Datasets are sets of interactions from your contact center that have been recorded and parsed
Process of analyzing data and breaking it into parts. for you to analyze. These interactions include voice calls, emails, chats, supported digital channels, or any combination of these. Voice calls include written transcripts you can view. Datasets span a specific time period and match any filter criteria you apply.
Filter criteria provides options to include or exclude interactions that meet some or all of the qualifications you enter. For example, you could create a dataset of interactions spanning the last 90 days that mention the keyword Collins but exclude the keyword Longbourn.
Maria Bertram is a data analyst in the Classics, Inc. contact center for the Mansfield Park brand of book-related clothing. Her manager has noticed that Classics seems to be losing younger customers lately to a new competitor, Fables Ltd. The manager wants to make sure none of the contact center agents are recommending Fables to these customers, since Fables recently introduced new merchandise that's receiving a lot of social media buzz.
Maria creates a dataset for her manager to analyze. She configures it for a period of the last 90 days. It includes interactions where the keyword Fables was mentioned but excludes interactions where only the customer said that keyword.
Key Facts About Datasets
- Voice data becomes available as soon as the call is transcribed into text. This typically takes three to five hours after the call ends, depending on the length of the call and the call volume at the time. When call volume is low, data may become available within as little as an hour. However, it may take several hours if call volume is high.
- Email, chat, and digital interactions are available immediately after the interaction ends.
- Up to 15 datasets are supported per business unit High-level organizational grouping used to manage technical support, billing, and global settings for your CXone environment.
- You cannot change a dataset name after you create it. You cannot use special characters in the dataset name. This makes it important to carefully plan naming conventions for your datasets in advance. Make sure you can quickly and easily identify the data contained in each dataset. It can also be helpful to know at a glance who created the data set. Some users find that the dataset topic or name of the team being analyzed followed by the creator initials is a useful naming convention. In the previous example, Maria could create a dataset named Fables Mentions MB.
- If your company has Interaction Analytics for multiple languages, you can create datasets for the different languages. You cannot create a single dataset that includes interactions in more than one language.
- You can filter the data contained in a dataset based on keywords, phrases Combination of words that have special significance when used together in a specified order, such as "want to cancel"., or entities Keyword or phrase defined in your company profile in Interaction Analytics. Related to an entity type. Can include variants. interactions contain or do not contain. You can choose which channels to include and the period of time to cover. You can include or exclude interactions by sentiment Overall mood or result of the interaction as determined by analysis of words, phrases, and context of the transcript. Interactions can be positive (blue), negative (red), mixed (dark gray), or neutral (light gray)., frustration Looks for cues to identify customer frustration. The cues include words and phrases like, "I'm very angry". Frustration isn't the same as negative sentiment. Frustration cues show that a customer is upset rather than just discussing something negative., or resolution. You can also filter by metrics tags like specific teams, skills, or agent names. The maximum number of metric tags you can add to filter criteria is 50.
- When you create a dataset, you can apply a category template Category groupings that help you use the data for a specific purpose. Out-of-the-box category templates include Intent to Buy and Risk Aversion. and a workspace template Multiple workspaces grouped as a reusable template. right from the dataset page.