- We facilitate forecasting through Data Science using seasonal and non-seasonal drivers; detecting anomalies and structural shifts.
- With pattern detection, we identify relevant data elements through pattern analysis, correlation analysis and anomaly detection to give you data quality validation.
- With feature design, we build features based on pattern identification level shift adjustments, Fourier transforms, associations and regressed features.
- We give forecast recommendations at multiple levels for anomaly/spike alerts and assessments against historical benchmarks. We also validate actual and forecasted comparison, gap assessment, feature rectification, and model refraining, if required.
- We help you personalize the user experience of your customers’ entire life cycle through deployed enterprise-grade machine learning based solutions.
- Whether you are looking to deploy a scaled one-to-one marketing strategy, personalized web experience, or intelligent chatbots for customer services, Nabler’s AI and ML solutions can help you with better converting CTAs, relevant product recommendations, higher converting landing pages, and enhanced customer loyalty.
- We use probabilistic models to attribute conversion to CTAs or channels or campaigns for effective marketing analysis.
- Through the attribution model, we give you a campaign strategy optimization solution, which is a mix and sequence of the deployment parameters and solution design by gathering DFP’s User ID level log data from Google Marketing Platform with descriptions and integrations of multiple files.
- We also sequence impressions at user ID and bidding rate changes, add meta data for context, provide recommendations on the strongest and weakest links, and attribution modelling of clicks and revenue.
- We give you historical and current behavior attributes that segment visitors in a cluster.
- These clusters are based on product, channel and content affinity, purchase intent, navigational sequence, and level of customer loyalty and engagement.
- For effective customer segmentation, we use key indicators like context information (customer attributes, weather, days, date range and time slot); campaign responses(frequency, recency, channel and content); purchase history of products as in repeat, upsell and X-sell sequence, and browsing history with visitor, session, and hit level attributes.
Our Key Differentiators
The Tools We Work With
Find out how we helped a reputed, multinational IT firm organize and transform their marketing Big Data to prepare for the future. Read the case study.