The SaaS model streamlined the processes involved in optimization by making data segmentation, collection and dissemination much more accessible.
Traditionally, on-premises software providers run into complex problems when trying to gauge and interpret levels of user satisfaction. The only contact an on-premises software provider has with its business users is the installation process and a customer support center. So how do you know if your users are satisfied with the program? How can you know what bugs to fix and what features to add? How can you know how to retain them?
The simple answer is you don’t.
On-premises solutions inherently limit the face-to-face contact a software provider has with its users, consequently blocking the avenue for two-way feedback. On-premises software providers may send out three to four surveys per year to users in hopes of obtaining valuable feedback, but generally users have very little incentive to participate in such surveys.
The introduction of the SaaS model in B2B applications opened the floodgates for a wealth of information that software providers can collect. A deep understanding of an application’s users is now possible – one that, when collected and interpreted properly, can reduce churn rates through the microsegmentation of data.
One of the goals of microsegmentation is to create a one-on-one, tailored customer experience. In practice, this means personal interaction, guidance and aid in each step of the user’s life cycle.
Where does the art of microsegmentation begin? As always, the devil is in the details. And the details are in the data.
1. Important data types for microsegmentation
Collecting even the seemingly minute pieces of data will show you how your customers interact with your platform/application.
Demographic information is important to understanding who your customers are. Things like age, geolocation, gender, occupation and industry experience are general data points that you can use to begin the process of microsegmentation. Collecting data like age, gender and occupation often sometimes requires more delicate techniques (to be discussed in the sections below); however information like geolocation can be collected in automated ways.
Any quantifiable information that represents an action or event that took place on your platform is a useful piece of information that should be tracked, measured and recorded. For example, using a specific feature, spending three minutes on a specific page in your knowledge base, or sharing a specific piece of content are all forms of data that should be tracked and recorded.
2. How to collect this data
There are a variety of platforms available that allow you to easily track and record user actions and events. Tools like heatmapping solutions can give you a visual representation (a heatmap) of all of the clicks performed on a specific page on your website, while more comprehensive solutions enable you to map user flows, compile reports and track A/B tests to help optimize funnels.
Solutions like KISSmetrics, CrazyEgg and Mixpanel can be embedded within your website, giving you the ability to set predefined goals that can be measured and tracked. Moreover, by integrating these solutions into a customer management system, you’ll be able to view and organize the information, giving you a more thorough understanding of what your customers are doing on the platform.
3. Segmenting the data
After going through the necessary steps to set up your tracking system, you’ll have a database and an analytics dashboard with which you can track your users and their interactions with your platform or application.
Now you’ll need to find cohorts, or data segments, in which to compile your users. Depending on what market you’re in, you’ll need to define the cohorts appropriately.
For example, here’s a cohort:
“Male, free trial subscriber; aged 20-30 years; no recorded usage in last 5 days.”
And this is the corresponding event:
A <male>; between the ages of <20-30>; signed up for <30 days free trial>; did not <login> for the last <5 days>.
This event will generate a list of users under the age of 30 that have shown interest by signing up for a trial, but for whatever reason are not using the application.
The amount of cohorts you can define are, for all intents and purposes, unlimited. The deeper your microsegmentation goes, the easier it will be to identify user types, optimize the user experience at different points in the funnel and ultimately increase user engagement in extremely focused ways.
You can easily optimize segments of your funnel through A/B and multivariate testing. By separating cohorts into two equal groups, you’ll be able to run ongoing tests, ultimately seeing what resonates better with them.
4. Engaging With each segment
Your dashboard and statistics will give you a very clear depiction of the customer segments that experience the highest churn rates and those that experience the least amount of churn. From there, you can break down and analyze why each segment is performing as it is.
Perhaps your email communications with users high up in the funnel (e.g., in the example above) are too general. Maybe you need to lend more of a helping hand to users higher up in the funnel in order to spark their interest and motivate them to start engaging with your solution.
Automated emails are always a good idea, no matter what the case. If a user just signed up for a free trial, you can and should send an email as a reminder of the signup and contains some use cases for your product (and even some success stories from like-minded users). Engaging users in targeted ways keeps your solution fresh in their mind; furthermore, it lets them know that you’re passionate, capable and driven to help them succeed.
The details are in the data
For SaaS companies with the capabilities to do so, microsegmentation is the next step in customer retention. It gives software providers the targeted insights they need to make actionable decisions. It’s not only key to reducing churn rates but can also lead to better, more targeted product development that will enable your product to better align with client interests down the road.
Roey Libfeld is head of business development and market research at Discovercloud.com. Roey is an expert in the field of big data and an eager researcher of the B2B realm. He’s motivated by the notion that there is a solution to any business need. Roey has started consulting with B2B companies on how to achieve maximum productivity.