Swiggy plans to reduce customer wait time by utilising the history of order-level and delivery fleet data
Zomato provides business dashboard for restaurants on the web and app claiming it will help restaurants understand purchase funnel
Swiggy is preparing food graph that will break down a food dish by recipe, cooking style, ingredients used, among others
Food delivery giants Zomato and Swiggy are increasingly turning to artificial intelligence (AI) and machine learning (ML) to drive growth amid increasing protests by restaurants in the so-called Logout campaign. Even as Zomato laid off around 540 employees citing redundancy of many jobs because of automation, especially in support roles across its customer, merchant and delivery partner teams, it’s looking to use AI and automation in other aspects of its B2B business. And now both Swiggy and Zomato are turning to data to tackle growing demand and changing customer preferences, according to a report in the Mint.
Zomato claims that improvement in its after-sales technology through automation will drive growth amid increasing demands. On the other hand, Swiggy plans to reduce customer wait times and retain its loyal base of customers by utilising the history of order-level data and delivery fleet data. The Bengaluru-based company says it’s processing around 40 Bn messages per day, all of which are considered unique data points to improve customer and delivery service.
“We will probably touch 100 Bn messages within a year,” – Dale Vaz, engineering and data sciences head, Swiggy.
Swiggy Plans Food Graph To Enhance Customer Experience
Swiggy claims more than 130K restaurant partners on its platform and Gurugram-based Zomato says it has over 150K restaurants. Each also claims to process more than a million orders a day from more than 300 cities. Naturally, this means both handle a large amount of data on a daily basis.
Leveraging this, Swiggy is currently building a concept called “food graph” which breaks down a food dish by recipe, cooking style, ingredients used, calorie value, and variations of the dish.
The food delivery major will then combine the food graph with a customer’s previous food preferences using data analytics to derive a personalised restaurant feed for each user. The list of restaurants will thus be according to the user’s taste and preferences, and not just their location.
“For example, a user may prefer an Andhra style biryani over a Lucknow style biryani… so we are trying to get to that level of precision in our understanding of the customer. Food is a personal choice and cannot be generalized on the basis of the location of the customer alone,” Vaz was quoted as saying.
While Zomato hasn’t announced anything similar to a food graph, it says it’s looking to give restaurants more insight about customer behaviour through a web and app-based business dashboard. This dashboard not only tells restaurants where the user arrived from, but also educates them on purchase funnels — the number of visitors, the number of people who added items to cart, and the number of orders. It’s already tracking dish-level ratings for many restaurants, and is working towards adding more features to the dashboard.
Will AI, Data Analytics Increase Operational Costs For Restaurants?
Swiggy says that the food graph will break down a food dish by recipe, cooking style, ingredients used, calorie value, and variations of the dish. To provide such data, restaurants, especially smaller ones, will have to spend money or resources in tracking the ingredients that go into every dish. Mapping every information down may also add to the existing high operational costs, along with paying for promotions and ad spots on platforms such as Zomato and Swiggy.
With every new initiative from food aggregators, small restaurants have to keep rejigging their business models to cater to the new features, which are largely built for customers. Additionally, even after doing so, the customers may be led to only restaurants that they have been ordering from in the past.
Restaurants have been reiterating that in spite of such new programmes creating dents in margins and profits, their participation is largely because of the fear of missing out. In fact, as delivery services turn to AI for such personalised recommendations, restaurants have been blaming the deep discounting offered by them for hurting profits through the Logout movement against Zomato and Swiggy, which has also attracted the government’s attention.
Does Food Graph Actually Benefit Customers?
Zomato and Swiggy claim that switch to data analytics is majorly aimed at reducing wait time for consumers. However, how such data will actually help Indian consumers, who are known to be unique in their choices and have varied taste palates is yet to be seen.
Manish Singhal, founding partner of pi Ventures, told Mint, “It is very difficult to model human nature accurately when it comes to food. Artificial Intelligence might be able to do a good job in predicting and bringing back the customer to the platform but it will only make an incremental difference. It will not change the world for these companies. But this is not because the AI models are not mature enough, it’s more because of human nature.”
Logout Campaign Impacts Zomato, Swiggy
Since August this year, restaurants have been protesting against heavy discounting and non-uniform policies offered by food aggregators. More than 300 restaurants under NRAI started the Logout campaign on Twitter in August against the likes of Zomato, Swiggy as well as other discovery platforms. However, since then Dineout has clarified the communication around its discounting policy for customers and also clarified how the Gourmet Passport loyalty programme works, which convinced restaurants to log back into Dineout and Gourmet Passport.
The main pain point between NRAI and Zomato has been the very successful Zomato Gold programme, which offers one-on-one offers on food and drinks to dine-in customers at partner restaurants. In September, Zomato diluted the programme but introduced the Gold offering on delivery as well, which led to further discontent among NRAI members.
Since August, more than 2,000 restaurants have joined the protest, which gained national momentum earlier this month, as along with FHRAI, several other associations such as AHAR, Thane Hotel Association, Pune Restaurants & Hotel Association (PRAHA), NHRA, Vadodara Food Entrepreneurs (VFE) also joined the #Logout movement.
The restaurants said that frequent deep discounting is not good for businesses that are already struggling with increasing raw material and higher real estate costs. And the current switch to AI analytics is likely to further increase operational costs for small restaurants thereby escalating the trouble.
So while the demand for app-based food delivery services has risen significantly, de-democratising food choices may not be a palatable idea for consumers and restaurants.