Customer Analytics

Identifying, attracting and retaining the right kind of customers is key to the success of any business, so having the right tools is essential to maximizing your potential. The best way to learn about your customers' preferences and behaviors is with customer analytics, which helps you visualize your customer data and allows you to deliver personalized, relevant messages at exactly the right times.

Customer Analytics plays an important role for companies in fully recognizing their customers' interests and preferences. And if you can use this data effectively, it will always be easy for your company to achieve the kind of development and success it deserves or expects.

As anaplatform, the aim of our Customer Analytics service is to respond quickly to market opportunities of companies, to develop product offers and to improve customer satisfaction. Our Customer Analytics service will be answering all these questions.

What Does Customer Analytics Do For You?

Customer analytics enables you to use customer behavior data from the organization to help important business decisions through market segmentation and predictive analysis. Our analytics help you understand what tactics, products and services your customers will be interested in.

MainPlatform offers you advanced customer experience technologies. It allows you to connect with your customers and better understand what they honestly think. You can discover key relationships and patterns that can help you improve your customer service operations and improve your results.

With Customer Analytics, we offer models to identify, differentiate and predict customer behavior to support your marketing teams. Dilerseniz bu modelleri sizinle beraber geliştiriyoruz.

• Define customer segmentation with machine learning models,
• Target potential customers with location model,
• Measure customer turnover, identify risks and find new leads,
• Monitor loyal customers,
• Department and basket analysis,
• Analyze customer satisfaction,
• Controlling & declining goods and warehouse inventory,
• Monitor the income and expense balance between branches.

This is how we can count Customer Analytics types according to their methods;

• Descriptive analytics
• Predictive customer analytics
• Customer Experience Analytics
• Customer Engagement Analytics
• Customer Retention Analytics
• Customer Lifetime Analytics
• Voice of the Customer Analytics

Bankacılık için Müşteri Analitiği

Banking services are changing at an unprecedented rate. Banks are balancing many priorities, including managing revenues and low interest rates, alongside the growing demands of customers changing their behavior as they deal with their own financial pressures. How you deal with these challenges will not only determine the future of your bank's brand; will significantly affect your customers and employees.

anaplatform's Customer Analytics Solutions are designed to help Banks meet both consumer demands and employee needs while adapting to changing regulations. They help banks unlock more meaningful customer relationships and create new business growth opportunities. And with enhanced data insight, they are in a better position to predict what customers want and transform the way they engage and interact with them..

E-Commerce Customer Analytics

The first step in customer acquisition for e-commerce companies is to ensure that the consumer takes the first step into the sales channel. We use communication channels to promote our product/service and persuade the user. The most common acquisition channels; Paid performance advertising channels such as Google, Instagram and search engines where we get organic traffic with search engine optimization -SEO- come. The aim is to ensure that the most suitable customer with high purchasing potential visits our website and downloads our application. Common performance indicators are return on ad spend ROAS, cost-per-acquisition CAC, click-through rate CTR, and Bounce Rate metrics that measure the interest of the page visited and the incoming user..

Birliktelik Kuralları Analizi ile Birliktelik Kuralı Yöntemleri ile E-Ticaret Satışlarının Analizi

Birliktelik Kural Çıkarımı (Association rule mining), büyük veritabanlarındaki değişkenler arasındaki ilginç ilişkileri keşfetmek için kural tabanlı bir makine öğrenme yöntemidir.

Nasıl Çalışır?

• Minimum Destek ve minimum Güven parametre değerleri belirlenir.
• Veri seti taranarak her bir ürün için tekil olarak frekans sayıları (Destek değerleri belirlenir.
• ukarıdaki işlemin ardından ürünler ikişerli olarak gruplanarak frekans değerleri elde edilir.
• Aynı şekilde üçlü, dörtlü vb. gruplandırmalar yaparak gruplara ait frekans bilgileri ile Minimum Destek değeri karşılaştırılı, uygun olmayanlar çözümlemeden çıkarılır.
• Yukarıdaki işlemler bittikten sonra Nitelik Kümesi (Itemsets) ortaya çıkarılır. Güven parametre değerinin üzerinde olan ürünler ile kurallar oluşturulur.

Sigortacılık Sektörü için Müşteri Analitiği

Sigortacılık Sektörü müşteri kazanmanın zor olduğu sektörlerden birisidir. Yeni sigorta müşterisi, diğer herhangi bir rekabetçi hizmet endüstrisindeki müşterilere çok benziyor. Kendi kendilerini yönetirler ve istediklerini elde etmek için çeşitli kanallardan alışveriş yapmaya hazırdırlar. Ayrıca ihtiyaçlarına uygun benzersiz deneyimler arıyorlar.

Bu tür bir rekabet baskısı, sigorta şirketlerini müşteri odaklılıklarını artırmaya itiyor. Bu, ürün odaklı satıştan ihtiyaca dayalı özel tekliflere önemli bir kültürel ve teknolojik geçişi içerir. Bu, son derece kişiselleştirilmiş iletişim yoluyla müşterileri çekmek ve elde tutmak anlamına gelir. Bu yeni müşteri merkezli dünyada, müşteri ihtiyaçlarını ve tercihlerini gerçekten anlama yeteneği, müşteri sadakati oluşturmak için çok önemlidir. VeriPark bunu başarmanıza yardımcı olabilir.

Uygulama Örnekleri

• Binanın seçilen fiziksel özellikleri ve bina için ödenen vergiler (yerel, okul, ilçe) bir evin satış fiyatının tahmin edilmesi.
• Yaş, eğitim, gelir ve sigara fiyatı gibi çeşitli sosyoekonomik ve demografik değişkenlerin bir fonksiyonu olarak sigara tüketimini tahmin etmek.

Müşteri Analiz Örnekleri

• Market Basket Analizi
• RFM Analizi
• Kampanya Etkinlik Analizi
• Kârlılık Analizi
• Müşteri Yaşam Boyu Değeri

Loyalty Management

Today's consumers demand services that go beyond their basic banking needs and expect to be rewarded for their loyalty. Built on anaplatform's powerful Customer Analytics, Loyalty Management Solution offers financial institutions an end-to-end loyalty management system that promotes loyalty and long-term relationship with customers while accelerating customer spend and retention. It enables financial institutions to maximize their customer value with personalized rewards in line with their expectations.

Our omnichannel loyalty solution helps create highly flexible loyalty and rewards programs that are integrated across all industries, with platforms ranging from online and mobile to kiosks and POS terminals. Programs can be multi-layered and cumulative; The more customers interact with the services, the more rewards they can earn. By implementing the Loyalty Management Solution, companies can also run co-marketing campaigns with selected trade chains and redemption partners.

Smart Customer Segmentation

Customer segmentation is the cornerstone of effective business management, marketing and product development in all consumer industries. Many firms have developed in-depth business knowledge that applies to pools of customers using the logic of business rules, subdividing the overall customer base based on actual or potential revenue, product mix, digital engagement, and much more. This current customer analytics provides powerful insight and is often driven by qualitative insights or historical practice. For example, 82% of their managers say their teams have difficulty identifying new customer segments, which can increase their acquisition costs and reduce their retention rates. Leveraging a purely data-driven approach to segmentation opens up the possibility of new perspectives that complement rather than replace existing expertise.