Mylist Platform Thrives With Diversity via NamSor Algorithm Software

Dubai e-Retailer can better target customers

NamSor Algorithms help Mylist platform to leverage information from its current customer database; changing the direction, future, and finances of the company!

NamSor software, which determines Ethnicity, Origin, and Gender of an individual based on their name and surname, has delivered tremendous results to the company Mylist in Dubai. Mylist is a Gift & Reward e-commerce platform that allows you to create online gift lists for weddings, birthdays, baby showers, and other social events. Operating in Dubai, a global city known for its diverse cultural communities, the Company is looking to benefit from the cultural wealth of one of its most valuable assets: its customer database!

As a Data Scientist, Baptiste Quidet, the data scientist, based in Dubai, who conducted the analysis said, “Working both for Mylist and for NamSor, my main responsibility is to connect NamSor’s software to Mylist’s customer database. After some work and data preparation, I linked NamSor API to Mylist customer tables in Power BI. The results of this project have truly been useful to Mylist’s analyst team, as NamSor’s software really helped to confirm views on portfolio identity and/or sometimes disprove common misconceptions about specific business situations. For instance, the study showed, with a high confidence level that an individual from Saudi Arabia spends on average on Mylist platform, twice as much as an individual from the U.K. In a similar confidence level, the analysis proved that participants of gift lists are more likely to be female.” This information is quite valuable when targeting a particular market.

Furthermore, this information gleaned by NamSor Algorithm Software serves as a guide on the statistical learning side and giving its users an edge for predicting revenues. Mr. Quidet went on to say, “The results showed that by simply adding features for gender and origin, Mylist could improve its precision rate by 25%! Then, each origin became a categorical feature in our predictive model, and it improved precision in the prediction of online orders and total revenue.”

How does Data Science add value to the business model?

Mylist has been growing at a steady pace across various countries throughout the Middle East. We centered our analysis on one of its numerous databases; the Business to Customer segment, which now has a strong foothold in Saudi Arabia and Egypt, as well as its main business location, the UAE. In order to capitalize on the wealth that the database has to offer, it was fundamental to fully understand who the customer is, as well as understanding their needs. To better understand the customer, we decided to focus on their country of birth. In addition, we also determined how long the customer had been currently living in one specific location, which could help us to determine their specific needs in order to customize our services, tailoring it to them specifically.

How does NamSor add value?

Data scientists for companies prefer to use NamSor as it is easy to make requests to its API, especially with the launch of V2. NamSor covers all languages and alphabets and has worked with linguists, anthropologists, and historians to identify the origin of diasporas across the globe. We used an integration with Power BI, which was very hands-on, and added additional tables including Gender and Origin, with a score associated with each individual to provide information on the confidence level. The geographical map in Power BI recognizes country code, sub-region or region.

We can then illustrate metrics such as: the average spent on the platform per region/country, and use it to investigate further data records.

At last, in regards to the predictive model, adding NamSor add-on gave stronger statistical results for model precision.

In the linear regression model, the adjusted coefficient of determination R^2 has improved by 60 basis points. We did this by using gender and countries of origin of the host, from 87.8 to 88.4%. We also noticed that by informing the model of gender and countries of origin of the host, we reduced the error rate (Mean Squared Error of estimated versus target value) by 25%.

We can also see the improvement in the Learning curve of the final model, who tries to predict the revenue per gift list with Polynomial model.

It is clear that NamSor features for Origin and Gender help modeling revenue of the gift list business. Indeed, as we identify consuming patterns among nationalities and geographic areas, we empower management to make better-targeted and educated marketing strategies. 


"Machine learning techniques" can be easily applied and companies with fast-growing business models such as Mylist can benefit very quickly from numerous open-source libraries to feed live information into data-process pipelines to get the Business Intelligence they need for their business instantly, and with limited resources. NamSor best illustrates how to leverage the potential of a customer portfolio very simply and for any business sector. Thanks to its API, we also proved that it improves the performance of machine learning models. With a more globalized and connected world, diasporas are increasingly moving, and a company that depends on knowing their customers will be challenged to keep track of their base. Therefore, it is fundamental that companies apply these techniques to follow migrations, as well as the evolving needs of their customers.

About NamSor

NamSor™ Applied Onomastics is a European vendor of sociolinguistics software (NamSor sorts names). NamSor’s mission is to help business owners and their management teams better understand international flows of money, ideas, and people in order to maximize profits and streamline efficiency.

Source: NamSor


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