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Solution-Tree Framework | Yara Rewards Program, How to improve customer…
Solution-Tree Framework | Yara Rewards Program
How to improve customer enrollment to the rewards program?
Redemption process should be smooth
Points getting credited to customer's bucket instantly
Save member preferences and auto fill while check out redeem products
Enriching Customer service
Providing customers with online Voice-based/ text-based chatbot support to assist farmers while using the rewards platform (P2)
Integrate with third party chatbot applications(P2)
Implement Natural language processing based Voice assistants (P3
Collect Customer feedback before and after the rollout of new features on the Rewards platform (P1)
Integrate Qualtrics to collect Net Promotor Score and Event-based feedback surveys ( when the user redeems, etc.) (P1)
Reward options should deliver value to farmers
Value as a product
Redeem rewards can offer cross-bundled products to users. Example user can redeem 3kgs of fertilizer worth points and get 1 kg of pesticide free (P3)
Value as a service
tie-up with third party vendors in the region offering agricultural equipment on rental basis
loyalty program
Providing customers with a farmers credit card and crediting earned points which can be redeemed via both online & offline channels (P3)
Providing customers with a crop insurance plan as a reward bonus will help them save the crop from any natural disaster
Increase memberships
Reward Word of Mouth:
Allow single sign on connectivity to social media apps (P1) via Rewards platform
Reward a member for sharing a post on any social media app (P1)
Make sign up superfast : take minimal information which is required - this will increase sign ups
Reward a member on sign up (P1)
Provide an Omni-channel Rewards experience to customers - Store, Web, Mobile
Reward a member for purchasing online or in-store (P2)
Engage current members and attract new ones
Gamification
Reward farmer for completing an activity on the platform like completing a reveal card, playing an audio/video, quiz etc. (P3)
Leverage Customer 360 degree Data to provide personalized recommendation to every member
Capability of Predicting a customer's future order / interest in a redeemable product (P4)
Using advanced Neural networks based machine learning model to perform predictive analysis and recommend products to a particular customer (P3)
Segmentation of customer persona
Enrolled versus Non-enrolled
Demographic information
Geographic information
Integrate the Rewards platform with other Yara web and mobile, POS, and In-store applications to fetch customer metadata (P1)
Integrate with Google Analytics/CRM vendor to get customer 360 Data (P2)
Understand user behavior on the rewards platform by integrating with Google analytics to get transactional member data - No. of orders, average order value, most redeemed product, etc (P1)
Provide a recommended product to the member based on purchase history (P1)
Promote upselling by selling related products (P2)
Promote similar products which are redeemed the most (P1)
Use the news feed to highlight promotional offers for the most purchased product by a member (P2)
Use the k-means clustering model to perform customer segmentation (P2)