Customer engagement is key for your software-as-a-service – SaaS business. To understand how to successfully measure user engagement to successfully measure customer engagement, you first need to understand what engages users and how. In the SaaS environment, you achieve this basis of customer engagement by analyzing and understanding actions users take on your application and how they use it. Interpreting your customers’ actions and defining what they actually do in your application is not as easy as it seems. But we’re here to help!
A SaaS company must develop tools that will help its service measure customer behavior. These tools must be capable of answering key strategic and tactical questions to help evolve the product portfolio to engage current and future customers in deeper and richer ways. Questions you can take into consideration and use to assess customer behavior include:
- Have the users tried the service multiple times?
- How much time are users spending on your service?
- Which features are customers using and how frequently?
- Do they completely understand the value of your offering?
The basic metrics you can include to statistically analyze customer behavior include:
- Performance latency
- User productivity
- Changes in usage frequency or duration
- Search terms and actions
- Conversion analysis for specific tasks
- Analysis of leakage points and completion rates
- Discoverability of features
- Reduction in support costs or training.
SaaS provides continuous monitoring and direct measurement of customer interaction and engagement, but you have to identify key predictive indicators, or KPIs, plus track and dashboard this information for each customer. Let’s examine how the analysis of metrics can help in a specific situation, such as using frequency and length of use as KPIs of churn or advocacy. The first sign you are going to lose a customer is when they stop using Saas. An example would be a customer who has not logged in over a specific period of time, such as 30 days. Such a customer is a high risk of churn. By tracking and measuring this information, you can trigger an alert letting you know some action needs to be taken to avoid losing the customer.
Once you have real-time data monitoring in place, you can use it to conduct predictive analysis and identify individual churn risks and user preferences for profitable upsell and cross-sell opportunities. SaaS dashboards and predictive analysis can tell customer reps which activities will give them the biggest impact on financial results and which ones offer little value to customer engagement.
You can combine several key metrics, such as the amount of time your customer spent using the application, how often they visit, and what activities they engage in, and develop an engagement score. Keep in mind that customer interaction with your customer reps and marketing material is another factor to use when measuring the level of your customer engagement. Remember that the same tools that help you measure and understand customer behavior help you analyze the collected data to identify areas of improvement and the actions you need to take. For example, you could ask yourself the following questions:
- Are new features adding value?
- Are new users helped by tutorials and other guides or are they still unsure of what to do?
- Is the new design helping convert more trials?
Customer engagement can help answer your tough product and marketing questions. The key is to determine which parts of your product different customers use and to directly target customers for primary market research. After all, if you provide an online destination where they want to visit, you will increase awareness of your brand, drive people to your service, and end up engaging your customers again and again.
Contact us to learn more about your customers’ digital lifecycle, and how we can help you analyze customer engagement and improve your commerce.
