A Behavioral segmentation — or Likelihood to Buy model — is the one that ingests behavioral data (in-app usage, website activity, marketing campaigns, etc.) of users/visitors to measure the engagement of the lead. (Has the lead tried to engage with you?). Because the input of the model uses behavioral data, the scores are recomputed several times throughout the day to reflect as much as possible the level of intent of the lead at a certain time.
How is the Likelihood to Buy score built?
Essentially the score is built on "Active events" which are triggered when the lead has taken action (e.g. connected to their account, added users to the account, opened email, visited a web page, registered to a webinar, filled out a form ....) and we ignore any "Passive event" (e.g. received an email or invitation and didn't take action, system events fired like "enrichment"). In addition, the score is also degraded by "Negative events" that suggest the person is not interested (e.g. requests to unsubscribe, bounced emails...).
How will the Likelihood to Buy score evolve?
The score will be updated in batch every 4 hours with any new activity.
The score will decrease over time to differentiate the people who recently showed activity or requested a demo versus the ones who did it 6 months ago. We usually apply a time decay of 90 days, meaning the score will return to 0 if there was no event logged for this person in the previous 3 months.
What Behavioral data points can be used?
The idea is to catch events which are most likely leading to a conversion and reflecting intent. It means identifying what events will distinguish a "hot" lead from a lead just surfing the web or vaguely curious of your product.
The list of activities below is given as example and is not exhaustive nor all necessary as it depends on what you would like the Likelihood to Buy score to reflect the most and on data availability.
- App Usage
This is highly specific to your product and what main events you are tracking.
- New user added / deleted
- Account deactivated
- Core product action
- Created project
- Web Activity
- Demo request / contact us form submission
- Sign up for free account
- Chatbot conversation
- Watched demo
- Webpages viewed : home page, pricing page, features page, blog, forum, case studies, partners, blog pages
- Marketing Activity
- Webinar registration, attendance
- Conference / event registration, attendance
- eBook, case study or Whitepaper downloads
- Signup for newsletter
- Email Activity
- Marketing emails opened, clicked, replied
- Email bounced (hard or soft)
- Unsubscribe request
- Sales Activity
- Call scheduled / attended / cancelled
If you are sending all your data, we will need to understand:
- how you link those events to a lead (email address)
- if this link and tracking is reliable
- which events are post or pre-conversion
- which events are non-user activity (technical process triggered like enrichment_provider, data_submitted...)
We have worked in the past with the following integrations
- Salesforce campaigns responses
- Salesforce tasks
- ... and some more
If you have any question, you can shoot us an email at firstname.lastname@example.org
The MadKudu Team,