SaaSThe Novel Age of SaaS and Artificial Intelligence

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More and more software companies have started popping up in recent years as technology is the order of the day. The tectonic levels of transformation since all this first started has been immense.

SaaS (Software as a service) is such a fast-paced realm with too much competitive dynamics that being abreast of it has become difficult. And it’s not only the competitiveness of this field, but the customer expectations have also evolved with it.

A recent study by Price Intelligently on SaaS economics has pointed out that those SaaS companies that began about five to six years ago encountered an average of 2.7 competitors in the initial years of their business venture. But those who founded their companies about a year before faced around 97 competitors.

Machine learning and AI (artificial intelligence) have brought a vast and unsettling wave in the technology world. And it is estimated that the companies based on SaaS will outperform and out-market their competitors. In this article, we will see how some companies are doing it already and succeeding.

Hyper-Personalized Marketing to Leads

The expectations of customers have changed. Many customers are now open to the idea of letting go of some of their privacy in return for some customized recommendations for them.

Customers now expect that brands would offer those personalized products and experiences. This has changed a lot in the B2B (business to business) sector. There is an extensive sales cycle in the business industry, and numerous customer points are anticipated there. In their research, Salesforce has said that by 2020, a quarter of the business to business customers can expect their suppliers to predict and meet their demands even before they are made.

Artificial intelligence and machine learning have been helping SaaS companies with their outstanding predictive analysis and pattern recognition. This way, SaaS companies have been able to make personalized products for their customers. It doesn’t matter if it is a DTC (direct to consumer) or business to business (BTB).  Their services are conditioned for this.

The same was the case with a digital adoption platform, a platform for engagement, enterprise-level class guidance, and automation, making its employees more productive and efficient. Companies executives can better reflect the digital realm. Different organizations can make the best use of all of their digital assets through this platform. They aim to fully transform the experience of their users in today’s prodigious digital world.

WalkMe has been catering to enterprise and business-to-business communities. They have targeted such a wide range of markets, which includes multiple sized and vertical organizations. They also own a versatile content of customer personas.

For their marketing and sales team, the following were the two problems:

  1. How will the quality of leadership be chosen between marketing and sales?
  2. How will they customize their messages and lead personalized campaigns for different personas having versatile needs?

To avoid all this scenario of sales representatives’ wasteful efforts and expand conversion rates, WalkMe collaborated with AI-powered and predictive learning platforms. The use of AI and machine learning helped them identify the top 45% of leads that contributed to 80% of the company’s revenues.

WalkMe’s sales and marketing teams could shape their meetings and campaigns around their leads with the highest potential after acquiring the data needed. This effort resulted in about 11% improved deal quality, which was twice as predicted. It not only boosted deal quality but also gave around 50% more opportunity to them.

Significant Support and Effective Automation

WalkMe started with the two-person Saas venture, which included Joe d’Elia and Pardeep Kullar. In the beginning, it wasn’t easy to be stretched between marketing, sales, and the customer support system for the email verification software named Anymail finder.

The said pair got repeated questions about all this, and then they were forced to answer back to every query via the email system. When another SaaS company provided them with another AI chatbot for a customer support issue, they optimized their sales process and customer support with pre-meditated solutions for the general problems. The chatbot also gave them some valuable messaging metrics. The metrics made sure that the automated responses given were the most effective ones regarding the situation.

After getting important metrics for optimal functioning, this two-person collaboration successfully decreased the overall response time to about three minutes. They also managed the bot to handle the more significant part of the enormous volume of customer service demands.

According to one of the cofounders, Pardeep, this chatbot thing got them about 60% additional revenue. Using the bot, they got every 14 out of 15 biggest buyers to use the chatbot system before purchasing any product.

Thousands of companies now use Anymail finder every day to get verified emails. Using Anymail, companies can find more and more leads and eventually making more sales than before. Their website has a job search title to find an ideal consumer even when the searcher does not know their customer’s names. It also includes bulk search features that can be used to hunt down multiple options in bulk. You just need to use their file upload to search hundreds of emails simultaneously.

Moreover, Anymail provides several tutorials to help their customers find more leads for their businesses. Anymail’s founder’s story is evidence that AI is helping a lot with customer-oriented support, sales, and lead qualification, even with tight budgets and nimble teams for SaaS companies.

Scaling the Disrupting and Unscalable Industries

The United States had its first-ever attempt in 1962 to send mariner one NASA’s spacecraft to the planet VENUS. That mission was groundbreaking in the field of space navigation. But it was also an unfortunate one in the end as it was very costly and anticlimactic.

After initiation, the rocket lop-sided off the course, and then after a lot of unsuccessful attempts to recuperate it, NASA was required to distend their $18-million valuable spacecraft. What was the reason for the error in trajectory? An appallingly trivial coding issue. A hyphen was missing in their code. While NASA may have been very discouraged by this failed attempt, it is a stark reminder of how a coding error or a software bug can incur huge losses to a mission that close. SaaS companies might take it as an abysmal user experience, an intense drop in their revenue, or a higher churn.

But how about a software system identifying and correcting bugs for your comfort rather than a bug is appearing or being flagged and then assigned through a duty management system for fixing it. And imagine all of these bug issues solved without any human intervention. It may seem like a futuristic and a fancy dream for now. Still, companies like Microsoft are already using machine learning and artificial intelligence for creating software that self-codes and can fix bugs and errors before they appear and incur a loss.

Disruptive artificial intelligence-based SaaS startups can improve unscalable businesses, and it will continue to do so.

Another example of an artificial intelligence-based SaaS solution is a company named Tractable, founded in 2014, which is for automobile-based insurance companies. This company got a total of about $34.8 million in its funding. This company is using computer vision for analyzing motor vehicle-based accidents using a special machine learning software. Afterward, this software can foretell the repair costs for vehicle accidents in real-time, the same as an actual adept person would. This allows the repair shops and insurers to review claims made about autos at a large scale instantly, that too, with very high accuracy.

The New Age Of Artificial Intelligence-based SaaS Is Here

Artificial intelligence marks the onset of the newest age for consumers and businesses. This era is the one that is going to empower different companies to be more effective and efficient in the bulk of manual processes and customers’ attention. It is also encouraging for troublesome SaaS products that need scaling a human-like experience to resolve former unscalable logjam problems.

In a market where evolution and adaptation are going on at a high pace, the SaaS companies which want to touch the new heights need to have an open mind for machine learning and artificial intelligence in their technology stack for a bright future. Unleashing the potential of artificial intelligence and machine learning is the only way to be a part of the current competition out there. SaaS companies are going to give all the customized experience to the companies that collaborate with them. Companies like WalkMe are the most inspiring examples in this AI-based era.

 

 

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