“Pickshare Ad Manager”

This project was carried out as part of the TechLabs “Digital Shaper Program” in Dortmund (summer term 2021).

In a nutshell:

Within the scope of our practical project, we were working for pickshare, a logistics startup specializing in last-mile deliveries. Thanks to their daily business operations, pickshare has unique access to the personal data of their users, which they would like to leverage by introducing an ad manager. pickshare asked us to build this ad manager. Our aim for this project was to use and apply the knowledge acquired throughout our TechLabs Journey to building an ad manager that would help Pickshare to make use of the relevant data at their disposal and to enable their business partners to target users in a way that would provide both users and partners with the valuable experiences.

Introduction:

Within the scope of our practical project, we were creating an ad manager for pickshare, a logistics startup specializing in last-mile deliveries, with our team made up of Digital Shapers from the Data Science as well as UX Design Track. Thanks to their daily business operations, pickshare has unique access to the personal data of their users, which they would like to leverage by introducing an ad manager. While pickshare collects and has access to a lot of relevant user information, the startup hasn’t taken full advantage of the data yet.

We wanted to solve that problem by building an ad manager for pickshare by using and applying the knowledge acquired throughout our TechLabs journey in Data Science and UX Design. Within the scope of our project, we were aiming to cluster and analyze the relevant user data at Pickshare’s disposal to build an ad manager prototype based on which Pickshare’s business partners would be enabled to target users in a meaningful way to create valuable experiences and benefits for the users as well as the business partners.

Methodology:

The team members specializing in data science started by clustering user data in order to sort out the essential datasets from all available datasets. In addition to that, the data scientists were looking into how to identify the most valuable opportunities within the users’ segments to allow for precise and relevant ad targeting. Based on the resulting clustering, a click dummy for a dashboard was built. The team members specializing in UX design were approaching the project from the business partner side by researching and analyzing potential business partners for the ad manager. They identified the needs and pain points of business partners, i.e., that would use the ad manager to target users on pickshare. Moreover, a diverse set of personas was created based on our own research and the application of our acquired knowledge to enable Pickshare to better understand their potential customers and gain insights into media buyer personas. In addition to that, the customer journey was analyzed, and the prototype of an ad manager was created to demonstrate what an ad manager within the Pickshare app should look like and what options should be included.

Results:

After analyzing the data provided by pickshare, our data science group tried to figure out three important points:

1. Cities have the most users (Figure 1)
2. Cities have the most orders (Figure 2)
3. Number of packages per user (Figure 3)
4. Top 5 most ordered senders (Figure 4)

The solution of our project is an ad manager prototype for pickshare, which provides clustered datasets, a dashboard, an analysis of the target group, which was consolidated in four diverse personas and their demands and needs, as well as an ad manager prototype based on the customer journey and competitor analysis. Throughout the project phase of our TechLabs Journey, we have laid the foundation for pickshare to build their ad manager upon. Unfortunately, it was not possible to get real data from pickshare. This was our biggest obstacle as we mainly had to depend on our own research, which is why our results can be seen as general guidelines for ad managers and are less tailored to pickshare specifically. Nevertheless, we did our best to apply the gathered knowledge in our practical project and enjoyed working and growing together in our interdisciplinary team!

Sources:

• Getting the city list of germany from: https://moduliertersingvogel.de/2017/09/03/german-cities-list/
  https://de.wikipedia.org/wiki/Liste_derSt%C3%A4dte_in_Deutschland
• Getting plz of german cities from:
  https://www.suche-postleitzahl.org/downloads

GitHub repository and further repositories:

• https://github.com/TechLabs-Dortmund/pick-share
• https://www.figma.com/file/wRUDtBkWJS3foKCgbsSgYQ/Pickshare?node-id=3625%3A100

Team Members:

Data Science:

• My Nguyen: Studies Digital Transformation at FH Dortmund
• Christoph Klippenstein: Studies Mechanical Engineering at TU Dortmund, specialized in mechanical simulations
• Shourav Deb Nath: Studies Manufacturing Technology (MS) at TU Dortmund

UX-Design:

• Hannah Cordes: Working in Marketing & Communications at ThreeFold
• Semiha Acilan: Studies Business and Economics at TU Dortmund
• Vera Eger: Studies Business, Organizational and Sozial Psychology (MS) at MU Munich

Team Mentors:

• Milan Niehaus, Project Manager TechLabs
• Nicole Wikenheiser, Project Manager pickshare
• Saumya Bhatt, User Experience Design Mentor

Disclaimer:

This project was carried out as an unpaid cooperation with the company pickshare® GmbH. This consisted of the support of the techies in terms of technical and thematic aspects.