Experience Training

Review and correct the featured snippets that the Extractive QA algorithm surfaces from your unstructured data for particular queries. For example, take the query, "Do you offer a month to month subscription plan?" If the administrator notices the algorithm incorrectly highlighted the early termination fee "£59.99," rather than the real answer, "£17.99 per month," they could correct this in real time.

Help to correct the NLP filters that are applied for each query with NLP Filter Training. For example, if the query "Locations near Phoenix that offer in store pickup" triggered the NLP filter on the service "same-day delivery," an administrator could reject this in NLP Filter Training.

If spell check suggests the wrong spelling, administrators can fix this instantly. For example, when there is a brand-specific word like "Yext," spell check may deem this a typo and suggest the user meant to write, "next." The administrator can reject this autocorrect and instead allow "Yext" to be considered a word by our spell check.

With no waiting period to see changes in your search experience, administrators can see an immediate impact as they modify queries. Our Search Algorithm will immediately stop surfacing any rejected results and will even use this as training data for similar situations in the future. End users will benefit from these quick fixes in real time by helping ensure they're being served the most relevant results possible.