1.1 Bookings Story - Main Story
Headline - the sentiment is based on performance relative to historical trends. This takes into account comparisons to the most recent period as well as the average across previous periods. Previous periods here is defined as the last 12 periods.
e.g. - "Great Bookings in Q3"
Comparison to previous periods - the sentiment is based on comparison to average bookings over previous periods. Previous periods here is defined as the last 12 periods.
e.g. - "Quarter to date, bookings are in line with past periods."
Comparison to average for previous periods - compares bookings from the selected period to the average of previous periods. Previous periods here is defined as the last 12 periods.
e.g. - "Bookings are $801k, which is $348.7k (77%) greater than average bookings at this time each quarter from Q2 2017 to Q4 2019 ($452.3k)."
Best period - looks at all of the recent periods and calls out the period with the most bookings. Recent periods here is defined as the last 12 periods. Note, this content only appears when timeframe type is “Last”.
e.g. - "The best quarter since Q2 2017 by bookings was last quarter."
Number of deals and average deal size - For the selected period, it calls out the component metrics of bookings: number of deals and the average deal size.
e.g. - "They were made up of 104 deals, with an average deal size of $43.3k"
Change in bookings - Compares the bookings from the selected period to bookings from the previous period. It calls out the percentage difference between those values. When the time frame period is set to “Last”, it makes a year-over-year comparison as well.
e.g. - "Bookings were up 7% relative to the quarter before and 20% relative to the same quarter last year"
Opportunities expected to close - Calls out which opportunities are expected to close in the remainder of the selected period. This would include opportunities that are not yet closed but have a close day that falls within the remainder of the current period. In the example below, we’re part of the way through Q4 (say, November 12), and we’re looking at Bookings this Quarter. Opportunities expected to close would include any open opportunity with a closed date before the end of Q4 (12/31). Note, this content only appears when timeframe type is “This”.
e.g. - "There are 86 open opportunities expected to close in Q4."
Driver list - looks across five unique dimensions (e.g. region, salesperson, etc.), and each dimension has a number of entities (e.g. north region, south region, Bob, Sally). Each entity has an aggregate value of bookings, and the entities are ranked against one another, even across dimensions. The top three entities across all five dimensions are called out as drivers. This analysis is looking at the change (increase or decrease) in bookings from the previous period, as opposed to the absolute bookings for the selected period. Note that the dimensions used for driver analysis are customizable in Lexio.
e.g. - "Looking across the most relevant dimensions, the decrease in bookings relative to the same period last quarter was primarily driven by Nina Mclaughlin ($294k), the Financial Services industry ($182k), and the Upsell opportunity type ($144k)."
Metric attribution analysis - explains the cause of the change in bookings from the previous period to the selected period. This can be attributed to one or both of the component metrics of bookings: number of deals and the average deal size.
e.g. "The decrease in bookings relative to the same period last quarter is due to the decrease in number of deals."
Metric attribution details - describes the change of each component metric from the previous period to the selected period.
e.g. "The number of deals is down 44%, but the average deal size is up 61%."
Cycle Time paragraph
Cycle time average - calls out the average cycle time of the deals closed within the selected period. Cycle time is calculated as the difference between the Close Date and Created Date for any opportunity that was closed and won. It only includes opportunities that closed within the selected time period.
e.g. - "The deals' cycle times averaged 90.45 days."
Cycle time range - calls out opportunities with the shortest and longest cycle times.
e.g. - "They ranged from Harvey and Sons's low of 38 days to Carroll and Sons's high of 149 days."