The new customer insights dashboard replaces the customer health dashboard that was previously found in the "customer" tab.

This dashboard provides marketers with metrics and tools to classify and analyse their customer base, highlighting their common behaviors and evolution. The key objective of this dashboard is to find new opportunities and/or find insight that helps marketers optimise existing marketing campaigns.

Customer snapshot panel (all time)

The first panel gives an overview of your entire database by grouping contacts into several buckets.

  • Lifecycle stage - based on at risk / lapsed segments
  • Frequency -  based on number of orders:
    1 time: 1 order
    Repeat: 2 orders
    Loyal: 3 - 4 orders
    VIP: >4 orders
  • Customer value - we calculate the average AOV for all customers and then bucket them into:
    Low: < 0.75 * avg_aov
    Medium: 0.75 - 1.25 * avg_aov
    High: 1.25 - 2.5 * avg_aov
    Very High: >  2.5 * avg_aov
  • Email Engagement

The email engagement bands displayed in the Customer insights dashboard and available as customer filters in the segment explorer are now updated so they are based on lower and upper threshold factors applied to a per account average.Thresholds are set based upon 0.5 and 1.5 factors.

Important: We calculate a contact specific email engagement score based on all deliveries, opens and clicks per contact in a set window of 180 days. Age weights are applied to the score so more recent contact events have a greater weighting than older events.

Important: If a contact has not received the minimum number of events in the time window a per account specific average is proportionally applied to ensure contacts who have not had the opportunity to engage are not defined as unengaged. For example, if a contact has not been targeted in any recent campaigns this will not disproportionately impact their score.

This populates a table with NULL, -1, 0, 1, 2 or 3 values for no data, new customers, not engaged, low, medium and high respectively.

  • Null: no data
  • No engagement: Score of 0
  • Low: Score < (0.5 * average)
  • Medium: Score between 0.5 * average
  • High: Score > (1.5 * average)
  • New: contacts that have subscribed in the last 4 weeks and that have not interacted with (opened or clicked) an email. Once those people start interacting they are moved to their respective interaction bucket.

The drop-down let you choose whether you want to see the numbers based on contacts or revenue. For example, if you choose "total revenue" the numbers will represent CLV and the percentages will indicate how much each segment represents of the total value.

If the user wants more insight into each bucket they can click on "show breakdown" to get more detail into each segment and various metrics. For example, the user can see number of on time and repeat customers as well as AOV and CLV for each segment.

Dimension matrix panel (all time)

This panel enables you to get quick insight into potential opportunities by overlaying different customer dimensions. The table displays the number of contacts and the percentage of each quadrant based on the two selected dimensions.

Here are some use cases:

  • Lifecycle status + email engagement: see which leads have medium or high engagement and try and get them over the line by adjusting your automation or broadcast campaigns.
  • Lifecycle status + email engagement: see which at risk and/or lapsed customers have medium or high engagement and try save them or win them back by offering additional incentives.
  • Frequency + customer value: highlight VVIPs by looking at customers which are in the high / very high and loyal / very loyal quadrants.
  • Lifecycle status + customer value: see how many of your customers are at risk or lapsed that have a high or very high customer value, and create a strategy to win them back via automation or broadcast campaigns.

Important: you can click on any quadrant and this will take you to the segment explorer, where you can save that quadrant as a segment. However, all these segments and dimensions are also available in the customer filter to avoid creating additional segments.

New vs returning customers (date filter)

This panel gives you a quick overview of your new vs returning customers as well as lapsed customers.

New = anyone that placed their first order in that month. Please note that a new customer can place more than one order in the same month and still be considered as new.

Returning = any customer that repeated but was not new (all repeat customers - new customers). 

Lapsed = anyone that has "lapsed" that month depending on your account definition.

Important: these are mutually exclusive.

Customer events (date filter)

This panel provides insight into what events lead to specific customer actions. There are five key metrics: 

  • Unique customers
  • Customers gained
  • Customers who placed a second order
  • Customers won back
  • Customer saved

For each metric, there is a table which can be grouped by products, product attributes, categories, gender, campaigns, sources and coupon codes. You can also filter the table by store - please note that the store filter  does not apply to the KPIs / graph above the table.

Here are some use cases:

  • See which campaigns and/or what product attributes or categories help convert leads into customers
  • See which campaigns and/or what product attributes or categories drive 2nd time buyers
  • See what product attributes or categories save or win back lapsed customers
  • See if you welcome campaign is successfully converting leads into customers
  • See if your at-risk and/or winback campaigns are successfully saving customers
  • See which product to promote in your newsletter campaign depending on specific goals.