Customer behavior analytics, is important to understand how users interact with a brand, now it can be done in a more objective and real way, using Big Data management techniques.
Customer behavioral analytics is the process of collecting and analyzing data that, together with technology tools such as Big Data, machine learning and location intelligence, help gain long-term insights into average purchase value, customer lifetime and user interaction with a brand, enabling companies to incorporate data-driven business strategies that facilitate decision making and revenue maximization.
Also Read:”Supply Chains Predictive Analytic benefits“
This type of analysis is already used by streaming platforms such as Netflix and Spotify, which are constantly striving to learn more about users’ tastes and preferences in order to personalize and improve their experience.
How do they do this?
This technological tools record data on customer behavior, buying habits, favorite products, etc., thus predicting which products customers might be interested in and when they might want to buy another product.
Equipped with this data, buying behavior patterns that are typical of a target audience are established, producing unified reports that answer questions such as:
- What is the most common time of purchase?
- What are the main obstacles to completing an order?
- What aspects of functionality and design were misunderstood by the user?
- What areas should you focus on to bring tangible improvement to your customers?
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Real time Feedback on a product or service with the help of machine learning, allows you to adapt services to the preferences of each customer as they use it.
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How does the implementation of these tools help?
- They understand customer habits and motivation by providing a unique perspective of online and physical stores, creating indicators of how customers view a business.
- They identify and anticipate customer issues, such as product, store or service design failure, thus maximizing purchase conversions.
- Maximize marketing campaigns by modeling potential customers and targeting them with effective advertising based on patterns of purchase transaction behavior, locations and product favorites, optimizing costs.
- Segments target audiences into groups based on their characteristics, including location, gender, age, status, education and occupation, determining average search history, purchase frequency, value, urgency and customer shopping experiences.
- It allows you to create a competitive analysis that consists of analyzing competitors’ products, strategies and performance, thereby improving your own products and services and gaining competitive advantage.
At PREDIK Data Driven, we build customized customer research solutions that are based on big data, machine learning and location intelligence, helping our clients gather information and turn it into actionable insights for decision making.
Do you need customized solutions to identify your customers’ behavioral patterns? contact us!
