Since using Lytics behavioral scores directly requires a level of understanding of the data science at play, Lytics also offers out-of-the-box behavioral audiences.
These audiences are essentially blends of scores that can be used alone or as a rule in a custom audience. For example, Casual Visitors describes users who come and go without showing much activity per session. The definition using Lytics scores is
Users with an intensity score less than 25. Now, instead of needing to know exactly what "intensity" means in this context, or what the significance of the number 25 is, the audience Casual Visitors can be used as a building block.
In this example audience, the Casual Visitors characteristic is being used to filter the users who have a high affinity for "Computing". Note that the number of people who have a high affinity for "Computing" is 276,046, but the number of people who have a high affinity for "Computing" and qualify as a Casual Visitor is 185,747.
Reducing the size of an audience is a great way to make a campaign more efficient. Additionally, splitting an audience based on behavioral properties is a great way to introduce different modes of communication for different archetypes of users. For instance, Casual Visitors may not stick around long enough to answer their own questions, try engaging them with a slideout on early page visits. The opposite of Casual Visitors, Deeply Engaged Visitors, are probably determined to find that information on their own and would find a popup to be annoying. Splitting the audience keeps both archetypes engaged without accidentally detering anyone.
The Full Set of Out-of-the-box Behavioral Audiences
- Frequent Users: Users who interact with your brand a lot. Definition: Frequency Score > 65.
- Infrequent Users: Users who interact with your brand occasionally. Definition: Frequency Score < 35.
- Deeply Engaged Users: Users who show a lot of activity when they do interact with your brand. Definition: Intensity Score > 75.
- Casual Visitors: Users who show little activity when they do interact with your brand. Definition: Intensity Score < 25.
- Likely To Re-engage: Users likely to come back based on their past activity patterns. Definition: Propensity Score > 75.
- Unlikely To Re-engage: Users not likely to come back based on their past activity patterns. Definition: Propensity Score < 35.
- At Risk Users: Users whose interaction behavior is changing for the worse. Definition: Momentum Score >= 10 and Momentum Score <= 30.
- Binge Users: Users who show a lot of activity when they do interact with your brand. Definition: Frequency Score <= 20 and Intensity Score >= 50.
- Perusers: Users who visit often but rarely interact deeply with your brand. Definition: Frequency Score >= 70 and Intensity Score <= 20.
Lytics Behavioral Audiences
The follow out-of-the-box audiences are prefixed with "Lytics" and can be found in the Audiences list.
- Lytics New: Users who were created within the past 7 days. Definition: _created > "now-7d".
- Lytics Disengaged: Users who show minimal or no activity for a prolonged period of time. Definition: Frequency <= 5 and Intensity = 0 and Momentum = 0 and Quantity <= 3 and _created < "now-7d".
- Lytics Previously Engaged: Users who are currently disengaged with your brand, but had been previously. Definition: Momentum <= 10 and NOT Lytics Disengaged and NOT Lytics New
- Lytics Highly Engaged: Users who engage most frequently and consistently of your users. Definition: Quantity >= 50 and Frequency >= 50 and Intensity >= 25 and Momentum >= 40 and NOT Lytics New and NOT Lytics Previously Engaged.
- Lytics Currently Engaged: Users who are currently engaging with your brand. Definition: Momentum > 10 and NOT Lytics Highly Engaged and NOT Lytics Disengaged.
Taking it further
Remember that each of these out-of-the-box behavioral audiences can be recreated with the audience builder using Lytics scores user fields. Mastering Lytics scores will open up the possibility of new combinations of score thresholds that result in new behavioral audiences to be used as building blocks in campaigns.