Skip to content

All-time perfect delivery! Make it happen!

Delivery reliability

Know what your customers want and make them happy:
How AI based processes increase customer satisfaction and turnover – by improving the delivery chain

Delivery reliability is a key performance indicator when it comes to customer satisfaction. And customer satisfaction should be the goal of every company that strives for a successful and sustainable market position. Keeping the delivery chain impeccable is not that easy, though, because it requires serving the customer's exact needs appropriately – and in advance. Doing this manually takes too much time and capacities. So this is how you can use your existing customer data to get the improvement of customer experience started: at any touchpoint and with a remarkable financial outcome.

Recent studies prove why happy customers should be a genuine interest of every company:

  • Those with highly satisfied and, thus, loyal customers increase their sales about 2.5 times faster than their competitors. So, effective customer experience management leads to successful business.
Return on happy customers
  • The other fact is: Customer experience very often suffers from disruptive factors within the supply chain. Disruptive factors, however, are very often linked to the “last mile” in distribution logistics: when goods are delivered from the local distribution centers to the end customer. The delivery reliability of shipping service providers affects customer perception and is therefore particularly important. Monitoring delivery reliability should be a central component of shipping and transport controlling. But how?

It’s hard keeping track of all your processes by hand

Just a small proportion of B2B corporates are able to control their delivery processes from A to Z in order to find deficiencies – since, in most cases, this is a manual act, remarkably time and capacity consuming. Plus, it’s difficult to identify the right grip and the most efficient way of handling the process. Mostly, troubleshooting can only take place after the error has already happened. Just imagine your customer service was in charge to coordinate all interactions between your customers and every other involved team. Its superordinate position demands keeping up with every communication and collaboration.


Advance is better than retrospect

Friction losses are inevitable in this complex situation and make dissatisfaction unavoidable, especially on the part of the customers. They might complain about not having been served as fast and correctly as expected. Bringing their irritation and complaints to customer service, there is no chance for the unit but trying to keep the annoyance on the lowest level possible. But in order to turn customer service into a value driver instead of just letting them firefight, they need to be proactively informed about any inconvenience their clients might be confronted with. In consequence, they would be able to act in advance. This is where AI comes into play: cloud-based analytical services that predict customers’ demands and wishes and fulfil their needs, based on already existent data.


Customer happiness, created by AI

We developed a smart, efficient and provider agnostic solution on behalf of increased customer satisfaction: Sharcx. It runs on private cloud environments, using Data Collection Mechanisms, monitoring customer experience at every touchpoint, creating experience alerts and passing on customer notification.

Too fast? Here come the details:

  • The Sharcx.suite helps analyze the relevant delivery processes step by step.
  • First, it tracks and comprehends the key drivers which lead to the specific customers discontent, for example a non-transparent delivery process, lacking of information the customer needs for detailed business planning. This crucial information is attained by the Sharcx.collector.
  • The takes it from there: It enables customer service for example to make an agreement to define and onboard a group of pilot customers.
  • After that, the Sharcx.toolbox permanently monitors the pilot customers’ deliveries and automatically sends information to customer service in cases of potential delay. Thanks to this process, you enable your customer service to focus on their main job again by gaining back their control of the situations.

Sharcx Alerts

Predictions, based on big data

Sharcx’ predictive services are based on a big data model. In an individualized manner, the framework identifies any factors that influence customer satisfaction performance, for example both expectations and pain points on the part of the customer. It then compares these indicators with previous transaction data. The result is a personalized impact model that is able warn of any disruptive factors in the future. Natural Language Processing is used to analyze the customer's mood. This is combined with a predictive model based on machine learning, using both historical and current business process data. Our automated services are configured based on key measures to improve customer satisfaction.

Do you want to serve all-time happy customers? Profit from Sharcx – and get results such as substantial delivery time saving, enhanced delivery reliability, reduced customer complaint rate – and a well-informed customer service who is able to predict the future. A prosperous one, of course.

Get more information