Table 2 K-analytics in context of self-service/customer support & services implementation

Provider 1

Solution Activity by Month by Author

Adoption – includes number of search and views (searches vs. views within last 14 days)

Effectiveness – did the knowledge solve the issues?

Average Session Length

Utilization –percentage of solutions accessed and useful/new knowledge utilization for solutions created within the last three months

Aging – freshness of the knowledge and reviews needed/Published solution edited in last 14 days

KCS – amount of solutions were flagged and fixed

Provider 2

Size and usage

Size:

Visit duration

Search logs:

QA traffic chart

- number of online questions/number of online answers

- keywords & trends, answered (popular searches, what customers are really interested in) and list of unanswered questions (top unanswered questions)

Number of liked answers (which questions are most satisfactory for customers)/ statistics of numbers of liked' and 'disliked' per each Q&A

Search results shown to the users

Most Escalated questions

- items in publishing center/amount of new and unhandled requests

Contextual search filter:

- graphic visualization of a question’s progress over time

Filter user queries by contextual answers (category, location, etc.…)

Usage: number of answered requests/number of answers added/number of answers deleted

Provider 3

Query Count (number of reported queries)

Query Pipeline

Name of a search interface from which the search events are performed.

Average Click Rank Over Time

Advanced Query + Expression/Keyword

Group To which a user performing the search event belongs

Audience page

Click count and Manual Query count data in relation with users performing the search events.

Search Result title and ID

Content gaps: frequent searches with no results or no clicks

Has Clicks: last search event, at least one click in the search results list/Has Results: last search event, query that returned at least one result.

Queries and Keywords pages:

most frequent queries and keywords with the poorest Relevance index based on Click count and Average click rank

Documents page documents with the poorest rank based on the Relevance index

Search Cause: automatic and manual refinements

Provider 4

Knowledge Article Version (KAV): information about individual translations, such as their creation dates, published channels, and number of associated cases.

Knowledge Article Searches: number of searches per day, month, or year for each channel and role

Knowledge Article Votes: number of votes per day, month, or year for each channel and role.

Case association count: Number of cases attached to the article

Cumulative Count: total number of article searches

Knowledge Article Views: number of views per day, month, or year for each channel and role

Knowledge Keyword Search: keywords users are looking for

Score: Article's average view rating.

Archived By: User who archived the article.

Knowledge Search Activity: number of searches per day, month, or year for each channel and language.

▪ For each search: Date, ID and title of the article that was clicked

▪ keywords users are looking, average number of:

○ Results: The number of search results that were returned for the search term.

○ Articles that appear in the search results

▪ For each article, average number of: Click, Unique users who clicked it

Average Click Rank:

order in which the article appeared in search results when users clicked it

Channel: channel that’s applicable to the article.

Provider 5

Total queries overtime

Clicks per visitor average

Number of Queries with clicks

Unique visitors

Number of Queries without clicks

Visits/sessions

Number of Queries with no results

Top queries

Top keywords

Search relevance:

Click ranks over time

Queries without clicks over time

Details of queries with low relevance

Details of keywords with low relevance

Content gaps:

Click through ratio

Details of queries without results

Details of keywords without results