For previous article, I shared the ‘Target audience’ that you would need to consider before building a dashboard. I concluded that my target audience is going to be a H&M product team. In this article, I will explain how to create dashboard for product team member.
- Table
We have three dataset; articles, customers and transactions. Each of the tables has the following columns.
- articles : article_id, product_id, product_code, prod_name
- customers : customer_id, FN, active, club_member_status, fashion_news_frequency
- Transactions : t_dat, customer_id, article_id, price, sales_channel_id
2. Dashboard
- H&M Product hierarchy
The purpose of this dashboard is to figure out product hierarchy at once. As the bar chart shown, you would identify the hierarchy is following way; Index group, product group name, section name and product name
- Pareto Analysis
I created a ‘Pareto Chart’. The main concept of this chart is a ‘80/20 rule, meaning that the about 80% of results comes from 20% of factors. As I think it will allow H&M product team to identify which 20% of products accounted for the most 80% of the sales and number of orders.
This graph showed the ordered frequency values for the different levels of categorical variables. For my case, I calculated the sales and number of orders for frequency values and product name for categorical values.
We needed a product name, price and number of orders to calculate the sales. To achieve this goal, I joined all three tables; articles, transactions and customers. For sales, we multiply the number of orders and product price.
- Scatter plot
I built this graph to figure out the relationship between price and number of orders. I think it helps H&M product team to identify the price density distribution. It is clear that the most of product price is spread out from 0 to 5.
- H&M customer information : Age & Membership
Last contents of dashboard is a customer information. While it might be quite a old-fashioned to target marketing based on age, it’s basically useful to know about customers.
We don’t necessarily need to focus all the numbers in table, instead focusing significant difference between each of age. It showed that most H&M customer is 20–30 age. That age customers makes up for 80% of sales, which can conclude that they’re regular customer.
Next part of this worksheet is about the ‘H&M club member status’. I guess it’s a H&M membership program. You would know the younger generation tend to likely to active in this membership. At the end, the H&M product team would be consider the marketing strategy to encourage senior customer join their membership program.
3. Conclusion
As I’ve already explained the pre-step before creating our dashboard. I suggested you guys to decide our target-audience. Then it would be more clear what story that you’re going to put on your dashboard. I shared my dashboard with this link for someone who want to know deeply about my dashboard.
