Consumer Analytics

Features

Integrations

Glossary

Partner

The name of the Brand or Merchant configured in Ignite by Acorn-i.

Vendor

A Vendor in Ignite refers to the business entity and technology provider that facilitates advertising or commerce. This encompasses two main types of providers:

• Marketplaces/Direct-to-Consumer Websites: These are the retail platforms where products are sold and tracked (e.g., Amazon.com, Walmart.com). They provide the commerce data (orders, sales) that Ignite attributes to advertising.
• AdTech Platforms: These are the advertising technology systems through which campaigns are executed and media is purchased (e.g., Amazon DSP, Google Ads, Meta Ads).

Vendor Subtype

The Vendor Subtype column is applicable for Amazon as they offer a range of services that suit different needs of Agencies and Brands. For example, the split between Amazon Seller Central and Amazon Vendor Central.

Channel

Channel is a composite data point within Ignite that uniquely identifies the combination of a specific Vendor and its corresponding Market. It provides a granular classification of where advertising spend is being allocated and where sales are being driven. This field allows for distinct analysis of performance across different platforms and their respective locales.

• Format: Typically represented as ‘[Vendor Name] [ISO Country Code]’.
• Examples: “Amazon DE” (representing Amazon’s platforms in Germany), “Google GB” (Google Ads activity in Great Britain), “Walmart Seller US” (Walmart Connect activity in the United States).

Understanding the Channel is vital for optimizing localized campaigns and products to compare performance across AdTech and retail integrations.

Market

Market defines the specific geographical region or country where advertising activities and sales are occurring. It is represented by a two-letter ISO Country Code (e.g., “US” for United States, “GB” for Great Britain, “DE” for Germany). This data point is essential for segmenting performance based on locale, accounting for regional consumer behaviour, currency differences, and market-specific advertising strategies.

Buyer Type

This data point segments customers based on the number of purchases they have made over their lifetime.

• Single Buyer: A customer who has made only one purchase with your business.
• Multi-Buyer: A customer who has made two or more purchases with your business.

Customer Type

This data point classifies a user’s relationship with Ignite based on their account and purchase history.

• New Customer: A user who has registered with Ignite but has not yet made a purchase or subscribed to a paid plan.
• Existing Customer: A user who has made at least one purchase or is a current subscriber. This classification includes both active and inactive customers.
• Anonymous: A user who is interacting with the application or website without being logged in or having an identifiable account.

Customer Acquisition Date

This data point shows the specific month, quarter or year that the customer was acquired by the business, based on their first purchase.

Customer Acquisition Brand

When your business is multi-brand, this data point shows which Brand drove the initial customer acquisition. It’s used to identify which of your brands are most effective at bringing in new customers.

Customer Acquisition Promotion

This data point indicates the promotion code that the customer used when placing their first order, allowing you to track which promotions are most effective for attracting new customers.

Example: You can analyse which acquisition promotion code, such as “WELCOME25”, brought in the most new customers.

Customer Acquisition Product Line

This data point categorises new customers based on the Product Line they first purchased from. It helps you understand which of your core product groups are most effective as a gateway for new customer acquisition.

Customer Acquisition Product Action

This data point shows the specific Product Action associated with a customer’s first purchase. Since this is an optional free text field, it’s particularly useful for advanced reporting and for grouping products around a common usage that led to an acquisition.

Customer Acquisition Product Packaging

This data point segments newly acquired customers by the Product Packaging of their first purchase—whether it was a single unit or a multi-pack. This helps you understand which packaging strategy is most successful at attracting first-time buyers.

Customer Acquisition Product Size

This data point allows you to analyse which Product Size led to a new customer’s first purchase. It provides insight into whether smaller, larger, or standard-sized products are more effective at bringing in new business.

Customer Acquisition Product Range

This data point provides a high-level view of which Product Range a customer’s first purchase belongs to. It allows you to see the overall effectiveness of your entire product portfolio in attracting new users.

Customer Acquisition Product Type

This data point classifies new customers by the broad Product Type they first purchased. It’s a fundamental way to understand which categories of your business are the strongest at customer acquisition.

Recency Band

This data point categorizes customers based on how recently they made their last purchase. It’s a key indicator of their current engagement level with your product or service.

• Active: A customer who has made a purchase very recently (e.g., within the last 30 days).
• Inactive: A customer who has not made a purchase in a while but is not yet considered “lapsing” (e.g., in the last 60-180 days).
• Lapsing: A customer who is showing a significant drop in activity and is at risk of churning (e.g., they haven’t purchased in the last 180-365 days).
• Lost: A customer who has not made a purchase in a very long time (e.g., over a year).

Frequency Band

This data point classifies customers by how often they make purchases within a defined period.

• Prospect: A user who has not yet made a purchase.
• Repeat Buyer: A customer who has made a second purchase after their initial one.
• Frequent Buyer: A customer who makes purchases on a regular basis.
• Loyal: The most frequent buyers who demonstrate a strong, ongoing commitment to your brand.

Value Band

This data point segments customers based on the total amount of money they have spent.

• Lowest Spenders: The bottom tier of customers by total spend.
• Average Spenders: Customers who fall within the middle range of spending.
• High Spenders: The customers who spend well above average.
• Top Spenders: The highest-spending customers.

Behavioural Segment

The Behavioural Segment data point combines a customer’s Recency, Frequency, and Monetary value to provide a clear description of their behaviour. This helps you quickly understand and target different groups of customers.

New-to-Brand Customers

These customers have recently engaged with your brand and are still considered “new.”

• Single Buyer: A new customer who has placed only one order.
• Multi Buyer: A new customer who has placed two or more orders.

Loyal Customers

These are your best customers, actively purchasing from your brand.

• Potentially Loyal: A customer who is starting to regularly purchase from you, with an active recency and a medium monetary value. They are on their way to becoming a top customer.
• Loyal: A customer who consistently purchases from you and has a high monetary value. They are not yet your top-tier customer but are highly valuable to your brand.
• Champion: Your highest-value customers. They purchase frequently, have an active recency, and have the highest monetary value.

At-Risk & Lost Customers

These customers have stopped purchasing and are at risk of being lost, or are already gone.

• Lapsing Customer: A customer who has stopped purchasing and has an inactive recency band. They were not previously a high-value customer.
• Lapsing Champion: A high-value customer who has stopped purchasing. They have an inactive recency band, meaning they haven’t placed an order in a while.
• Lost Customer: A customer you’ve lost for an extended period. They have a lapsing or lost recency band, indicating no recent purchases.
• Lost Champion: A former high-value customer who has not purchased from you for a long time. They have a lapsing or lost recency band.

Customers

The total count of unique customers in your database. This metric gives you a snapshot of your entire customer base, regardless of whether they have made a recent purchase. It’s a foundational number for understanding the scale of your audience.

Buyers

The Number of Buyers calculation will return the unique number of customers who placed orders during the selected date range. A Buyer is a Customer who placed an order during a chosen time frame. Lastly, a Buyer is unique to a particular Channel.

Buyer Rate

This is the pulse check of your customer engagement. The Buyer Rate is the percentage of your existing customer base that actively bought from you during the selected time frame. It’s an essential metric for measuring how effective your retention efforts are.

$$Buyer Rate = \frac{Buyers}{Number\; Existing\; of\; Customers} \times 100$$

Lifetime Orders

The total number of orders placed by a single customer segment over their entire purchasing history. This metric helps you understand a customer segment’s purchasing habits from the very beginning.

Lifetime Units Purchased

The total number of individual items or units a single customer segment has bought across their entire purchasing history. For example, if a customer buys two T-shirts in one order and a pair of trousers in another, their lifetime units purchased is three.

Lifetime Value

The total revenue generated by a single customer segment over their entire relationship with your business. This is a crucial metric for understanding the long-term profitability of your customer segments. A simple way to think about it is the sum of all money a customer segment has spent with you.

Average Customer Recency

The average number of days since each customer’s last purchase. The lower the number, the more recently your customer base has been making purchases, which is a good indicator of health and engagement. This metric helps you identify customers who may be at risk of churning.

Average Customer Frequency

The average number of orders each customer has placed over their lifetime. This metric is a measure of customer loyalty and engagement. A higher frequency indicates a more active customer base.

Average Customer Value

The average amount of money each customer has spent over their entire relationship with your business. It is calculated by dividing the total revenue from all customers by the total number of customers. This metric helps you understand the typical spend of a customer in your database.