Customer Lifecycle FAQ

The Lifecycle Report 

How am I supposed to use the Customer Lifecycle report / what is its value?

The purpose of the Customer Lifecycle report is to showcase opportunities that exist in your business to impact the behavior of your guests through Bridg lifecycle marketing, and ultimately have a measurable impact you can measure in revenue. 

To begin, the best opportunities will always be those that represent the largest portions of your customers (New, Active, Lapsing, Lapsed). In 2016, Bridg will be looking towards developing the ability to target more defined segments of customers.

The Customer Lifecycle report can also be used as a reference point for customer-based metrics about your business, such as 1) how many customers your business has 2) what % of your customers were new in a given time period 3) customer frequency. For most brands, these metrics have been accessible only with a loyalty program, and only applicable to the customers within that program. With Bridg, these metrics are available across all of your customers. 

What is a Lifecycle campaign?

A Lifecycle campaign is an email campaign that triggers to a customer based on where they are in their lifecycle. The phases of the customer lifecycle include New, Active, Lapsing and Lost, and customers are sorted into each segment daily based on how they’re transacting. Once they move into a given segment, a lifecycle campaign triggers to them automatically.

In Bridg, customers are segmented based on their individual purchase behavior, rather than global rules (such as "anyone who hasn’t come in 30 days"). For example, a customer who typically visits once per week will be identified by our system as lapsing much sooner than someone who typically transacts once per month. This makes segmentation more accurate, and the triggered messaging more likely to be relevant.

How does Bridg identify customers in my data?

Bridg uses a combination of unique identifiers present in your POS data to identify unique customers above a certain confidence threshold. Once a customer is identified, their purchase behavior is tracked moving forward, so we are able to track their movements in and out of Lapsing, Lapsed, Active, etc. 

How does Bridg handle cash transactions?

This is proprietary technology, but our data scientists have developed complex models of how customers transact in cash that allow us to give you the most accurate picture of your customers' transactions as possible. These models are refined regularly.

Sub-segments

What are Repeat Customers? Should I care about them? 

Repeat customers are those that transacted during the selected time period (such as Q1 2016), who had transacted previously as well. They are returning customers, rather than customers who visited for the first time. 

Repeat customers are not a segment you will target with Lifecycle campaigns, however. Rather, Bridg enables you to target customers based on their unique purchase behavior (whether they're Active, Lapsing, or Lapsed), regardless of whether they transacted last year or not. However, Repeat Customers are a distinct segment of people - when you add them to New Customers, you get the total number of customers who visited during the selected time period. 

The totals in the sub-segments do not add up to the totals at the top. Why?

Customers we’ve identified via credit card transactions are sorted into the segments first. Then, cash transactions are distributed across the various customer segments and associated with a certain number of customers based on our data models of cash transaction.

The distribution is done at the top-line separately from the sub-segments, causing a slight difference in the total number of customers. However, this difference is merely the result of data modeling being done in two separate instances. Since the cash customers are not unique customers you will be messaging, and intended only to provide a high level picture of how customers are distributed across segments, we've maintained the report in this form.

The frequency of each frequency band is higher than it should be. Why?

Same reason as above. Customers identified in credit card transactions are sorted into segments first, based on the criteria (1 visit, 2 visit). We then associate a given amount of cash transactions with both credit card customers and additional cash-only customers we believe they represent. These additional cash transactions increase the average frequency of the customers in each segment.  

Bridg Data Sync

The numbers in my report look different today than yesterday. Why is that?

Our agent is designed to update existing data in our system based on changes made to the grind files on the BOH machine. If files are removed / updated that we’ve pulled previously, our agent will re-pull those files and adjust the report accordingly.

 

 

 

 

 

 

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