05:15 PM EST Reads: 3,545
In his General Session at DevOps Summit, Asaf Yigal, Co-Founder & VP of Product at Logz.io, will explore the value of Kibana 4 for log analysis and will give a real live, hands-on tutorial on how to set up Kibana 4 and get the most out of Apache log files. He will examine three use cases: IT operations, business intelligence, and security and compliance. This is a hands-on session that will require participants to bring their own laptops, and we will provide the rest.
Jan. 20, 2017 05:15 PM EST Reads: 4,965
A look across the tech landscape at the disruptive technologies that are increasing in prominence and speculate as to which will be most impactful for communications – namely, AI and Cloud Computing. In his session at 20th Cloud Expo, Curtis Peterson, VP of Operations at RingCentral, will highlight the current challenges of these transformative technologies and share strategies for preparing your organization for these changes. This “view from the top” will outline the latest trends and developm...
Jan. 20, 2017 04:45 PM EST Reads: 1,096
@DevOpsSummit taking place June 6-8, 2017 at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @DevOpsSummit at Cloud Expo New York Call for Papers is now open.
Jan. 20, 2017 01:30 PM EST Reads: 3,609
"There's a growing demand from users for things to be faster. When you think about all the transactions or interactions users will have with your product and everything that is between those transactions and interactions - what drives us at Catchpoint Systems is the idea to measure that and to analyze it," explained Leo Vasiliou, Director of Web Performance Engineering at Catchpoint Systems, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York Ci...
Jan. 20, 2017 01:30 PM EST Reads: 5,746
The 20th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held June 6-8, 2017, at the Javits Center in New York City, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Containers, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal ...
Jan. 20, 2017 01:30 PM EST Reads: 5,252