Retail Banking

Use Case - Drive continuous engagement across channels and products

Where maya.ai operates across customer lifecycle First 90 Spend Travel Reactivation days activation Current zone of Digital influence Eat Referral/ engagement Category advocacy activation Share Shop of wallet New Silent Acquisition Attrition Lend Insure Save Data: Lack of external data means reliance on Engagement: Fragmented communication leads to demographics and transactions. maya.ai enhances suboptimal impact. We combine multiple channels & use actions with behavioural preferences combined with cases into 1 digital personalised engagement touchpoint. contextual interactions

Customer journey framework for banking products personalization ACTION CHANNEL PRODUCT ACTION CHANNEL PRODUCT ACTION CHANNEL PRODUCT TRIGGER 2 TRIGGER 4 T TRIGGER 1 T TRIGGER 3 TRIGGER 5 T 0 +15 +30 Product mix: ACTION CHANNEL PRODUCT ACTION CHANNEL PRODUCT Product holding (savings a/c, finances, etc.) Behaviour Mix: Spends on merchants, increasing balances etc. Optimized approach towards Automated orchestration Freedom to customize driving customer value via the platform triggers and actions

Cross channel engagement for sample persona 1 Automated Offer Automated notifications that 3 Automated 5 7 recommendation 1 communication highlight nearby communication to at Kofuku and 5 to the customer merchants with the customers other restaurants discounts Offer Supplementary Salary transfer recommendations Card Spend increase for Debit Cards SMS / Email: 1 day after App: Nearby deals notification SMS: 2-3 days later App notifications: 3 weeks later T + T + T Transfers the same Multiple branch visits for 15 Transacts at Hamleys, Toys 30 Frequently transacts with Urban Kitchen amount from outside checking balance ‘R’ Us and Kofuku accounts Persona 1 SMS –On the same day SMS: 60 minutes from RM: 1 week later purchase Product mix: Has a savings a/c and a Mobile App Premium DIning debit card Activation Spend Increase Card Behaviour Mix: Automated Offer Customer is message to the recommendations profiled and sent Impulse buying 2 customer 4 for merchants like 6 to the CRM along Hamleyssent with the attributes Excessive spending Transacts on dining and lifestyle merchants Product Action

Cross channel engagement for sample persona 2 Automated Automated 3 Customer profiled 6 8 Offer communication message sent on and sent to the recommendation 1 to the customer Whatsapp/SMS CRM along with at Kofuku and 5 the attributes other restaurants Personal Finance WhatsappBanking Forex Prepaid Spend increase Recommendation Card SMS / Email: 1 day after SMS/Whatsapp: 1 week later RM: 1 week later App notifications: 3 weeks later T + T + T Personal Loan matures in Repeated usage of the app for 15 Transacts at SpiceJet multiple 30 Historically made high ticket 30 days transferring and maintenance times purchases in the auto category Persona 2 SMS: 60 minutes from RM: 1 week later purchase RM: 1 month later Product mix: SMS –On the same day Has a current a/c and a Digital sales for Spend Increase Car Finance Motor Insurance credit card Personal Finance Spend Increase Behaviour Mix: Staycations and Offer E-mail sent to the In-app notification hotel recommendations SMS/E-mail sent customer to the selected recommendations for merchants to the customer recommending Tech-Savvy 2 customer 4 sent to the 5 similar to Spicejet 7 motor insurance Automobile Enthusiast, customer via e-Mail Frequent Flyer Future Entrepreneur Product Action