Digital customer experience analytics for AI SaaS: How to get insights from your users

Competition in the AI SaaS landscape is fierce, we know that.

So as AI SaaS companies scale and target new markets, they often overestimate their understanding of them because of different nuances and various factors at play.

What often ends up happening is the promise is over hyped, which usually leaves teams with one shot to impress users and get the most amount of user experience data from them.

The term used to collect and interpret this specific type of data is called ‘digital customer experience analytics’, and it goes beyond basic tracking of user behaviour.

Simply put, it’s how you can derive actionable insights that guide user centric development and ultimately the success of your product in any market.

Why AI SaaS Companies Need Digital Customer Experience Analytics

The biggest risk SaaS companies face from an overhyped promise is high churn, which happens as a result of not understanding your users’s pains and needs deeply enough.

Signs of this will be apparent if you come across these challenges:

• Discovering edge cases too late
• Failing to optimise features based on user activity
• Struggle to pinpoint specific user pains and bottlenecks

These signs are all precursors to eventual product failure, even more so in competitive markets like AI SaaS.

Digital customer experience analytics is a way of collecting and leveraging user understanding for more effective iteration cycles and faster time to product market fit.

This is because real world data from user interactions is the biggest pool of insights for companies building AI SaaS, and the best method of mitigating churn early on.

The best analytics tool you can use for developing an AI SaaS today is Phospho, and you can try it for free by signing up here.

Key Features of Digital Customer Experience Analytics Tools (and Why Phospho Stands Out)

Phospho is an open source digital experience analytics platform specifically designed to help AI SaaS teams log, evaluate, and extract actionable insights from user interactions to continuously improve their products.

Real-time Monitoring

When building an AI LLM integrated product, there’s no better source of data and insights than real-time user interactions with your AI model. We say in nearly every article, but what better feedback than verbatim in-app queries whilst customers are using the product?

Phospho logs, monitors, and evaluates user interactions and LLM outputs in real time for complete visibility into how your AI SaaS is performing with users.

A really effective way to leverage real-time data is through ad hoc analysis where you can query your own data for immediate insights instead of waiting for reports that rely on retrospective data. If you want to understand how to do this with Phospho you can read our previous article on it here.

Deep Insights Extraction

Deep insights requires more than basic analytics. Advanced AI data analytics tools like Phospho help you understand not just the what, but also the why behind your user behaviour so you can identify edge cases, bottlenecks, and common frustrations with your AI model’s performance.

Identifying patterns and trends in user interactions can be used to proactively test and investigate potential issues before they become problematic which is something you cannot do with traditional analytics that rely on retrospective data and static KPIs.

With Phospho’s custom KPIs, user interactions or patterns that meet a defined criteria are ‘flagged’ for investigation. This way you can track the metrics that matter most with any degree of specificity or edge case.

Example KPIs for an AI SaaS - How many users ask the same question twice? What percentage of users need to refine their inputs for our AI model to provide satisfactory responses?

For a better understanding of how Phospho can provide actionable insights for teams building AI SaaS, read our previous article here.

Continuous Evaluation & Iteration

The iterative nature of AI models means we need to keep a constant eye on potential performance changes that may affect our users’ experience when interacting with your AI SaaS.

Once we have the actionable insights from leveraging Phospho and implement them, we need to evaluate whether our AI model’s performance with our users has improved.

Unlike basic analytics tools, Phospho lets teams A/B test different versions of their AI model to qualitatively compare which iterations perform the best. This way AI SaaS companies can continuously evaluate, fine tune, and improve their AI model’s performance.

For example, using Phospho’s custom KPIs you can definitively test which version of your AI SaaS better handles ambiguous user inputs. You could then test which versions better classify user inputs as figurative or literal speech for more accurate and relevant responses.

To understand why AI SaaS companies need advanced analytics to extract insights rich enough for effective AI product iteration, read our article on it here.

Customizable Dashboards & Reporting

It’s one thing to collect lots of valuable data, but another to interpret any of it. To do so quickly we can rely on data visualisations to simplify large volumes of complex data for insights at a glance. With Phospho you can create custom dashboards to visualise exactly the data you need.

For example, you can set up a dashboard to visualise your AI model’s performance under specific scenarios, real-time sentiment around specific new features, or retention drop offs for different topics of queries.

If you want to see how to create custom dashboards with phospho, read our article on that here. Or if you instead want to better understand data visualisation with phospho, read this article here.

Easy Integrations

Phospho integrates easily with popular tech stacks and tools e.g Python, OpenAI, LangChain, CSV. You can test it for yourself, it’s as easy as importing a file like anywhere else! You can see us do it here.

We also have an API you can seamlessly connect to existing workflows or tech stacks to access real-time user analytics from your AI SaaS. From there you can set up custom KPIs, alerts, and visualise anything you want with your data.

We have plenty of documentation to support you here.

How to Use Phospho to Gain Actionable Insights from Your AI SaaS Users (5 Easy Steps)

AI SaaS companies can quickly detect and stay ahead of any user frustrations or market changes with Phospho’s real-time insights, custom KPIs, and continuous evaluation pipelines.

Here’s a quick 5 step guide on how to get started:

Step 1: Set up real time monitoring

Start by integrating Phospho with your AI SaaS to log and monitor all your user interactions and responses from your AI model. Use these logs to gain a basic understanding of how your users are interacting with your product and get a feel for Phospho’s platform.

Step 2: Create personalised KPIs

You can now start defining custom KPIs relevant to your product goals e.g average number of responses before user is satisfied.

Tip: you can set customised alerts such as Slack messages for when Phospho detects these criteria are met.

Step 3: Run A/B Tests

Regularly test different versions or iterations of your AI SaaS to evaluate any improvements in performance. Phospho can automate this process so you can keep an active eye on the performance of new models.

Step 4: Use custom dasboards

Set up your dashboard to track and visualise in real-time the most pressing metrics to your AI SaaS right now. Whether its mitigating churn, reducing friction during onboarding, or improving accuracy in responses.

Tip: when releasing a new version, set personalised metrics based on what you tried to achieve with this iteration, and visualise these A/B tests on your custom dashboard.

Step 5: Continuous iteration

Use Phospho’s flexibility to derive insights specific to your needs and AI SaaS to continuously fine tune your AI model’s performance. User interactions will constantly change and evolve, it’s important to continuously monitor your AI SaaS performance and adjust your AI model accordingly based on the feedback you’re gathering.

Sign up to Phospho for free here to get started with these steps.

Maximise your AI SaaS: Digital Customer Experience Analytics With Phospho

As AI is continuing to evolve as rapidly as it is, the AI SaaS market will demand more personalization and set higher expectations.

AI SaaS companies must prioritize the user experience to stay competitive. Phospho’s edge is that it’s an analytics platform is specifically designed for developing AI products more effectively and in closer alignment with your users.

An AI SaaS company’s ability to adjust its AI models and optimize the user experience based on real-time insights will be its biggest competitive advantage and differentiator.

You can start using Phospho for free by signing up here.