Journeys Analysis
The Journeys sheet gives insights into how users are getting to content, whether they are making decisive journeys in the UI or taking their time to browse. This categorization of journeys enables the operator to identify patterns of discovery for content across different devices, genres, and session types.
Here we analyse the efficacy of delivering users to content across different menu screens and content swimlanes in the user interface. We also look at search behaviour. The Search table calls out the number of searches for specific content and also which ones led to a viewing session on either Live or VOD.
On the Features sheet, individual application features can be analysed to see how often and for how long each feature is used per household. These insights can be used to help identify which features are actually leading to a change in viewing for different devices and content genres.
Metrics Overview
We have defined a journey as the series of interactions between two viewing sessions or to a viewing session from standby. Since no two people get to a channel in an identical fashion, we have classified all journeys into five categories, based on journey duration and number of UI interactions. With these two parameters, we have defined five journey types:
Decisive journeys - These are short, direct journeys to content that indicate an intent of appointment to view.
Opportunity journeys - These are longer direct journeys. These represent an opportunity to improve our UI since they also indicate an appointment to view.
Browsing journeys - These are long journeys. Users are taking time and browsing through the content catalogue to get to these. We typically see this is very high for Movie viewing.
Binge Watch journeys - These are journeys with no interaction and users continue watching the next asset in a VOD boxset or playlist, typical of binge-watching
Passive journeys - These are Live content only journeys that typically start from standby and have very few steps. These journeys demonstrate minimal use of the UI.
Additional metrics and insights include:
Metric | Description |
|---|---|
App usage trends | % of users who use the app to view content Ratio of browsing to viewing time Allows operator to understand app-level drop-off rates Returning versus new users – (Daily trend) - Captures the impact of marketing, social media activities, other promotions |
Usage sessions | Understand the stickiness of the content proposition Average duration off a single session/ Median of the typical number of daily usage sessions |
Feature Performance Metrics | Evaluate the reach of a feature within the active base Understand the frequency of usage that this feature is generating Understand the impact on content conversion and engagement it is having |
Purchase Conversion Metrics | Identify the top content purchases Identify the journeys that led to purchases (recommendations, searches, social media Identify cart abandonment scenarios and drill down more into causes (also include other purchase errors) Highlight the areas for better purchase conversion |
