“Data! Data Data! I can’t make bricks without clay!” is a famous line from Sherlock Holmes, the main character in the most famous crime fiction of all time that was first published in 1892.
This famous line indicates that the power of data has not just started being recognized in the digital age. It has been around for a long time, from the start of civilization. It has been there since ancient trade when our ancestors decided what to trade with neighbours or when middle-aged merchants chose what would make the best sales. These are all the initial stages of data analytics.
Data Analytics plays a vital role in making informed business decisions. It is what drives businesses forward productively and profitably. Nowadays, there is a countless amount of data circulating on the internet, serving innumerable purposes of analysis. Just learn how to ask the right questions and find the best analytical tools. It will answer whatever you need. This is how data became the key to accelerate the growth and success of businesses.
Sertis would like to take you through 5 examples of businesses that made their amazing success out of data. Here you might find some fresh ideas to apply to your business.
If you are interested in utilizing data with your business to pave the way to success just like these examples, get to know more about our solutions here https://www.sertiscorp.com
Amazon
We all know what Amazon is, the most dominant e-commerce company, with more than 150 million users around the world. Amazon has expanded to other industries such as Amazon Prime and Amazon Web Services (AWS) and has acquired other potential companies.
Amazon started from an online book shop before it became the best-selling e-commerce. 27 years after it was first established, e-commerce has still remained Amazon’s biggest source of income. (Even though AWS is the biggest source of profit now) The key to this power is nothing but data.
Utilizing data is necessary for Amazon. There are a huge amount of users bringing data into their systems every minute. Amazon collects all of the data and uses it to improve its service all the time. Their recommendation system is more than just recommending related products. The collaborative filtering technique is employed. With this technique, Amazon’s way to understand one user’s preferences is by the analysis of other users’ profiles who have mutual characteristics. Despite 12 million products, we can find the thing that we want or even the thing that we have never thought we would want before by Amazon’s recommendation system. It is no doubt that 35% of the sales each year comes from this recommendation system.
Amazon applies data to almost every part of their operation — supply chain development, pricing, etc., This resulted in Amazon being one of the most successful companies in the world
Sephora
Sephora is like a paradise for cosmetic lovers because of all the high-end skincare and makeups all in one place. Sephora proves its success with 2,600 stores around the world. Just like other retail businesses, the key to its success is data.
Apart from using data to improve customer experience, Sephora also used data to solve ‘racial bias’. Despite not many complaints about the issue, once Sephora knew it existed, they took it seriously.
Sephora spent a year gathering data and researching racial bias in retail. The research showed that clients were experiencing racial bias and discrimination in every 2 in 5 stores, especially black people. Product choices in the market were also somehow limited to certain races. Another shocking result was that only 30% of the shoppers who experienced unfair treatment acted on that. That was why the problem had been brushed under the rug.
Sephora put their effort into tackling the problems by doubling black-owned brands, implementing new training and performance reviews based on fair treatment. Its care and fairness were how Sephora managed to win customers’ hearts.
Starbucks
Starbucks is famous for its customer service. Every time we walk into the store, warm scents of coffee, along with friendly staff, is welcoming us. Furthermore, we often see stories of good customer services from Starbucks that people share, which show how much they care about their customers.
Due to the covid-19 situation, every dine-in restaurant and coffeehouse shifted to takeout or delivery. Here is why customer service and human connection, the identity of Starbucks, may be unable to function perfectly as before. During this time, Starbucks operates only via its application and drive-thru. They have to find a way to transit their human-centric experience to a digital platform while considering both staff and customers’ safety as the priority.
Data was what made the overnight transition smooth and remain well-performed throughout the crisis. The Analytics & Insights and Technology Data & Analytics teams created a dashboard, called Daily Top Line, to gather all the data circulated in the operating system, analyse, and make the real-time data accessible for everyone in need. This method was to accommodate and accelerate the decision-making process.
This data also allowed Starbucks to initiate several special services to maintain a human-centric relationship with customers. For example, Starbucks Now™, mobile order and pay service, Starbucks® Delivery, and Deep Brew, AI-based recommendation system. Deep Brew would collect customers data to recommend the menu that they’d like. For drive-thru, Deep Brew would recommend the drink based on weather, seasons, and time. They also support voice-ordering. Although we have to remain social-distant for a while, these technologies help preserve the human connection and warm experience we get from Starbucks.
Airbnb
Airbnb is one of the most famous rental platforms. Despite being established in 2016, the company is so successful that its values already soared to 130 billion. What is the key to Airbnb’s success? Yes, it’s data.
Every day, Airbnb collect almost 20 terabytes of data and store around 1.4 petabytes. As with other digital platforms, data is an essential factor to drive the business forward. They applied data to every sector, for example, constantly performing A/B testing to give users the best experience and provide them with the easiest way to find the right accommodations. Additionally, they apply image recognition to identify what characteristics in the images that each customer finds attractive. Then, they created a feedback loop with hosts to continually improve their photos. (Free professional photographer service is available.)
Airbnb realizes another issue with stars ratings that somehow they are unreliable. Guests may give a good review because they are forced or just careless. Airbnb utilizes Natural language processing (NLP) to detect the true feeling of customers via written reviews on the review board. Another example of Airbnb being customer-centric was when data show that Asia users often leave the site after visiting the ‘Neighborhood’ page, they replace that feature with ‘Top destinations’, resulting in a 10% booking increase.
Besides, they apply predictive modelling to help the host get the best pricing, regression analysis to define the feature that most influences users’ decision-making and collaborative filtering to understand and recommend the right place for customers.
Netflix
Netflix is one of the most successful online streaming in the world. We are all familiar with it, aren’t we? The reasons why users choose Netflix over other streaming services is that it doesn’t have ads, users can choose what they want to watch, they can binge-watch, and the content is well-curated, the survey indicated. Apart from having no ads, every factor that made Netflix wins users’ hearts is all about its content.
On our Netflix profile, there are various kinds of movies and TV shows. We often find the show we settle with on the homepage, even before going to the search bar. All the contents on our profile aren’t random. They are all carefully selected and well-curated by Netflix’s algorithms.
What is extraordinary about Netflix’s recommendation systems? The answer is it is far more detailed than we might expect. Netflix gather all the data from the date, place, time, we watch each content to the device we use. They also know when and how often we pause during the show. They see if we complete each show and how long we take. Have you ever rewatch specific scenes in your favourite movie over and over again? Netflix also captures screenshots of those scenes to collect data. They also consider the time we spent searching before choosing and which keyword we used. All of these metrics are taken into consideration to improve their algorithms.
Netflix’s intelligence made us feel they can read our minds. 80% of the users follow Netflix recommendations. That resulted in a 74% Customer Retention Rate. The number has decreased a little bit since the coming of Disney+. However, Netflix has still been the number 1 streaming service with 209 million users, twice as much as Disney+’s.
References:
- https://python.plainenglish.io/how-netflix-uses-data-analytics-data-science-general-research-case-study-4d525b881038
- https://www.dezyre.com/article/how-data-science-increased-airbnbs-valuation-to-25-5-bn
- https://www.tableau.com/about/blog/2021/1/how-starbucks-uses-analytics-enhance-customer-experience
- https://www.forbes.com/sites/soniathompson/2021/01/13/how-sephora-is-using-data-to-eliminate-racial-bias-and-foster-belonging-in-their-customer-experience/?sh=7e356a78fefc
- https://bernardmarr.com/amazon-using-big-data-to-understand-customers/
Written by: Sertis
Originally published at https://www.sertiscorp.com/
