SaaS6 Ways A SaaS Company Can Benefit from AI

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AI (artificial intelligence) and machine learning have long been a myth for companies and businesses. But now, recent advancements in the availability of the enormous amount of data and computing power has made these far-fetched ideas a thing of the past. The reality is that artificial intelligence and machine learning is the order of the day.

Lately, machine learning and artificial intelligence have become one of the biggest trends, which are not surprising as Software-as-a-Service (SaaS) is such a big part of this revolutionary change. A few weeks ago, Sundar Pichai, Google CEO, spoke at an event sponsored for humanity issues. He told the audience that artificial intelligence and machine learning could significantly impact everything, maybe even more than fire or electricity. In the current article, I’m going to explore how SaaS companies are using machine learning/artificial intelligence in their upcoming ventures.

SaaS Companies Today

A report published by IDC says that the SaaS sector makes up about 68 percent of the whole cloud market share. Before, it had been the slowest expanding sector in the cloud market, making only 22 percent growth every year until the last year.

The idea of seeing how the hottest investors look at the market is shown by an indicator called venture capital funding. This venture capital funding has gone downhill when we look at the SaaS startup ventures. TechCrunch, an American online publishing company focusing solely on the tech industry, attributed all of this, mainly to the saturation in the market. It also says that newbies are seeking funding and trying to compete with huge established players.

The SaaS market’s growth rate is now expected to be lower than what we have seen before. But despite this, the SaaS market is expected to show some growth. The SaaS industry is mature now. The winners coming out of all this seem to be those who can keep an eye on the next big things. Machine learning and artificial intelligence would help create a more calculated position for his sector.

All the biggest companies like Google, Microsoft, and Amazon in the tech market reveal offers that use artificial intelligence. Another big company, Oracle, is an influential player in the SaaS market that places its biggest bet on machine learning and artificial intelligence. They say that this may overtake salesforce in the SaaS. This indicates that machine learning and artificial intelligence might be the next biggest step in improving a SaaS and making its prominent position in the market.

How SaaS Companies use AI and machine learning

SaaS is now taking upon the trend of machine learning and artificial intelligence. The investors are now taking a particular interest in this area. Here are some of the solutions by SaaS where artificial intelligence has a prominent role.

1. Hyper-personalization

Artificial intelligence has the potential to bring hyper-personalization to the SaaS. We have already seen this customization in different mobile apps; for example, My Starbucks Barista by Starbucks. The ability to learn by artificial intelligence and regular language processing based on the customer’s recent interactions can help design user interfaces that cater to the customer.

Here is an example. If we think about some SaaS that doesn’t have AI competence and keep adding more and more features and functions to it, we will only be cramming the user interface over and over. This will increase the complexity for the customer. On the contrary, if Artificial intelligence is used, it will help with customization and an easier understanding of its features.

2.Engaging with Automation

Automation combined with machine learning and artificial intelligence can be beneficial in many different ways. It can enhance user experience where formerly manual tasks were compulsory; for example, it is a chatbot that assists the users by answering the basic questions.

Automation shrinks the costs as it excludes the necessity to employ surplus people for handling more work. A chatbot responds to login reset requests with a robotic answer in the form of a link to an information base, releasing customer support representatives to concentrate on further perplexing questions.

Of the many challenges faced by SaaS, one is keeping the customers quite engaged from every possible perspective. This can prove very challenging while giving the best solutions to the customer service needs and, at the same time, making sure that each customer is satisfied with his experience. Artificial intelligence can be beneficial due to this decreasing detachment and making it feel like a human effort.

There are many examples of different applications like Verizon or banking apps using this feature, where bots respond to the questions all the time. In rare cases, the bot refers the customer to a human operator if it’s necessary.

3. Event Predictions

Many possible ways are there where artificial intelligence is present in the SaaS. It can force predictive analytics to generate an improved user experience and aid in removing churn for SaaS. For instance, machine learning helps predict user preference or conduct, ultimately triggering actions or alerts when the user appears to be disengaging.

4. Understanding Intent with Product Search

When the customer explores an item for consumption, how can we discover the consumer’s personalized results? One aspect used in the products’ ranking is user clicked rates or an item’s sell-through charges. The user’s interactive data provides the link from his query to the item page view until the purchase event. We can produce graphs between questions and products through extensive data analysis of inquiry logs and between different consumer items.

To comprehend user request intent, we can also mine information. For example, when a customer requests “Toyota Prius,” we see if they are looking for a new car or spare parts for the vehicle? Question objective detection can come from comprehending the user, other customers’ searches, and query terms’ semantics.

5. Code Review for Release Management

The concerns for the SaaS whooshing the code and then setting up early is not a good idea. It will only cause a bug or crash that upsets all users, which can be very expensive. Potential liability and reputation issues thrive, yet being capable of quickly organizing can be a discrete advantage.  Especially if you’re in a viable market, this variation between leading and lagging can be vital if you are first to approach people.

Artificial intelligence can augment SaaS developers’ coding capabilities and hence becoming a game-changer. It can do so by creating essential checks to see if the coding is good. The whole organizing can reduce to a short time from months if artificial intelligence can confirm that the SaaS can serve thousands of customers in a short time.

An example of AI with SaaS is Docker, which tests and checks the code for quick implementation. Another example is the University of Cambridge and Microsoft trying to teach artificial intelligence to code independently.

6. Identifying Threats with Enhanced Security

Security issues of the cloud have always been a sizzling topic among the SaaS, and old-style security methods are not helpful. There are perimeter devices that need human input to fill in for new threats.

Artificial intelligence provides SaaS the opportunity of security services that reproduce and learn from new security fears spontaneously. Oracle has lately added artificial intelligence and machine learning to its cloud security services. This feature has facilitated automated threat findings.

SaaS Company: Future Opportunities

Artificial intelligence now symbolizes a novel cohort of SaaS products. It is a chance to embrace a novel method to have market power. Today, we see many big players moving to this realm already, and experts of this industry predict that it will continue to expand.

Overall, the most recurrent solicitations of machine learning in SaaS this day are applications in efficiency, which means automating the highest-volume manual processes and bringing down the costs.  As a result, if you are looking to shape a machine learning-based SaaS business, you will need to find a costly internal procedure and then automate it.

Are you considering machine learning and artificial intelligence for your SaaS business? The time is now to employ it to expand your venture using machine learning and AI as it is no more thing of the past but a reality of today. The biggest tech companies like Microsoft and Oracle are employing this trick to expand their customer base and target exact consumers that may be interested in buying their products.

It is no longer feasible to give random suggestions to the customers as the competition has been becoming fierce with every passing day, and if you don’t gear up with it, it will be very costly. No business can flourish; no application can gain popularity; no service can work the best if it is not personalized according to the user’s mind. For this, AI is the answer.

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