UberEats is a food delivery platform partnered with restaurants all over the globe to bring customers meals right to their doorstep and is co-owned by leader in business disruption, Uber. If you were to conduct a Google Image search of the brand, here is what you would find…

Images retrieved from Google search of “UberEats”

… the UberEats logo stamped on a colorful array of gourmet, fresh and healthy foods. These are the images potential customers could use to develop their perception of the UberEats brand. However, these are not the types of images actual customers are publishing on Twitter about UberEats. Here is what an Alto big data analysis uncovered about the UberEats brand positioning and its mark on the restaurant and food industry.

After collecting Twitter data in English from the US market from December 1st to 31st 2016, our team of data scientists began to identify a gap between the images customers shared about UberEats and Google’s image dataset publicly representing the brand. This disconnection led us to discover Google Images shortcomings when representing brands and how the user photos found in big data analytics offer a more realistic and accurate reflection of products and services. This reflection can be converted into the insight required for brands to increase the manageability of their public image.

After mining the data, our team of data scientists applied algorithms and data visualization models to uncover:

  • Key communities driving conversations about UberEats
  • Top influencers creating current brand positioning of UberEats
  • Most-shared (viral) content in the digital conversation about UberEats
  • Visual narratives surrounding UberEats

Network Analysis

Our network analysis showed that 34% of users produced 97.8% of the comments within the digital conversation about UberEats. We identified the role of BOTs to drive the conversation about UberEats through disseminating tweets with discount codes and promotions, representing 87% of the activity related with the brand. Key influencers were mostly unrelated to the food and restaurant industry.

Low density and high community isolation shows disconnected ecosystem.
Five communities detected, the largest comprised of bots.
Four profiles and 3,391 bots driving high activity with low-impact through promotional spamming

These findings presented an opportunity for UberEats to have a stronger presence in the online conversation about their brand, as a majority of the images come from uncontrolled media sources, unrelated to the brand.

Influencers leading the conversation about the brand are also not from the sector and industry their service is intended to disrupt. This could point to an opportunity for UberEats to adjust their paid media strategy, in order to establish stronger ties with influencers from the food and restaurant industries.

Our data scientists were then able to draw the conclusion that despite Google portraying a strong visual representation of the brand delivering healthy, gourmet foods, the images users published about their orders were more diverse and heavily focused on junk food.

Visual Narratives

We collected thousands of images from the Twitter conversation about UberEats and applied data visualization algorithms to find the most-shared images and to categorize them based on the type of food in the photographs.

Dataset of the 600 most-shared images
Cluster A. Junk Food

The majority of images in this cluster are of donuts, hamburgers and pizza.

Cluster B. Mostly desserts and UberEats APP

This cluster is comprised of images of Uber discounts, the app interface and desserts.

Cluster C. Brands news & McDonald’s

The final cluster is made up of images highlighting the McDonald’s and UberEats partnership


Visual categorization of user-shared images

As the results show, users are not ordering gourmet or healthy foods on the app as Google’s image dataset suggests. They are ordering the exact opposite with 23.89% of visuals beings of donuts, 8.22% being of hamburgers and 4.67% of pizza.

Google Vs. Reality

Here are a few of the images users shared compared to those found on Google. While Google perpetuates an idealized representation of the brand, users provide a more realistic perspective. This points to an opportunity for UberEats to adjust their creative direction and take on a native advertising approach to marketing to ensure images resonate better with their audiences.


Key Insights: How to make data-driven decisions

Through our big data analysis, we identified opportunities for UberEats to get a hard look at the most-shared images related to their brand, key verbatim and communities within the social media conversation and Google Images depiction of their brand verse real customers. Here are just a few of the key insights brands, especially in the food and restaurant industries, can use to increase their brand manageability:

  • Partner with fast food restaurants, such as McDonalds, to expand service of top products ordered on app
  • Align brand and consumer image by analyzing public discussion
  • Contribute actively to the social media discussion to avoid losing control of public brand image
  • Monitor the dissemination of sales codes and promotions to avoid BOTs impacting strategy

Want to learn more?

To view the full analysis or to discover how to use big data analytics to improve your business operations please contact media@alto-analytics.com. To learn more about Alto Data Analytics’s articles and ongoing projects, please sign up to our newsletter below.

Article written by Clarissa Watson, Head of Marketing