# Data Analytics Introduction

Welcome to Hackle Data Analytics!\
Data Analytics is a data analytics platform that lets anyone independently understand customer journeys and business performance.

![](/files/lSPrlMf0zN5bQjIuHCR3)

## Overview

With Data Analytics, you can instantly visualize and analyze the consolidated behavior logs of all users who visit your App or Web service, regardless of whether A/B Tests are running.

Even without any knowledge of queries, you can freely configure time ranges and detailed conditions to uncover insights hidden in your data.

For example, the following types of analysis are possible:

* User acquisition and visit analysis (by OS, channel, region, etc.)
* Conversion rate trend analysis for all conversions (sign-up, search, purchase, etc.)
* Business KPI trends (revenue, average order value, subscriber count, etc.)

## Teams that need Data Analytics

Service data analysis benefits not only the product team but every team.\
When all teams understand customers from the same perspective, decision-making accelerates and the customer experience improves.

* PMs and product owners who want to understand the customer journey and maximize product growth through data-driven decisions
* Marketers who want to achieve maximum efficiency across multiple acquisition channels and Web/App products
* Data analysts who want to minimize repetitive analysis work and focus on advanced analytics
* Executives who want an at-a-glance view of business KPIs and want to introduce a data-driven culture

## Supported analysis types

Sometimes simple data trends are not enough to extract the insights you need.\
Use Insight Analysis to break down user events into various segments.

You can also conduct in-depth retention analysis through Retention Analysis. You can also analyze your service's key funnels using multiple criteria.

## How does Data Analytics compare to other analytics tools?

* **vs Google Analytics**\
  Google Analytics is an excellent web traffic analysis tool. However, because it is fundamentally page URL and session-based, it can be difficult to consolidate and analyze the behavior of customers who move between Web and App products. In particular, when data volume is large, data sampling issues can make analysis results unreliable.\
  Additionally, you can only view data that the tool provides rather than selecting the specific data you want to analyze, which makes it difficult to meet the diverse needs of different teams.
* **vs Amplitude**\
  Amplitude is a leading Product Data Analytics tool. Amplitude provides powerful analytics capabilities, but there is a learning curve to becoming familiar with how to use it. When selecting multiple items in event segment analysis, you must always use the same criteria, which means you cannot view revenue and order count in a single chart.\
  Additionally, for experiment platforms such as A/B Tests and Feature Flags, each event is reportedly billed separately for the analytics platform and the experiment platform.
* **vs Mixpanel**\
  Mixpanel is also a widely used Product Data Analytics tool. Mixpanel makes it easy to leverage various analytics features. However, it does not provide experiment platform features such as A/B Tests and Feature Flags outside of data analytics.
* **Hackle Data Analytics**\
  Hackle is different. You can consolidate behavior logs from Web and App products and analyze the full dataset in real time without sampling.\
  Hackle provides a one-stop solution for both an experiment platform and a data analytics platform for product growth. Even if a single event is used for A/B Tests, Feature Flags, and Data Analytics simultaneously, it is billed as only one event.


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