Customer analytics data is the foundational pillar of all successful marketing strategies, revenue predictions, and product iterations.
No product, marketing, or business decision should ever be made without careful consideration of your customer analytics.
What are the main types of Customer Analytics Data?
1. Website behaviour
This tracks how your visitors navigate and engage with your website. Knowing this is crucial to optimising your website sales funnel and converting those curious visitors into long-term customers. For example, track which pages see the highest number of views and engaged time, and add a Prompt to initiate a conversation. Or, identify which articles on your Blog drive the most traffic to your signup page and boost them with some paid ads.
2. In-app / Event behaviour
Once a prospect signups to your platform, the journey is only just beginning! By tracking their crucial first steps with your product, you can build out and refine your onboarding process. You can learn which features prospects need to activate in their first few sessions to start seeing immediate value from your product.
Build these steps into your Support documentation and tutorials. Or, identify any bottlenecks in your onboarding, and send this feedback to your Product team to make in-platforms changes.
3. Interactions with CS & Support
Having a Live Chat function is another useful channel to collect customer data. By analysing your customers’ interactions with your Support team, you can identify any consistent trends. Are customers frequently running into the same issue? Update your Support docs. Are customers consistently making the same feature request? Mark this as a priority for your product roadmap.
4. Online reviews / surveys (NPS / focus groups)
Of course, customer analytics data isn’t all about tracking clicks, events and metrics! Customers can also leave a wealth of data in the form of feedback on review sites. You can proactively reach out to customers for input by implementing in-platform NPS surveys, sending CSAT questionnaires for completed Support interactions, or even going old-school with an in-person focus group. At GoSquared, we use the ‘Delighted’ platform to send in-platform NPS surveys and host regular client calls to ask them for feedback on improving the product.
How can you process Customer Analytics data?
Descriptive
This covers both a real-time and historical analysis of what is happening across your Marketing site and product. What pages are users clicking? Where are they coming from? What were your most successful Marketing campaigns last quarter? GoSquared’s Analytics ‘Now’ and ‘Trends’ Dashboards provide a platform to answer these questions, giving you a HQ overview of exactly how users are engaging with your site. (And you don’t need a data science degree to understand it..!)
Diagnostic
This is the trouble-shooting use case for customer analytics data. Tracking your users’ behaviour enables you to identify any obstacles in your platform. For example, are users consistently dropping off at a specific stage in the customer journey? Use this data to hone in on that segment and find what product iterations need to be made to fix it.
Segmentation
Various sections of your user base will have common characteristics, behaviours or aspirations. By understanding your users with this level of detail, you can segment your user base intelligently into groups. This enables you to scale your Marketing, Sales and Onboarding processes while still retaining a sense of personal touch for your clients.
Predictive
If you have an intimate understanding of how your users have behaved in the past, you can go a long way to predicting how they will act in the future. This is crucial for those tough calls on which changes to prioritise for the product or crucial business decisions around pricing models.
In addition, understanding how your users are likely to behave enables you to offer proactive outreach. For example, suppose a particular segment of your client base has consistently experienced issues in a specific step of your onboarding process. In that case, you can automate an in-app message at this exact stage to offer a training slot with one of your Customer Success team. That way, you can address any issues before they develop into problems.
Why is Customer Analytics Data so important?
In today’s hyper-competitive SaaS landscape, it’s the companies who best understand their users who will rise above the rest. As a result, your prospects have near-infinite access to information, a plethora of competitors to choose from, and unprecedented ease of software migration.
Every interaction a prospect makes with your Marketing pages can be used to optimise your funnel. Every interaction a user makes with your product can be used to inform your product roadmap. Finally, all these individual snippets of information can be pieced together to form an overall picture of how your customers perceive your brand and product.
It’s the ultimate way to see the world through your customers’ eyes.
Customer Analytics can provide answers to questions, such as:
- What is our most profitable marketing channel?
- What does a good user onboarding experience look like?
- What behaviours do clients display before churning?
- Which segment of our clients yields the highest MRR?
- What are our key activation features?
Do not leave key decisions to gut instinct or guesswork. Walk a mile in your client’s shoes, and use the data to make the right future decisions for your business, product and customers 🙌
