About APPCARD
Appcard is an AI powered, Loyalty, personalized marketing, digital coupons and customer retention solution, enabling actionable insights into customers. It enables increased sales and ROI by delivering the right message to the right customer at the right time with the help of Machine learning and proprietary algorithms. It can be used by Multi location Retailers and Franchises, and independent grocers and brands.
Appcard collects item level purchase data with customer identities and consolidates it for the AI to work on and create customer profiles with spending habits, and generates promotions and rewards programs that deliver value. Customer check-in and New customer enrollment process is simple involving swiping a loyalty card or entering a mobile phone number.
Appcard Loyalty and Rewards solution enables selecting from a structured and proven program or a customized design that suits the business needs. The Data and Reporting module enables customer behaviour analytics and insights and uses machine learning for customer segmentation based on various criteria.
Evaluating APPCARD for your Customer Loyalty Management need?
Our AI advisor, Wyz, harnessed 2025 insights from peers and experts who used APPCARD to help you determine how well it fits your Customer Loyalty Management needs.
Reviews
Cuspera curates public sources on the Interest such as peer reviews, customer case studies and testimonials and expert blogs along with software vendor provided installation data to help you assess how well APPCARD solves your Customer Loyalty Management needs.
Customer Testimonials
David Speigelhoff
Owner
Gooseberries Fresh Food Market
David Speigelhoff
Owner
Gooseberries Fresh Food Market
Case Studies
Peer and Expert Opinions
for
APPCARD
Goals
Improve ROI and Enhance customer relationships are the most popular goals peers achieved using APPCARD .
Channels
It is the best suited for promotions, coupons, e-mail, channels.
Processes
Peers recommend personalized marketing, loyalty management, engagement management, as the business processes that they have been most satisfied while using APPCARD .
Read Peer and Expert Experience for Business Use Cases
Personalized marketing With Promotions and Coupons
Loyalty management
Create engagement based loyalty With Promotions and Coupons
Engagement management With Promotions
Engaging and following up With Promotions
Social media management
Social media analytics
Campaign management With Promotions and Coupons
Communication management With E mail and User generated content and Blogs
Sending & publishing communications With E mail and User generated content and Blogs
Digital marketing With Promotions and Coupons
Competitive intelligence
Channel marketing With Omnichannel and Mobile and Mobile app
Business development
Sales document management With Offline and Point of sale
Digital signature With Offline and Point of sale and On premises
Contract management
Generation of new leads With Offline and Point of sale
Promotion management With Promotions and E mail
Lead qualification
Lead qualification: technographic
Segmentation and targeting With E mail and Text sms
Lifetime value management With Offline and On premises
Advertisement With Promotions and Display advertisement
Workflow management With Website and Offline and Point of sale
Courses & assessment With User generated content and Blogs
Create learning path With User generated content and Blogs
Helpdesk management
Content management With Promotions
Customer case management
Lead analytics
Contact list management
Training & onboarding
Customer feedback management
Collaboration With Support groups and Omnichannel
APPCARD Alternatives
Peer and Expert Opinion on Features
for
APPCARD
- Low
- Medium
- High
Personalization
Alerts: popups & Notifications
Capture information
Ticketing
Dashboard
IT and Other Capabilities
for
APPCARD
- Low
- Medium
- High
data
Data Import
Data Export
Support
24/7 Support
Chat Support
Phone Support
Email Support
Other
Failure Risk Guidance Security Report ?
Overall Risk Meter
Top Failure Risks for APPCARD
Vendor Profile Details
