Profile properties are where the BlueConic customer data platform stores information on your customers or visitors. For example, if a user subscribes to a newsletter, the email address is stored in the profile. Many profile properties record information about the user or visitor (email address, interests, city, products bought, etc.).
How do I collect behavioral customer data?
In addition to profile properties you explicitly create and collect, BlueConic also observes users' behavior and stores that information in real time in behavioral profile properties that assign numerical values to your customers' behavior on your site. These values track how frequently customers are active on your site, their level of activity, the intensity of their visits, and relative increase or decrease in activity (momentum scores). Behavioral scores range from 0 to 100, making it easy to compare profiles on the same scale.
How do behavioral profile properties differ from regular profile properties?
Behavioral profile properties are distinctive in several ways:
- They update in real time.
- They compare the entire population of visitors.
- They automatically change over time--even if the visitor is offline.
- Scores are calculated at the start of each visit and remain the same during that visit.
Data is collected by the Global Listener, which tracks contact moments, such as website visits. You can inspect or visualize the behavioral scores for an individual profile by selecting Profiles from the main BlueConic menu and choosing a profile to view.
How do marketers use behavioral profile properties?
Marketing teams can use behavioral profile properties and related segments for targeting, messaging, lead generation, and re-engagement campaigns. See the use case ideas for each profile property below and also Using real-time behavioral customer data.
To see behavioral profile properties for your profiles, select Profiles from the BlueConic menu and select the Profile overview tab.
Real-time behavioral profile properties
The Recency profile property measures how active a customer has been on your site lately, with a score of 100 for profiles active on your site today, ranging to 0 for profiles whose last activity was 100 days or more. A profile with a recency score of 80 was last active on your site 20 days ago.
Marketing teams use the recency score to:
- Identify active users with high scores who might respond to offers.
- Re-engage users who have low scores for recency, inviting them back with custom offers or discounts.
- Re-activate users who haven't visited recently by sending email or mobile communications.
Recency scores are updated after the current visit.
Prebuilt behavioral segment: BlueConic provides a prebuilt "Visitors from the past 7 days" segment based on the recency score. It includes all profiles with a recency score of 93 or higher. See Behavioral customer segments for details.
The frequency score shows how often a customer visits your site. Marketing teams use this information to customize messaging:
- Is a certain customer already a high scorer? Elevate the conversation to a call center.
- For customers who are not so active, use an email campaign to restart the conversation.
Prebuilt behavioral segment: BlueConic uses this score as the basis for a prebuilt "Highly frequent visitors" segment. It includes all profiles with a frequency score of 85 or higher. See Behavioral customer segments for details.
The intensity score measures how intense the customer's interactions are on your site (i.e. the average number of page views per visit).
Marketing teams use this information to customize content and product content:
- High scores identify customers who enjoy in-depth content (lots of page views), so deliver more content to this group.
- Cross the list of highly intense visitors with those who have not yet supplied an email address, and spur them to action with a CTA tied to their interests.
- Low intensity scores point to customers who consume content in smaller doses.
- With content metering, lower intensity might show customers hitting a paywall.
Prebuilt behavioral segment: BlueConic uses the intensity score to create a prebuilt segment for "Highly intense visitors." It includes all profiles with an intensity level score of 85 or higher. See Behavioral customer segments for details.
Behavioral: Recent intensity
The recent intensity profile property shows the amount of a customer's recent activity on your site over the past 30 days. This value decays over time, so after 72 days the value is half of what it was.
Marketing teams use this information to customize messaging:
- Customers with high recent intensity scores are increasing their interaction with your site, you can devise offers and messages to encourage them to buy, subscribe, or take the next step down the marketing funnel.
- If a customer is suddenly less active than usual, send an email or message to re-ignite interest and activity.
Prebuilt behavioral segment: BlueConic uses the intensity score to create a prebuilt segment for "Recently very intense visitors." It includes all profiles with a recent intensity level of 75 or higher. See Behavioral customer segments for details.
The momentum score compares a customer's past 7 days of activity with the same person's average 7 days of activity. Momentum scores range from 0 (this profile has visited far less this week than usual) to 100 (this profile has had much more contact with your site in the past 7 days). For example, if someone typically visits your site 5 times per week, but increases their activity to have 20 different contacts this week, their momentum score would be 95.
Momentum scores are valuable clues to determine whether a customer is trending toward more engagement or less:
- A sudden increase in momentum might signal a propensity to buy or engage. You may want to target these users with special offers
- You can use this score to target low-momentum customers with a re-engagement campaign that reaches out to visitors who've been inactive for the past week.
Prebuilt behavioral segment: BlueConic uses momentum scores to build two prebuilt customer segments: "Visitors with high momentum" (momentum scores over 75) and "Visitors with low momentum" (momentum scores under 10). See Behavioral customer segments for details on these segments.
- Marketing use cases: See Using real-time behavioral customer data for ideas for behavioral targeting and messaging.
- Segmenting customers based on behavioral data: BlueConic provides prebuilt six behavioral segments based on the behavioral profile properties. See Behavioral customer segments for details on using these segments to reach your marketing goals.
Calculating behavioral profile property values
This section provides details and formulas for how BlueConic calculates the values stored in the five behavioral profile properties: activity, frequency, intensity, recent intensity, and momentum.
All scores are calculated at the start of each visit (20 minutes of inactivity) and remain the same during that visit. For example, if the visitor pays three visits to your channels in a single day, then the score of the behavioral profile properties will be re-calculated three times for that visitor.
The "Frequency," "Intensity," and "Recent intensity" properties compare the visitors behavioral scores to the scores of all other visitors to your channels. To avoid clutter by outliers, the top 5% of highest scoring visitors will be ignored. The highest value that is left after removing the top 5% of individuals, sets the mark for the 100-index value. This recalibration is done once per day.
Recency indicates the number of days since the visitor was last active. This value is 100 if the visitor has been active today, 99 for yesterday, 98 for two days ago, and so on. This value is 0 if the visitor has been inactive for 99 days or more.
|Minimum||0||Active 99 days ago or more|
Recency = 100 - dlv
dlv = Number of days since the last visit
Frequency provides a ranking from 0 to 100 for the average number of visits this person made per day from the first visit until today. All individual profiles in your universe are considered (leaving out the top 5% of outliers). Visitors with the highest average in your universe receive a frequency value of 100. The value is 0 for visitors with an average of (nearly) 0 visits per day from their first visit date.
|Maximum||100||Among the most frequent visitors in the universe|
|Minimum||0||Among the least frequent visitors in the universe|
Frequency = (v * 100) / (dfv * fmax)
v = Total number of visits
dfv = Number of days since the first visit
fmax = Highest daily frequency of all visitors, ignoring the top 5% of values
Intensity indicates the average number of page views per visit from the person's first visit until today. This value is 100 for visitors with the highest intensity average since their first visit in your universe, leaving out the top 5% of outliers. This value is 0 for visitors with an average intensity of (almost) 0 per day since their first visit.
|Maximum||100||Among the visitors with the highest average intensity|
|Minimum||0||Among the visitors with the lowest average intensity|
in = round((pn / pmax) * 10)
Overall Intensity = (100 * Σ i1..n) / (dfv * imax)
in = Intensity of single visit n
imax = Highest daily intensity of all visitors, ignoring the top 5% of values
pn = Number of pageviews for visit n
pmax = Highest number of pageviews of all visitors, ignoring the top 5% of values
Σ i1..n = Sum of all single visit intensities
dfv = Number of days since the first visit
Index for the recent intensity (amount of activity during one visit) of the visitor. The impact of an activity on the value will decrease over time. This value is 100 for visitors with the highest recent intensity in your universe. This value is 0 for visitors with a recent intensity of (almost) 0.
|Maximum||100||Among the visitors with the highest recent intensity|
|Minimum||0||Among the visitors with the lowest recent intensity|
The formula for recent intensity is basically the same as for intensity (shown above), with one difference: the value of the intensity per visit (in) decays over time. Every 72 days, the value will be the half of what it was. For example, if the intensity of a visit was 8 on the day of the visit, it will be 4 after 72 days, and 2 after 144 days.
Momentum considers the past 7 days of a visitor's activity and compares it to the average 7-day activity of that visitor in all time. The value is 50 when the last 7 days' activity is the same as the average. If there is more activity than the average, the value will be higher, with a maximum of 100. If there is less activity than average, the value is lower, with a minimum of 0.
|Maximum||100||Much more active this week than usual|
|Average||50||Same level of activity as usual|
|Minimum||0||No activity at all, or much less active this week than usual|
IF first visit date is less than 7 days ago
THEN momentum = 50
IF number of visits in last 7 days is 0
THEN momentum = 0
IF number of visits per day since the first visit is greater than or equal to that of the last 7 days
THEN momentum = (vf / vw) * 50
IF number of visits per day since the first visit is lower than that of the last 7 days
THEN momentum = 100 – (vf / vw) * 50
vw = Number of visits per day in the last 7 days
vf = Number of visits per days since the first visit
- A new visitor had 3 contacts since the first visit 6 days ago; their momentum is 50.
- An inactive visitor had 0 contacts in last 7 days and has 0.12 visits per day since the first visit; their momentum equals 0.
- A visitor with decreased momentum has 2 visits per day since first visit and 1 visit per day over the last 7 days; their momentum is: (1 / 2) * 50 = 25.
- A visitor with increased momentum has 0.5 visits per day since first visit and 1 visit per day over the last 7 days; their momentum value will be: 100 – (0.5 / 1) * 50 = 75.
Managing privacy, consent, and behavioral profile properties
With the privacy legislations GDPR and CCPA in mind, it's possible to disable the collection and calculation of the behavioral profile properties. The data needed for these properties is provided by the Global Listener, so consent for these behavioral profile properties is tied to the Global Listener.
You can enable consent management for behavioral profile properties by adding the Global Listener to a BlueConic marketing objective that has consent management enabled. Once this is enabled, the profile properties will only be available for profiles that have given consent to the objective.
Learn more about using BlueConic objectives to manage customer privacy and consent for GDPR and CCPA.