Reduce churn rate of your AI software in 4 steps using Phospho:

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Churn rate is one of the clearest metrics to indicate whether your AI software is valuable or not.

Let’s set some early context…

The average churn rate for software companies hovers around 14%. Anything in single digits is considered a ‘good’ churn rate, with the best SaaS companies even hitting rates as low as 1-3%.

Churn rate is a really popular metric because we can use it to understand our AI SaaS’s ability to engage and retain users to inform decisions about product improvement.

In this article, we’ll be going over how we can reduce churn rate with 4 key principles that lead to reducing churn.

Monitor User Interactions in Real-Time

Real time monitoring, especially for AI software with any conversational features, is really effective for spotting issues before they become more problematic i.e lots of users decide to churn.

By using real-time analytics tools like Phospho to track and log user interactions as they happen, you can spot bottleneck and pain point patterns as they emerge to then address quickly before it escalates into a significant problem for more users.

Let’s look at a simple example. Your AI SaaS is a project management app with a conversational AI component. You notice through on your Phospho dashboard that your logged interactions are showing a pattern of more and more user queries about how to integrate a popular third party tool. By quickly identifying this trend of frustration connecting a commonly used tool, your development team can focus on investigating the issue and deploying a fix quickly to prevent potential churn.

In Phospho you can set up alerts and custom metrics/KPIs using natural language to notify you of patterns in any user behaviour as they happen, meaning teams can intervene promptly and proactively to address any range of issues before potential churn takes place.

To get an idea of how impactful it is to start analysing your text data, read our previous article on it here.

Analyze User Data for Actionable Insights

When we log and track user queries and AI model outputs from our AI SaaS, we’re actually collecting a huge pool of text data.

This data is extremely rich in actionable insights because what better feedback can you get than real verbatim conversations your users are having in-app?

Interpreting this data is a lot easier with visualisations. With Phospho you creative freedom to visualise your AI SaaS interactions with customised dashboards and KPIs to simplify large volumes of unstructured text data for insights at a glance.

For a deeper dive on this, you can see how to create custom dashboards with phospho in our previous article here. Or if you instead want to better understand how to do data visualisation with phospho, read this article here.

This approach with Phospho helps you leverage user data more effectively to identify and rectify patterns that can correlate with lower retention or higher churn risk much quicker. Traditional analytics tools cannot collect, process or visualise the same user data with the same degree of customisation and specificity.

Implement Continuous Evaluation and Iteration

User needs are always going to evolve. It’s for this reason that improving our AI SaaS is an ongoing effort, not a one time job…

But we all know this already, so the key is in understanding how we can do that more effectively than our market competitors.

For that we’ll need to accomplish 3 things:

1. A non-invasive iterative feedback loop to inform development
2. Ensure each iteration is aligned with real user needs
3. Evaluate our AI model’s performance in a measurable way

We’ve ticked off the first and second requirements with Phospho’s logging and analysis of real-time user interactions.

To accurately evaluate our AI model’s performance, Phospho’s automated evaluation pipeline can be used to continuously measure custom KPIs in real time, detect hallucinations or anomalies, and flag or alert trends that indicate a any dips in performance that directly impact user satisfaction and retention.

You can use the above 3 things to fuel really effective iteration cycles. By A/B testing your iterations with Phospho you can also see which versions of your AI SaaS perform better for your users.

When A/B testing, it’s important to establish clear goals with each iteration and thereby define and set up specific success metrics so we can qualitatively compare different iterations against measurable benchmarks.

Personalize User Experiences

One of the best ways to reduce churn is to personalise the user experience so that it addresses their needs better than anywhere else.

The three previous principles are all leverage to perform iteration cycles that achieve more personalised user experiences for our customers by continuously adapting to the evolving needs of our user base. It’s critical for an AI SaaS to understand their users in today’s SaaS market, to better understand how you can do that with Phospho read our previous article here.

The data we collect and interpret with Phospho helps us extract insights to understand individual user preferences and pain points we can use to personalise interactions under certain scenarios, customise responses, and build relevant features based on user behaviour.

The real value with Phospho is the ability rich insights extraction to be scaled to handle personalisation for growing user bases without having to compromise on performance.

You can sign up and start using Phospho for free here.

Additional Information: How to Implement These Steps

We’ve got a quick guide for you below, but for a deeper step by step process you can read our previous articles that explain it further here and here. You just have to scroll down a bit.

Tip: if at any point you need specific questions answered for your setup process, you can talk to our documentation page with the search bar - it uses our own AI model, Tak.

Step 1 - Connect Phospho either to your AI SaaS with our API for real-time capability, or by uploading any data files to our platform to perform analysis on historical data.

Step 2 - Configure your custom KPIs and events for detection to automate a large chunk of the insights extraction process. You can read about how to do that here in our docs.

Step 3 - You can use Phospho lab (our hosted version you can install locally) or our API to set up your evaluation pipeline using natural language instructions. This will then run constant evaluation on messages, events, KPIs, sentiment and other enabled analytics you can configure.

Step 4 - Use Phospho’s extensive analytics capabilities to visualise complex data, segment users, and develop personalised user experiences. Use automated A/B tests to see if your iterations have improved performance, churn, retention, or any metric you wish.

You can get started now for free by signing up here.

Conclusion: Reduce Churn With Phospho

The best way to reduce churn is for your AI SaaS to have a high user satisfaction, but to do that we need to understand our users well enough to keep iterating with their evolving needs.

Phospho is a tool that allows this for AI SaaS teams with its comprehensive analytics capabilities specifically designed for optimising AI software and LLM apps with deeper user understanding.

You can use Phospho for free by signing up here and start improving your AI software with actionable insights and more effective iteration.