Transforming data for good decision-making

StatLog uses analysis techniques and the best cutting-edge tools to transform data and economic analysis for business decisions.

Our expertise at work


 Spin sports et plein air

Retail, sports and outdoor activities



The management executives of Spin sports et plein air were looking for tools that would allow them to better understand and analyze the impact of their actions on their company. StatLog set up mechanisms to combine data from different sources to create a dashboard with a series of indicators to break down and measure the impact of different actions on the company’s net revenue. The tools StatLog developed also helped Spin in purchasing and inventory management. A solid base was put in place so Spin can now use econometrics to extract maximum value from their data.


Reinventing objectives and assessing whether these were accomplished successfully.

The main objective: Maximize net income by unit of traffic.

The challenge: Measuring, interpreting and demonstrating the influence of controllable and uncontrollable variables on income per unit of traffic.

“Like most businesses, we have been collecting information at our retail outlets for many years which we were using to produce reports for our management team. StatLog completely changed how we see things. From the very same sources of information, StatLog created indicators and new dashboards so that we could understand the real changes brought about by our actions. Now, our reports are not just simple balance sheets. We have tools that allow us to predict impact and make more informed decisions. We see now our data in a whole new way.”

– Ian Beaulieu, President



Sizing up the background
StatLog met with Spin to truly understand the functioning of its various sales points, history, main challenges, objectives, etc.

Collecting information
Data sources were inventoried and a database for analysis was created. The data came from traffic counters and accounting, various sales points and time-sheet management systems.

Analyzing the data
We used this database for analysis to produce several descriptive graphics and statistics. We detected the anomalies and worked to understand the seasonal trends and relationships between various variables.

Validating quality
We analyzed the descriptive graphics and statistics (produced in the previous phase) to take stock of the quality of the data. We also validated the evolution of various data against the company’s history. Our goal was to make sure the company was using reliable, representative and precise data since it would be the basis of its decisions!

Structure of the information during analysis



Our findings

  1. Gross sales was the only indicator informing management’s decisions, even when many other variables generated by the company’s activities were available
  2. The company’s only strategy was advertising to increase traffic
  3. The company was not drawing the most benefit from each potential customer who came into its stores
  4. The company was not optimizing the use of its resources


Presenting the data
We presented our findings on the gathered and analyzed data to Spin’s management team to cooborate the trends we saw and our overall observations. We also presented them with an inventory of available data.

Identifying areas
We determined the strategies that had to be implemented to reach Spin’s ultimate goal of maximizing its net revenue by unit of traffic:

  1. Increase the conversion rate (percentage of units of traffic converted into sales)
  2. Increase the number of articles sold by transaction
  3. Increase the dollars by transaction
  4. Reduce operational costs (increase efficiency)

Identifying indicators
We specified the following indicators to help Spin reach their objective:

  1. Operational profit per unit of traffic
  2. The conversion rate corresponding to the percentage of units of traffic converted into sales
  3. The average number of items sold
  4. The average sale amount
  5. The availability corresponding to the number of employee minutes per unit of traffic
  6. The productivity corresponding to the number of sales per employee hours

Proposed processing structure




Automating analysis
We developed a dashboard prototype that was updated weekly with the mentioned indicators.

Deploying tools
This prototype was sent to Spin’s top managers.

Carrying out the strategies
Spin managers articulated the strategies to affect the various indicators and these were communicated to Spin’s various sales points.

Tracking results
The dashboard monitored the impact of the strategies on various indicators.


Spin’s foundation was now laid and they could go on to implement their second objective: Implementing indicators to measure Customer Lifetime Value and the additional anticipated traffic resulting from actions intended to increase this traffic.

Spin’s final objective was to compare the cost and profits of any traffic-increasing action (i.e. advertising).

Competitive advantages:

  1. Maximizing the value of each unit of traffic
  2. Knowing the value of each customer and centering decisions around this value
  3. Identifying customer profiles and personalizing communications strategies to improve customer experience
  4. Understanding the impact of marketing and advertising on traffic and conversion rates
  5. Identifying trends using web data