Food ordering has evolved!
We use AI and smart algorithms to help restaurants and delivery apps
increase sales and margins in new exciting ways
We use AI and smart algorithms to help restaurants and delivery apps increase sales and margins in new exciting ways
Elevating profit in a low margins market
Elevating profit in a low margins market
Kollective’s smart methods and CTAs are automatically enacted in the most effective way during the ordering process. Not only do they encourage consumers to order more, they dramatically optimize delivery and boost efficiency.
Forming food-oriented communities
Once integrated, Kollective is using available data to:

Map clusters of users per their location.

Define groups in these clusters as communities per their preferences and belongings.

Leverage individuals connectivity in these communities’ to create effective interactions that drive sales.

THE KOLLECTIVE ECOSYSTEM
Kollective takes mobile engagement automation to the next level while forming a unique eco-system, where users, restaurants and delivery apps profit.
Restaurants
Tell us they love the platform, because they benefit from boosts of high value orders and much lower costs of delivery.
Kollective’s predictive tools grants restaurants the flexibility to manage supply based on communities’ demand in an optimal, profitable way.
Consumers
Enjoy a unique experience providing them an easy, fun way to order food and save a lot of time and money.
Delivery services / companies
Enjoy increased sales with profitable, aggregated orders by location (optimised logistics).
AI-based CTA, prediction and promotion
Kollective uses AI and prediction algorithms to create effective CTAs, promotions and user engagement, while boosting efficiency.
Learning about a community’s behavior, effective connections and members’ habits, along with real time analysed interactions and demand figures, allows Kollective to:
Use smart, effective real time CTAs that incentivise sales and prevent abandonment.
Optimise logistics by affecting orders location and frequency.
Prioritise order display by dynamically learned interactions and influence.
Promote and sync supply in a restaurant with demand in a community.
Enable ULTRA-FAST delivery by predicting desired dishes.
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