5 Ways Scuba Helps SaaS Brands Understand “Impossible” User Behaviors
By Camila Martinez-Granata
In 2022, brands now have so much data, they don’t know what to do with it. Given the sheer quantity of data SaaS companies collect–and so many disparate user events to track–it’s easy for any brand to become overwhelmed.
Chances are, your SaaS brand already utilizes a suite of BI tools to manage your user event data. However, what SaaS brands may not realize is that most traditional BI tools are not built to scale–or explore data in the way you need to in today’s world. Billions of user events could be underutilized due to system constraints, leading to brands missing critical insights simply because their BI software wasn’t designed for it. Not to mention, companies are forced to decide what data is valuable and worth analyzing before even seeing it.
Fortunately, there is a turnkey solution to tracking your brand’s otherwise impossible event data: Scuba’s real-time continuous intelligence platform.
Read on to find out why it’s critical for SaaS companies meaningfully track user events–and how Scuba Analytics can provide insights into never-before-tracked data.
How & why SaaS tracks user events
User event data refers to tracked user events, such as clicking a button, loading a new page, or responding to a survey. These events can provide a granular, near real-time view of how users interact with products throughout their customer journey, allowing brands to glean valuable insights into user activity.
Here are some of the most common methods brands use to track user events:
- Data analytics platforms (DAPs): DAPs can offer a comprehensive suite of services and technologies that allow brands to analyze, interact with, explore, and visualize massive quantities of data.
- Customer data platforms (CDPs): CDPs can pull event data from multiple sources to create holistic customer profiles.
- Enterprise data warehouses (EDWs): EDWs are systems that aggregate data from multiple sources, typically large quantities of historical data.
- Business intelligence (BI) tools: BI tools take your data analytics to create interactive visualizations for various purposes, including statistics, predictive analytics, data mining, text mining, and forecasting.
Once user event data is collected and analyzed using one or more of the above tools, companies use that data for a variety of functions, including:
- Optimizing product performance: User event data helps brands understand their users' wants, needs, and behaviors. If your brand isn’t leveraging user event data to improve product performance, most likely, your competitors are–63% of SaaS brands report leveraging user event data to fine-tune their products.
- Improving customer experience (CX): Quality CX is instrumental to any brand aiming to reduce churn and increase activation rates. 70% of SaaS brands report leveraging user event data to improve their CX.
- Detect pain points: Regardless of industry, the importance of a low customer effort score (CES) cannot be overstated. Proactive brands do not wait for users to inform them of pain points. Rather, brands can leverage user event data–like sudden incomplete user journeys or drop-offs–to quickly identify pain points before losing more customers.
- Identify glitches and bugs: It can be difficult to differentiate the forest from the trees when you’re lost in the forest–the same is true when identifying glitches or bugs within a homogenous data set. Fortunately, by aggregating user event data into a simplified view, outlier data points caused by glitches or bugs become much easier to identify. Once identified, these outliers can provide invaluable insight to brands, such as their average cases or any implementation issues.
How other BI tools & platforms fall short
While the tools and platforms listed above won’t hurt your brand, the false sense of security they provide might. Simply put, most BI and reporting platforms weren’t built to handle real-time, time series data tracking or glean granular insights.
Some drawbacks of traditional BI tools and platforms include:
- Poor scalability: Scalability is a two-way street. Your brand’s analytics tools should be capable of scaling up to quickly ingest large quantities of data. But, it should also quickly scale down in cases where you require granular insights from a specific data set. Traditional BI tools lack this flexibility, forcing brands to rely on time-consuming one-off queries to get answers.
- No real-time tracking: Ask yourself: would you be comfortable operating a vehicle without mirrors? Sure, you could physically check your blind spots, but every moment your eyes are not locked on the road means you are operating off incomplete information and putting yourself at unnecessary risk. Brands that rely on traditional BI tools do just that. Real-time tracking presents the complete picture of your users' event data. Without it, they could be steering headfirst into danger.
- Slower insights: The most competitive brands are proactive, not reactive. Adapting to dynamic, rapidly changing conditions requires your analytics and reporting tools to produce insights just as quickly. Traditional analytics tools slow your time to insight to a trickle–Bleacher Report once waited six months to receive insights, until Scuba sped up the process by 95%.
- Less flexibility: Most BI tools achieve rapid query performance by either indexing data, pre-aggregating data, or a combination of the two. Pre-determining a few of the most common variables may be sufficient for answering surface-level queries, but what about brands that require the flexibility to combine variables to ask complex questions? Unfortunately, traditional BI tools sacrifice flexibility for speed, meaning the insights most valuable to your brand could be inaccessible.
To track the right events, ask the right questions
To ensure valuable insights don’t drown in a sea of extraneous data, brands must prioritize the most important user events to track. However, no SaaS company is the same, even within the same industry. The most important user events for one brand may not be the best fit for yours. Before investing valuable resources into user event tracking, begin by asking: what are the most pressing questions my brand needs answered?
To uncover the right answers, you must first ask the right questions. Begin by first determining a broad arena to examine, such as marketing or product development. Then, hone in on a specific issue within that arena. Here are a few common questions SaaS brands ask–and how to answer them by tracking specific user events.
- How can I improve marketing ROI?
Daily active users, monthly active users, & monthly unique users: As their names suggest, these user events indicate the number of users and visit frequency. Daily active users provide the greatest ROI–it costs 6 to 7 times more to find a new customer versus retaining existing ones.
- How can I decrease customer churn?
- Contact Center Performance: Contact centers are often the first–and last–line of defense against customer churn, so tracking customer satisfaction when interacting with contact agents can provide valuable insights. One metric to consider is First Contact Resolution (FCR). As a general rule, brands should aim for an FCR rate of at least 70%.
- Engagement: An engaged customer is a loyal customer. By tracking engagement activities like survey responses or clicking on emails, brands can flag users with diminishing engagement and respond before they fall off completely.
- How can I convert visitors and non-paying users into paying customers?
- Marketing-Qualified Lead (MQL) events: MQLs refers to users who are likely to purchase your product, as indicated by criteria such as frequent site visits, or downloading informational materials. By tracking MQL user events, your sales team will be armed with the necessary insights to close the sale.
- Product-Qualified Lead (PQL) events: PQLs refer to potential customers who have used your service and are likely to become paying customers. 49% of high-growth SaaS brands have adopted PQL strategies, the most common being limited free trials. If your brand leverages a PQL strategy, make sure to track user events to indicate likely buyers.
- Time spent on page: Time users spent on a page, such as reading product pages or blog posts can be a helpful indicator of their interest in your brand’s service. Just remember that not all time is equal–if users spend more time on the page because they are confused, this event is a detriment, not a boon.
- How can I improve completion times?
- Marketing funnel: The importance of customer journey analytics cannot be overstated. By tracking customer journeys against intended marketing funnels, brands can gain invaluable UX insights into how customers actually interact with their services.
- Pain points & drop-offs: The longer a pain point goes undetected, the more damage it does to a brand’s reputation and bottom line. Slow completion times or drop-offs are often indicative of pain points. Hone in on any irregular user events to further optimize your brand’s UX.
While deciding what user behavior to track is always important, Scuba gives companies the power to take data exploration and analysis a step further. With Scuba, companies can sift through all their user data and uncover the most important behaviors and actions–without having to pre-determine the limited set of which events and behavior to collect. And, uncover questions users may not have even considered or thought of asking.
5 “impossible” questions only Scuba can answer
Most BI tools are capable of tracking standard user events, but what if your brand needs to go deeper? What if, instead of asking if user churn has increased, you need to know why user churn has increased, within a specific thirty-day period, among a certain demographic?
Suddenly, “standard” isn’t good enough. And while you are forced to wait weeks on costly ad-hoc queries to make sense of last quarter’s event data, your competitor has capitalized on the opportunity and stolen points off your market share.
This is the true power of Scuba’s real-time data analytics platform: scalable data tracking and the flexibility to mix and match nearly any question to isolate otherwise “impossible” user events–all in real-time. If you can formulate the question, Scuba is capable of answering it. Here are five examples of “impossible” questions made possible with Scuba’s scalable event tracking.
1. Why are feature A drop-off rates higher among certain users?
By isolating various event data sets and presenting them together with a simplified view, Scuba is capable of unearthing region-specific behavioral insights your marketing and sales teams can now capitalize on.
2. How much time was spent on our site using feature B versus feature C?
Other BI tools may track a user's total time on site, but they lack the scalability to track specific feature usage, let alone compare time spent on one feature versus another. Scuba can do just that, granting your product teams valuable insight into which features should be further developed. With Scuba, companies can understand where on the site users are spending their time on–without having to predetermine which events are important. Instead, Scuba lets the data tell you.
3. Why are completion times longer for some users?
Why do some users take hours to complete a task, while others only take a few minutes? Traditional BI tools may obfuscate the real answer behind averages or aggregated data, but Scuba can derive granular insights by honing in on the most minute user events–even down to the raw data.
4. Is this outlier event extreme across all historical data?
Incorporating historical data into data analysis can provide companies with context and an added layer of understanding of a particular event over time. Asana adopted Scuba to replace their time-consuming, siloed data analytics, including historical product development event data. Within a few months, Asana product engineers were using Scuba to compare performance data against older products, as well as monitor user behavior anomalies.
5. Asking the “next question” that you don’t even know yet.
As mentioned previously, Scuba’s platform removes the need for brands to pre-determine a limited set of which events and behavior to collect–and helps users iterate questions they haven’t even thought of or considered. For example, a data engineer may have set up an analyst to understand revenue per user. But, if they see something they don’t expect, such as revenue for new users being lower this month, an iterative analysis might open up a dozen new questions the analyst may not have known to ask or where to look next. Meaning, Scuba helps users iterate on their questions and leads them to questions they hadn’t thought to ask.
Leave no stone unturned (or unknown) with Scuba
It may be the shoddy craftsperson who blames their tools, but that doesn’t mean they should tolerate subpar equipment either. The same goes for SaaS brands. Your brand requires a data platform capable of uncovering any insight and scaling to any data set.
With Scuba’s continuous intelligence platform, your brand can leverage your event data to its full potential. Unlock otherwise impossible insights and share them effortlessly across your entire organization with Scuba's intuitive, non-technical UI. Since our data analytics platform operates in real-time, you won’t have to wait until next quarter to act upon those granular insights.
The best SaaS brands need the best tools. Data management should never hamper your growth. With Scuba, the only limit is your own ingenuity.
Recent Blog Posts
- 3 Powerful Time-Series Analysis Techniques to Drive Better Insights
- 6 Ways Time-Series Analytics can Help Your Business
- Scuba Analytics Recognized for Employee Happiness, Benefits, & Perks with 2 Comparably Awards
- How Data Sovereignty can Affect Your Cloud Strategy
- 5 Ways Scuba Helps SaaS Brands Understand “Impossible” User Behaviors
- 8 Essential Customer Metrics to Help Your SaaS Brand Stand Out
Popular Blog Posts
- It's Time to Stop Being “Data-Driven” (And Start Being Data-Informed)
- 48 Analytics Quotes from the Experts
- How to Conduct a Behavioral Analysis (in 7 Steps)
- 6 Common Types of Behavioral Segmentation for Understanding Your Customers
- 27 Amazing Tech and Product Blogs: Theory, Tactics, Frameworks
- 6 Essential Mental Models for Product Managers