Integrated Solution Enables Real-Time Model Deployment Across Entire CDP Profile Database for Immediate Marketing Activation
BlueConic, the world’s leading customer data platform (CDP), announced the release of its AI Workbench, which puts the power of machine learning directly in the hands of the marketing organization to enable more intelligent 1:1 customer experiences.
@BlueConic, the world’s leading customer data platform (CDP), announced the release of its AI Workbench, which puts the power of machine learning directly in the hands of the marketing organization to enable more intelligent 1:1 customer experiences.
Data scientists, business intelligence (BI) professionals, and marketers have come to expect inefficiencies when applying data science to marketing. Marketers are dependent on data science and BI teams for modeling, and when it comes to building models, data science and BI teams are hindered by fragmented marketing data sources and systems.
Read More: SalesTech Interview with John Norton, Chief Revenue Officer at Calabrio
Using AI Workbench, BlueConic customers can now leverage their unified profile database to build and deploy models. Because it is fully integrated into the BlueConic CDP, customers can also test models within the same environment, and then deploy the models in real time to enrich profiles with intelligent customer scores, enable smarter segmentation, and activate marketing based on the output. Additionally, marketers without a data science background can easily select from a gallery of models available out-of-the-box, such as customer lifetime value, propensity to buy/churn/etc., uplift, and lookalike, and then deploy them right from the interface.
“Our customers are already using machine learning in BlueConic for predictive behavioral scoring and 1:1 recommendations, but now we’ve added a solution for both marketers and data scientists who want to build, import, or select their own models,” says Bart Heilbron, CEO at BlueConic. “Due to the close proximity of the model to the unified profile database that is also connected to the marketer’s activation channels, data scientists can now build and deploy a model in minutes and days rather than weeks or months so marketers can build smarter segments for immediate activation.”
Read More: HG Insights Partners with Forrester to Expand Worldwide Technology Adoption Coverage
With AI Workbench, data scientists, BI professionals, and marketers will benefit from:
Access to unified customer data for modeling. A Gartner survey found that 46% of data scientists spend their time doing data preparation for the marketing analytics team. BlueConic customers can stop wasting time pulling lists, deduping contacts, and merging these lists prior to building a model. Instead, BlueConic provides access to a single, profile database for modeling, which includes both anonymous and known customer data.
Immediate deployment of models. Data scientists often can’t create a single model that can be applied across all marketing systems. With direct access to a library of embedded Jupyter notebooks in AI Workbench, models can be scheduled to run at a specified cadence to update profiles and associated segments. These segments can then be passed to activation channels via BlueConic connections.
Enable efficiencies across teams. AI Workbench will help marketing and data science teams realize new efficiencies. Data scientists can spend their time building and iterating on models that will provide greater value. Marketing teams gain immediate access to those models for activation. Together, they can test and learn at an accelerated pace.
“For the last year, we’ve been testing AI Workbench across dozens of our customers’ datasets in multiple industries,” explains Bart Leusink, Data Science Engineer at BlueConic. “Using BlueConic’s database for machine learning enables our customers to realize the full potential of both their machine learning models – and the data scientist responsible for building them.”
Read More: 6sense Secures $27 Million to Advance Bold Vision in B2B and ABM
