1. Introduction

Definition

"Analytics within the offer" is a built-in report inside a specific offer card in Leeloo.AI that shows aggregated metrics for that offer over a selected period: amount of orders, rejections, purchase requests, returns, views, and sales. The section gives the B2B operator a single view of "what is happening to this particular offer".

Offer analytics primarily belongs to the Analyze stage of the customer lifecycle — it is a read-only consumer module that reads from Orders & Sales, Client's Card, and event tracking, but does not write back. Additionally, the metrics it surfaces feed decisions made at the Convert stage — how effectively the offer closes payment.

Architecturally, it is a widget inside the Offer entity in the Sales Tunnels → Offers module. The widget reads views, buy_request, order_paid, refund, and order_rejected events and aggregates them across the selected time interval.

The B2B operator (product manager, marketer, sales team) uses analytics to quickly understand the state of a specific offer: are there enough views for current sales, what's the request-to-payment conversion, what's the refund share. The operator picks a time period and compares periods to evaluate trends.

The B2C customer does not interact with analytics directly — they don't even see it. However, every action they take (viewing the card, clicking "Buy", successful payment, initiating a refund) automatically becomes a data point in this report.

Analytics does not write to the Client's Card, but it actively reads orders of specific clients from there and aggregates them into a per-offer picture. This is a textbook example of a read-only consumer module in the Leeloo.AI architecture.

After reading you will understand:

• where to find the analytics of a specific offer in the platform UI;

• which metrics the report shows and what they mean;

• how to set an arbitrary time period for viewing;

• how to use analytics to evaluate the effectiveness of an offer;

• which lifecycle stages this section is tied to and which modules it reads from.

Purpose

Offer analytics solves the "give me a quick slice for this specific offer" task — without building a separate report in the global Analytics or Dashboard module. It is a hypothesis-testing tool: launch an offer, come back in a day or two, open its analytics, look at conversion.

At the Analyze stage the section gives the operator an aggregated picture of a specific offer's performance: how many opens, how many "Buy" clicks, how many successful payments, how many refunds. All numbers are presented as sums and counts sliced by the chosen time period. Job — turn raw events into legible KPIs at the level of a single offer.

At the Convert stage analytics helps the operator decide the fate of the offer: if the view-to-payment conversion is low — reconsider the offer, price, page; if refunds are above norm — investigate product quality or expectations setting. Job — close the "launch → measure → improve" loop within a single offer.

2. Overview of the "Analytics" section

Analytics is opened from a specific offer card. The section contains a metrics block (amount of orders, rejections, purchase requests, returns, views, sales), a time-period selector, and trend charts.

2.1. How to open offer analytics

To get more detailed information about a previously created offer you can use the "Analytics" section on the corresponding offer page. To get to the section:

1. Go to the "Sales Tunnels" section;

2. Select the "Offers" subsection;

3. Click on the offer you are interested in.

After going to the page of the required offer you can view the analytics for it — the section opens right inside the card.

2.2. Which metrics are displayed

This tab contains the following data:

• Amount of orders — total for successfully paid orders within the period;

• Rejections — number of checkouts that the client started but didn't complete;

• Purchase requests — clicks on the "Buy" button;

• Returns — count and amount of refunds;

• Views — number of times the offer card was shown;

• Sales — number of successfully paid orders.

Every metric is sliced by the selected time interval and can be compared period over period.

2.3. Setting the time period

You can also set the required time period for which information is needed. This lets you analyze the offer at different horizons: day, week, month, quarter, custom range. Comparing periods makes it easy to spot trends and anomalies.

Related instructions

Key terms