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On this page, you can find documentation about x-bees Snalytics which provides all the information you need to keep on top of your business. Created: May 2022 Permalink: https://confluence.wildix.com/x/BYL6Bg |
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Switch between table/ chart view
You can change the view of your answer so it appears as either a table or a chart. To change the view of your answer, toggle between either a table or a chart type:
Your search needs at least one attribute and one measure to be presented as a chart. When you display your data as a chart, x-bees automatically selects the type of chart that works best for your data. If you want to use another type, click Change visualization (chart icon) on the right:
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The answer opens and besides viewing its details. Also, using the Explore this data panel on the right, you can modify the answer by applying additional filters, adding/ replacing columns, choose data for comparison:
Keyword reference
Use keywords to help define a search.
General
| Note |
|---|
Note: When using the top or bottom keywords without specifying a number (n), the number defaults to |
| Keyword | Description |
|---|---|
| top n | Generates the top n items from a sorted result. ExamplesExample: top 10 sales rep revenue top sales rep by count sales for average revenue > 10000 sales rep average revenue for each region topcaller callee direction status duration today top 5 |
| top n measure1 by attribute|measure2 | Calculates top n items, then sorts the top items by another measure or attribute. Contrast with top with top n (swaps the order of operations). Example: top 10 sales rep revenue by profit margincaller by conversations this month |
| bottom n | Generates the bottom n items from a sorted result. ExamplesExample: bottom 25 customer by revenue for each sales rep bottom revenue average bottom revenue by state customer by revenue for each sales rep bottom 10 caller by conversations this month |
| sort by | Sorts the result set by an attribute or measure. ExamplesExample: revenue by state caller callee direction status duration today sort by average revenue descendingduration |
| by <measure> | Treats the measure as an attribute and groups the result set by it. ExamplesExample: conversations by day |
Date
| Keyword | Examples | ||
|---|---|---|---|
| after | conversations after 10/31/2022 | ||
| before | conversations before 03/01/2022 | ||
between ... and ... | conversations between 01/30/2022 and 01/30/2022 | ||
| dailyday | conversations daily | ||
| daily year-over-year | growth of revenue by order date daily year-over-year | ||
| day | count monday restaurant | ||
day of week | conversations by day of week last 6 3 months | ||
| growth of … by ... | growth of sales by order dateconversations by time last month unanswered | ||
| growth of … by … daily | growth of sales conversations by order date time daily last month unanswered | ||
| growth of … by … monthly | growth of sales conversations by date shipped monthly sales > 24000time monthly unanswered | ||
| growth of … by … quarterly | growth of sales conversations by date shipped time quarterly unanswered | ||
| growth of … by … weekly | growth of sales conversations by receipt date weekly for pro-ski2000 | ||
| hourly | conversations by callee hourly | ||
time weekly last month unanswered | |||
| last day by | conversations last day by callee | ||
| last month | conversations last month by callee | ||
last month by | conversations last month by day | ||
| last n days | conversations last 7 days | ||
| last n months | conversations last 10 months by day | ||
| last n quarters | conversations last 2 quarters by month by service | ||
| last n weeks | conversations last 10 weeks by day | ||
last n years | conversations last 2 years by service | last quarter | conversations last quarter |
| last week | conversations last week by service | ||
| last year | conversations last year by callee | ||
| month | conversations by month last year | ||
| month | conversations January | ||
| month to date | sales by product conversations month to date sales > 2400?? | ||
month year | conversations by service February 2022 | ||
| monthly | conversations by service monthly | ||
| monthly year-over-year | growth of revenue by receipt date monthly year-over-year | ||
| n days ago | conversations 2 days ago | ||
| last n days for each month | conversations 2 days for each month | ||
| last n days for each quarter | conversations last 15 days for each quarter | ||
| last n days for each week | conversations last 2 days for each week | ||
| last n days for each year | conversations last 300 days for each year | ||
| last n hours for each day | conversations last 2 hours for each day | ||
| n months | conversations last 6 months | ||
| n months ago | conversations 2 months ago by service | ||
last n months for each quarter | conversations last 2 months for each quarter | ||
| last n months for each year | conversations last 8 months for each year | ||
| n quarters ago | conversations 4 quarters ago by service | ||
| last n quarters for each year | last 2 quarters for each year | n weeks ago | conversations 4 weeks ago by callee |
| last n weeks for each month | conversations last 3 weeks for each month | ||
| last n weeks for each quarter | last 2 weeks for each quarter | ||
| last n weeks for each year | last 3 weeks for each year | ||
| n years | opportunities next 5 years by revenue | ||
| n years ago | conversations 2 years ago by service | ||
| next day | shipments next day by order | ||
| next month | appointments next month by day | ||
| next n days | shipments next 7 days | ||
| next n months | openings next 6 months location | ||
| next n quarters | opportunities next 2 quarters by campaign | ||
next n weeks | shipments next 10 weeks by day | ||
| next n years | projected deals next 5 years | ||
| next quarter | opportunities next quarter amount > 30000 | ||
| next week | shipments next week by store | ||
| next year | opportunities next year by sales rep | ||
quarter to date | sales by quarter to date | sales by product quarter to date for top 10 products by salesquarterly | conversations quarterly by service |
quarterly year-over-year | growth of revenue by date shipped quarterly year-over-year | ||
| this day | conversations this day by callee | ||
this month | conversations this month by day | ||
| this quarter | conversations this quarter by callee | ||
| this week | conversations this week by service | ||
| this year | conversations this year by callee | ||
| today | conversations today by callee | ||
| week | conversations by week last quarter | ||
| week to date | sales by order date week to date for pro-ski200 | ||
| weekly | conversations weekly | ||
| weekly year-over-year | growth of revenue by date shipped weekly year-over-yearto date for pro-ski200 | ||
| year | revenue by product 2014 product name contains snowboard | ||
year to date | sales by product year to date | ||
| yearly | shipments by product yearly | ||
| yesterday | sales yesterday for pro-ski200 by store |
...
| Keyword | Examples | |
|---|---|---|
| detailed | conversation time detailed | |
| last hour | count unique conversations last hour | |
| last minute | count conversations last minute | |
| n hours | count conversations [ last | next ] 12 hours | |
| n hours ago | conversations 2 hours ago | |
| n minutes | count conversations [ last | next ] 30 minutes | |
| n minutes ago | sum conversations by service 10 minutes agonext hour | count projected visitors next hour |
| next minute | count projected visitors next minute | |
| this hour | conversations this hour | |
| this minute | conversations this minute |
Text
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product name begins with 'pro'
// returns all products that start with 'pro'
product name begins with 'pro'
product name begins with 'sport'
// returns all products that start with 'pro'
// OR 'sport'
product name begins with 'pro'
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| Keyword | Examples | ||
|---|---|---|---|
| begins with | conversations name begins with 'joe' by name // returns all products that start with 'pro' // AND have color that starts with 'bl' (blue or black) | contains | product name contains "alpine" description contains "snow shoe"the list of conversations that have name starting with 'Joe' |
| contains | conversations name contains 'bill' by name | ||
| ends with | product conversations name ends with 'deluxejoe' | ||
| similar to | course conversations name similar to 'handjoseph' | ||
| not begins with | product conversations name not begins with "tom'bill's" | ||
| not contains | product color conversations name not contains 'tan' product color not contains 'red'joe' | ||
| not ends with | product conversations name not ends with "trial"'joe' | ||
| not similar to | course conversations name not similar to 'hand' |
...
| Note |
|---|
Notes:
For example, if you search for If you search for |
Number
| Keyword | Examples |
|---|---|
| average | conversations average duration by service this month |
| count | count service unique count caller by service |
max | max sales by visitor by sitetalk time conversations by service |
| min | min revenue by store by campaign for cost > 5000answer time by service |
| standard deviation | standard deviation revenue by product by month for date after 10/31/2010 |
| sum | sum revenue |
| unique count | unique count conversation id |
| variance | variance sale amount by visitor by product for last yearduration by service |
Comparative
| Keyword | Examples | ||
|---|---|---|---|
| all | conversations uk_support vs all
| ||
| between... and... | revenue between 0 and 1000 | ||
= (equal) | unique count visitor by store purchased products = 3 for last 5 days | ||
| everything | revenue asia conversations uk_support vs everything
| ||
| > (greater than) | sum sale amount by visitor by product for last year sale amount > 2000 | ||
>= (greater than or equal) | count calls by employee lastname >= m | ||
< (less than) | unique count visitor by product by store for sale amount < 20 | ||
<= (less than or equal) | count shipments by city latitude <= 0 | ||
!= (not equal) sum sale amount region != canada date != last 5 days | caller callee direction status duration today callee !={null} | ||
vs, versus | conversations uk_support vs us_support |
You can use special constants for null and empty values with the = and != keywords: {null} and {empty}.
For example: customer name = {empty} or department service != {null}.
Location
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revenue store name county near san francisco
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revenue store name county near alameda within 50 miles
Period
| Keyword | Examples |
|---|---|
| day | conversations by day |
| day of month | sales conversations day of month by month |
| day of quarter | deals conversations day of quarter by year |
day of week | customers conversations by week day of week |
| day of year | ad clicks conversations day of year by year |
| hour | conversations by hour weekly |
| month of quarter | conversations month of quarter by year |
| quarter | conversations by quarter |
quarter of year | conversations quarter of year |
| week of month | conversations week of month |
| week of quarter | conversations week of quarter |
week of year | conversations week of year |
In / Not in
| Keyword | Description |
|---|---|
| in | Query in query search (intersection of two sets). Must match last attribute before keyword with first attribute inside subsearch. Syntax: attribute in (attribute subsearch) Examples: store name in (top 10 store name by sales footwear) product name 2014 product name in (product name 2013) sales |
not in | Relative complement of two sets. Must match last attribute before keyword with first attribute inside subsearch. Syntax: attribute not in (attribute subsearch) Example: product name 2014 product name not in (product name 2013) sales |
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