Likelihood to Engage
The Likelihood to Engage model finds correlation between the past email
behavior and the near-future email engagement. In other words, the model
predicts the probability of the user opening an email in the near future, based
on the past email interaction behavior.
Based on the user behavior, CDP defines the likelihood to engage segments as
Newbie, Opt-Out, Forgotten, Phantom, Enthusiast, Mainstreet, and Sleepy. These
segments help marketers create the most relevant strategies for each group.
Use cases
Enthusiasts - individuals most likely to engage on email
- Understand these users, their origin, and their likings, and leverage
the information in lookalike audiences.
- Leverage their engagement to create value and content for your brand in social
media, surveys, and product ratings.
Mainstreet - individuals with a medium likelihood to engage
Increase engagement by more personalized email content such as newsletter
segments or personalized product recommendations.
Sleepy - individuals with a low likelihood to engage
- Lower contact frequency.
- Re-engage through special programs to drive engagement.
Newbie - individuals who subscribed within the last 60 days
- Implement a welcome email series to start a relationship with newbies
on a right footing.
- Maintain proper hygiene in email frequency to avoid spamming the users and
prompting the fresh contacts to unsubscribe.
Opt-Out - individuals who opted out of email
Re-engage the high value customers through other channels such as Facebook,
Instagram, direct mail, or online.
Forgotten - individuals who did not receive an email within the last 60 days
Understand the reasons for not contacting such users.
Phantom - individuals did not open an email in their lifetime
- Reduce frequency.
- Run special winback campaigns with aggressive email subjects and offers.
- Identify disposable email addresses.
No-Email - individuals without an email or a valid email
- Engage through other channels.
- Inform individuals about the benefits of sharing their emails at the
store or on the website.
Target audience
The Likelihood to Engage model predicts the engagement behavior of individuals
based on past email interactions. This model scores all individuals in the
customer pool.
How does the model work?
For each contact, the model calculates:
- the email behavior features such as send, open, click frequency, volume, and
recency
CDP trains and tests the model on the historical data where the outcome is
known. Post training, the model is deployed to predict the future email
engagement.
The output of the model is the likelihood to engage for each customer.
This probability is segmented in 10 equal-sized deciles, 1 being the most likely decile to yield
engagement:
| Decile |
Description |
Email segment |
|---|
| 1 |
High |
Enthusiast |
| 2, 3, 4, 5, 6, 7, 8 |
Medium |
Mainstreet |
| 9, 10 |
Low |
Sleepy |
| NA |
Does not engage |
Phantom |
| NA |
Does not qualify |
Newbies, Forgotten, Opt-outs |
Using the Likelihood to Engage model
CDP displays the output from the Likelihood to Engage model in:
- 360 > 360 Profiles
- Actions > Campaigns and Actions > Campaigns+
- Analytics > Metrics
To learn more about how the Likelihood to Engage model can enhance
your marketing workflow, contact us.
