ReachSuite Analytics into Rich Buyer Intent Insights

comprehensive breakdown of how to analyze ReachSuite Analytics to uncover valuable insights into buyer intent and behavior

For Account Executive & Sales Engineers

INDIVIDUAL EXPERIENCE ANALYTICS VIEW

Median time spent per session (in seconds)

  • FORMULA: sum of selected experience’s session’s time, divided by the number of sessions
  • HOW TO INTERPRET THE DATA? the higher the #, the higher intent and interest the buyer has for your platform. Treat this like time on page or time on a video

Total number of sessions

  • FORMULA: sum of selected experience’s sessions on that experience
  • HOW TO INTERPRET THE DATA? the higher the #, the higher intent and interest the buyer has for your platform. It also means that the buyer is likely sharing this within their organization

Total number of CTA clicks

  • FORMULA: sum of selected experience’s conversions on that experience
  • HOW TO INTERPRET THE DATA? Each CTA click is a conversion to your landing page - the higher the click #, the higher the intent that the buyer wants to take the next step

Where in this experience do people bounce the highest?

  • FORMULA: Sum of selected experience’s bounces, grouped by widget, in order from 1-n (it should be like widget 1,2,3 etc.)
  • HOW TO INTERPRET THE DATA? This is a part of the experience where buyers do not have interest - if you see this pattern recur, you should optimize away from this portion of the product and relay this insight to your marketing / product team

How many sessions has this experience had? (over time)

  • FORMULA: sum of selected experience’s sessions, grouped by day, in ascending order so it presents from Jan 1 - Jan 30 (for example)
  • HOW TO INTERPRET THE DATA? Here you can see if the buyer intent is increasing (the # of sessions is growing over time) or decreasing

How many people are clicking the CTA in this experience?

  • FORMULA: sum of selected experience’s conversions, grouped by day, in ascending order so it presents from Jan 1 - Jan 30 (for example)
  • HOW TO INTERPRET THE DATA? Here you can see if the buyer intent is increasing (the # of sessions is growing over time) or decreasing

Average time spent per widget

  • FORMULA: sum of selected experience’s view time (see definition above) between steps (see definition above) divided number of sessions
  • HOW TO INTERPRET THE DATA? This is important for marketing and product to weigh where people are most interested - especially for sales reps - the highest the time in between a widget, the longer they spent, which correlates with their interest in that portion of the product. Use this to guide early conversations

Segmentation branches

  • FORMULA: total number of segmentation branch picklist values selected grouped by picklist value selected
  • HOW TO INTERPRET THE DATA? Treat this as automated discovery questions - their response to the segmentation branch questions can be used to narrow in on their use-case, persona, or pain point enabling you to have a more pointed, strategic conversation

For Sales Managers, Marketing, & Revenue Operations

AGGREGATE EXPERIENCE ANALYTICS VIEW

Sessions on all experiences

  • FORMULA: sum of all experience sessions
  • HOW TO INTERPRET THE DATA? This is a very simple number - just the overall session count across your experience set

How many sessions on all experiences? (over time)

  • FORMULA: sum of all experience sessions, grouped by day, in ascending order so it presents from Jan 1 - Jan 30 (for example)
  • HOW TO INTERPRET THE DATA? Managers should use this to guide their team’s usage - the chart should have a steady increase up and to the right

CTA clicks by day

  • FORMULA: sum of all experience conversions (see definition above, conversion), grouped by day, in ascending order so it presents from Jan 1 - Jan 30 (for example)
  • HOW TO INTERPRET THE DATA? Managers should use this to guide their team’s usage - the chart should have a steady increase up and to the right

Experiences with most sessions

  • FORMULA:  sum of each experience sessions in list view, descending order (most to least)
  • HOW TO INTERPRET THE DATA? Managers should use this to understand which experiences are being used the most and least. This can guide product and marketing messaging and focus ICPs / personas / pain points / use-cases

Experiences with most conversions

  • FORMULA:  sum of each experience conversions (see definition above, conversion) in list view, descending order (most to least)
  • HOW TO INTERPRET THE DATA? Managers should use this to understand which experiences are being used the most and least. This can guide product and marketing messaging and focus ICPs / personas / pain points / use-cases

Experience owners with most sessions

  • FORMULA: sum of each experience sessions, grouped by experience owner in descending order (most to least) 
  • HOW TO INTERPRET THE DATA? Managers should use this to understand which team members are leveraging experiences the most.

Experience owners with most conversions

  • FORMULA: sum of each experience conversions (see definition above, conversion), grouped by experience owner in descending order (most to least)
  • HOW TO INTERPRET THE DATA? Managers should use this to understand which team members are leveraging experiences most effectively.