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description: Bringing Analysis On-Chain
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# What is LPSignal

This article explores on-chain analysis, its use cases, key players, and LPSignal's role in the space.

At its core, LPSignal is an analytical tool that allows traders to obtain the maximum amount of information before opening a position. For that reason, we thought why not delve into the analysis, because there's a lot to learn. Again, this article is a follow-up to the webinar, which you can view below.

#### On-Chain vs Off-Chain Data <a href="#on-chain-vs-off-chain-data" id="on-chain-vs-off-chain-data"></a>

There are two types of data in the crypto world: on-chain data and off-chain data.

Off-chain transactions are not (or at least not fully) executed and recorded on the blockchain. Centralized exchanges like Binance or Coinbase sometimes provide data either publicly or privately, and all data is off-chain because it's not visible on the public ledger. If you only analyze the blockchain, the deposit and withdrawal transactions are verifiable, and the rest of the data needs to be trusted. As an analyst, it is not a best practice to rely on data that may have errors. Therefore, any distortion in the data provided can lead us to make wrong investment decisions.

On-chain, on the other hand, every transaction is recorded on the blockchain and publicly available. Any activity to buy, sell, pledge tokens or smart contracts can be read and analyzed, and we can ensure that it is valid data. All of this valuable information is stored in its original format, which brings us to the main challenge of on-chain analytics - analyzing the areas of information we hold.

On-chain data can be broadly classified into three distinct categories:

* Transaction data (e.g. sending and receiving address, transferred amount, remaining value for a certain address)
* Block data (e.g. timestamps, miner fees, rewards)
* Smart contract code (i.e. coded execution logic on a Blockchain)

#### Use Cases <a href="#use-cases" id="use-cases"></a>

It's great to have access to all this data, but what can it be used for? We have specified five valid use cases for on-chain analysis.

* **Cryptocurrency Investment Analysis**

It is well known that cryptocurrencies are the underlying monetary assets of the blockchain and can lead to huge investments. Buying ether or Bitcoin a few years ago might have brought life-changing gains, but how could you possibly analyze the network? One approach is to use on-chain analysis. There are many factors to consider, including miners, stakeholders, block value, and economic incentives, which can be difficult to understand without considering the on-chain situation.

For example, the Bitcoin network is protected by miners, who in return receive block rewards and transaction fees that provide security to the network. A key metric for Bitcoin blockchain analysis is the change in miner incentives. A change in miner incentives could trigger a change in your investment philosophy, making on-chain data very useful.

* **Token Performance Monitoring**

Unlike cryptocurrencies, which are blockchain native assets, tokens are created using scripts or smart contracts. Tokens accumulate value based on the design of the protocol and the economic system inside and outside the blockchain. When investing in these tokens, understanding protocol design and usage is critical. Blockchain token analytics helps you track the usage of the protocol and the whereabouts of the token. Metrics such as active addresses, total trading volume, and on-chain trading volume can help you decide whether or not to invest.

Decentralized finance (DeFi) is an ecosystem of blockchain-native financial instruments, including lending, pledging, liquidity mining, and more. Smart contract protocols support these financial instruments. When analyzing the health of the DeFi protocol, it is necessary to examine the metrics associated with a particular protocol design.

For example, Uniswap is a decentralized exchange (DEX) protocol that can be analyzed using metrics such as total trading volume and average transaction size.

Another example is Compound, a type of loan agreement. Metrics such as total number of borrowers, total number of lenders, and volume can help you understand the growth of agreements and evaluate your investment decisions.

* **Macro Trends**

Blockchain analysis can also help you understand macro trends in the crypto industry. By analyzing metrics such as active addresses, transaction volume, asset distribution, and more, you can track the overall health and growth of the crypto ecosystem.

* **Blockchain Research**

Blockchain technology is still in its infancy and is an exciting area of research, both technically and economically. Blockchain analytics provides valuable insights into encrypted networks and helps researchers better understand them.

* **Market Sentiment**

Cryptocurrency market sentiment is also known as cryptocurrency investor sentiment and can be described as the overall attitude of investors towards the cryptocurrency market. This psychology of market players can reflect the overall price trend. Market sentiment drives supply and demand, which leads to price movements in the cryptocurrency market.

Market sentiment uses investors' mood and feelings about an asset to predict price movements.

Technical analysts and day traders rely on market sentiment, which sways their technical indicators due to short-term price fluctuations resulting from crypto market sentiment.

#### Builders in the Field of Analytics <a href="#builders-in-the-field-of-analytics" id="builders-in-the-field-of-analytics"></a>

The rise of on-chain data analytics projects began in 2020, with what became known as the "DeFi Summer." Since then, the market has been growing rapidly - as of April 2022, at least two companies (Nansen and Dune) are valued at more than $1 billion.

The market can be separated into three major domains:

**On-chain Data Analytics Platforms:** These platforms allow users to leverage millions of on-chain data points and create dedicated dashboards and charts. Such products are aimed at advanced and professional users, as they may require coding and programming skills to create dashboards, but offer virtually unlimited data analysis capabilities.

**Charting for Permissionless Markets:** These are dedicated solutions for developers and professional/institutional traders.&#x20;

**API Data Providers:** The project provides API access to market and on-chain data points for use in automation platforms and B2B solutions. The end user does not have a graphical interface, so coding skills are required.

All three market segments are critical to the growth and development of on-chain data. The two unicorns mentioned are both on-chain data analytics platforms with a focus on advanced and professional users. They are usually the first to capture any market - including the cryptocurrency market. Let's take a deeper look at these companies.

Of course, our favorite analytics platform is LPSignal. LPSignal deals with a different market segment than Nansen and Dune, focusing on charting the permissionless market. These markets are occupied by retail and leisure traders and will fill more as the industry develops, putting LPSignal on a path to growth.

LPSignal offers:

* A simple & easy to use interface to interact, browse & filter Token TX data
* Data support for 8 prominent chains along with trading capabilities on 7 of them
* Token Profile to insights into token activity & holdings distribution
* Trader Profile to deep dive and analyze wallet balances & activities
* Multi-Charting functionality

The platform also provides information on market and liquidity activity, price alerts, and public apis. You can use our API to find information about token prices, trading pairs, traders, AMM, on-chain transactions and more. Check our Gitbook and developer documentation.
