What are AI Filters?
AI Filters (previously AI Answers) allow you to create a question that will be associated with each feedback. An example question could be something like:
Does this feedback describe a software bug
What is the client emotion in this feedback
Is the customer voicing this feedback likely to churn
Our AI will then take your question, and for each individual feedback, attempt to answer that question. So if you have 100 comments, AI Filters would be able to tell you how many it believes describe a software bug, or how many people are going to churn.
While we have over 50 questions already developed, ranging from things like "is this feedback mentioning a competitor?" to "does this feedback complain about one of our premier products?", Lumoa does allow you to create your own question. This question can be tailor made to fit your specific data, and focus on the things that matter specifically to your organization and internal metrics.
How can I start using AI Filters?
Currently, AI Filters can only be configured by Lumoa. This is because the process that goes into creating them, and making sure they work with your specific data, on any question that you create, can be a bit complex.
We recommend that you contact your CS manager, or email [email protected], if you want to get started using AI Filters. That way we can make sure we understand your use case, and work with you to get the specific results you need.
How can I view AI Filters?
AI Filters will be created as a tag associated with your data. This means that, like all other tags, you could use the filters menu to filter to all responses that report a bug, as seen below:
Conversely, you could also create a custom graph widget that would look at this information, and update itself over time. Below you can see custom graphs made for things like:
client emotion throughout the feedback,
whether this customer will churn,
is this customer reporting a bug,
whether this feedback contains a feature request:
What kinds of questions can I ask for AI Filters?
Theoretically, you can ask any question you want. However, AI Filters will only be able to look at your customer open text comments when generating a response. This means, even if you create a question around "pricing", the AI might not be able to answer it if there are no comments in your data talking about "pricing".
Additionally, the questions that you ask are defined by generative AI. Meaning making sure that you ask the right question, and formatted in the right way, will lead to better results. While our AI experts can help you format your question for maximum success, its important to think about why you are asking this question - what is the goal behind question? What information are you looking to obtain? Would you consider this question successful if it gave you Answer A, or Answer B?
One way to understand how generative AI works is to imagine an untrained person (or even a teenager/child) who is unfamiliar with your business reading through the conversation and evaluating the response based solely on the answer options provided.
Lets take an example and assume we want to see all feedback talking about a "Price Estimate: Does the customer service agent provide a price estimate during the interaction? (Yes/No/Unclear)"
To improve the accuracy of responses to this prompt, consider the following refinements:
1. Be More Specific About "Price Estimate"
Issue: The term "price estimate" might be interpreted differently—does it mean an exact quote, a rough range, or mentioning pricing at all?
Improvement: Clarify what qualifies as a price estimate.
Example Revision:
"Does the customer service agent provide a specific price or a price range for the requested product or service during the interaction? (Yes/No/Unclear)"
2. Define "During the Interaction"
Issue: What if the agent promises to send a quote later? Or refers the customer to a website?
Improvement: Specify if the price must be stated directly in the conversation or if referring to another source counts.
Example Revision:
"Does the customer service agent state a price or price range verbally during the interaction, without referring the customer to another source? (Yes/No/Unclear)"
3. Consider Adding Contextual Conditions
If the agent is unable to provide a price due to company policy or missing information, should the response still be "No"?
Example Revision for More Context:
"Does the customer service agent provide a price estimate when requested by the customer? (Yes/No/Unclear)"
Get in touch
📧 Do you have any questions or comments about using Lumoa? Please don't hesitate to email Lumoa Support at [email protected].