Data-driven customer experience empowers you to take full advantage of interconnected data while building trust, transparency, and long-term relationships.
Naresh Khanduri
Data-driven Marketing
We optimize customer acquisition, improve customer retention and CLV, and enhance the efficiency and effectiveness of digital advertising programs.
Data-driven marketing brings together customer data across your ecosystem to build unified customer profiles and activate personalized and respectful marketing based on customer behaviour, preferences and patterns while carefully complying with all data privacy laws and other regulatory requirements and in a manner that doesn’t feel invasive, unsettling, or untrustworthy to the customer, hence making it Respectful Personalization.
We help you boost revenues and maximize conversions by using data to create an engaging personalized customer experience.
Data-driven Sales
We leverage historical data to forecast sales based on previous sales, market trends and other key factors.
We help optimize your leads and revenues, while fulfilling customer needs by using dynamic pricing of products and services in line with different data trends like demand, seasonality, propensity to buy, storage capacity to name a few.
Data-driven Service
We help combine customer data and service agents’ data to match customer behaviours along with competencies to direct the interactions hence making customers happy and loyal.
Happier customers spend more. Combining customer data with service agent data helps provide a seamless experience to customers which augment rate of retention and boosts service agents’ job satisfaction.
We help detect unsatisfied customers and help increase loyalty through antichurn scoring, intervention by service agents and more.
Data-driven Commerce
Based on a customer’s web activity, we automatically tailor search and category pages which helps increase revenue and ARPU (average revenue per user).
We use customer data and purchasing history to recommend the right product to customers thus increasing revenue and ARPU.
Leveraging data, organizations can calculate CLTV through average order value, purchase frequency, return behaviour, past purchases, loyalty, etc. This can help brands target their efforts on the right customers.