Segment builder features

4 Apr ‘17

Our system receives data from various sources: order data from the back end, behavioural data from the tracker, messaging data, and call centre data.

Here’s what you can do with this data right in the admin panel:

  • individual customer information
  • available filters and segments
  • interesting use cases

Customer view

Personal information

  • Personal data
  • Contact info
  • Subscriptions
  • Additional info

Each client creates their own fields for additional info. For example, this might include bonus programme status or number of children.

You can set up the fields via the interface without a developer.

User list

The «Actions» tab shows customer behaviour

  • User activity: visiting the site, placing an order, opening a message
  • Customer-relations activity: sending a message or delivering an order

You see:

  1. Activity description
  2. Activity date
  3. Activity point of contact

Every type of activity has detailed information available:

  • orders – products, quantity and status
  • messages – link to template
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Here, we can see that a message was sent first, then the user visited the site and placed an order.Every type of activity has detailed information available: for example, here’s what you can see for an order.

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Customer and activity filters

Personal data

  • Standard
    • email
    • age
    • city
    • region
    • zone
    • birth date
    • birthday
    • gender
    • mobile number
    • first name
    • middle name
    • last name
    • map
  • Additional
    • common first name typos
    • common last name typos
    • birthBonusCount
    • welcome points balance

Current status

  • segment
  • time in segment
  • test
  • subscriptions
  • blocked
  • deleted
  • campaign participation

Technical

  • ID
  • external ID
  • suitable triggers
  • campaign notifications

Behaviour – aggregates

  • average check
  • sum of orders
  • change in balance
  • current balance
  • retail orders
  • promo code
Search for users
Search for users whose email address contains @mail and who have their name in the system
Search for customers
Search for customers with common name typos
Search for customers with an additional field
Search for customers with an additional field filled in and a valid mobile number
Search for customers with subscriptions or who have deleted their profiles
Search for customers with subscriptions or who have deleted their profiles
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Filters can be combined as needed, for example to send messages
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Search for customers with average checks of 5,000-7,000 in January
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Behaviour – activity

When

  • time period
  • time since activity date
  • time since current date

Where

  • brand
  • channel/point of contact
  • session

What

  • balance change
  • retail order
  • link click
  • template action
  • email status
  • SMS status

Who

  • customer

Additional info

  • varies by customer
  • activity based
  • product-category based
  • product based
  • database entry source
  • first in category
  • last in category

Technical

  • ID
  • staff
  • importing and editing
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Search for site visits from social media channel
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Search for orders delivered in past 15 days
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Search for number of activities from mobile devices
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Search for number of activities with a particular product

Real-life use cases

Build a segment and view reports

An RFM segment has been set up on the «Customers» page, consisting of two independent segments:

  • one searches for customers with more than 2 retail orders
  • the other filters for retail orders placed in the past 120 days

Here, in the «Reports» section, we can generate a segment trends report summarising customer growth and order quantity.

 Sample RFM segment

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Segment trends report

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Compare segments to find insights

The system has an area dedicated to segment reporting.

For example, we can compare the average check in the main group and control group segments.

The main group received messages, but not the control group. We can see that there are fewer customers from the main group with no orders than in the control group.

Or, for example, we can compare the number of purchases made by iOS vs Android users. In this case, iOS users are not as loyal to the shop.

There are significantly fewer customers with no purchases in the main group than in the control group

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Do customers using iOS devices buy less in this shop than Android users?

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Set up campaigns with complex conditions

We can work with the most diverse trigger requirements.

Here, we’re limiting the trigger to individual product categories by price, and sending emails only to particular addresses.

Here’s an example of an unusual abandoned cart trigger

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List of products for the trigger
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Choosing a segment for manual messages

Simple and complex segments can be used for messages: you can limit to subscribers or set up a more complex message list.

For example, you can choose customers based on their interests without using special limits. Then you can build a report and compare message results.

Here’s a sample of message filters

By interest

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Standard
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«Message comparison» report in graph format
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«Message profitability» report in Excel format
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