Due to the fact that AI has proven their effectiveness in such fields of human activity as
- and many others,
more and more entrepreneurs and business owners are keen to try computer vision, machine learning and natural language processing in order to attract new customers, provide their current customers with better service and solve numerous logistics problems.
So how AI can help businesses now? At what stage of the product or service life cycle the use of artificial intelligence can cut costs and increase profits?
In fact, such a solution can help from the very first steps of both manufacturing a product and providing a service.
It is a well known fact that regardless of the business type a huge number of potential consumers of a service or product could be lost at the following steps:
- placing an order/fill out an application
- finding the information they are looking for on the website
- getting an urgent consultation.
These situations are common customer pain points which do not allow the business to expand its client base and grow further. These points are the most painful for the business if only we are not talking about pain points related to banking services, taxation, problems of a purely technical nature and others not directly related to the consumer of the service or product.
In the past, in order to reduce the risk of losing clients, the business preferred to
- hire entire agencies,
- order call-center services,
- pay for third-party companies services
to ensure uninterrupted customer relations starting from the initial processing of incoming requests and ending with 24/7 after-sales support and consulting.
These activities are an additional line of significant expenses in the company’s budget. Besides it leads to dependence on the quality of work of third-party firms.
Not to mention possible leaks of sensitive commercial data.
Another way to handle all those incoming requests would be just to assign such tasks to the company’s employees who have its own price and disadvantages.
At the same time a combined AI solution can cover almost a major part of business needs in this direction. Yes, not all, but at least significantly reduce this line of expenses.
Imagine that you are a small but an actively growing future rival of “U-Haul” or a some other transportation service giant.
- How embedding AI would help your business in terms of processing incoming requests and customer support
- What it takes to successfully integrate such a solution into an existing business flow?
Regardless of the channel through which customer applications and requests come to you, the combination of NLP, CV and ML can simplify and smoothen the requests processing:
- NLP will recognize the meaning of the content in the application fields filled in on your website/mobile application, correctly sort the collected data and send it further in accordance with the request processing pipeline built in your company.
- ML will use refined and sorted data in the future when calculating the preliminary order price.
- CV would be of use if requests, applications or orders come to you on paper and gets scanned.
All is done AUTOMATICALLY which will allow you to reduce your employees workload for these tasks (read “reduce costs”) and assign their hours to other important tasks.
To process applications filled out through a web form with AI solution it is enough to provide the team of AI experts with
- application form templates,
- list all business rules that should be taken into account,
- indicate how the system should behave in case of deviations from the standard scenario.
Wherein you can point out those cases where a special approach is required such as:
- your pipeline for VIP customers requests,
- the desired approach in case a specific trigger word is found in the form
- the required approach if the form was left uncompleted.
The best thing for these cases is that the next step can also be performed using AI. An automatic call-notification to the client that the application form is not completed if calls are preferable for this customer. Or maybe sending a message via the messenger if such information is indicated in your CRM system. Or just instantly informing one of the customer service managers if the notification requires personal intervention.
Only remember that all those nuances must be communicated to the team of AI experts on a pre-sale phase.
Here is Part 2.