Case study Week 2

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School

Clark University *

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Course

3820

Subject

Marketing

Date

Feb 20, 2024

Type

docx

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Uploaded by BrigadierSteel13231

Executive Summary: In the fast-changing world of marketing and sales, Artificial Intelligence (AI) is a big deal. This case study talks about how AI influences how companies do marketing and sales, stressing the need to use predictive analytics to make customers more engaged. Lessons from smart companies in unpredictable markets show how AI can predict what customers will do and help in managing relationships with them.Managers and important people in this field struggle to quickly adjust to what customers want and the uncertainties in the market. Traditional ways often can't keep up in connecting marketing efforts to actual results in real- time, so a new strategy is needed. The recommended plan suggests bringing AI into marketing and sales completely. This means creating smart AI models, forming teams that work together, and teaching employees about the new AI way. This plan makes sense because it can help adapt quickly, use resources better, and make customers happier. By using AI to bring together marketing and sales, companies can handle the challenges of the modern market and keep up with what's happening for long-term success. 2]. Statement of the Problem: Many businesses are facing a tough time figuring out how much return or money they're getting back from what they put into marketing. Even though in marketing we need to put a lot of effort to be in competition. Even with digital tools, it's still hard for them to quickly adjust to changes in the market, especially during uncertain times like the start of the pandemic in 2020 and economic shifts in 2022. This has made it crucial for businesses to take a more active approach in using customer information. Problem: Managers are finding it hard to understand clearly how much they're getting back from their marketing efforts with the old fashioned ways and also marketing is also very expensive now a days. Symptoms and Root Causes: The old ways of doing things make it tough to connect what a business does in marketing to how customers react to that stratagy. This leads to a lack of clarity on what's working. The real issue is the need to quickly adjust to changes in the market, especially during tricky times like the early days of the pandemic. Differentiating Short Term from Long Term Problems: Right now, the immediate problem is the challenge of keeping track of what they get back from marketing, which is a short-term issue. But looking ahead, the bigger challenge is making marketing strategies that can adjust to the ever-changing market conditions in the long run, especially during uncertain times.

Conclusion on Decision: The big decision is all about finding ways to better connect the investment that we put into marketing with what comes back. Managers need to deal with the immediate challenge of tracking returns and the long-term challenge of making decisions that fit with how the market is changing, especially after the pandemic. 3]. Causes of the Problem: The issues businesses face in understanding the returns on their marketing efforts have a few main reasons tied to old-fashioned methods and how companies are set up. Not Getting Feedback Quickly: Using the old ways of marketing means companies don't get quick feedback on what's working. No Clear Way to See What's Working: The old methods make it tough to connect what a business does in marketing to how customers react. This leads to a lack of clarity on what's actually working. Slow to Change with the Market: Using traditional ways makes it hard for companies to quickly adjust to changes in the market, especially during tricky times like the early days of the pandemic. Big Gap Between Plans and Actions: The old approach creates a gap between what management plans and what actually happens on the frontline. This makes it tough to put effective marketing strategies into action. Marketing is Expensive: The most important issue is that marketing costs a lot, and the rising expenses make it even more challenging to figure out if the money spent is bringing good results. In simple terms, the problems come from using old ways, making it hard to know what's working and adapt quickly. Using theories and models helps us understand these problems better and opens the door for smart solutions like AI and predictive analytics. 4]. Decision Criteria and Alternative Solutions: Time for Implementation: Evaluate how quickly each solution can be put into action. Tangible Costs: Examine the financial aspects associated with each solution. Acceptability to Management: Assess the willingness of management to adopt and implement each solution.

Alternative Solutions:  Traditional Approach (Option 1): Pros : Cost-effective but lacks adaptability. Cons : Not responsive to changing market dynamics.  Partial AI Integration (Option 2): Pros : Improves prediction capabilities. Cons : Maintains organizational silos and may not realize AI's full potential in the short term.  Full AI Integration (Option 3): Pros : Utilizes AI fully, enables real-time tracking, improves customer engagement. Cons : Requires significant upfront investment, potential resistance, and integration challenges. Evaluation:  Option 1: Cost-effective but lacks adaptability to changing market dynamics.  Option 2: Improves prediction capabilities but retains organizational silos.  Option 3: Fully integrates AI, allowing real-time adaptation, efficient resource allocation, and improved customer experience. As per me, Option 3 is the best because it uses AI in a complete way. This helps the company quickly adjust to changes, use resources better, and make customers happier. It's a smart choice for both short-term problems and long-term success in a fast-changing market. 5]. Recommended Solution, Implementation, and Justification: Recommended Solution: Combine AI with both marketing and sales teams for better collaboration. Implementation: Who : Form teams with people from marketing, sales, and IT. What : Create a smart computer program that predicts trends and focuses on what customers want. When : Start making this change right after managers agree to it, so it happens quickly. How : Teach employees how to use the new AI program and show them why it's helpful. Contingency Plan: If there are problems:  Help and train employees more.  Introduce AI slowly so everyone gets used to it.  Explain the good things about AI to address worries and show the positive results.

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Justification: This solution fits with modern ideas about managing a business:  Flexibility: Using AI helps us adjust to changes in the market.  Putting Customers First: AI helps us give customers what they want, making them happier.  Technology is OK: Training employees deals with any worries and makes sure the new system works well. 5]. Additional Question: How Does AI Help Businesses Reach Goals through Customer Segmentation? Using AI for customer segmentation is a game-changer in reaching business goals. Below are some reasons:  Understanding Customers Better : AI is like a super detective, figuring out what customers like and how they behave.  Personalized Marketing Magic : With AI, businesses can create special messages for each customer group, making them feel extra special.  Smart Resource Use : AI helps businesses spend their time and money wisely by finding the best customer groups.  Efficiency Boost : AI makes sure everything runs smoothly behind the scenes in marketing and sales. Also, while AI is fantastic, businesses need to use it responsibly, respecting customer privacy and being fair to everyone. This smart use of AI helps businesses succeed in today's tricky market.

Case study Week 2

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