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Harnessing the Power of Data in Live Commerce: ‘Live Data Insight’ of Shoplive

December 28, 2023
In today's rapidly evolving e-commerce landscape, data has become essential for strategic decision-making. Understanding the needs, Shoplive has integrated live streaming with advanced real-time data analytics. This integration transforms e-commerce into a data-driven field, crucial for understanding customer behavior, forecasting market trends, and creating personalized shopping experiences.
Shoplive Data Insight Example
Establishing Effective Marketing Strategies Using Live Streaming Data

Shoplive's 'Live Data Insight' feature allows for a variety of analyses, such as identifying the most popular products during the stream and moments of increased interaction, by real-time tracking of all viewer activities (likes, comments, product clicks, coupon downloads, etc.). The possibilities for utilizing analyzed data are endless. Based on this data, future content can be custom planned/produced, inventory adjusted, and various marketing strategies such as curation, push notifications, and special promotions can be developed to increase sales and satisfy users.

Company A effectively leveraged Shoplive's 'Live Data Insight' to conduct in-depth analyses and optimization of user activities and traffic across multiple marketing channels. As a result, they achieved a 25% cost reduction in their next live streaming campaign compared to the first. This case clearly demonstrates how Shoplive's effective live commerce solutions and data-driven optimization strategies can contribute to the marketing success of our clients.

Exploring the Live Data Insight Dashboard

You can find detailed information and explanations about the data in the dashboard from the 'Shoplive Data Insight Example' image above here.

A. View Data: Metrics for Audience Data and Live Stream Popularity Analysis
  1. Page Views

    This is the fundamental data that shows how many times the live stream was viewed. (Note: Previews of the live stream before entering the player are not included in this metric)
  2. Total viewers / Total login viewers / Peak concurrent viewers

    'Total viewers' represents the total number of logged-in/non-logged in users, while 'Total login viewers' refers to users who have accessed through an authentication process. Comparing these two data sets allows for analysis of the ratio between users with and without existing membership information. 'Peak concurrent viewers' indicates the maximum number of users watching simultaneously.
  3. New login users

    This metric represents users who are either non-members signing up and logging in for the first time or existing members watching the live stream for the first time. It helps to gauge the influx of new members and users returning from long inactivity (such as dormant accounts).
  4. Total viewing time / Average viewing time

    Viewing time is a crucial metric for measuring the success of a live stream. Since the longer users watch the live stream, the more likely they are to engage (e.g., increased purchases, participation), monitoring viewing time helps in planning future live streams and discussing potential improvements and direction.

B. Activity Data: Metrics for Analyzing User Participation in Live Stream
  1. Likes / Number of viewers that clicked Like / Average number of Likes

    'Likes' are a primary metric measuring public reaction to content. Beyond just gauging reactions, Shoplive's 'Live Data Insight' allows real-time tracking of specific moments in the live stream that generate the most likes. Brands/businesses can use this data to plan future live streams, gaining insights into which segments received positive reactions and effectively engaged viewers.

    Moreover, when repurposing live stream into shortform content, analyzing the movement of high 'Likes' counts and various viewer activity metrics collected during the live stream can be used to automatically create content that is more likely to attract user interest.

  2. Chats / Chat viewers/ Average number of chats

    'Chats' is an indicator of user participation in the live stream and the only avenue for brands/businesses to communicate with users during the live. Data on chat allows real-time monitoring of interest and interaction levels with the content during the live stream.

    Additionally, chat data, including 'All chats', 'Highlighted chats', and 'Filtered chats', can be downloaded as individual files for post-event analysis of detailed chat content that may have been missed during the live. This data can be used operationally, such as gathering specific feedbacks on the live stream or targeting users with high chat activity for additional user management.

C. Product Data: Metrics for Product Interest Analysis
  1. Clicks / Click viewers / Average number of clicks

    These metrics represent the number of visits to the product detail pages. 'Clicks' is the total number of visits to the product detail pages, 'Click viewers' indicates the number of unique visitors who visited the product detail pages at least once, and 'Average Clicks' is the average number of visits per user. One of the most important KPIs in conducting live streams is the increase in sales.

    Therefore, users who have visited the product detail page at least once during the live stream can be considered potential customers for the brand/business. Thus, this product data can be used to monitor conversion rates and measure interest in the product.

  2. Banner clicks

    'Banners' serve not only to direct users to the product detail pages but also to various other landing pages as desired by the brand/business. 'Banner Clicks' data can be used as a tool to monitor the achievement of various brand/business objectives beyond product sales during the live stream, such as introducing other products or directing traffic to the company’s platform.

Replay Data

In the 'Data Download' section for detailed analysis of 'Live Data Insight', not only the data collected during the live stream but also the 'Replay' viewing and user activity data are included. 'Replay' can be used after the live stream ends to repurpose the live content for 'Content Archiving' purposes and to increase engagement with users who could not watch the live stream. The viewing data and user activity data from 'Replays' help measure the interaction level of users who missed the live streams and their interest in the products. It can also be used to increase interest in upcoming streams.



Brands/businesses across various sectors can expect to create synergies in developing sophisticated business strategies in the E-commerce industry by utilizing Shoplive's 'Live Data Insight' during live streams. Establish data-driven business strategies with Shoplive's 'Live Data Insight'!