Kannects is one of the most powerful and flexible data aggregation/reporting platforms in the industry and has been a pivotal solution platform for multiple market research clients and various other entities.
Kannects is built on a cloud-based big data infrastructure designed to utilize the object storage systems of the cloud (Amazon's S3 and Microsoft's Azure Blob Storage) with a parquet compressed data storage format.
The Kannects platform utilizes a distributed query engine which means that it can process a job on a single or across multiple virtual machines on the cloud. This makes it scalable to meet almost any type of service level.
The Kannects data storage and compute capacity are separate and can be scaled independently. This makes Kannects very cost effective. The cloud utilities make it easy to scale Kannects up when needed.
Simple, flexible, and powerful end-user interface provides access to the lowest level data without any requirement for coding or scripting: virtually anyone in the organization can build sophisticated analytic reporting.
The Kannects interface and the underlying processing engine are designed to give users maximum flexibility in defining data dimensions.
Designed for those looking to access the power of the data to address their specific need rather than being forced to use an inflexible visualization of what someone else thinks is needed: data extracts and reports are delivered directly into Excel for easy additional manipulation and visualization.
Users can create custom product definitions by uploading product attribute dictionary files and selecting/combining attributes to define products or other desired groupings
Ability to leverage multiple dictionaries across the product and consumer dimensions: a user can upload their own data dictionary and immediately have all of dictionary attributes accessed through the user interface for selection including an ability to combined values within a dictionary characteristic to create new characteristics
Dynamic segmentations: users can create segments on the fly to gain further insight into consumer, shopper, buyer, or customer-level behavior including loyalty, most-valued customer, new, lost, retained buyers, heaviest consumers, channel switchers, etc.
Powerful consumer analytic models: Trial and Repeat, Source of Volume, Purchase Cycles, Exposed / Non-Exposed lift analytics, etc.
Data Weighting and Projection: Ability to upload target universe incidences for use in an Iterative Proportional Fitting module to balance a sample to match key universe cohorts as specified by an end-user.
Flexibility in a working relationship: We’re open to working with you in a manner that best fits your needs