Project Description

Case Study

“A forecast is like a compass, it guides your steps, and you need to re-do it or re-check it often, to get a grasp of the constantly changing situation.”

Vicent Botella Soler
Innovation & Machine Learning Manager, ForwardKeys

Retail tourism is becoming a more important market year by year. The current question is how to create an effective marketing campaign to attract these international tourists?

This case study focusses on a large luxury retail store with multiple establishments. The retailer works together with many well-known luxury brands operating all over the world. They are not just experts in selling products but also offer meaningful experiences. For example, changing in-store themes according to the season, such as Christmas. They are constantly innovating and improving to stay ahead of the competition and maintain their position as a market leader.

The background

Keeping up with the fast-moving tourism market

The tourism market shifts incredibly fast and each year brings new tourists from different countries to a destination. The issue The Westin faced was that they were not able to predict who their future target audiences would be, and when they would book. This was caused by the fact that they only had historical data and were not able to view traveller movements from a broader perspective.

Firstly, it had a negative impact on the accuracy of their room rates which therefore negatively impacted on the revenue.

Secondly, it meant that the marketing budget was not used optimally. They misspent the budget on marketing their property at the wrong places, to the wrong audiences as the majority of visitors would come from a different country.

The objective

Is ForwardKeys’ data representative?

The retailer had several needs. First of all, they needed to check whether there was a correlation between our data and their data. This was incredibly important as it would be the foundation that would demonstrate that our data could be used to fill the information gaps for the retailer, as well as help with further needs regarding retail tourists.

These needs consisted in the following:
• They wanted to get a better understanding of their international travellers in order to create a customer profile.
• The retailer wanted changes in sales to these tourists to be explained.
• They needed the ability to forecast sales made to the potential retail tourist.

The solution

The use of a correlation analysis

To establish that our data was relevant to this retailer, we offered to carry out a correlation analysis.

To perform this analysis, we took some of our client’s sales data and compared it with our data on traveller flows. If the results showed that there was a correlation, it would mean that we could now use our platform to explain past and future sales, based on the travellers at the location.

For example, if there was a sudden increase in sales, we could see where visitors came from during that period, and our analysts could help explain the reasons behind these sales trends.

Finally, and most importantly, this meant we could provide the retailer with forecasts which were incredibly useful for their retail tourism marketing campaigns, and for forecasting future sales.

The results & continued work

Possibilities of ForwardKeys’ data

The results of this correlation analysis showed a near-perfect correlation, which allowed us to use our database to create profiles for the retailer. After conducting the correlation analysis, we were able to add some characteristics to the target group.

In this case, it was shown that their customers mainly travelled in a group of at least 2 people and stayed at least 1 night at the location of interest. This information allowed the retailer to adjust their marketing strategy to fit people with these characteristics.

Because of the close correlation, we now can inform them regularly about the evolution of these particular traveller profiles. This helped them significantly with their marketing. With this information, they were able to spear-head the retail tourism sector by using a more targeted marketing mix that matched the needs of the real travellers interests.

To create an effective retail tourism marketing campaign, we also provided them with several other reports. An example is the destination and forward 90-180-270 report. In our reports case study we explain how these reports were used in more detail.

In conclusion, through the historic analysis of the sales performance and our correlation analysis, the client gained an understanding of the expected sales performance in the coming 3 – 4 months. With this information they were able to plan in-store staffing, promotions and products offerings based on the nationalities that would be visiting at the various times. Hence, using their marketing budgets more effectively for a higher ROI.

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