MoEngage is an AI-powered customer engagement platform that orchestrates personalized marketing across push, email, in-app and web channels.
MoEngage helps consumer brands understand and engage users through a customer data platform, journey orchestration and AI optimization. Its Sherpa AI engine predicts churn, optimal send times and next-best offers per user, while the platform unifies behavioral data from apps, websites and offline sources. Campaigns run across push notifications, email, SMS, in-app messages and web personalization from one console. It is widely adopted by mobile-first businesses across Asia, and increasingly globally.
MoEngage is sold as an enterprise subscription based on monthly active users and channels; pricing comes from the sales team.
Mobile-first consumer brands — retail, fintech, media, travel — that run large-scale lifecycle marketing and need AI optimization over their own behavioral data.
Retail brands trigger cross-channel journeys when carts are abandoned, switching from push to email based on what each customer actually opens. Media apps use AI send-time optimization to lift engagement without increasing message volume.
Connect your apps and data warehouse, import customer profiles, and run one high-value journey before scaling to a full campaign calendar.
No self-serve free tier; demos and enterprise pricing are arranged with the vendor.
Yes — comprehensive APIs cover event ingestion, user attributes and campaign triggers.
Versus Braze or Iterable, MoEngage competes on mobile push depth and price-to-value, especially for APAC-based businesses.
Pricing is based on the number of profiles and channels you engage; most mid-market customers start with a subset of channels and expand as journeys prove value.
MoEngage is aimed at growth-stage and enterprise teams; smaller businesses with simple needs may find lighter tools more economical.
Push notifications, email, in-app messages, SMS, web push, on-site messaging and WhatsApp orchestrate inside one journey builder, with per-channel optimization deciding how each customer is reached. Teams manage the whole mix without separate tools.
Algorithms optimize send times, channel selection and content variants per individual user, learning continuously from engagement signals across your customer base to improve campaign performance.