{"id":185240,"date":"2023-05-11T10:47:49","date_gmt":"2023-05-11T02:47:49","guid":{"rendered":"https:\/\/www.grab.com\/sg\/?post_type=editorial&p=185240"},"modified":"2025-11-26T12:13:45","modified_gmt":"2025-11-26T04:13:45","slug":"personalising-food-recommendations-on-grabfood","status":"publish","type":"editorial","link":"https:\/\/www.grab.com\/sg\/inside-grab\/stories\/personalising-food-recommendations-on-grabfood\/","title":{"rendered":"Personalising food recommendations on GrabFood"},"content":{"rendered":"\t\t
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Consumers are spending an average of 17 minutes browsing on GrabFood before placing their order, according to our 2022 food and grocery trends report<\/a>. Some 74 per cent also browse without a particular cuisine in mind.<\/p>

While we\u2019re proud to offer a wide variety of options to choose from, we want to help to serve up what the user wants, to help them get to a suitable choice sooner.<\/p>

To increase the likelihood of users finding something they like, we use machine learning-driven search and recommendations to create personalised food discovery experiences.\u00a0<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Learning what users want<\/h5>

User behaviour on the app such as order history and clicks gives us a good sense of the likes and dislikes of the user.<\/p>

Over time, the recommendation system will form a more accurate profile of a person to give us deeper insight into their culinary preferences at different times of the day, budgets and willingness to wait for orders.<\/p>

What users want to eat varies throughout the day. About two in five consumers snack at least once a week across the region, with cravings hitting most frequently at teatime between 3 and 5pm, according to data from our report.<\/p>

(Read more:<\/strong> How Southeast Asia ate in 2022<\/a>)<\/p>

The top teatime food order in Vietnam last year was fresh spring rolls while that in Indonesia was dim sum. Across the region, drinks like milk tea and coffee were popular at teatime.<\/p>

We take such information into consideration to generate a list of personalised options for each user on the home screen of the app.<\/p>

On the other hand, users who already have a dish or restaurant in mind should be able to cart out their items as seamlessly as possible.<\/p>

For example, those who frequent the same restaurant can repeat the order quickly through an \u201cOrder Again\u201d section, without having to start a search from the top.<\/p>

Our search algorithms also ensure that users can find what they are looking for with ease by ranking search results based on historical data.<\/p>

For instance, if a user consistently patronises the same restaurant every time she searches for Japanese food, that particular restaurant could emerge as the top search result for the user when searching for Japanese food in the future.<\/p>

It\u2019s different in every country<\/h5>

Even as we continue to fine-tune our algorithms and recommendation system, we have to take into account that we serve a vast, non-homogenous region with diverse tastes and preferences.<\/p>

That\u2019s why respective country teams also play an important role in crunching data and customising sections on the app in order to curate options that cater to the local palate.<\/p>

For instance, we observed that local food still dominated most markets last year. In Vietnam, bahn mi emerged among the top trending food orders for the year. In Malaysia, people popularly ordered roti canai and nasi lemak.<\/p>

Helping users find more<\/h5>

While having the app know you is more convenient, users have told us that part of the fun of looking through a delivery app is in getting ideas for new options.<\/p>

So we also increase the chances of discovering new food options on our platform. One way is to present options that deviate slightly from their go-tos.<\/p>

We also recommend substitutes or similar options when a search for a particular dish or restaurant is unavailable, or has very few matches.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\tFresh recommendations help prevent users from dropping off the app when they can\u2019t find what they are looking for.<\/b>\t\t\t<\/p>\n\t\t\t\t\t<\/blockquote>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Grab\u2019s food trends report showed about 88 per cent of consumers have discovered a new store through delivery apps while 90 per cent have ordered from a store they have not tried in person.<\/p>

Fresh recommendations that are related to their search query encourage users to consider substitutes that will satisfy their cravings, and prevent them from dropping off the app when they can\u2019t find what they are looking for.<\/p>

Another discovery tool we\u2019ve introduced is in-app ratings and reviews. As people get more reliant on user reviews to make their buying decisions online, this behaviour has bled into food delivery apps<\/a>, too.<\/p>

Consumers can now view merchant ratings and read food reviews from fellow Grab users within the Grab app. They can also order the same dishes from reviews by hitting the \u201corder now\u201d button.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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