SaaS practitioners, the future of SaaS software development trend analysis in the future

In recent years, SaaS products have also become more and more popular. With the economic recovery and industrial upgrading, how will SaaS develop? The author of this article elaborates from the perspective of one product of 6 aspects. The future development trend of SaaS is explained. Let's take a look at the practitioners or entrepreneurs of SaaS.

With the post -epidemic era, the economic recovery and industry upgrade, more and more industries have begun to pay attention to the characteristics of SaaS, the value cognition of SaaS has gradually increased, and the habit of paying for corporate users has gradually been cultivated.

As SaaS practitioners or entrepreneurs, we need to focus on the future development trends of SaaS. We have better combine our own SaaS product solution to better combine the trend development.

1. Artificial Intelligence (AI)

To this day, artificial intelligence (AI) has become the most popular development trend at the moment. AL represents the new generation of SaaS products. We have seen many industry giants have entered this field. For example, large technology companies we are familiar with , Microsoft and Amazon both showed products using artificial intelligence. Another large company Oracle is an influential participant in the SaaS market, and it bets its biggest betting on machine learning and artificial intelligence.

Artificial intelligence technology has made some major progress in 2021. Investors are very interested in this field. The application of artificial intelligence (AI) in some vertical industries has begun to subvert the traditional rules of the industry. Industry experts predict that it will be in Continue to grow, the market value is expected to reach $ 997.8 billion by 2028.

In general, the most common application of machine learning in SaaS today is efficient application -automated a large number of manual processes and reduce costs. Artificial intelligence provides users with excellent response capabilities and interaction in business scenarios, realize the automation and personalization of services, improve security, and supplement manpower.

AI and SaaS product characteristics binding direction:

(1) Personalization

Artificial intelligence (AI) can bring personalized embodiment to SaaS products. The combination of software and natural language processing (NLP) can automatically handle human voice mode and voice control. And it can be deployed across the customer service function, and it can better meet and solve the needs of customers through the personalized customization of user preferences.

For example: Mystarbucks Barista in Starbucks, users only need to make food and beverages and mobile online payment only through voice, which greatly saves the waiting time for waiting in line. At the same time, users can also use voice online to interact with AI, just like talking to barista online, and this AI smart product can intelligently recommend intelligent recommendation according to the preferences and special tastes of past users.

The ability to learn based on the recent interaction of customers through artificial intelligence and conventional language processing can help design to cater to the customer's user interface. If there is no AI capabilities SaaS, it will be upgraded with the upgrade and iteration of SaaS products. The more features and functions, filling the operating interface of this user, which will increase the responsibility and learning cost of customer use of products.

(2) Decision speed

"Treatment of cost reduction and efficiency" has always been the purpose of the enterprise, and SaaS, which supports artificial intelligence, has accelerated the internal process and operations, enabling enterprises to quickly obtain questions, quickly predict and speed up the overall response level.

过去SaaS业务场景在用户的操作产品功能和业务审核下推流程式的开展，当AI人工智能结合参与到SaaS产品中后，这种业务的流程的开展会更加迅速，并且系统能够替代用户做一些Conventional prediction actions to accelerate user decision -making operations.

(3) Digital intelligence

At present, more and more excellent SaaS BI data analysis products on the market are for enterprises for data analysis selection. In the future, this data analysis product based on SaaS -based artificial intelligence platform can dynamically analyze and investigate emerging consumption in complex data pools in complex data pools. Intent, interest, and behavior, at the same time integrate valuable data from various sources and clean up, and subdivide it in a way to provide the best business value.

2. Vertical SaaS

The development of the SaaS industry in China and the United States has emerged with general SaaS products, and then extended to vertical. At present, domestic universal products account for about two -thirds of the overall SaaS industry. However, more and more industry trends have shown that vertical SaaS has begun to be widely used in the market, and vertical SaaS solutions aim to provide specific industry needs.

General -purpose products are suitable for the needs of extensive public. They are not deeply supported by some specific industries or scenes, and the solutions are not innovative. It gives users a experience that "everything wants to solve everything, but it is not good to solve".

Vertical SaaS products are usually developed by the specific industries that have in -depth industry knowledge and professional solutions. This type of product allows users to enjoy the unique process design function and business scenario solution in the industry.

Vertical SaaS products provide the following values:

Commercial value: The vertical industry SaaS product aims to meet the needs of its industry. It can provide efficient operations for enterprises in specific industries and achieve performance targets, and provide enterprises with a higher degree of commercial value. Reasonable data governance: Vertical SaaS products contain a specific data cleaning rules and compliance functions corresponding to the industry, solve data governance procedures, provide higher transparency to the data of upstream and downstream business links, and solve the problem of information islands in the business process. Provide enterprises with more decision -making data analysis. The new niche market: Vertical SaaS is the core with solving very specific industry pain points, so that the demand for solutions in the industry's users in the industry has shown an upward trend. The niche market accelerates financing progress. Accelerating the construction of enterprise information and digitalization: Most companies do not have a deep understanding of informatization and digitalization. They are not enough to solve business scenarios. They are often used for informationization and use systems to use the system. The consequence of this lack of information about informatization is to launch a lot of systems or buy a bunch of SaaS products, but it is impossible to associate business management through the system. Because of the deep cultivation of the industry, the vertical SaaS knows that the business reached by the business facing the business in the industry can quickly make up for the gap between the business link, accelerate the interaction of information and data, and play a targeted business problem. Higher standardization: The reason why more and more companies tend to choose their corresponding vertical SaaS products instead of universal SaaS, because vertical SaaS can provide higher standardized product solutions and business scenarios. In the future, the vertical SaaS provider of specific industries In the increasingly fierce market competition, in order to distinguish its products from the competition, it will provide higher -quality products and services to meet the needs of users. This will give birth to a large number of The innovative niche solution has become more standardized and rationalized by the entire specific industry products. 3. Data -driven SaaS With the acceleration of the digital transformation of various industries, under the environment of government informatization, digital policy support, and fierce competition environment in the market, enterprises are using big data and analysis And strategic decision.

Therefore, more and more data analysis of customer behavior, market trends, and more insights have been increasingly demanding. From the data analysis, it is found that business value has become the long -term desire of the enterprise. Innovative investment driven by analysis drive is expected to soar. SaaS providers saw this opportunity, and continued to develop strong business intelligence (BI) tools and their platforms, providing high -end BI tools with extensive functions with concentrated instrument boards to prediction.

This kind of data -driven SaaS data product is more concentrated in analysis. Users can change from a single data scenario to a multi -dimensional data analysis, and use dynamic performance data to find new business insights.

4. Machine learning (ML)

Similar to artificial intelligence, in the field of SAAS industry, machine learning will achieve great growth in application in the next few years. The continuous changes in user business, the scene will be gradually complex, and there will be some challenges to the solution and functions of SaaS products. Machine learning can make SaaS products more self -improved, thereby improving operations and intelligence.

Such as data pre -processing, facial recognition, data visualization, natural language processing (NLP), prediction and prevention analysis, and deep learning are based on machine learning (ML) scene functions. In the future (Machine learning is service).

5. Ecological API integrated link

With the continuous evolution of business and extension of the business scenario of the enterprise, the solution of a single SaaS product will be largely limited. With the explosive growth of the SaaS solution and the adoption of the market, the need for integrating solutions to multiple SaaS products into existing business systems. For example: Some companies have already had their own supply chain ERP system (self -developed or leased SaaS products). With the development of business, business data generated on the original system needs to be integrated and analyzed.

At this time, the company will hope that the product (SaaS BI system) of the product (SaaS BI system) will be able to conduct integrated analysis of business data. However Automation and humanization. For example, some SaaS BI systems do not provide the API interface for docking external system data sources. All data analysis requires users to import the data through the Excel table by themselves. This complicated way greatly reduces the desire of user purchases.

Some SaaS providers use application redirects to redirect customers to third -party systems to provide specific APIs so that customers can integrate cloud solutions in their existing systems. Although this method can solve the needs of user business scenarios to a certain extent, it plays a opposite role for users' retention.

For SaaS start -ups, it is best not to repeat wheels. Enterprises only need to ensure their core competitiveness functions and focus on the core functions of differentiation. Other non -core scenarios can be introduced by third -party APIs to create a whole full The full business scenario of the link provides valuable time and resources for the early listing of the product. Now more and more SaaS suppliers tend to provide more powerful integrated functions, rather than redirect their customers to third parties. In the future, ecological integration API links will become another major trend of SaaS products, especially vertical vertical The industry will be widely used.

As a SaaS supplier, if the function of ecological API links with external service providers, you should learn about the following issues in advance to ensure that your integrated scheme meets the needs of the user's business:

External providers can provide the functions of my products to integrate SaaS into my existing business system. In the process of completing the integration, is my SaaS data be protected? Can the provider integrate my original old version system? 6. Migrate to PaaS

When a digital transformation is undergoing digital transformation, it encounters the biggest challenge: lack of professional and R & D engineers. Not only are large enterprises encounter this problem, but also in small and medium -sized enterprises with limited budgets. This low -cost tentative SaaS solution has become an urgent demand for enterprises. The growth of this type of market demand has enabled low -code and code -free platforms to quickly popularize.

Enterprises adopt a low -code platform to accelerate the development and deployment of new applications to verify the rationality and efficiency of internal business process scenarios. With the development of the SaaS industry and the replacement of innovative solutions, many SaaS suppliers will focus on the retaining of customers, not the acquisition of customers. We expect that SaaS will further migrate to the field of PaaS (platform is service) in the next three years -these development enables enterprises to build custom applications as additional components for their original services. Companies such as Salesforce and Box recently launched PAAS -centric services, with a view to occupying a strong market share in its niche market. We expect that this SaaS trend will become more common in the coming year.

Columnist

Big D, WeChat public account: TOB product innovation study, everyone is a product manager columnist. Tob SaaS product expert. He has served as the Internet director and director of the information and technology department in many domestic listed companies. He has led the team to commercialize the closed loop of the product from 0 to N multiple times.

This article was originally published in everyone's product manager. Reprinting is prohibited without permission.

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