Starbucks is already a pioneer in the process of knowing how to keep their customers coming back.
Around 90 million transactions happen at Starbucks stores every week at its 25000 stores worldwide.
Not only Starbucks brews fresh coffee to its customers to boost alertness through caffeine but brews up their customer data to enhance personalization to its burgeoning customer base.
The coffee giant is a lavish user of Big data and Artificial Intelligence for Hyper personalizing their e-mails and notification messages to its customers. This is the cutting edge of using data analytics to help make exact impromptu decisions in sales, marketing and operations that pours in the maximum ROI and a wide satisfied customer base.
This Article is a refreshing and fulfilling one in terms of how Starbucks used different technologies and the desired outcomes after the analytics and AI implementation.
Profiting from advanced analytics and AI:
Starbucks introduced its customer-focused mobile app and member rewards program to sneak personalization into the plan. It increased the data collected from their own customers, understood the preferences and behaviours towards interests pertaining to the purchasing habits.
They personalize the experience for each and every customer based on a unique AI algorithm based on the customers’ preferences and spending habits.
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How Starbucks uses AI for Hyper-personalization?
- They introduced a loyalty program that is incredibly successful. Critically acclaimed over 17.6 million active members at the end of Q4, 2019. This is a 15% increase compared to last year.
- The loyalty program is introduced in their app downloads where they target their users and absorb behavioural patterns to push notifications regarding food and beverage suggestions personalized for each customer.
- The Customized and specially made AI algorithm analyzes the past purchase history of the customer, interests, tastes and preferences to predict future recommendations.
- They even engage their loyalty customers with personalized rewards and games through e-mails and mobile.
Top brands like Starbucks have moved to predictive personalization, in which AI and Machine learning analyzes the customer behaviour and interests with a whole lot of factors to predict meaningful recommendations to improve hyper-personalization factor, thereby inducing customers to purchase.
How Starbucks uses Customer behaviour analysis to attain threefold improved e-mail response rates?
Starbucks is certainly leading the way of using & integrating disparate technologies to provide a consistent customer experience / Coffee Experience.
- A few years back, they redesigned their whole email program using AI to create 400,000 personalized versions of e-mails every week which led 3X response rates.
- “Each email,” says Gerri martin-Flickinger, Starbucks’ chief technology officer, “is uniquely generated based on every individual customer’s behaviours and anticipated behaviours. There are no variants and there are no pre-determined algorithms around specific offers and rewards.”
- Their real-time hyper-personalized e-mail takes in a lot of inputs from different customer sources, such as third party data. These are given in as few inputs into the algorithm that gives useful information to drive their marketing campaigns.
- This tends to drive up tickets and transactions.
Image source: Geekwire.com
How Starbucks is using AI, Predictive Analytics and IoT – What’s the big deal about their “Deep Brew”?
In the Starbucks latest Q4, 2019 earnings call, “Deep Brew” – a new AI initiative was talked about. Deep Brew is a concept which was put forth to further drive the hyper-personalization engine of Starbucks and help to optimize store labour allocations.
- They planned to leverage Deep Brew strategy to drive inventory management at ease in their stores, optimize their labour allocations to help their partners and labour to free up more time to connect to customers.
- Starbucks uses AI through its Mastrena espresso machines, which they are currently adding across the U.S fleet which is expected to get over next year.
- These coffee machines have IoT sensors built into them which collect every data happening and sends it to the relevant support centre.
- With Predictive analytics, the Deep Brew capabilities can analyze every shot of espresso that’s being pulled and predict maintenance thereby preventive measures are filled before breakdowns.
- Anticipates equipment maintenance and streamlines supply chain logistics and more.
How Starbucks uses Reinforcement learning technology to provide personalized recommendations experience through its mobile app?
Starbucks has been using this technology called Reinforcement learning technology which is a type of machine learning. This technology was in place to predict recommendations for users under environments that are volatile to unpredictability, complexity based on external feedback.
- Customers receive personalized and customized order suggestions that are generated through Reinforcement learning to receive thoughtful recommendations based on the food and beverage behaviour of similar customers.
- This technology enforces in learning more about customers’ preferences.
- If a customer is consistent in ordering, dairy-free and vegan food and beverages then the app steer clears foods containing dairy and recommends non-dairy vegan food and drinks.
- Machine learning also touches multiple facets in the business like optimizing inventory, engaging partners, rethinking store designs and creating barista schedules.
How Starbucks is exploring Blockchain to share coffee’s journey with customers and coffee farmers?
Starbucks R&D is now developing ways to explore the journey of the coffee that it makes from the farm to the cup. They are in the process of developing ways to integrate people who drink it with the people who grow it.
- They are developing a feature in its mobile app that showcases where their coffee comes from, giving attention to details like the location of the coffee grown, where and when was it roasted and the kind of support Starbucks is doing to the farmers and more.
- In 2018 alone, Starbucks worked with 380,000 coffee farms.
- This is enhancing the digital traceability for both the customers and the farmers. Customers will know more about the coffee they drink and the farmers will get to know where their coffee beans go after they sell them.
- This transparency will enhance the whole coffee’s journey thereby improving the empowerment of farmers and customers get the view of what impact the coffee they buy creates among the real people to support.
Success Components of Starbucks:
Rewards – The most sought-after active members’ reward program with everyday relevancy and interests
Payment – The easier and sensible payment ways
Hyper-Personalization – Offers, rewards, loyalty member programs, personal recommendations, tailored to individual behaviour and needs
Ordering – The fastest and the most convenient method of order and pickup
Technology and Deployment – Adaptation to the newer technologies to increase customer experience/coffee experience
What Starbucks success looks like?
- Increase in effective marketing campaigns by 2X
- Increased email redemptions up to 3X
- 3X increase in incremental spends via offer redemptions through email and personalized app reward programs
- 24% of the total Starbucks’ transactions happen via its mobile app.
- More than 90 million transactions every week and still growing.
- 15% active member increase year-over-year and active 18 million customer base.
- Massive customer retention and loyalty. More than 48% regularly use Starbucks’ app.
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