From non-customers to becoming active, happy customers, we pave the journey by converging and optimizing best customer engagement practices and advancements of AI in data science for your businesses.Services
We offer solutions that measure your customers’ perspectives and map out their journey while incorporating contextual engagements that balance between customer satisfaction and confidentiality.Solutions
Why Priority Dynamics?
Our team is a combination of experienced marketing and customer management specialists and highly skilled data science practitioner, ready to work collaboratively and creatively on the data-driven projects that transform how companies do business. We explore, visualize, share insights and deploy optimized models that will help businesses to adopt and implement analytical initiatives in data management replacing traditional evaluations. Below are some of the business solutions we have performed and enabled using our customizable data processing systems and Artificial Intelligence.
Replacing Traditional Market Surveys Using Telco Data
Traditional market surveys take time and effort to generate market insights, which by the time it reaches the audience its relevancy degrades. Using rich telco data, not only that the personal information can be securely guarded, this system is able to produce up-to-date and wider insights that are easier to refresh, thus, making the whole exercise more cost effective and practical.
Detect Shift In Revenue Pattern Using Segment Migration Modelling
Ever face a situation where there’s no net growth of revenue even after multiple campaigns reported to have positive take up rate? That’s because the campaigns are reducing the revenue of other products and the effect of future spending is being brought forward to present data, causing minimal to no change in consumer behavior that contributes to the revenue growth. There is no point running more campaigns if the data is not measured and tracked correctly.
Lead Generation And Qualifying Big Data
Public domain and social network provide high volume of data that mainly consist of incomplete, noisy and unreliable information. Filtering these data can provide triggers for customer awareness or acquisition initiatives. Coupled with telco data, data monetization can be a practical and profitable business.