You run one business, so why do you treat it like a collection of unrelated activities?
You manage:
Employees via a workforce management system
Projects via a task manager
Your fleet via a mobility platform
Customers via a CRM solution
Revenue via a billing system
etc, etc.
But all these elements interact. For example, if you are under-staffed or your workforce is inefficient, vehicles will not get recharged, which leads to unhappy customers, and then revenue drops. Can someone that only sees the drop in revenue identify the root cause and take steps to fix it?
To run your business at peak effectiveness and profitability, you need each “silo” process to consider data generated by related “silos” upstream and downstream. This is the approach Anadue takes.
That doesn’t mean that everyone wants to see the same reports, or would even understand data meant for another function. We all have our specializations, and Anadue understands that data needs to be presented in the format that best suits the objectives of each user.
Let’s consider the example of Customer Service, the department responsible for handling customer queries and complaints. Every day the Customer Service department has to review the list of “one star” feedback comments submitted by customers via the Rider App. They need to decide whether to offer refunds to these riders or not. From a business point of view, “good” customers need to be looked after to reduce the risk of them leaving the service, but it would be a mistake to refund “bad” customers that are “gaming the system” and leaving negative feedback after a good ride. What information should be presented to Customer Service agents to ensure speedy, accurate, and good-quality customer care?
The most obvious information is about the ride the feedback applies to. How long did the ride take? What distance was traveled? Did the “unhappy” rider get good value for money? This data is usually not available from the Rider App, but can be retrieved from the Mobility Platform and presented with the Rider Feedback.
Secondly, who is this rider? Not in the sense of seeing their name and address, but what type of user are they? How long have they been a customer? How many rides have they previously taken? Are they a “pay as you go” customer or have they bought a daily/weekly/monthly pass? What’s their average monthly spend? Do they usually leave positive feedback after rides, or do they have a habit of leaving one-star feedback? This data needs to be collected from various sources and presented to the Customer Service agent with the Rider App feedback in an easy-to-understand format.
Now let's see who else could use the same data collected and presented to Customer Service. Sales and Marketing would get value from the analysis of all customer feedback comments to see if there were recurring problems that could be fixed to increase rides. For example, are a lot of people commenting on the price, the service area or the times of operation?
Operations could learn if just a few vehicles are responsible for a high percentage of the 1-star feedback comments, so these can be targeted for extra maintenance and/or repair. Maybe there are common themes that identify a problem with the whole fleet? Or maybe many people complain that vehicles need to be recharged more frequently?
In just a few paragraphs, it’s become clear that combining data from multiple sources and sharing it (in appropriate formats) to multiple functions has enormous value. Customer satisfaction is improved, revenue is increased, costs are cut, and business critical problems can be identified and resolved.
Anadue is leading the field in treating data as a valuable resource that can be applied across the entire shared micromobility business. Our customers have a strategic advantage as Operators focus on profitability in this rapidly maturing market.
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