Burberry wanted total integration across the company for its customers & employees as well as keeping the traditional heritage, but being at the forefront of being a digital brand. Data and analytics enabled them to achieve a rare level of seamless integration of all social and digital channels.
- Customers are able to connect with all aspects of the business, e.g. music, video, product offers
- Chat with Customer Service Representatives who know who you are!
- Pre-test aspects of marketing & communications with their community
- Customers can suggest the design for the next iconic trench coat
- One brand voice – strong identity across all online platforms
Coca-Cola uses data analytics to ensure they produce orange juice that has a consistent taste all year-round, although the oranges used have a peak-growing season of just three months.
They have developed an algorithm called the "Black Book" model, that combines various data sets such as satellite imagery, weather date, expected crop yields, cost pressures, regional consumer preferences, detailed data about the myriad 600 different flavours that make up an orange, and many other variables such as acidity or sweetness rates to tell Coca-Cola how to blend the orange juice to create a consistent taste, even down to the pulp content.
McDonald’s is moving toward a data-driven culture. They moved from using averages to trend analytics that provide a lot more insight in what was happening at which local stores. They combined datasets and visualised it to better understand the cause and effect in the differences between stores. In other words, they combined multiple graphs to understand the correlation. These correlations were used to create more clear, relevant and actionable actions, resulting in saving money and time across the organisation.
McDonald’s uses data and analytics to optimize the drive-thru experience. They analyse and optimise across three different factors: Design of the drive-thru, Information that is provided to the customer during the drive-thru and the people waiting in line to order at a drive-thru. A large family in a van ordering a large menu can create a negative experience for that single customer waiting behind the van that only wants a milkshake. Therefore, they analyse the demand patterns in order to predict them.
Whirlpool wanted to be able to leverage the web and over 8.5 million annual customer and repair visit interactions captured in service notes to drive marketing programs, product development, and quality initiatives.
- Whirlpool listens and acts on customer data in their service department, their innovation and product developments groups, and in market everyday
- Whirlpool gets early warning for safety and warranty issues and in many cases have been able to mitigate expensive recalls
- 80% savings on their costs of recalls due to early detection
- Deeper understanding of their customers’ needs and wants – and of their competition and what they are doing to win over customers
With more than 70 million registered users in more than 500 global markets, Groupon has been dubbed the “fastest growing company ever” by Forbes magazine. Data is one of Groupon’s most strategic assets; Groupon relies on information from both vendors and customers to make daily deal transactions run smoothly and seamlessly.
Analytics provide data-driven answers to business questions, to develop new products and to optimise various processes. Analytics are used in every stage of the business, from finding the best merchants for each market, to pairing customers with the most relevant deals and optimising the layout of each page of their website.
Spotify is a data-driven company and aims to make music special for everyone. Today, the company hosts more than 2 billion playlists and gives consumers access to more than 30 million songs. Users can search for music across any device by artist, album, genre, playlist or record label, while features like Discover Weekly suggest personalised playlists for millions of people around the world. Most of the data is user-centric data -Spotify's billions of log messages allow them to provide music recommendations or select the next song heard, for example. This data however is also used in decision-making, providing forecasting information and business analytics. Spotify posts detailed analytical pieces about worldwide listening habits, playlist behaviours, genre differences and the statistical effect that third-party festivals have on streams.
Big data & analytics gives Spotify incredible insight into user behavior. Its ‘Discover’ page taps into its analytics to help users find artists and songs they may never have heard before – so as to keep them listening on the platform. Without big data, Spotify would not have become the global success it is today. With an ever-growing presence in many countries and a growing listeners base only more data will be created in the coming years. More data will mean better recommendations, better predictions, more users and thus more pay-outs to the rights holders. Big data truly enabled Spotify to transform the music industry.