Data science to optimize sales at Ölgerðin

Picture of how we would for example organize the products on the website.
The current sales process when customers order through a representative of the company.
The current website.

Inspiration

By meticulously asking the mentors about the processes surrounding sales and customer service we narrowed in on 3 areas where we believe we can make a difference in the company.

What it does

We want to make Ölgerðin start using more of their sales data for 3 different reasons. First of all we want to better approximate when customers want and need to be contacted about sales. By making sure customers are contacted the right amount of times we can hopefully increase customer satisfaction. Sometimes human error while entering orders leads to expensive mistakes in the form of sending the wrong amount of products or even just the wrong products entirely. By comparing new orders to old orders we should be able to intervene and contact the customer before we send out the wrong order. By doing this we can hopefully decrease the carbon footprint while also increasing customer satisfaction. Lastly we want to reorganize the sales website. At the moment the top products when you log in to the sales part of the website are randomly assigned. We believe by using data from past orders we can organize the website in a more efficient way to hopefully increase sales. Lastly we want the website to be smart enough so that when I put Gin into my basket I get recommendations for which Tonic to buy with it.

How I built it

Since we don't have any data we ended up not typing a single line of code. We did make a mock-up of how we wanted the website to organize the products in a more efficient way but unfortunately we couldn't make any mock-ups of the other solutions.

Challenges I ran into

The big challenge we ran into was not having data to actually make the models so I hope you don't judge us for not actually having made the models.

Accomplishments that we're proud of

We're proud of how we worked as a team to find the solutions for how we can improve these processes at Ölgerðin.

What we learned

We learned that their are not many processes inside the company which we we could make more efficient. Therefore we are happy to have in the beginning of the project started to focus on improving on the little things.

What's next for Data science to optimize sales at Ölgerðin

Hopefully we get into a meeting with staffers at Ölgerðin and can work with them to implement this technology to increase productivity and sustainability throughout the company.