What is data science and what is it used for?

Data science is the use of statistical and analytical methods to analyze large datasets, perform modeling, discover patterns, and make data-driven decisions. Data science enables businesses and organizations to extract valuable insights from their data. It is also used to make predictions, identify trends, understand customer behavior, develop data-driven strategies, and optimize business processes.

What skills are needed for data science?

Data science requires various skills. These include knowledge of statistics, mathematics, and probability theory, data analysis and visualization skills, proficiency in programming languages (such as Python or R) and database query languages (such as SQL). Additionally, expertise and experience in areas such as big data management, machine learning, and deep learning are necessary. It is also important for a good data scientist to possess analytical thinking, problem-solving, and communication skills.

How does the data science process work?

The data science process typically consists of several steps. First, the problem and objective need to be defined. Then, data collection and data cleaning stages are performed. The data is analyzed, visualized, and modeled. In this stage, statistical methods, machine learning algorithms, or deep learning models are utilized. The performance of the model is evaluated, and improvement steps are taken. Finally, the results are interpreted and reported. The data science process usually continues in a cyclical manner, allowing for the continuous updating of data-driven decisions.

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Data Science

We analyze your data using advanced machine learning methods, enabling us to predict your customers' shopping habits, spending behaviors, and future actions. Based on these insights, we shape your marketing strategies to help you increase sales.

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Data Science

The Key to Capturing Your Customers: Creating Personalized Marketing Strategies with Data Analysis

At Perfist, we believe that a detailed understanding of your customers' behaviors and habits is key to creating effective marketing strategies. That's why we analyze your data using advanced machine learning methods to predict your customers' shopping habits, spending behaviors, and future actions. With these insights, we help shape your marketing strategies to increase your sales

Our Values

Hedeflere Yönelik Çalışıyoruz

Analysis

We use advanced methods such as machine learning and exploratory data analysis to analyze your customers' shopping habits and spending behaviors.

Segmentation

We use advanced methods such as machine learning and exploratory data analysis to analyze your customers' shopping habits and spending behaviors.

Strategy

We use advanced methods such as machine learning and exploratory data analysis to analyze your customers' shopping habits and spending behaviors.

Success Stories

Workindo

It is a platform where you can manage material purchase and sale, team building, job acquisition, and recruitment processes from one place by bringing together construction companies and construction workers. In short, Workindo can be called the meeting point of the construction industry.

Tarım Garaj

Tarım Garaj, headquartered in Konya, is one of Turkey's largest suppliers of Agriculture and Livestock materials. Tarım Garaj, which supplies products not only to Konya but to all of Turkey via e-commerce, continues its successful business life with its wide product range and strong customer relations.

Mühle

Mühle is a well-established company that produces shaving and men's care products, founded in 1945 in Stützengrün, East Germany. All their products are manufactured using traditional handcrafts only from high-quality materials. Mühle is one of the world's largest manufacturers of male care products.

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Frequently asked questions

We Solve the Problems With Our Expert Team

What is customer segmentation and why is it important?

Customer segmentation is a method of grouping customers with similar characteristics into specific groups. This helps identify the unique behaviors and preferences of each group, which can be used to create customized marketing strategies. Customer segmentation is important because it allows for a more personalized marketing approach, which can increase customer satisfaction and sales.

Which data sources do you use?

We use a variety of data sources, including customer purchase history, demographic information, and website interactions. This data includes the name, quantity, price, and date of purchase of products/services.

Which analysis methods do you use?

We use methods such as RFM (recency, frequency, monetary value), CLTV (customer lifetime value), and time series analysis to analyze customer behavior and predict future actions.

Which data analysis tools do you use?

We use a range of tools such as R, Python, SQL, Tableau, and Looker Studio to perform data analysis.

What data-driven marketing strategies do you recommend?

Our data-driven marketing strategies include segmentation, personalized offers, and customer loyalty programs based on each customer's shopping habits and interests.

Customer Feedback

Those Who Empower

Duygu Dülger

Workindo Marketing Manager

After associating with Perfist, our conversion cost has decreased by approximately 20%, and the conversion rate increased by around 30%. We had positive results from the new techniques and campaign types we tested.

Büşra Odekov

Brand Owner

The perfist team is consist of experienced and professional people. Actually, we have witnessed the founder’s delicacy about the team’s qualifications in person. We are aware of the advertisements and activities that are set up are really advanced.