We left another Black Friday behind. Over 100 million people in America went shopping on Black Friday. In the U.S. alone, people spent 7.2 million USD in online platforms on 29th November. Globally, digital sales hit $20 billion on Black Friday.
In Europe, there were 90 percent more transactions on Black Friday when compared to the average Friday in 2018. Additionaly, spending is increased 175 percent on these transactions compared to average Friday.
There have been many big advertising campaigns during Black Friday. This period was priceless to understand customers. Metrics such as the reactions of the customers to the special offers, the duration of the products being campaigned, are essential factors that can be analyzed in this period.
At this point, we see that e-commerce sites are leading the competition. They had the chance to update their Black Friday campaigns instantly according to this data by identifying which type of product customers were looking for and how long they had purchased.
Traditional brick-mortar stores have applied a technology heat map when they need a tool that can compete with e-commerce at this point. Heat mapping offers simple solutions to give retailers insights into whether their campaigns are successful. While heat maps have many benefits to retailers, there are three main benefits:
1) You can detect the dense areas & dead zones in the store and take action to optimize these areas
2) You can compare areas on a time-based basis and determine which days the department is busy. You can understand whether you have reached your customer density target during campaign periods or how density has been reflected in sales.
3) By comparing the same department’s densities in different stores, it can be identified which stores are more efficient than others. Actions can be taken in inefficient stores by researching root causes.
Despite this much benefit, there are many points where the heat map is insufficient.
In the business world, the statistics are vital; the heat maps are insufficient at this point. It is not sufficient to show different customer densities with several colors in today’s conditions.
Why Heat Maps are Insufficient?
Quantitative data should be determined, and customer density should be specified. The number of customers changing across the store and the department should be shown. It is not enough to show the change of map colors.
It is not enough to compare the departments in different stores through colors. It is necessary to see how many customers came to that department. Furthermore, determining how long the incoming customers spend in the department is valuable information to understand the customer.
Real-time Based Customer Analytics
At this point, as we mentioned before, understanding the customer experience in campaigns becomes essential. In Black Friday, the metrics like the number of customers increased, how long the customers spent in stores and departments, are crucial for retail.
Udentify comes into play at this point, which allows retailers to take the lead in the competition. Udentify enables real-time customer analytics to optimize departments and stores. If we examine the main aspects of the system through sample cases, we can see the contributions that Udentify can offer retailers on Black Friday.
What Udentify offer to you?
- The graph below shows the number of customers and the time spent in the store per customer. We see that the number of customers peaked but the time spent is decreasing. As a result of this graph, it can be concluded that the time spent by the customers coming to the store should be increased. The department-specific analyzes can be used to determine the sources of the increase in the number of customers and the decrease in time spent per customer. The results can be drawn here to determine the direction of the campaign.
- In the chart below, the green part shows the sales quantity. The red part is the sales amount. It shows that the number of sales peaked on November 29th. However, the sale amount could not reach the desired amount despite the peak in the number of sales. There may be root causes in the lower refractions of the graph. By changing the product group positions within the department, the performance of the products with a high impact on sales amounts can be increased. Another strategy is to change the way the campaign is run. The number of sales can be increased by setting up a campaign aiming at the selling of products at high prices.
- Besides, department-based determination of the customer density of the store can be used to improve the performance of the other departments. Departments can be placed most efficiently, and the customer journey within the store can be utilized. Correlations can be determined by analyzing in-store department-based densities during campaign periods.
As we said in the beginning, e-commerce sites have updated their Black Friday and other campaigns according to customers. So as a retailer, are you sure that the next campaign is correct?