Dunkin' Brands' president said selling Starbucks creamer would strengthen its brand's association with hot coffee and drive more hot coffee sales. The coffee creamer market is affected by trends of home brewing and advanced brewing systems. Starbucks should enter the creamer market because consumers are willing to pay higher prices, it has established distribution channels, and outperforms Dunkin' Donuts on key metrics like taste, variety, and quality. The report recommends Starbucks launch a creamer called "Affogato" and a marketing campaign to introduce the new product.
The first Starbucks opened in Seattle, Washington, on March 30, 1971,
By three partners who met while they were students at the University of San Francisco
English teacher Jerry Baldwin
History teacher Zev Siegl, and
Writer Gordon Bowker
The three were inspired to sell high-quality coffee beans and equipment by coffee roasting entrepreneur Alfred Peet after he taught them his style of roasting beans.
The first Starbucks opened in Seattle, Washington, on March 30, 1971,
By three partners who met while they were students at the University of San Francisco
English teacher Jerry Baldwin
History teacher Zev Siegl, and
Writer Gordon Bowker
The three were inspired to sell high-quality coffee beans and equipment by coffee roasting entrepreneur Alfred Peet after he taught them his style of roasting beans.
Starbucks has evolved from a mere seller of coffee products to a full-fledged chain “restaurant”, offering not only coffee products but also other beverages, foods, and merchandise.
Starbucks is still a global leader in the coffee shop chain business
Introduced an online app making it more convenient for customers to locate stores and place orders
Starbucks slogan of “Uniquely Starbucks” continues to play a huge role in company’s success
Foudation of business strategy of starbucks is a word file which talks about how the starbucks positioned themselves and their strategies to fight against competitors.
Starbucks India or it can be called as Tatabucks. As Starbucks Corporation and Tata Global Beverages announced 50:50 joint venture called Tata Starbucks Ltd. in January 2012 which operate and own outlets branded Starbucks “A Tata Alliance”. An agreement was also signed between Starbucks and Tata coffee that coffee would 100% locally sourced and roasted
Starbucks has evolved from a mere seller of coffee products to a full-fledged chain “restaurant”, offering not only coffee products but also other beverages, foods, and merchandise.
Starbucks is still a global leader in the coffee shop chain business
Introduced an online app making it more convenient for customers to locate stores and place orders
Starbucks slogan of “Uniquely Starbucks” continues to play a huge role in company’s success
Foudation of business strategy of starbucks is a word file which talks about how the starbucks positioned themselves and their strategies to fight against competitors.
Starbucks India or it can be called as Tatabucks. As Starbucks Corporation and Tata Global Beverages announced 50:50 joint venture called Tata Starbucks Ltd. in January 2012 which operate and own outlets branded Starbucks “A Tata Alliance”. An agreement was also signed between Starbucks and Tata coffee that coffee would 100% locally sourced and roasted
An interesting analysis of Starbucks's SWOT, 4Ps, Strategy, Marketing, Finance etc. Hope you will enjoy this presentation. Go through the slides and don't forget to hit like and share buttons. All the best.
Starbucks: A Story Of Growth, is a case study analysis on how Starbucks came up with different strategies to renovate and grow its market shares against various competition.
Which are the opportunities and threats in Starbucks external environment?
Which are the strategic capabilities, which Starbucks could leverage to enter the tea market?
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
2. “…strengthen [the] brand’s association with hot coffee, increase [its]
visibility at grocery stores around the country, and ultimately drive more
hot coffee sales when consumers visit [its] restaurants.”
- John Costello, Dunkin’ Brands’ President, Global Marketing
and Innovation
5. FORCES AFFECTING COFFEE CREAMER MARKET
Sociocultural:
54%
Focus on
home
brewing
Technological:
50%
Advanced
brewing
systems
Economic:
1.6%
Future of
declining
input costs
6. S W
TO
• Expansive network
• Drink variety
• Brand recognition
• My Starbucks IDEA
• Higher priced items
• Social stigmas
• Brand dissolution
• Number of competitors
• Diversify product offerings
• Foreign market expansion
• Partnerships
• Mobile technology
• Competitor market position
• Production costs
• New product acceptance
• Low margin business
7. STARBUCKS CHOICE DRIVERS
Favorability of
STARBUCKS
Probability to
Purchase
STARBUCKS
9.357
R2 = .173
Quality
STARBUCKS
Brand
R2 = .225
TASTE
Variety of
Flavors
R2 = .520
10. PRICE FREQUENCY
$1.00-3.00 $3.00-4.00
$4.00-5.00 $5.00-6.00
$6.00-7.00 $7.00-8.00
$8.00 and above
DEMOGRAPHIC FACTORS
Dunkin’ Donuts Gender Education Age
Favorability towards DD 0.421 0.957 0.625
Probability of Purchasing
DD Coffee Creamer
0.706 0.932 0.403
Max Price willing to pay for
DD
0.194 0.343 0.956
Starbucks Gender Education Age
Favorability towards
Starbucks
0.932 0.602 0.148
Probability of Purchasing
Starbucks Coffee Creamer
0.635 0.305 0.655
Max Price willing to pay for
Starbucks
0.585 0.410 0.901
![“…strengthen [the] brand’s association with hot coffee, increase [its]
visibility at grocery stores around the country, and ultimately drive more
hot coffee sales when consumers visit [its] restaurants.”
- John Costello, Dunkin’ Brands’ President, Global Marketing
and Innovation](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)