We discovered a lack of personal relationship between the customer and the delivery service.
Our product IndiVood tries to improve the relationship by personalizing the food presented to the customer.
The goal is that the costumer comes back to his new found favorite delivery service.
By syncing your fitness and personal data with our application we are able to generate a personal profile specifically for your diet.
With this profile we can recommend a suitable choice of food fitting to your life. Thanks to IndiVood untypical target groups for delivery services can be reached.
They gain the chance to seperate from the national players and profile themselves towards the customers.
Even small companies can use this concept, optimize the ordering transactions and provide better content for the customers.
With IndiVood new opportunities for advertizing and partnerships arise. Cooperations with gyms or health centers are self-evident.
Conclusively we want to emphasize that our concept is not only applicable for the personalization based on the score of fitness-data.
Of course the idea is adaptable in a further context. At this point it’s also imaginable that the user also receives suggestions based on his allergical fettle. It also seems obvious to not only offer our idea to customer services – there is a widespread scope for application situations.
Let’s summarize: The concept is a win-win situation for both, the customer and the provider. Our app video prototype points it out impressively:
We are looking forward to integrate our concept in the impersonal online world.
Never rust, embrace that change in a direction of customized proposals.
It’s worth it!
In the past few days we came to the following insight:
„How might we use live data from the destination to select the best route?“
The service is based on an app that integrates data given by users with live-data on route and destination (like scanning free parking spots) to determine the most efficient means of traveling based on the customer‘s preferences and the enviromental conditions.
For this to work, the customer needs to provide information on which services he is already registered with. Based on the users needs like cost and time efficiency, comfort etc. the system suggests a route and possibly a combination of different services. It will guide the user to a parking spot and inform possible connecting services. For instance the system might suggest the use of a taxi, if no parking spots are available at the destination, combined with car sharing to reduce the overall cost of the trip. This use case is also illustrated in a video:
This service allows the user to save time and money. He can scale his preferences and the app might even suggest services the user was not previously aware of. Most importantly, it will take the hassle out of inner city travel. Especially the search for parking spots can be very stressful.
As mentioned, our system requires live data on traffic and available parking spaces. Means to gather such data are currently being researched by various institutions. If our servcie where to become real we have to collaborate with these entities as well as consolidate input of various data sources and of develop the actual algorithms. Further improvements to the service could also involve parking spot reservation.
After finishing our field study and making use of different ideation methods, we decided to make damage detection and documentation for car rental services easier. During our field study we found out, that manual damage detection is a very time consuming and error-prone step, because car renters don’t just not tell about bumps, but even try to hide smaller ones.
That’s why we want to automate the process completely. Doing that we do not only save time, but increase also traceability of damage, in order to avoid renters complaining about paying for damage which might have already been there before they rented out the car.As you can see in our storyboard , a 3D car scanner would detect damages, ask the operator to recheck marked areas and in case of a a bigger defect, it could even adjust fleet management.
In our user research process we encountered among other potential needs for improvement (e.g. indoor navigation) that the functionality of the MVG Info Point at the Münchner Freiheit station is still restricted. Therefore we asked ourselves how we might add further functionality and improve the interaction. After various storyboards we decided upon adding a navigation feature and supporting smartphone users without data volume. Shortly thereafter we created a final storyboard combining our key-ideas as preparation for the video prototype.
The story is about a foreigner who gets lost on his way to the Deutsches Museum in Munich. Due to the lack of data volume his smartphone fails to be of any use. Luckily he discovers the Info Point which offers a navigation service including an option to send the selected route directions to a connected phone. He compares the different travel options, decides to take public transportation and transfers the instructions. With the help of the newly acquired mobile turn-by-turn directions he arrives at his destination.
After a week of extensive user research and analysis, we managed to extract the main problems in food delivery companies, that use bikes. We came to the conclusion that the most painful problem is to keep food undamaged during delivery.
Often the food arrives in bad condition, especially soup, because delivering food on a bike is sometimes literally a rocky road.
Given this information, we choose to develop a concept to improve food packaging. We explored different solutions, including a gyroscope, balloons, bubble wrap, but we choose the easiest(and probably cheapest) option. We decided on using inflated plastic bags to prevent the food containers from moving in the bike delivery box.
Our final storyboard(and video prototype) is an fantasy interpretetion of the delivery flow, showing how much effort the delivery guy puts into it, and highlighting how important it is to make this process easier and more succesful with our concept.
We did research on food delivery services. Analyzing our data from the interviews and observations we found out that establishing good customer relations is most important.
Especially customers who order through the big companies like Lieferando or Lieferheld don’t even know where their meals have been cooked.
This results in a lack of customer relation and dependence. We developed our own concept of a local system that could be installed separately for any food delivery service.
We call it „IndiVood“!
IndiVood makes it possible to suggest individual meals to the customers. These suggestions are made according to the personal taste and furthermore fit to the activities of the customers.
This customer focused approach will result in better customer relation and a higher level of customer satisfaction.
We are eager to produce a Videoprototype based on the storyboard.
Our team did extensive research on transportation providers in a social setting. After careful analysis of the data acquired, we came to the conclusion, that all services share one common problem: How to properly acquire, organize and use data that is needed for everyday business.
Our storyboard focuses on the dangers that might arise from paper-based organisation of important information, where important facts might get lost in transit. While in real life not every incident of information lost in transit does not have to prove to be fatal, it still could be – this is reason we also portray it accordingly.
Subsequently, we will turn back the time – in a literal and a figurative sense: We go back in time and explore the world with a proper data-management-system, here dubbed “WeCare”, that does not only unclutter the administrative agent’s desk but also saves the protagonist’s wife from becoming a widow – all with the power of a Customer Relationship Management-system, that offers not only a complete overview for the scheduler in the office but also mobile apps for the driving staff and the customers involved.