AI Marketing Strategy: Grow Your Business With AI

1. Intro: Are you a small business owner looking to stay ahead of the competition and harness the power of artificial intelligence in your marketing? If so, you're in the right place. Hi, everyone. My name is Louise, and I've been working in digital marketing now for over 13 years in various industries. I also love helping small businesses with their marketing strategies through my freelance projects and courses. I have a master's degree in digital marketing communications, and I've recently completed the CIM qualification in AI and marketing, and I'm excited to share my knowledge and experience with you. AI is taking the world by storm and is rapidly transforming how we do business. Over 80% of industry experts are already using AI in their marketing. UK AI market alone is booming. Currently worth over 16.8 billion and expected to skyrocket to 801.6 billion by 2035. But while AI offers incredible benefits, like automating repetitive tasks, and making content creation and data analysis more efficient, it can be overwhelming. In fact, nearly half of marketers feel daunted by the prospect of integrating AI into their workflows. That's where this course can help. Together, we'll break down how you can strategically incorporate AI into your marketing without feeling overwhelmed. We'll cover the pros, cons, and challenges of AI in marketing, help you evaluate if AI aligns with your business goals and guide you in designing effective AI marketing objectives. You'll also learn how to select the right AI tools for you and analyze your success. By the end of this class, you'll be able to decide whether AI is the right fit for your business and integrated into your marketing strategy. Also have a practical workbook to guide you every step of the way. This course is designed for beginners and intermediates who are interested in learning more about marketing strategy and AI. If you're looking for a more in depth overview of how to create a marketing strategy for your business, I do have another course on how to create a marketing strategy for your small business. So if that's of interest to you, then please feel free to check that out. All you need to get started with this course is an Internet connection. I'm excited to get started. So if this course sounds interesting to you, then I'll see you in class. 2. Class Project: Welcome to your class project. Or your class project, you'll be creating your very own AI marketing strategy tailored to your business. This project will guide you step by step through the process of evaluating your current marketing efforts, identifying areas where AI can enhance your strategy, selecting appropriate AI tools, and planning for seamless implementation and a measurement of success. To help you along the way, I've prepared a project workbook available to download in the projects and resources. This workbook will be your roadmap, guiding you through each step as we progress through the course. After each lesson, you'll find a task designed to help you complete a section of your workbook. Don't worry if you can't fill in everything right away. This template is meant to be a practical tool that you can use in the real world. At the end of the course, I'd love for you to share just one section of your strategy in the project gallery. This could be anything that you feel proud of or excited about. I can't wait to see your strategies and provide feedback. Remember, I'm here to help, so don't hesitate to ask questions as we work through your project. Before we start, make sure to head over to the projects and resource section and download your workload Our first lesson we'll explore what AI is, how it works, and some of its powerful applications in marketing. If this sounds interesting to you, then I'll see 3. What is AI?: Welcome to our first lesson. Before we start crafting your AI marketing strategy, let's start with the basics. What exactly is AI? Artificial intelligence or AI is technology that enables computers and machines to simulate human intelligence and problem solving capabilities. Simply put, AI is programmed to emulate the human mind. This allows it to perform complex tasks, make decisions, learn, and solve problems in real time. Right now, all of the AI tools that we use in marketing can be classified as narrow AI. This means that they're designed to perform a specific task. For example, like search engines, chat bots, or digital assistants like Siri, while these tools are powerful, they can't operate outside of their programmed tasks. How does AI work? AI works by processing large amounts of data, whether that's text, images, or speech, using a series of algorithms. These algorithms learn and adapt based on user feedback, patterns, or errors. The quality of the data fed into AI systems is absolutely crucial. Por data leads to poor results. It's essential to make sure that your data is accurate and relevant. We'll go into more detail about the importance of data and AI later on in the course. Let's explore some AI use cases. First, we have natural language processing or NLP, which enables machines to understand human language. The goal of NLP is to enable computers to understand, interpret, generate, and respond to human language in a way that's both meaningful and useful. Some example, use cases in marketing would be an AI driven chat bot, an AI tool for sentiment analysis in social media, AI driven content generation, or voice search using technology like Alex. Next, we have machine learning. This is a subset of AI that enables a system to learn and improve without being explicitly programmed. Machine learning algorithms work by recognizing patterns and data and making predictions when new data is inputted into the system. Some examples of machine learning use cases in marketing could be recommendation systems. For example, like Amazon, suggesting products or spotify, suggesting songs based on previous listening behavior, predictive analytic tools, sales forecasting, social media scheduling tools and advanced customer segmentation and personalization. Tools that use machine learning include Google Analytics and customer relationship management tools like HubSpot. These tools use machine learning to analyze large datasets, identify patterns, make predictions, and provide actionable insights, enabling businesses to enhance their marketing efforts, personalize customer experiences and improve overall performance. Next, we have generative AI. Generative AI is a specialized subset of machine learning, focused on creating new original content such as images, text, music, or videos from existing data. Cases in marketing, would be tools that use AI to automate and enhance the creation of various types of marketing content. For example, tools like chat GPT, Google Bard, copy.ai, Magic write in Canva, as well as Google's Document AI that can summarize large documents. Next, we have computer vision. Computer vision enables machines to interpret and make decisions based on visual data. In other words, it aims to imitate human site. Marketing use cases can include visual search capabilities on e commerce sites, interactive campaigns using augmented reality, analyzing brand related images on social media. Facial recognition, automated image descriptions, and extracting text or insights from long documents. Some example tools include Google Vision AI and Hoot suites, Insights, which offer image analysis, object detection, and social media monitoring with image recognition. Next, we have robotic process automation or RPA. RPA automates repetitive tasks, using software robots or bots, streamlining processes like data entry, customer on boarding and campaign management. Tools like automation anywhere can help to automate data extraction, customer segmentation, and marketing analytics. Finally, we have autonomous systems. These are systems that can perform tasks without human intervention. Some use cases are drones, autonomous vehicles, or robotic process automation. An example of this in action is Amazon's drone delivery service primer. This is currently available in parts of the US, but is expected to expand into the UK and Italy by the end of 2024. Amazon also have over 750,000 robots working with their employees, taking on highly repetitive tasks and freeing up employees to focus on other areas. AI is everywhere right now and is growing rapidly in popularity. In a HobSpot survey, 64% of marketing professionals said that they use AI tools in some form with 40% using AI for data analysis, 39% for research, and 38% for content creation. AI is now integrated into many creative tools like Canva, organization tools like Notion, search engines like Bing, and analytics tools like Google Analytics. Applications of AI in marketing can include content creation, customer insights, and data analysis, image and speech recognition, chat box, and customer service, sales forecasting, using predictive analytics, targeted advertising, dynamic pricing, content personalization, and recommendations, social listening, automation of admin or repetitive tasks, which can give you more time to focus on strategy, adoptimization, and automated email campaigns. As AI technology continues to advance, the possibilities for its application in marketing are virtually limitless. Offering marketers new opportunities to enhance efficiency, effectiveness, and customer engagement. While this course covers the basics of AI, I encourage you to explore the further reading that is listed in the course workbook. Now it's time for your first class project. For this class project, I'd like you to write a brief summary explaining AI and its relevance to marketing. Include at least two real world examples of AI in marketing. There's a section to write your response in the strategy workbook provided in the projects and resources section. So if you haven't downloaded it, then go ahead and download that now. In the next lesson, we'll be looking at the benefits of AI for your business. I'll see you. 4. Benefits of AI: This lesson, we'll explore some of the benefits that AI can bring to your business and to your marketing strategy. The first benefit is improved customer experience. AI tools can provide improved personalization and advanced segmentation. AI systems can analyze complex data sets quickly. For example, online browsing behavior, purchase history, social media interactions, and then provide personalized insights or actions tailored to individual users. An example of this is Netflix's use of recommendations, which is driven by AI. The platform learns user preferences based on content watch how often when and even if content gets skipped or paused. This allows the platform to make personalized recommendations to individual users. This can lead to increased engagement on the platform and long term brand loyalty. AI can also help businesses to improve their customer service. For example, AI chat bots can help businesses deal with queries faster and ensure that support is available 247. Can help to give businesses a competitive edge, increase customer satisfaction, and reduce customer churn. Another way that AI can help with improving the customer experience is with improved customer insights. For example, predictive analytics in AI uses historical data to predict future outcomes. This could help with identifying lapsed customers before they lapse, helping with sales forecasting and creating more refined customer segments. AI can also analyze customer feedback and social media interactions, to gauge sentiment and improve overall customer satisfaction. Another major benefit of AI for businesses is improved ROI. Improved customer experience means better engagement and improved ROI for your campaigns. AI can also analyze campaign performance in real time and suggest and implement improvements with no human intervention. This can result in better engagement and improved ROI. The major benefit of AI businesses is greater efficiency and speed. Day to day tasks can be automated with AI. For example, scheduling social media posts, analyzing survey data, or responding to simple customer queries. This helps you to do more with less and spend more time focusing on more strategic or creative tasks. According to a recent survey, AI can help save the average professional 2.5 hours a day, and 95% say that it helps them spend less time on manual tasks. AI can also help with content creation and curation. For example, tools like Canva and chat GPT can be used to help consistently create vast amounts of content quickly and accurately to help save you time and giving you more chance to be creative. AI can also help with improved ad targeting. For example, determining which ads are likely to perform better and which users are more likely to engage and adjusting the messages and optimizing the ads in real time. This can help businesses to save time and focus their efforts elsewhere. The major benefit of AI for businesses is cost savings. Automation of repetitive or admin tasks presents obvious cost savings, as resources can be allocated more effectively, allowing you and your team to work on more strategic or important tasks. Improved add targeting and customer personalization means better ROI and less wastage on ineffective campaigns, and dynamic pricing can help to adjust prices in real time based on demand, competition, and stock, increasing sales and profits. The area that AI provides benefits to businesses is improved decision making. AI ensures that every decision is backed by data analysis. This leads to more informed and effective strategies and businesses being proactive instead of reactive, which means reduced wastage. AI also provides real time analysis, allowing businesses to respond swiftly to changing conditions and opportunities. AI can also predict future trends and outcomes based on historical data, helping businesses to anticipate market changes and adjust their strategies accordingly. Of course, implementing AI can give businesses a significant competitive advantage. Is because it enables businesses to be more agile, quickly reacting to market changes and opportunities, as well as providing innovative products, services, and customer experiences. The final benefit of AI for businesses is scalability. AI systems can scale up operations without the need for proportional increases in workforce, making it easier to handle growth and expansion. AI tools can also adapt to increased data loads and more complex tasks as the business grows, ensuring continuous efficiency and performance. For the class project, I'd like you to head over to your project workbook and list and describe three major benefits of implementing AI in your marketing strategy. Be sure to explain how each benefit can potentially impact your business. In the next lesson, we will explore how to evaluate your existing marketing strategy and understand where AI can fit in. 5. Evaluating Where You Are Now: Before implementing AI into your business, it's important to take a step back and be strategic about what tools you choose. And more importantly, why? Ensuring AI tools always align with your business goals. Goal here is to understand where you are now and identify how AI can enhance your existing efforts, not replace them. The first step is to understand your current position. First, let's evaluate your current business goals and marketing objectives. What are you focusing on right now? Are you aiming to increase conversions, improve engagement, boost brand awareness, generate leads, or enhance customer retention. Clearly defining these goals is the foundation of any effective AI marketing strategy. Well as focusing on your current business goals, you need to also think about who your target customer is. It's important to understand your customer, including their motivations and challenges so that any AI tools or strategies that you implement meets the needs and preferences of your audience. The next step is to audit your existing tools. Here, you want to take a close look at the tools that you're currently using. Can include customer databases, e mail systems, customer service tools, analytics platforms, and social media tools. Ask yourself, where can AI fit into these tools to streamline processes and improve outcomes? Assess your current technology, infrastructure, to make sure that it can support AI tools. This would include evaluating your hardware, software, and network capabilities. You also want to ensure that your current systems can integrate with AI tools without significant disruptions. Next, you want to assess current performance and KPIs. Analyze your current performance metrics and KPIs, including the performance of your website and each marketing channel that you use. Look at engagements like click through rates, open rates, and social media interactions. Are there areas where AI could help to improve these metrics? For example, if you have a high bans rate on your website, could implementing an AI chat bot help to potentially reduce this? Specific pain points where AI can make a tangible difference. You could also compare your current metrics with industry standards to identify gaps and any areas for improvements. Next, you want to look at any customer feedback and pain points. Customer feedback is a gold mine for identifying opportunities for AI integration. What are your customers saying about your current strategies? They're recurring customer complaints or suggestions. For example, if customers frequently mention receiving too many e mail campaigns, then AI could help tailor the frequency and content based on individual behaviors. Another thing that can help here is to map out your customer's journey. Here, you would map out the customer journey and pinpoint every interaction that they have with your brand. For example, from clicking on an ad on social media to navigating your website, to adding something to the basket. To potentially abandoning their cart or making a purchase? Each of these touchpoints presents an opportunity for AI to enhance the customer experience. Next, you should also carry out a workflow and team analysis. This would involve identifying the tasks that consume the most time and identifying how AI could help to streamline these. It's also important to assess the skills and resources within your business. Do you have the expertise needed to implement it in AI tools, or will additional training be required? Side your budget here as well. While some AI tools can be expensive upfront, they can offer significant ROI in the long term. Next, you also want to carry out a data audit. So this would involve looking at what data you currently have available now and where it is stored, as well as how it's collected. It would also involve looking at the accuracy, relevancy, and completeness of your data. It would also involve identifying any missing data or gaps or areas for improvements and any plans for how you want to collect that data going forward. Also want to make sure that your current data practices comply with regulations in your country, for example, GDPR in the UK, and then you would want to create a plan for how you will maintain data quality over time. This could involve regular data audits, data policies, or training, for example. Final area to consider when you're reviewing where you are now as a business is competitors. Here you'd want to look at how your competitors are using AI in their marketing, identify any AI tools they're using and evaluate the effectiveness of these tools. Just a quick recap of the main areas to look at when you're evaluating your existing marketing strategy and where you are now. Business goals and marketing objectives, your target customer, your existing tools, your existing performance and KPIs. Any customer feedback that you have and pain points, looking at the customer journey, looking at workflow and team analysis, looking at your data and doing a data audit, and finally, competitor analysis. Once you've considered all of these areas, you should have a good understanding of your current situation. The next step is to identify gaps and areas where AI could potentially fit in and enhance your strategy. For example, do you have repetitive tasks that AI could automate? Do you need help with content production, improving customer service, or boosting engagement? Be useful here to conduct a SWAT analysis, identifying strengths, opportunities, weaknesses, and threats, and I've provided a template for you to do this in the course workbook. Now it's time for your class project. For your class project, use the workbook provided in the projects and resources section to conduct an audit of your current marketing strategies and tools. Identify at least three areas where AI could improve your efforts. You can use the project workbook to help you, which has sections to cover each of the areas that we've discussed in this lesson. In the next lesson, we'll explore how to align your AI initiatives with your business goals to ensure maximum impact. 6. Aligning Business Goals: Now you've evaluated where your business stands, it's time to think about the specific goals that you want to achieve with AI. This step is crucial to ensure that you choose the right AI tools that will truly benefit your business and align with your goals. From the audit we just completed, you can start to identify the challenges that AI can help you to address. Are your key focuses, for example, on improving customer service, improving customer engagement, or increasing sales or leads. Perhaps you aim to raise brand awareness or reach a new audience. Whatever your goals, your AI tools need to be aligned with them. This is because different goals will require different tools and approaches. Let's look at the main areas where AI can enhance your marketing strategy. We have content creation, curation, and optimization. For example, AI tools can automatically generate content like product descriptions, blug posts, or social media ads. They can also optimize existing content for SEO, readability, and engagement, ensuring it resonates with your target audience and performs well in search engines. Personalized recommendations. AI powered product recommendations analyze customer data to provide personalized suggestions. These can be displayed on websites, in e mail campaigns or through targeted ads, increasing customer engagement and driving conversions. Customer segmentation. AI tools can segment customers based on behavior, preferences, and demographics. This allows for personalized marketing messages and tailored offers to specific customer groups enhancing the relevance of your campaigns. Social media listening and sentiment analysis. AI algorithms can analyze social media posts, customer reviews, and other online content to gauge sentiment and identify trends. This helps marketers understand customer perceptions, track brand sentiment, and respond to issues in real time. Conversion rate optimization, AI can improve personalization, AB testing, content optimization, and chat bot implementation to enhance user experience and increase conversion rates. Customer service and chat bots. AI powered chat bots and virtual assistants provide instant customer support. They can answer FAQs, help users find products, and facilitate transactions, improving customer experience and driving sales. Sales forecasting and customer behavior prediction. AI algorithms can analyze large datasets to predict future trends, customer behavior and market demand. These insights helped in making informed decisions about product development, pricing strategies, and advertising campaigns. Dynamic pricing for E commerce. AI can adjust prices in real time based on demand and stock levels, optimizing revenue and inventory management, task automation. Tomate repetitive tasks like email responses, social media post scheduling, invoice processing, and recruitment screening with AI to save time and resources. Image or voice based search, enhance user experience and engagement by integrating image and voice search capabilities onto your website. This makes it more accessible and user friendly. E mail marketing, automation, and optimization. AI can automate email campaigns, segment e mail lists, personalize content, recommend products, and optimize send times to increase open rates, click through rates, conversions, and ROI. An example of this is Winston AI in doot digital, which analyzes your data to sug personalized product recommendations, such as trending, last browse, most viewed, best sellers, bought together. It can also suggest copy and subject lines that will appeal to your subscribers. Dot digital also use predictive analytics to show which customers are likely to churn or buy again soon, as well as predicting a customers lifetime value and future orders. Targeting and optimization. AI can create highly targeted ad campaigns. Optimize ad spend and improve performance by analyzing user data. It can also generate multiple ad variations and test them in real time to identify the most effective creatives. Marketing analytics and reporting. AI can automate data collection and analysis, providing real time insights and detailed reports on marketing performance. This helps track KPIs, measure campaign effectiveness and make data driven decisions. Aligning AI with your business goals. Let's look at some examples of how small businesses can align their business goals with AI tools and technologies. Let's say your business goal is to increase customer engagement. Here, you've got a couple of AI solutions that could help you to meet this goal, including chat bots and virtual assistance. Chat bots could be put onto your website and social media platforms to provide instant responses to customer inquiries, offer personalized recommendations, and engage users in real time. Some examples of tools that you could implement could be Interco, drift or Zendesk. Another solution that you could implement to meet your goal of increasing customer engagement could be personalized content recommendations. So here you could use AI to analyze customer behavior and preferences to deliver content that's personalized to them on your website through the form of product recommendations and offers. Some tool examples include dynamic yield and algola. Let's look at another example. Let's say that your overall goal is to enhance the customer experience. There's a couple of AI solutions that you could look at here, for example, visual and voice search. Could integrate AI powered visual and voice search on your website and mobile apps to help improve product discoverability, and customer convenience. Another thing you could do is personalize customer journeys. Use AI to map and personalize the entire customer journey, ensuring each touch point is optimized for the best possible experience. Tools that you can use to help with this include Salesforce Marketing Cloud or Adobe Experience Cloud. By aligning AI tools with specific goals, small businesses can create more personalized, effective and efficient marketing strategies. Ultimately, driving growth and improving customer satisfaction. Your class project, I'd like you to identify one to three priority business goals for your own business and what AI solutions you could potentially use to help meet those goals. In the next lesson, we'll learn more about how to set your specific AI marketing objectives based on your business goals. 7. Setting AI Objectives: Now you've chosen the goals that you want to focus on with your AI solution. It's time to clearly define what you aim to achieve with AI. Here I would create one to three AI marketing objectives that will have the most significant impact on your businesses success? Aligning these with your business goals and your current marketing strategy. Remember to ensure that your objectives are smart. This stands for specific, measurable, achievable, relevant, and time bound. Let's break this down with an example. Imagine you run an E Commerce website, and your most important business goal is to increase the percentage of repeat customers over the next six months. How can you use AI to achieve this? Instead of vaguely saying, I want to increase repeat customers using AI? A smart objective would be implement an AI driven personalized recommendation system on the E commerce platform to enhance the shopping experience and increase customer attention by 20% over the next six months year on year. This objective is smart because it specifies an exact requirement for the AI system, sets a time limit and includes a measurable target of 20%. Why do smart objectives Aart objectives are important because they help to provide clarity and focus. For example, clear objectives help you to focus on what needs to be achieved with the new AI tool. They also help you to measure results, including tracking progress, evaluating performance, and determining the ROI of the AI implementation. Setting realistic objectives avoids disappointment or failure. Always ensure the targets are achievable for your business. Ways align AI objectives with broader marketing goals to ensure they are relevant to what you want to achieve as a business. Setting deadlines is important to ensure targets are met and that progress is monitored. Overall, smart objectives provide a structured framework for implementing AI tools into your marketing strategy. They help to set clear achievable goals, measure progress, and drive success. How many objectives should you be looking at? Number of objectives to focus on depends on various factors, including your available resources, the size of your business, and also the complexity of the AI solutions that you plan on implementing. I would suggest no more than one to three objectives at this stage. So for your class project, I would like you to create one to three smart AI marketing objectives that align with your most important business goals. Use the workbook provided to document your objectives. In the next lesson, we will learn how to identify suitable AI tools to help meet your objectives. 8. Selecting AI Tools: Now that you've defined your key objectives and identify the type of AI solution you need. Let's talk about how to select the right AI tools for your business. When selecting an AI tool, it's important to consider several points to ensure that the tool not only meets your needs effectively, but also provides a good return on investment. Now we will run through the main areas to consider. Firstly, it's important to align the AI tool with your marketing objectives. Always ensure that any AI tool you select aligns with your objectives. Example, if we go back to my example objective from the previous lesson, which was to implement an AI driven personalized recommendation system on the E commerce platform to enhance the shopping experience and increase customer retention by 20% over the next six months. Here we want to focus on customer retention. Looking at AI recommendation systems would be appropriate and align with this objective. Wouldn't be looking at implementing social media monitoring tools, for example, as although useful, it wouldn't help us to meet this specific objective. In summary, verify that the tool that you choose has features that will help you to meet your specific marketing objectives. Consider the integration with your current systems. It's really important to make sure that the AI tool can seamlessly integrate with your existing marketing stack, such as your current CRM system, e mail marketing platforms, social media management tools, and e commerce platforms. Ability is important, so make sure that you choose a tool that can grow with your business and accommodate increased data and user loads as your business expands. Also make sure that the tool is affordable and fits within your budget. Estimate the costs associated with implementing AI tools, including purchase, implementation, and ongoing maintenance costs. Project the potential return on investment from using AI tools. Consider both short term and long term benefits. Assess the potential ROI by considering how much time, effort, and resources the tool can save you and how it can help boost your marketing performance and revenue. Ease of use is important. The tool should be user friendly and not require advanced technical knowledge. Ensure the vendor provides adequate training and ongoing support to help you get the most out of it. Also make sure your team has the necessary skills or arrange training if needed. Consider it the vendor reputation. Choose a vendor with a proven track record of delivering reliable and effective AI tools. Read customer reviews, and seek recommendations from other businesses to understand the vendor's reputation and the tools reliability. In short, the vendor offers robust customer support and maintenance services. Check for availability of support channels such as live chat, phone support, and account managers. Assess whether the AI tool allows for customization to fit your specific needs. Customizable tools can be tailored to better suit your business processes. Establish metrics to assess ROI, and continually review and adjust these as needed. We'll cover more about setting metrics in the upcoming lessons. Verify that the tool offers detailed performance metrics and reporting capabilities. This will help in tracking the effectiveness of the tool and making any necessary adjustments. Ensure the AI tool complies with data protection regulations such as GDPR, CCPA, and any other relevant standards for your country. Verify that the vendor has robust security measures in place to protect your data from breaches and unauthorized access. Select a vendor that invests in continuous innovation and stays up to date with the latest advancements in AI technology. Look at the vendors product roadmap to ensure they plan to enhance the tool with new features and improvements over time. Make sure you and your team also keep up to date with the latest trends to ensure you're using the best tools for your business. Consider the type of solution. There are many out of the box solutions available, such as tools like Chat GPT and Google Bard, and many others that will run through later. These are easy to implement and may be better suited to smaller businesses. Alternatively, you could develop a custom AI implementation which may require additional expertise, but can be highly effective in the long term. This option is probably more suitable for larger organizations and those with more available data. Finally, opt for tools that offer a free trial period or demo. This allows you to test the tool in your environment and ensure it meets your requirements before making a commitment. Carefully considering the points discussed in this lesson. You can select an AI tool that not only meets your current marketing needs, but also supports your businesses growth over time. Remember, it's not about having the most advanced AI tool. It's about choosing a tool that aligns with your goals and marketing objectives and helps to generate ROI. For the class project, I'd like you to research and select one to three AI tools that align with your identified business challenges and goals. Provide a brief overview of each tool, including its features, cost, and how it fits your business needs. In the next lesson, we'll explore the importance of data when implementing an AI tool. 9. Importance of Data: This lesson, we're exploring a crucial aspect of AI marketing data. The quality, relevancy, and accuracy of your data is vital for a successful AI marketing strategy. Before implementing any AI tool, it's essential to consider the data you have and the data that you may need to collect to help meet your specific goals. So why is data so important? Data is important when training AI models. For example, AI models learn from data. So high quality, relevant and clean data lead to better train models that can make more accurate predictions and decisions. While more data helps AI models to recognize patterns and nuances, always short you only collect necessary data to avoid unnecessary complexity and privacy issues. Personalization and targeting. Data on customer behavior, preferences, and demographics, enables AI to personalize marketing efforts, significantly improving engagement and conversion rates. Accurate data also allows for effective customer segmentation, enabling targeted marketing strategies tailored to different customer groups. Data driven insights also help to optimize marketing campaigns. AI tools analyze past performance to suggest improvements and optimize ad spend, targeting, and content strategies. Data also enables AI to automate routine tasks, like e mail marketing, social media posting, and customer support, increasing efficiency and freeing up time for strategic activities. AI tools use historical data to predict future trends and outcomes. Aiding in decision making for sales forecasting, customer behavior prediction, and identifying potential churn. Access to real time data allows AI to provide up to date insights, enabling quick responses to changing market conditions and customer needs. Data on customer queries and interactions helps to train AI powered chat box, to provide accurate and relevant responses, enhancing the customer experience. Analyzing how users interact with your website or app helps identify pain points and opportunities for improvement. Data is essential for tracking the performance of AI driven marketing initiatives. Metrics like conversion rate, click Ru rates, and customer acquisition costs help to measure ROI. Ongoing data collection and analysis allows businesses to continuously improve the AI models and marketing strategies based on Feed. Performance results. Ensuring data compliance with regulations like GDPR and CCPA is crucial. Proper data management helps to avoid legal issues and builds customer trust. Ensure users can opt out, are informed about data collection, and how their data will be used, and also ensure that data is stored securely. Ensuring data quality and diversity prevents biases in AI models, creating fair and ethical AI applications. Data can reveal new trends, customer needs, and market opportunities, driving innovation and helping businesses to stay competitive. Continuous data collection allows AI tools to adapt to new information, improving accuracy and effectiveness over time. Depending on your objectives, sources of data to fuel AI tools could be behavioral data. Tools like Google Analytics provide insights on website traffic, conversion rates, and user behavior. Social media. Engagement metrics, such as likes, shares, follower demographics, and trending topics, e mail marketing data, such as open rates, click through rates, conversion rates, list growth, and unsubscribe rates. Search engine data, such as keyword rankings, back links, search trends and popular searches, sales data, so trends from your CRM or point of sales systems. For example, purchase history, interaction history, average order value, product performance, stock, et cetera. Customer data, so customer profiles and demographics, customer support interactions, so FAQs, chat logs, call center interactions, product data from inventory management systems, such as stock levels, customer feedback, so reviews, surveys, and feedback data, and market and competitor data. So things like market research, reports, competitor analysis tools. Of course, as a small business, you may not have vast amounts of data available, but that's okay. If your business has limited data, you can still implement AI tools by prioritizing data collection. So gradually build your data set in a compliant and secure way. Use pre trained models. Use AI tools from providers like Google, Amazon, Microsoft, and Open AI, which are trained on large datasets and require minimal additional data. And start small. Introduce AI incrementally with projects that require less data, such as chat bots for simple customer queries. In summary, data is the foundation of any successful AI implementation. High quality, relevant, and well managed data, ensure that AI tools operate accurately and efficiently, delivering valuable insights and driving better business outcomes. For your class project, I'd like you to assess the quality and availability of your current data. Write a short paragraph outlining your data strategy in your project workbook. In the next lesson, we'll explore some common challenges of using AI in marketing. 10. Challenges of AI (part 1): Whilst AI is incredibly powerful and provides obvious benefits to businesses, it's also important to understand its limitations and challenges. Let's discuss these challenges now and how we can overcome them. The first challenge is that AI is not always correct. AI can and does make mistakes. It's crucial to back check and tweak content that AI produces, especially any important information such as stats. Avoid just copying and pasting AI generated text. This is especially important if you're using AI text for social media posts, blog posts, e mail marketing, or any other marketing copy. It's important that the copy is correct, but also still sounds like your brand and your brand voice. Chat bots, for example, they may misinterpret context, leading to inappropriate or incorrect responses. They might also not fully understand cultural differences, which may lead to messages that might be perceived as offensive or insensitive in certain contexts. AI models should be continuously trained with updated and relevant data to keep them accurate. In the case of chat bot, it's always a good idea to balance the use of chat box with real live human agents to avoid customers getting frustrated or becoming unengaged. This leads nicely on to the next point which is human touch. AI is great at producing vast amounts of quality data quickly, but it does lack human emotion and creativity. Over reliance on AI can lead to flawed marketing campaigns in the following ways. AI might miss subtle cultural and contextual nuances that human marketers can detect. AI generated content might also lack the emotional resonance and creativity that humans can provide. Over reliance on AI can stifle human creativity and innovation as marketers might defer too much to AI recommendations and overlook new out of the box ideas. I generated content can lead to a lack of originality, resulting in campaigns that feel generic and uninspired. And over automating customer interactions can lead to a lack of personalized service which can alienate customers who value human interaction. While 76% of professionals believe employees should use AI, they also caution against become overly reliant on it. Therefore, AI can be great for generating ideas, automating repetitive tasks that take up time or dealing with basic customer queries. But it's really important not to neglect the human touch in your marketing strategy. A balance will help you to maintain customer connection and brand loyalty. Another challenge of using AI in marketing is the quantity and quality of data required. AI algorithms need large amounts of high quality data to function effectively. If your data is fragmented or stored in different systems, this can be a challenge. Overcome this, conduct a thorough audit to identify inconsistencies, errors or gaps, as we've already discussed, invest in tools to clean and enrich your data and implement processes to collect data and maintain data quality over time. Another challenge of using AI in marketing is that it can require resource and it can be expensive. Implementing AI tools can be costly, both in terms of initial investment and also ongoing maintenance and support. Small businesses with limited resources may face challenges in allocating resources for AI initiatives and may need to carefully prioritize investments based on expected ROI. To overcome this, Consider combining AI's data driven insights with human creativity. Develop a detailed budget and ROI analysis to evaluate the potential costs and benefits of AI initiatives and prioritize investment based on expected ROI. Explore cost effective options such as Cloud based AI services or open source AI tools that offer scalability and flexibility without requiring significant upfront investment, consider starting small with out of the box AI solutions that require minimal data. Many tools are inexpensive and free and offer free trials. We will explore some of these tools later. A fear the challenge is around data security and privacy. Ing and analyzing customer data for AI applications raises concerns around data security and privacy. It's important to comply with the relevant regulations in your country and implement security measures to protect customer data from unauthorized access or misuse. The main points to consider here are. Always obtain explicit consent when collecting data, explaining why and how the data will be used. Only collect the data you need, and use anonymous data where possible. Users should always have control over their data and be able to opt out. Develop privacy policy that outlines how customer data will be collected, stored, and used, implement security measures such as encryption, access controls, and regular security audits to protect customer data from unauthorized access or breaches. Provide training and awareness programs for employees to ensure that they understand their responsibilities regarding data privacy and security. 11. Challenges of AI (part 2): It's important to be aware of the potential bias of AI tools, especially in the areas of targeted advertising and predictive analytics. For example, if a training data set over represents a certain demographic, AI models can produce outcomes favoring that group. An example could be an AI recruitment tool which favors male CVs and puts them forward for interviews more than female CVs due to the data that they were trained on being biased towards male candidates. It's important to be mindful of the potential of bias in data and algorithms and to take steps to mitigate the risks. These can include. Ensure data does not contain bias when it's collected. This not only allows for more accurate outputs, but will help to avoid legal issues and potential fines. Keep up to date with ethical guidelines in AI. Audit AI tools regularly to prevent bias, foster transparency and accountability in AI decision making by documenting the rationale behind their decisions. Implement rigorous testing and validation processes to identify and mitigate bias in your data and algorithms. Establish ethical guidelines and principles for AI usage within your organization and ensure that employees are trained to recognize and address ethical concerns. The next challenge is integration and compatibility. Integrating AI tools with existing systems can be complex, especially if your technology stack is diverse or outdated. Help overcome this, you should conduct a comprehensive assessment of all your existing technology and tools that you use and systems that you use to identify potential integration challenges and compatibility issues like we discussed in the audit section. This will then help you to be able to prioritize AI tools that offer seamless integration with your existing systems. You should also work closely with IT and engineering teams if you have them to ensure that integration efforts are well coordinated and implemented. The challenge in introducing AI into your marketing strategy is user acceptance and adoption. Introducing AI tools into your marketing strategy may require changes to your existing workflows and processes. This can meet resistance from employees and customers too. Research shows that only 20% of the UK population was willing to trust AI systems. What are some ways that you can overcome this? Ensuring buy in and acceptance from stakeholders through training and communication is crucial for successful AI adoption. Transparency is really important. It's important to be transparent with customers about the use of AI, how it works, and how their data is used. Highlight the benefits which will help to foster customer trust and loyalty. Nearly three quarters of UK adults believe that brands should always disclose their use of AI generated content and that fully automated AI driven marketing campaigns should be carefully regulated. Always try to strike a balance between automation and the human touch, as we've already discussed. Ensure AI tools have a feedback loop, so allow AI systems to learn from user feedback and refine, provide comprehensive training and support for employees or users to familiarize them with AI tools and workflows and address any concerns or resistance to change, and always make sure that AI tools are user friendly. Another challenge where marketing and AI is concerned is measuring ROI, measuring the ROI and effectiveness of AI initiatives can be challenging, particularly if the impact is not immediately apparent or if success metrics are unclear. Important to define clear objectives and KPIs upfront and implement robust tracking and analytics to monitor performance. Regularly assess ROI and review and adjust your strategies accordingly. The final challenge of implementing AI intermarketing strategies is skill and talent gap. Implementing AI technologies often requires specialized skills. Expertise in areas such as data science, machine learning, and programming, finding and retaining talent with the necessary skills can be challenging, particularly for small businesses with limited resources and budget. Me Ways to overcome this are to invest in training and upskilling programs, develop the skills, and expertise required for AI implementation, both within your marketing team and across the organization. Consider partnering with external consultants or hiring freelancers with specialized AI skills to supplement your internal capabilities. Also, consider online learning resources such as courses, tutorials, and webinars, to stay updated on the latest developments in AI technology and best practices. Proactively addressing these challenges and implementing best practices, you can increase the likelihood of success in implementing AI into your marketing strategy and maximize the potential benefits of AI technologies for your business. For the class project, I'd like you to identify and discuss two potential challenges of implementing AI into your marketing strategy. Propose solutions or mitigation strategies for these challenges, and detail this in your project Wbook. In the next lesson, we'll be looking at implementation of AI tools. 12. AI Implementation: You have established your objectives and identified the right AI tools for your business. It's important to develop a plan for implementation. This requires careful planning and a structured approach. Here are some things to consider. Always keep your objectives in mind. Establish key performance indicators, or KPIs to measure the success of your AI implementation. This could include metrics like reduced customer service response time, increased sales, conversions, or improved marketing ROI. Develop a clear roadmap for implementation, including timeline and milestones. A timeline with key milestones for the implementation process. Assign team members and allocate resources for the project. Identify potential risks and develop mitigation strategies. Prepare your data. Ensure your data is accurate, relevant, and clean, poor quality data, as we've already discussed, can lead to inaccurate AI predictions and outcomes. Implement strong data governance practices to maintain data, integrity, security, and compliance with regulations like GDPR. Integrate data from various sources to create a unified dataset. Start small. Gin with small scale pilot projects to test the AI tools effectiveness and whether they are meeting the KPIs. This allows you to evaluate its impact, collect, user feedback, and refine your approach without committing significant resources. Assess the results of your pilot project. If successful, gradually scale up your AI efforts, integrating more complex tools and processes, gradually integrate AI into your business processes. Start with the areas where AI can have the most immediate impact and expand from there. Utilize pre trained models and AI services from providers like Google, Amazon, and Microsoft. These models require less data and can be customized for your specific use cases. Focus on user training and adoption. Train your employees on how to use the AI tool effectively. Provide comprehensive training sessions, documentation, and ongoing support. Encourage employees and customers to embrace AI tools. Demonstrate the benefits and involve them in the implementation process to gain their buy in. Be transparent with your customers about how you use AI, especially in terms of data privacy and security. Ensure team collaboration, especially marketing and technical teams, Ensure teams are working towards the shared objectives. Knowledge sharing should always be encouraged. Regularly monitor the performance of the AI tool against your KPIs. Use insights from monitoring to make necessary adjustments. Establish a feedback loop to gather input from users and stakeholders. Use this feedback to improve the AI tool and its integration into your business processes. This is an example of an implementation plan. Obviously, it can be adapted for a specific business or situation. For example, Mumps one and two would be planning and data preparation. This is where you would define your AI objectives and metrics, and where you would conduct your data audit and clean data needed. Then months three to four, you may select your tool and run a small pilot project, and then Mus five to six would be where you would train your team on the new tools and evaluate the performance of the pilot project. Then after this, month seven and eight would be where you would scale up the successful AI initiatives, continuously monitor performance and gather feedback, and then ongoing Months Dan 12, you would stay updated with AI trends and optimize based on feedback and performance data. By following these best practices, businesses can effectively implement AI tools to enhance their businesses operations, improve customer experience, and help to meet their objectives. In summary, careful planning, starting small, ensuring data quality, and focusing on user adoption are key to successful AI implementation. Class project, I'd like you to use a template provided in the Project workbook to develop an implementation plan for integrating one of the selected AI tools you've already identified into your marketing strategy. Include timelines, resources needed, and key milestones. In the next lesson, we'll be looking at ways you can measure the success of your AI marketing strategy. 13. Measuring Success: You have implemented your new AI tool, it's vital to continually measure its effectiveness against your objectives. Here you would define your KPIs or key performance indicators. What will you measure to know whether your AI strategy is effective? The metrics you choose will depend on your specific objectives. But let's look at some examples. If you're measuring engagement or customer metrics, some of the things that you could measure include. Customer satisfaction. So here you could measure customer satisfaction through surveys, feedback forms, or net promoter score. For improvements in customer satisfaction ratings after implementing the AI tool. You could also look at conversion rates and track changes in conversion rates before and after implementing the AI tool. This could include online sales, lead generation, or any other relevant conversions. You could also monitor engagement metrics such as time spent on the website, click through rates, and interaction rates to see if the AI tool is enhancing user engagement. You want to measure operational efficiency, you can look at things like time saving, so evaluate the reduction in time spent on tasks automated by the AI tool. For example, if the AI tool automates customer support, you could track the time saved by your team. You could also calculate the cost savings resulting from the AI tool. This could include reduced labor costs, decreased error rates, and improved resource allocation. You could also measure changes in productivity. For example, if the AI tool is used for content generation, you could track the increase in the volume of content produced and the reduction in the time required to create it. You're measuring financial metrics, you could look at things like revenue growth. You could track revenue growth to see if the AI tool is contributing to the increased sales or revenue streams. You could compare revenue before and after the implementation. You can also calculate the ROI of the AI tool by comparing the financial benefits gained against the costs for its implementation and maintenance. Also measure any changes in the cost of acquiring new customers. An effective AI tool should help to reduce the customer acquisition cost by improving marketing efficiency. You can also measure AI specific metrics, things like accuracy and precision. If your AI tool involves predictions or classifications. For example, in the case of recommendation engines, you could monitor metrics such as accuracy. Position and recall. You can also measure error rates so you could track the reduction in error rates for tasks automated or enhanced by the AI tool. This is particularly relevant for tasks like data entry, billing, and customer support. You can also measure the reliability and uptime of the AI tool. So consistent performance without frequent downtimes is a key indicator of success. Things you could measure include user adoption and satisfaction, so you could monitor how quickly and extensively your employees and customers are adopting the AI tool. High adoption rates are a positive sign of the tools usability and value. You could also collect feedback from employees and customers who are using the AI tool. Positive feedback and reports of improved workflows or experiences can indicate success. Make sure you collect both qualitative and quantitative feedback to provide insights into potential improvements. For example, if you've implemented a chat bot, at the end, the customer could be asked to rate the experience and provide feedback. This is often called a feedback loop and will allow the AI tool to be improved and refined over time. You can also track the amount of training and support required for users to effectively use the AI tool. A successful tool should be intuitive and require minimal ongoing support. You can also compare performances against baseline data and benchmarks. For example, baseline data collected before the AI tool was implemented, and then you can look for any measurable improvements across key areas. You can also compare your results with industry benchmarks to gauge the AI tools effectiveness relative to your other businesses in your s. Also important to ensure continuous improvement and iteration. For example, monitor how the AI tool improves over time, with updates and additional data. Continuous improvements will indicate a successful, adaptive AI implementation. You can also conduct regular AB tests to compare the AI tools performance with previous methods. This helps to quantify the tools impact on specific metrics. For example, you could compare two versions of your website or ad campaign, one using an AI tool. Or AI generated copy, or test an AI driven customer recommendation against a manual recommendation and see which performs better. This can help you to continually learn and make improvements as you go along. Let's go back to my original objective from the previous lesson and suggest some KPIs that I could monitor as an example. As a reminder, the objective was, implement an AI driven personalized recommendation system on the E commerce platform to enhance the shopping experience and increase customer retention by 20% over the next six months. With this objective, I am focusing on increasing customer retention with AI. Metrics, I could measure include Customer retention rate, repeat purchase rate, click through rate on the recommendations, conversion rate from the recommendations, average order value, time on site, page views per session, sales or revenue from the recommendations, accuracy of recommendations, customer satisfaction with recommendations. The main takeaway is that you need to ensure that your metrics are helping you to monitor your specific objectives. By regularly tracking relevant metrics and comparing them to predefined benchmarks and baselines, you can ensure that the AI tool delivers value to your business and helps to support your strategic objectives. Regular reviews and adjustments based on these insights will help you to adjust your strategy as you go along and improve performance. To monitor your performance, you could use reporting tools such as Google Analytics, tableau, or PL BI, or use the reporting features that are integrated with the specific AI tool. For the class project, I would like you to define the KPIs or key performance indicators that you will use to measure the success of your AI marketing strategy. Explain how you will track these metrics and adjust your strategy based on the results. In the next lesson, we'll be looking at helpful AI tools for small businesses. 14. Helpful AI Tools: Reality, small businesses are unlikely to have the budget or resources to implement a large scale AI system, or the data, knowledge, or resources to train an AI tool. But don't worry. There are many free AI tools, as well as models that have already been trained on large datasets, by providers like Google, Amazon, Microsoft, and Open AI. These models can provide various tasks out of the box and require minimal additional data. Now I'm just going to run through some examples of AI tools that may benefit small businesses. First tool is Chat GPT by Open AI. Chat GPT generates any copy, it can generate marketing copy, blog post, social media content, product descriptions, e mail content. It can also help with providing creative ideas. It's actually available for free, but there are various pricing tiers based on usage. It's a really versatile tool for creating high quality conversational contents across various marketing channels. Also custom versions of Chat GPT that are called GPTs that you can, as of recently access with a free account. These are essentially tools created using at GPT that have been trained in specific areas. For example, writing, productivity, programming, marketing, copywriting, and more. So here's an example of something that I asked Chat GPT for just to give you an idea of what it can do. I've actually started to use C chat GPT f. I've now started to pay for that, but you don't need to pay for it. You can do a lot of this stuff just with the free version of Chat GPT. But I've asked it to create me some variations of a linked in post to help me to promote my latest skill share course. Within seconds, it comes back with five different options that I could use. Now, obviously, I wouldn't use them word for word. I would adapt them before I posted anything. But if you're busy and you've got a lot of things to do, it can really help to take the stress away of trying to think of ideas all of the time, and it gives you a good start. Other example of a tool that I use quite a lot is Canva. Canva has lots of AI features, things like Magic design, which allows you to describe what you want to have designed. For example, social posts and presentations or anything, and it will just design it for you. Then obviously, you can tweak it. There's also the same for video. There's Magic writes, so you can type a prompting, and then it will help you to generate content a little bit like chat GPT. Then there's other features like resize, so you can effortlessly change the size and format of designs. There's also text video, text image, Magic it, Magic grab, Magic Expand, and loads of other AI features. Canva is really good at allowing you to quickly and easily create graphics for social media, emails, or any marketing material that you have quickly, easily, and saves a lot of time. There is a free version of Canva, but the pro plan is pretty cheap. I think it costs me about 99 pounds for a year. Family is another tool that I use. It's an AI powered writing assistant that provides grammar and spell checks. Style and tone suggestions and also plagiarism detection. There's a free version available that I use, and that has basic features. But I think the premium plan start from about $12 a month. Grammy helps to enhance the quality of written communication for e mail, social, and marketing materials. There's also Trello, which again is something that I use, that's quite good for project management, and that's got AI powered automation for task management and workflow optimization. Again, there's a free version available, but the business plan is about $10 per user per month, and it's really good for organizing projects, tasks, and collaboration efforts efficiently. Another useful tool for small businesses is Hoot Suite. Hoot Suite has social media scheduling, monitoring, analytics, and also AI driven post recommendations. Also, they've got a tool called hourly writer AI, which helps you to create social media content like captions and posts very quickly and easily across all networks.'s also free for Hoot suite users for a limited time. Hoot Suite is also free, but they have professional plans available, and it allows businesses to manage and automate social media marketing, saving time on scheduling and monitoring posts. Another tool that can be useful for small businesses is copy AI. Copy AI helps to generate marketing, copy, blog post, product description, social media content, et cetera. Again, there's a free plan with limited features. Helps you to quickly create engaging marketing copy for various platforms. Another useful tool for businesses is Ad creative AI. This is an AI driven platform that generates high performing ad creators for various platforms. So Facebook, Instagram, Google Ads, Linked in. So if your business uses paid social media, then this be quite useful. You upload your logo, your brand colors, and it will generate paid social media ads for you for whatever platform you choose, and it will create hundreds of variations, and it will organize them by the ones that are generally the most engaging. You can choose different imagery, and it just creates them in seconds. It saves a lot of time and it can analyze performance data as well to optimize creatives, and it will integrate with your specific platform. Plans start from about $29 per month, but it's quite good for businesses looking to quickly generate and test. Lots of different add creatives to find the most effective ones. Another tool is Jasper AI. Jasper is AI driven content generation. So for long form articles, blog posts, social media. This produces high quality, engaging SEO optimized content, and includes various templates for different types of content. It supports long form content generation and ensures that content is on brand. It also has an extension for apps like G mail, word press, linked in. Plan start from $39 per month, and there is a free trial available. There is HubSpot CRM. This is CRM with marketing, sales, and customer service tools, including AI driven insights. There's a free plan available. Pad plans for additional features start at $45 per month. The use case of HubSpot is that it manages customer interactions and enhances marketing and sales processes. They also have specific hubs available for marketing, sales, customer service, content, operations and commerce. Also have a useful free blog ideas generator. Another tool is Lumen five, which is an AI powered video creation platform that transforms text content into engaging videos. There's a free plant available with basic features and paid plans start from $19 per month. This helps to create marketing and social media videos quickly and easily, and then there is Intercom AI driven customer chat bot for real time support. This is ideal for businesses looking to provide personalized customer interactions, automate support tasks, and engage users proactively. There's a free trial available, but to costs are from $39 a month. And they have an AI agent called Vin, which resolves 50% of customer questions instantly. These are just some of the AI tools available at the time of filming this course. AI tools are constantly evolving and being updated and changing. And it's really important to stay updated with AI news and technology and developments so that you can make sure you're using the best tools to help you meet your objectives. New tools are emerging every day, and it's really important to do your research. But the right tools aligned with your specific needs and marketing objectives can help to grow your business and your ROI. 15. Final Thoughts: Congratulations. You've made it to the end of this course. Thank you so much for taking the time to take this class. I really hope that you've learnt something new that will help benefit your business. If you enjoyed the course, please consider leaving me a review and feel free to follow me on Skillshare to keep updated with my future marketing courses. As a recap, we have learned about what AI is and the pros and cons for small businesses. We've also explored how to evaluate where you are now and align your business goals with potential AI tools. We've looked at the importance of data when it comes to implementing and getting the most out of AI, as well as best practices around implementation and measuring success. Finally, we've looked at some current AI tools that may be helpful for small businesses. Key takeaways from this course are to remember that the goal of using AI is not to replace the systems and processes you currently use, but to enhance them and make your life easier. Always align any AI tool or initiative with your marketing goals and develop smart objectives. Try to always balance AI automation with the human touch. Start small. Explore AI tools that can help you become more efficient by automating repetitive tasks. For example, solving repetitive queries, creating content quickly or scheduling social media posts. Will save time and allows you to focus on more strategic activities. Highlight any gaps and high impact areas where AI can deliver the most significant impact with minimal investment. Utilize free or low cost and pre trained AI models that require minimal data or customization like Chat GPT or granule or content enhancement. Continuously analyze your data against your KPIs to refine your strategy and improve outcomes. Be transparent with your customers about how you use AI, especially in terms of data privacy and security. Don't implement AI tools for the sake of it. It's not helpful or viable for you at this time, that's okay. You can always revisit this process in the future. Prioritize data. Now is the time to audit your data processes. Implement strong data governance practices to maintain data integrity, security, and compliance with regulations. Integrate data from various sources to create a unified data set. Keep learning and stay updated with new AI tools, AR regulations and emerging technologies. By subscribing to industry newsletters and blogs like Open AI, Google AI, and IBM Watson, or attending online conferences and webinars. I've included a list of places and sites where you can keep updated with everything AI in the project Workbook. Don't forget to complete your strategy workbook and share any sections or elements you feel comfortable with in the project gallery section. I'll be sure to leave feedback If you're interested in learning more about how to create a marketing strategy for a small business, then check out my other skill share course, for a more general overview. Thanks again for watching well done for making it to the end, and I'll see you in the next one.