Do you prefer Coke or Pepsi? Do you eat your burger with cheese or without? And what about coffee, Americano or espresso? Zomato ensures that every meal, for users with all kinds of preferences, is a great experience.
Zomato is an India-based restaurant directory startup, that provides detailed information regarding restaurants nearby, including scanned menus, and also user’s reviews and photos of their gastronomic experiences. Zomato also includes real-time information about the restaurant and lets users book tables through its iOS and Android apps.
The image bellow summarizes Zomato’s key features:
Zomato has 1,398,900 listed restaurants in 22 countries. With the recent acquisition of Urbanspoon, Zomato will break into the US market, competing against services like Foursquare and Yelp.
The business model is quite simple, Zomato hires people to visit restaurants and to send the data to the team, including up to date information on new openings and scanned copies of menus. Users can then share photos of their dishes and evaluate restaurants in order to help other users decide where to eat.
The detailed informations available for each restaurant is then a result of the combined inputs of both the Zomato’s team and the users.
At Zomato, user’s evaluation takes the form of both a rating, using a 5-points scale and a review. Given that consumers with more extreme opinions (very satisfied or dissatisfied) are more likely to rate (Li and Hitt, 2008), most restaurants have a score of either close to 1 or higher than 4, as the image bellow exemplifies.
Product rating is crucial for Zomato given that it is an integral element of online businesses especially for experience goods (Tsekouras, 2015) and because they are a reflection of product quality (Hu et al., 2009). Also, consumers tend to trust more opinions derived from others customers than information provided by the vendors themselves (Chevalier and Mayzlin, 2006), which is why having a high number of reviews is a key success factor for Zomato.
Social surroundings are then of crucial importance given that the success of Zomato relies on the degree to which there is interaction between users, through comments, ratings and a community creation of “foodies”, and the degree to which network effects take place i.e. where a good or service becomes more valuable because more people use it (Katz and Shapiro, 1994). As according to Grönroos and Voima (2013), the customer’s well-being of Zomato is increased through the process, as more user’s feedback is available for each restaurant.
As a startup, Zomato relies in eWOM in order to attract new users and generate brand awareness. Unlike traditional WOM, eWOM has much broader effects, in part because there is no need to have a pre existing connection between the sender and the receiver. As so, eWOM applies to Zomato since it operates in an online context whereas traditional WOM typically happens in a face-to-face context (King et al., 2014).
Zomato is providing value for the consumers whilst the consumers are also creating value for each other, through their evaluations and photos. This reflects a finding in the article by Saarijarvi et al (2013), which states that it is important to evaluate what kind of value is co-created and for whom, meaning that value can have a different meaning for different actors in the co-creation process.
Zomato also generates great value for restaurants. In fact it is one of the most cost-effective high-impact marketing platform for dining establishments.
Check out the best place for you at https://www.zomato.com/!
Chevalier, J. A. and D. Mayzlin (2006). “The Effect of Word of Mouth on Sales: Online Book Re- views.” Journal of Marketing Research 43(3), 345–354.
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King, R.A., Racherla, P., & Bush, V.D. (2014). What We Know and Don’t Know About Online Word-of-Mouth: A Review and Synthesis of the Literature. Journal of Interactive Marketing, 28(3), 167-183
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Saarijärvi, H., Kannan, P.K., & Kuusela, H. (2013). Value co-creation: theoretical approaches and practical implications. European Business Review, 25(1), 6-19.
Tsekouras, D. (2015) Variations On A Rating Scale: The Effect On Extreme Response Tendency In Product Ratings, working paper.