Categorize contacts based on keywords and phrases used in a conversation in Contact Lens
You can set up Contact Lens to track issues that you know exist in your contact center ("known knowns"), and monitor any changes over time.
You can label your contacts based on predefined criteria you set up, that is, keywords and phrases you want to detect. Through categorization, each contact is analyzed for these criteria, and labeled.
This is useful to do when, for example, you want to ensure that agents are using certain words or phrases in calls or chats, for compliance reasons. Or, for example, you want to investigate when customers use certain words and have a negative sentiment.
To set up this feature, add rules that contain the words or phrases that you want to highlight.
In a Contact details page for a chat, categories appear above the transcript, as shown in the following image.
The following image shows what a Contact details page looks like with a category for a call. The category is named cancellation. It contains the words or phrases you want to highlight in the analysis.
Add rules to categorize contacts
Step 1: Define conditions
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Log in to Amazon Connect with a user account that is assigned the CallCenterManager security profile, or that is enabled for Rules permissions.
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On the navigation menu, choose Analytics and optimization, Rules.
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Select Create a rule, Conversational analytics.
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Assign a name to the rule.
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Under When, use the dropdown list to choose post-call analysis, real-time analysis, post-chat analysis or real-time chat analysis.
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Choose Add condition, and then choose the type of match:
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Exact Match: Finds only the exact words or phrases. Enter the words or phrases, separated by a comma.
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Semantic Match: Finds words that may be synonyms. For example, if you enter "upset" it can match "not happy," or "hardly acceptable" can match with "unacceptable," and "unsubscribe" can match with "cancel subscription."
Similarly, it can semantically match phrases. For example, "thank you so much for helping me out," "thanks a lot and this is so helpful," and "I am so happy that you are able to help me."
This removes the need to define an exhaustive list of keywords while creating categories, and provides you the ability to cast a wider net for searching similar phrases that are important to you.
For best semantic matching results, provide keywords or phrases with similar meaning within a semantic matching card. Currently, you can provide a maximum of four keywords and phrases per semantic matching card.
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Pattern Match: Finds matches that may be less than 100 percent exact. You can also specify the distance between words. For example, if you are looking for contacts where the word "credit" was mentioned but you do not want to see any mention of the words "credit card," you can define a pattern matching category to look for the word "credit" that is not within a one-word distance of "card."
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Using Exact Match as an example, enter the words or phrases, separated by a comma, that you want to highlight.
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Choose Add. Each word or phrase separated by a comma gets its own line in the card.
The logic that Contact Lens uses to read these phrases is: (Hello AND thank AND you AND for AND calling AND Example AND Corp) OR (we AND value AND your AND business) OR (how AND may AND I AND assist AND you).
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To add more words or phrases, choose Add group of words or phrases. In the following image, the first group of words or phrases are what the agent might utter, and the second group is what the customer might utter.
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The logic that Contact Lens uses to read these phrases is: (Hello AND thank AND you AND for AND calling AND Example AND Corp) OR (we AND value AND your AND business) OR (how AND may AND I AND assist AND you).
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The two cards are connected with an AND. This means, one of the rows in the first card needs to be uttered AND then one of the phrases in the second card needs to be uttered.
The logic that Contact Lens uses to read the two cards of words or phrases is (card 1) AND (card 2).
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Choose Add condition to apply the rules to:
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Specific queues
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When contact attributes have certain values
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When sentiment scores have certain values
For example, the following image shows a rule that applies when an agent is working the BasicQueue or Billing and Payments queues, the customer is for auto insurance, and the agent is located in Seattle.
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Step 2: Define actions
In addition to categorizing a contact, you can define what actions Amazon Connect should take:
Step 3: Review and save
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When done, choose Save.
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After you add rules, they are applied to new contacts that occur after the rule was added. Rules are applied when Contact Lens analyzes conversations.
You cannot apply rules to past, stored conversations.