Thoughts from my journey

The Totango team is excited to announce the release of the Customer Health Dashboard which helps cloud application providers and software as a service companies of all kinds track and manage overall user happiness at a glance (Read Press Release).

The first of its kind, the Customer Health Dashboard is a configurable cloud-based tool that summarizes customer success and engagement using their realtime activity streams, capturing and calculating data like overall time spent, license use, CRM system feeds, and trouble tickets. With it, you can get a clear picture of your customer base’s health, identify customers at risk, and track trends across segments.

The Customer Health Dashboard is especially useful to businesses who see value in the growing trend of shifting focus from acquiring new customers to driving usage, adoption, and happiness in existing ones — the hallmarks of customer success.

For providers of software as a service, company revenue depends on having happy customers who keep renewing their subscriptions; the lifetime value of existing customers may end up far exceeding the gains made by simply picking up new ones. Customer success begins with customer acquisition and onboarding, but continues after a customer signs up with you; renewals and expansion sales depend critically on customer happiness.

Totango found in recent customer success research amongst over one million prospects and customers of software businesses that over 50% of paying customers aren’t using the service they paid for.  The same study also found an unsurprisingly near-perfect correlation between non-use and cancelations: cancelations of software subscriptions were almost always preceded by a period of non-use.

The Customer Health Dashboard can show you at a glance how well your success strategies are working and gives customer-facing personnel the tools to help customers be more successful where needed. Not only can you quickly locate your best customers, but you can also identify the ones requiring the most attention and take immediate action, engaging with them before they see a problem.

Interested in learning more about customer success management (CSM)? Totango would be delighted to host you at our free meetup on The Future of Customer Success on Thursday, April 5th, from 7-8:30pm in San Mateo, CA. Mikael Blaisdell, publisher of The HotLine Magazine, will be on hand to give a talk and host a Q&A. Come have a snack, meet your fellow CSM professionals, and stick around for some customer engagement tips from yours truly.

The research of The Customer Success Management Initiative is revealing that while many SaaS/Cloud companies are hiring individual Customer Success Managers, or even establishing entire teams of them, there is a wide range in the understanding the role. Given the lack of clear cut definitions, lines of authority and accountability, it’s no surprise that there would be an equally broad range in how the individuals and teams are equipped. After all, if your job is only about writing up case studies and customer references for use in marketing collateral, a telephone, laptop and perhaps a reasonable travel budget may be entirely sufficient. But if you’re truly charged with the responsibility for keeping customers and increasing their spending with your company, you’ll need much more.

A Question of Ownership

The first item on the CSM wish-list ought to be a clear charter. Who is to be responsible for what? What authority does the CSM role carry with it? Holding a professional (or anyone, frankly,) accountable for something over which they have no real operational control is a recipe for failure and turnover.

A “fire-fighter,” a customer retention specialist brought in only at the last moment to try to save a failing customer relationship, may only need to have the authority to make concessions within a determined range so that they know what they can and cannot offer to the customer. Their engagement will probably be of limited duration, and their performance metrics are likely to be based mostly on deals saved/lost statistics. However, if the customer retention manager’s responsibility also includes early detection of at-risk accounts, then Senior Management needs to provide appropriate access to data and tools to enable that aspect to be accomplished.

More than CRM

It’s an unusual company in this day and age that does not have a Customer Relationship Management system installed and in use. Unfortunately, in too many companies, the CRM system is really only about automating the Sales and Marketing functions, with a module or two for Case Management over in the Support group, In reality, there are three separate systems: Marketing, Sales and Support — that are designed and built for just those functions as individual activity areas. CRM systems are typically not designed for the Customer Success Manager, who needs to analyze a range of interaction data to detect patterns that indicate the actual health of the ongoing relationship between the customer and the company in time to do something about it when necessary.

An appropriate CSM system, for example, would alert the manager that a particular customer, one who perhaps represents 40% of the overall yearly corporate subscription income, was no longer using a key module of the product. This is not about a decline in simple logins and licenses, but in the usage of certain specific features of the application. Such a capability, vital to ensuring that a new customer is properly proceeding up the adoption curve, becomes even more important as a means of detecting an established customer that has started to disengage. To enable that insight, however, requires that you know which features of your product to track. That’s a subject for another day.

About the Author

Mikael Blaisdell, publisher of The HotLine Magazine, brings 30+ years of experience in the strategy, process, people and technology of customer support, retention and profitability to the emerging profession of Customer Success Management. He is also the moderator of the CSM Forum on LinkedIn. Read moer about The Customer Success Management Initiative, sponsored by Totango.

Another tip taken during Sales 2.0 from Darren Suomi, VP Sales at HootSuite – this time regarding self service model and how to adjust it to reduce churn.

You know how it is that you get many leads and you just don’t know who to refer first? This situation is common in many SaaS companies.

With the right metrics and cohort analysis, it’s easy to decide who are the more engaged customers that are ready for sale and it’s usually more likely that if you’ll approach those customers, they’ll signup for your product.

Darren is also claiming that even in a self service model (low-touch model) like HootSuite, once they find out who are their active users in their service, they proactively reaching them and by that they reduce churn.

Tomorrow I will publish a tip by Mark Roberge, VP Sales at HubSpot who will explain the difference between the hunters and the farmers skill sets.

To read the full transcription of the video, click here

Video Transcription:

I’m talking to Darren Suomi, VP of Sales from HootSuite.

Bring me a model which where we play, it is a self-service model. So, we’re really trying to look at it from turning down the churn. I guess I’m looking at what people are trying to play instead of going from just a self-service. We’re actually just playing with the model in terms of a little bit of more of a high touch point. So, we are really taking a look at our customer who are quite active on social media. We are actually proactively reaching out of them and seeing where we might be able to help them versus just letting them fend for themselves.

Last week, Jason Cohen wrote a very comprehensive blog on software-as-a-service churn: Deep Dive – Cancellation Rate in SaaS Business Models. I required everybody at Totango to read this blog and recommend that you do the same. Jason looks at many different definitions for the SaaS Cancellation Rate metric.

Eventually, Jason recommends performing cohort analysis when looking at cancellation rates. He suggests to divide customers in segments based on their “time to cancel” (i.e. cancelled after 30 days vs. cancelled after more than 30 days) and, for all intends and purposes, he recommends focusing in the long-term users who have greater business revenue potential and cancellation reasons which can be addressed and resolved more easily.

This is indeed an interesting way to look at it, and very analogous to the importance of the “time to convert” metric when it comes to inbound marketing and trial conversion. However, I argue that this is not the only, and maybe not always the best, way to do cohort analysis on SaaS churn.

Let’s take for example an email service application. If 2 users have signed up at the same time:

• One of them is using the service more frequently, creating many accounts, visits almost all application features and cancels after 10 days
• The other accesses the service 3 times a week but just checking very limited features and cancels after 31 days

Who should be given more weight?

If I’d measure by Jason, I would focus my efforts on the second user, but if I weigh my analysis with user behavior altogether, then my most valuable customer to understand is the first one.

So this leaves us with three promising ways to segment customers for cohort analysis:

1. Traditional way: create cohorts based on the week or month in which they signed up for the service. This will allow you to analyze the effect of changes you made to your product or service over time.
2. Jason’s way: to create cohorts based on the “time to cancel” (or the “time to convert” for that matter). This will allow you to focus on long-time users of your product and sift out those who signed up in error.
3. The customer engagement way: to create cohorts based on the “engagement level” with the product or service. This will allow you to focus on frequent users of your products, independent on how long it took them to cancel, but still sift out those who signed up in error (and never started to use the product).

Of course, in all cases, measurement is just the first phase of the process and the complementary phase must be to prioritize the changes needed in the service which would ultimately lead to increase customer satisfaction and customer engagement.

What about you? What is your definition for cohort analysis?