Effective marketing has long been dependent on gathering and understanding data resulting from consumer behaviors and preferences. In the emerging world of Big Data, the mountain of information available about every aspect of the marketplace can overwhelm analysts who search for insights and market signals. As a result, marketing is and will continue to benefit from advances in machine learning and data analysis algorithms. In this article, NearShore Technology looks at current trends related to machine learning and developing customer insights.
The Power of Analytics
Understanding customer preferences through data analysis has long been a key part of effective marketing. Effective analytics can guide decisions about providing content and offers to particular customers and allows firms to immediately address customer needs and concerns. The power of modern computing and machine learning is improving the quality of analysis in ways previously out of reach for even the largest companies.
Machine Learning and Predicting Customer Preferences
Machine learning and AI support advanced customer insights based on patterns found in past customer information. Adaptive algorithms learn from patterns in predicting current preferences and providing curated marketing proposals for particular customers in real-time. Machine learning can manage immense customer data in immense volumes in ways unreachable by traditional analytics. Modern algorithms can learn from prior mistakes and self-modify to more accurately predict future preferences. Broad changes in market conditions and other external factors can also be analyzed to fine-tune predictions based on current and historical data. Analysis through machine learning is also far less dependent on how clean and curated customer data is than traditional analysis.
Direct and Individualized Contact Through Machine Learning
Obtaining customer input through surveys and focus groups is notoriously difficult. Machine learning and AI help make this process much more effective through individualized contact at times most likely to find customers more receptive to providing feedback. Through email, texts, social media, and offers provided at the point of sale, firms can motivate customers to interact in real-time through specialized offers and other motivations to respond with meaningful data. Developing AI and machine learning tools can use customer incentives to set up online focus groups that provide nuanced and highly valuable data produced through group interaction that can be much more useful than one-way surveys.
Machine Learning Transforms Social Media Into Social Listening Tools
Social media platforms can provide data in quantities that swamp normal analytic tools. Machine learning technology provides efficient techniques for analyzing both individual and group market preference data immediately and in ways previously unavailable. Social media tools can gather input from customers and the general public that can be used to formulate advanced AI analysis and predicting trends. For example, the changes in consumer behavior in the aftermath of the Coronavirus pandemic are both certain to occur and extremely difficult to predict. Using social media to solicit customer opinions and how behaviors are likely to change in response to the public health crisis can provide valuable insights into future marketing strategies in an evolving marketplace.
About NearShore Technology
NearShore Technology is a US firm headquartered in Atlanta with offices throughout North America. The company focuses on meeting all the technology needs of its clients. NearShore partners with technology officers and leaders to provide effective and timely solutions that fit each customer’s unique needs. NearShore uses a family-based approach to provide superior IT, Medtech, Fintech, and related services to our customers and partners throughout North America.