5 Ways AI Improve Subscription-Based Businesses

Consumers Purchasing patterns changed from ownership to usership, growing subscription business revenue by 437 percent in a decade . Businesses are changing to include usage-based product lines to shift from manufacturing to a service economy. The software as a Service (SaaS) program is an example of a structure that allows clients to self-subscribe while offering various payment options, including weekly, monthly, and annual payments. The subscription solutions are further enticing by using bundled service pricing models to lower the user’s software expenditures. Pay-as-you-go payment is typical for software services, and it’s becoming a popular billing approach due to its ease and convenience.

Companies that leverage AI and data construct extremely successful conversion models. Which increases user engagement, customer loyalty and, most crucially, turns conversions into revenues. Those companies are at the vanguard of this shift.
AI can help subscription-based businesses in the following ways to be at the forefront of this shift:

1. Marketing and Sales

Sales and marketing departments frequently utilize AI-based solutions such as Configure-Price-Quote (CPQ) and Marketing Automation. In the next two years, sales executives forecast a 155 percent rise in AI uses across sales teams.

Artificial Intelligence (AI) and machine learning (ML) are essential marketing tools for SaaS companies looking to grow revenue by providing tailored client experience. Personalization of content and consumer experience are two of the most critical growth factors supporting the deployment of AI inside these businesses.
Customers have learned to demand individualized interactions and experiences in the medium or platform. Receiving an automated message promoting a free trial that a prospect has previously signed up for with a sales representative shows that the company is not listening. Customers pull away for various reasons, the most common of which is “irrelevant material.”
It’s hard to engage hundreds of leads and consumers with targeted content without empowering marketing teams with artificial intelligence. Predictive content solutions driven by AI allow marketing teams to become more strategic while reducing the workload. The AI-powered marketing tools can scan the business website for blog posts, case studies, fact sheets, publications, podcasts, and other content—AI forecasts which material will resonate with the prospect and eventually help them convert. AI could leverage insights to attract visitors across email, online, and social channels for a complete multi-channel strategy. Consequently, organizations can offer one-to-one quality marketing that was previously impossible to deliver without significant scalability.
AI-based solutions are now used by 22% of marketing specialists , with another 57% aiming to utilize them in the next two years. From tailored multichannel encounters to programmable advertising and media purchasing to forecasted customer journeys. The following graph shows nine major use cases that marketing teams are focusing on right now.

On the sales front, AI is assisting businesses in increasing lead numbers while also improving overall sales performance.
Artificial intelligence in sales may help businesses expedite their sales process by automating sales performance, tracking sales growth, and engaging with prospects, all of which can help improve their conversion rates.
For example, AI automation in sales has assisted in automating purchasing through bots, resulting in a reduction of 15 to 20% of expenses sourced through e-platforms.
Companies who use artificial intelligence in sales have witnessed – according to McKinsey:
Leads and appointments increased by 50%.
Overall expenditures are reduced by 40-60%.
Call time is reduced by 60-70 percent.
AI revolutionizes how things are, and keeping up with the competition necessitates automation.

2. Conversational AI Improves Client Retention

Natural language processing (NLP) is combined with conventional tools such as chatbots, voice assistants, or an engaging speech recognition system to serve consumers via a spoken or written interface.
How do users react when they are put on hold? Most likely, they aren’t interested in extending the conversation. If it frequently happens at any firm, the business will probably lose prospective new and old consumers because of impatience and irritation.
By default, conversational AI replies instantaneously; however, some consumers believe the virtual assistant answers too soon; hence conversational AI service providers add a 1-2 second delay makes the response look more “human.”
Several firms increase the hours their call centers are open to keep up with clients. Consumers are becoming more demanding, expecting assistance when required, not when the corporation believes it’s convenient.
At the first phase of total digitization, those that have effectively adopted conversational AI are already beginning to reduce the necessity of their human operators. They are enhancing client happiness by providing an always-accessible corporate representative and, in turn, saving money.
Most marketing specialists acknowledge how difficult it is to reclaim lost customers, as well as the hefty expenditures involved. A contemporary marketing team’s toolset should include a warning system for consumers ready to quit their subscription. Instead of being reactive, marketing teams should be proactive. Moreover, According to 82 percent of marketing executives, increasing customer experience is the most important aspect in their choice to use AI.

Service pauses or cancellations lower subscribers’ future value and results in lost revenue.
How do companies get a heads-up on users who are “at-risk”? Users’ online activity, membership characteristics, and product replies may all be utilized to gauge how far along their subscribers are in the cycle. The features are fed into a unique clustering algorithm, which creates an “At-Risk” group targeted with marketing efforts. Furthermore, there are updates daily and responses to every action taken by the user.

3. Estimate revenue growth and Anticipate Trends

In every sector, the most excellent approach to obtaining a competitive advantage is understanding more about the operations and market factors that impact the business than your competitors. Market leaders are distinguished from other companies by their increased competitive strength and capacity to do more in less time.
Predictive analytics allows SaaS businesses to take advantage of chances to engage proactively and anticipate results, allowing them to remain ahead of industry trends. As a result, based on prior success, they can cross-sell or up-sell their services.
In 2020, 69 percent of decision-makers felt analytics would be critical for corporate success, and 15% say it is essential for running their organizations currently.
AI-enabled forecasting of trends and important events of interest is possible because of the vast amounts of public data created every second worldwide. It opens up significant new possibilities for anticipating and addressing challenges in diverse marketplaces and proactively minimizing hostile digital risks to any company, brand, or customer.

4. Improving response times

AI is being utilized to recognize a client’s requirement and show the appropriate information, resulting in best-in-class customer support. Businesses have widely deployed AI chatbots to answer consumers’ most commonly requested inquiries. Companies can significantly enhance the customer experience while lowering expenses by answering more than half of frequent queries from the beginning.
Bots are proving to be an excellent approach for many businesses to handle a large volume of consumer queries. While it may take some time to set things up, test, and improve accuracy, it is suggested to start the process if the company’s workforce is behind on responding to queries. Bots can also save a lot of money over time if used correctly.

5. Making Use of Natural Language Processing

Collaborators may use language analysis technologies to gather essential information from client feedback and adjust their message accordingly.
Language analysis is a valuable tool for improving the quality of companies’ contact center experience. Your agents may use it to determine if the consumer they’re speaking with is pleased or dissatisfied and correspond to alter their tone and actions.
Behavioral and Analytics Tool (BEAT), an application built by Deloitte for a big financial services organization, is a fantastic language analysis example. BEAT listens to consumer phone conversations and translates the language and mood of the discussion to assess if the client was vulnerable and at risk of a bad outcome. Natural language understanding is one way for businesses to use AI (NLU). They can comprehend the interaction between the customer care representative and the consumer by employing real-time insight into consumer service calls, chats, and emails. AI can help better the customer experience by determining the amount of irritation, the necessity for referrals, and the speed of resolving problems.