BlueConic segments are dynamic groups of customer or visitor profiles characterized by a defined set of interests, preferences, demographic properties, and so forth. Based on how a customer behaves in your channels and the information you have gathered from them via listeners, online forms, links they have followed, what they have clicked, and so forth, you can classify customers, either by using a single filter or a sophisticated set of filters to create multidimensional, real-time customer segments.
Creating dynamic, multidimensional real-time customer segments
Customers and visitors in your online channels can belong to multiple segments, for example under 35 years old, interested in baseball, lives in Boston, referred to your online channel from a specific URL, read your December newsletter, and so forth.
Segmentation is real-time and dynamic, which means BlueConic uses the latest updates of profile property values to determine if a customer falls in a specific segment. Because these segments are not static lists, they do not go out-of-date. Customers fall into and out of segments based on their current profile properties, interests, and engagement.
Multidimensional customer segments in BlueConic
BlueConic customer segments are multidimensional, too. You can filter on several attributes at once, for example, creating a multidimensional customer segment based on CLV (customer lifetime value), interests, age, demographics, and so on.
Behavioral segmentation with BlueConic
Behavioral customer segments place customer profiles into segments based on those customers' interactions with your sites and channels based on recency, frequency, intensity, and momentum. BlueConic's behavioral customer segments are created by default, update in real time, and require no special configuration. You can use these segments for analytics and marketing campaigns.
Prebuilt behavioral segments in BlueConic
Marketing teams can use behavioral segments in combination with existing segments or profile properties to tailor messaging to the right customers at the right time.
Visitors from the past 7 days
Based on the profile property: Recency
Values range from a minimum of 93 (the last visit was 7 days ago) to 100 (visited today). This value is empty for profiles whose last visit was more than 99 days ago.
Use cases: Use the Visitors from the past 7 days segment to target customers who haven't visited in the past week. Re-engage them with fresh messaging.
Highly frequent visitors
Based on the profile property: Frequency
Values range from a minimum of 85 and maximum of 100. This value is empty for profiles that are among the least active in your channels.
Use cases: These customers visit often and clearly enjoy your content or products. Target them with deeper content. Or use the segment to exclude frequent visitors from seeing the same messages on each visit.
Visitors with a high intensity
Based on the profile property: Intensity
Values range from a minimum of 85 to a maximum of 100. This value is empty for profiles with the lowest average intensity in your channels.
Use cases: Combine this segment of high intensity customers with content or product interests to re-connect with this valuable group of customers.
Recently very active visitors
Based on the profile property: Recent intensity
Values range from a minimum of 75 to a maximum of 100. This value is empty for profiles with the lowest recent intensity in your channels.
Use cases: Target lead generation to active visitors who have not supplied an email address -- focusing your lead gen efforts on highly engaged people.
Visitors with high momentum
Based on the profile property: Momentum
Values range from a minimum of 75 to a maximum of 100 (for showing much more activity this week than on average). This value is empty for profiles with lower than average or no activity this week.
Use cases: Customers with high momentum are showing increasing activity on your site over the past 7 days. Send offers or ads to these customers to capitalize on their increased interest and propensity to buy.
Visitors with low momentum
Based on the profile property: Momentum
Values range between a minimum of 0 (inactive in the past 7 days) to 10 (minimal activity over time).
Use cases: Improve your re-engagement campaigns by combining the "low momentum" segment with additional attributes to target and bring customers back to your site.
Customizing behavioral segments
Use the prebuilt segments as the basis for your behavioral marketing campaigns. You can edit the minimum and maximum values to create your own definition for frequency, intensity, activity, and momentum. Select one of the behavioral segments, click its name in the left navigation to view the conditions that define this segment, and edit the score range. By default high intensity is calculated with a minimum of 85 out of 100. To add more profiles to this segment, you can change the minimum value to yield more profiles. Choose Save As to create a new, custom behavioral segment using your scoring thresholds.
Example: Targeting highly active users for whom you don't have an email address
Build a new segment based on the default Recent intensity segment
Add a filter to identify the group of profiles whose Email address profile property is empty.
Use this new segment to target these customers and visitors with ads or messages to ask for their email addresses.
Targeting profiles by group properties
Building customer segments lets you filter through all profiles to reach a targeted set of customer profiles, defined by filters such as profile properties, group properties, and consent objectives. Using groups in BlueConic, you can build segments based on household, company, or account properties (or any type of BlueConic group that you define).
For example, you could build a segment that targets profiles of people who are employed by companies in the software industry in California, who have consented to be contacted via email marketing.
Using date and time filters
If you add a "Date time" profile property as a condition for your segment, various filters display so you can find property values within a range of days, a range of hours, or before/after a certain time of day.
For instance, if you’re looking to determine which profiles last visited your site after February 1, 2024, you can add the “Last visited date” property as a condition and use the provided filters to specify that a profile only belongs to your segment if their last visit was after February 1.
FAQs
How does dynamic real-time segmentation work in BlueConic?
Dynamic segmentation in BlueConic means that the latest updates of profile property values are used to determine if a visitor falls in a specific segment in real time. BlueConic segments are also multidimensional. You can filter on several attributes at once, for example, creating a multidimensional customer segment based on CLV (customer lifetime value), interests, age, demographics, and so on.
How is data loaded when building segments?
To provide the most optimal experience with segmentation—especially if your segments are data-intensive—BlueConic uses a variety of mechanisms to load the available data quickly and accurately on Segment condition pages, including:
Non-blocking loading indicators: Segment filters with large datasets display a loading icon. This doesn't block segment configuration or saving, so you can continue working while data loads in the background.
Delayed load triggering: OR-block and segment profile counts load only after two seconds of inactivity to avoid redundant calculations. A loading indicator appears immediately upon condition changes, but the counts themselves will only update after a two-second pause in editing.
Progressive loading: For properties with many values, Segment conditions load them in blocks of 40 to improve performance. The first 40 appear immediately, and subsequent blocks load as you scroll.
Value limits: Segment condition pages support up to 1,000 values per property. A "Limit of 1000 values reached" message appears when you scroll to the maximum.
Hidden profile counts: For faster loading, you can toggle "View profile counts" to show only property values. Disabling this speeds up data retrieval, especially for large datasets, by omitting profile counts. While enabled (the default), both values and counts are shown. A reminder message appears if loading counts takes longer than three seconds.
Loading configured values: Previously configured values in a Segment condition load first when revisiting the value list, prioritizing quick access for deselection.
Skeleton graphs: For graph-based properties, a skeleton loader indicates loading, but condition configuration remains available.