Selecting the right restaurant app solution for your restaurant can be challenging. Many small to mid-sized restaurant brands recognize the importance of digital ordering and guest engagement but are not sure how to select a mobile app solution that their guests will actually adopt and use.
The key to introducing a successful mobile app is to find a solution that does more than simply allow guests to place orders from their phones. Below are five features to look for to ensure your mobile app actually engages guests and keeps them coming back.
Select a mobile app provider that creates native mobile apps for your restaurant brand as opposed to one that features your brand as part of their own marketplace. This way, guests can use the mobile app to interact with and create accounts with your brand directly. If your mobile app provider is also your online ordering provider, this will also allow guests to have a consistent experience across all first-party digital ordering channels.
Make sure your restaurant app solution offers a high level of customization when it comes to branding and images. Think of your mobile app as your digital storefront. Your guests want to see your food, not stock photos. Your mobile app should feature your branding, your logo, and your images across menu categories, items, and even down to the modifier level.
Since guests are creating accounts with your brand directly, having a built-in loyalty program is a great way to reward them for using the app and to keep them engaged. Look for a mobile app with flexible points and punch-based loyalty, which also makes it easy for guests to automatically earn and redeem rewards as they place orders and interact with your brand.
Help guests find new menu items and increase your avg. ticket size with a cross-sell and upsell engine that's built into the app ordering flow. Make sure this feature is automated and does not require you to create manual if/then statements in order to suggest items. If the upsell recommendation engine leverages machine learning, it will be able to autonomously suggest items based on same-store sales, what other guests typically purchase together, and avoid recommending items that could replace anything the guest has already added to their cart.