SaaS insights enable IT leaders to get the most value out of their SaaS subscriptions by making the insights actionable. Your SaaS product may generate the most earthshaking data-driven insights for enterprises. Still, without anticipating and addressing how customers will act on them, you’re creating barriers to sales and client success.
Most enterprise-focused software companies have successfully moved their products up the maturity curve from data to information to insights, creating the potential for significant impact with their customers by uncovering new ways to look at their businesses.
Today – Insights by me, figure out actions yourself
Maybe flashy dashboards and a suite of reports are sufficient for some applications — particularly new-to-world data with a high “wow” factor — but customers now often demand more. Action instead of merely actionable insights. There are a variety of options on how this can happen:
Customer automated: Downstream customer systems call your product’s APIs (or receive data via downloads), picking up the value ball and taking it across the goal line. Example: Content analytics tool feeding a marketing automation system.
Partner: Partners of your customers consume your insights and data, and in turn, deliver broader solutions to your shared client—examples: Lead generation tools feeding rep firms, application performance monitoring platforms used by outsourced tech providers.
Managed services: Your customer success or operations teams do some or all the legwork instead of customer personnel—example: Yield management in ad tech.
Open-loop: Your product automates insight-driven actions, but the results are only valid outside of your platform. Example: Content personalization for brand sites where separate systems determine attribution (if at all).
Closed-loop: Your product gathers and analyzes data, generates insights, automatically acts on those insights, and provides the metrics quantifying efficacy. Example: Website optimization platform that tests various designs, gathers success metrics, promotes winning components, and validates lift in conversion.
How actions are taken now
There’s no right answer that covers every industry, customer, and company stage.
For instance, highly disruptive solutions that attack previously intractable problems may have to be built in waves, starting with problem identification and iterating into a closed-loop solution once the issue is better understood and there’s a credible analytical foundation.
On that other end, manually intensive industries that are later adopters of automation may need the human bridge — the customer’s, vendor’s, or partner’s — between insight and action. An “action platform” instead of an analytics platform is the epitome of a turnkey solution.
Regardless of which outcome is most appropriate, everything starts with understanding your target customers’ internal/external processes and their perceived pain at each step along the way:
If you had an end-to-end solution, how would your answer change your customer’s processes in terms of eliminating inefficiencies, collapsing process steps, replacing inferior incumbent solutions, and automating manual work?
If your customer instead used an alternate model, such as in-house manual labor or a third-party provider, what are their costs to do this?
What’s the delta between how they and you perceive the problem, and what’s the root cause for the perception gap? How can you overcome it? And as you think about bridging that last mile between delivering insights and taking action, how do the various models above fit your targeted customers?
SaaS insights from beyond your core product
Handle Data from Any Source – SaaS companies already rely on established technology stacks for pulling customer data. Yet not every analytics tool integrates with every technology. The result is companies work with multiple tools or ignore channels altogether. No dashboard built on incomplete information will ever serve as the valuable resource your company needs. Ensure your analytics tool can integrate, upload, or stream data from both your 3rd party applications (SaaS apps) and existing application databases in real-time.
“40% of the insights delivered by customer intelligence teams are not actionable”
Complete your action loop
To optimize your business’s growth, you need to understand what users do to become customers and the value they deliver across the lifecycle. Behavioral metrics do just that. Every analytics dashboard should include them to draw a deeper understanding of how customer behavior is helping or slowing your growth. Some practices you should keep track of include:
Activated Customers: User sign-ups are great, but what does that mean if new customers never use your product? You need to define what an activated customer means to you. This can be completing specific tasks, such as onboarding training, or spending a certain number of hours spent using your product.
High vs. Low Engagement Customers: Monitoring low-activity and inactive users is valuable for several reasons. A sudden drop in user engagement may point to software issues. Inactive users may share certain qualities, such as location or belonging to the same industry.
Paying vs. Non-Paying Customers: Some SaaS companies offer free trials or a free “basic” of their platform with basic features. Understanding who upgrades and when can help you better market your product against the competition. Similarly, understanding users who never upgrade can help you identify industries and customer personas that may not be worth pursuing.
Understanding your customers and creating an engagement journey based on personas, segment, gathering insights beyond core product and help retain a user or increase the LTV by x%.
“Customer retention translates into profitability. According to Deloitte & Touche, customer-centric businesses that focus in digital insight are 60% more profitable than those that are not”
Will a unified approach address connect insights into actions?
Dashboards are only as good as the data they’re using. Today’s SaaS companies pull data from multiple customer touchpoints within and outside their apps. Insights across these channels are vital for understanding important metrics along the customer lifecycle. Visualizing these metrics is the true potential of analytics dashboards. Too often, however, company dashboards don’t offer a complete picture because they rely on incomplete data.
To create the perfect SaaS insights dashboard, you need to have the data manipulation capabilities to make one possible. Specifically, your SaaS analytics tools should be able to do the following:
Unify Data – Your perfect SaaS dashboard should be able to show meaningful insights drawn from multiple data sources into a single visualization. To do this, your analytics tool needs to be able to unify data from various channels. Otherwise, displays are limited to show one metric per visualization, which has significant drawbacks.
Companies that can unify their data can draw these higher-level insights that single data sources can’t. For product managers and company leadership alike, it’s these that genuinely matter.
Data Visualization That Matters and Drives Action – The truth is that not all metrics are important for SaaS companies; many of them are a distraction at best (think vanity metrics). Your dashboard should only include those that genuinely measure your company’s growth. We want to highlight the following core metrics every SaaS company should be monitoring.
Lifetime Value (LTV): The total value an average customer brings to your company over their entire time as a customer.
Customer Acquisition Cost (CAC): The average cost for acquiring a new customer. SaaS companies should also follow their LTV/CAC Ratio, which compares lifetime value to the amount of money spent to acquire them. Influential SaaS companies should have an LTV/CAC ratio of 3 or higher.
Churn: The percentage of customers who leave your company, typically calculated by month.
Retention: The percentage of customers who stay with your company, also typically calculated by month.
Average Revenue Per Account (ARPA): The average revenue from each account (customer).
Monthly Recurring Revenue (MRR): The revenue a SaaS company expects to earn every month.
Expansion: The amount of monthly revenue from existing customers. Account upgrades and adding new users to existing accounts are ways existing customers contribute to expansion.
Time Series: How metrics change over time.
“Customer-centric businesses that focus in digital insight are 60% more profitable than those that are not”
Your dashboard should show your critical metrics over several months so you can understand how your efforts (e.g., sales, marketing, development) are impacting growth. Tool help visualizes these metrics will help SaaS company monitor and reorganize their strategy to impact growth.