Building strong, lasting customer relationships is essential to any company’s success, but the question is how to do it effectively? Sending your customers information that is neither helpful, nor applicable to their interests or preferences is a waste of time for everyone. A meaningful customer relationship must be built on rich, multi-faceted understanding of your customers.
The key to creating a positive customer experience is data. Great data, that is. Data that helps to drive successful campaigns and encourages engagement throughout the customer journey. Data that provides an all-encompassing view of each individual customer, allowing marketers to create detailed customer profiles and cater to specific customer needs and interests.
With great data, you can make the right offers at the right time to the right customers. The Customer Data Strategies for Dummies e-book, developed by Informatica and presented by Trianz, is a great place to start your Customer 360 journey. The info-packed book provides detail into the next-generation customer 360 view, and explains the concepts marketers need to know to manage and use data as the strategic asset it is.
By creating enriching customer experiences based on valuable data and accompanied by the right strategy, companies are able to:
Companies compete on customer experience. With the support of a comprehensive strategy for clean, connected data, marketers can create a complete Customer 360 view. And that lets marketers draw the right insights, predict buying behavior, and deliver a customer experience that is truly a differentiator.
For more insight into how to provide the optimal customer experience visit trianz.com and download the “Meet Rising Expectations for Great Customer Service” paper.
If you find this information helpful, please feel free to share the blog post.
Contact Us Today
Finding Hidden Patterns and Correlations Innovative technologies such as artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) are transforming the way we approach data analytics. AI, ML and NLP are categorized under the umbrella term of “cognitive analytics,” which is an approach that leverages human-like computer intelligence to identify hidden patterns and correlations in data.Explore
The Rise in Big Data Analytics According to Internet World Stats, global internet usage increased by 1,339.6% between 2000-2021. With nearly thirteen times as many people using the internet, this has resulted in a massive increase in the amount of data being processed daily. Our increased sharing and consumption of digital media also compounds this increased usage to create an enormous pool of data for big data analytics firms to process.Explore
What Is an SQL Query Engine? SQL query engine architecture was designed to allow users to query a variety of data sources within a single query. While early SQL-based query engines such as Apache Hive allowed analysts to cut through the clutter of analytical data, they found running SQL analytics on multi-petabyte data warehouses to be a time-intensive process that was difficult to visualize and hard to scale.Explore
The Cloud is the Key to Transformation Success… Transitioning your applications to the cloud is undeniably a critical factor to a successful digital transformation endeavor. It’s more than just a lift-and-shift, however. Let’s explore several things that you need to consider before migrating your applications to the cloud, including: Readiness of your application portfolio Where to begin – the right business case and migration strategy Technology requirements and considerationsExplore