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Smart Implementation of AI in Data Analysis and Predictions

Along with updating your technology, data is carried in a huge way from various resources for AI implementation to carry out better business decisions. And for all data processing, Analytics has been an active part that is changing in the business for a long time. 

Organizations are mastering with skills to visualize and analyze data and predict for the future to increase business efficiency. 

And if we talk about marketing almost every marketing campaign relies on the data.

For any product or service, marketing from a digitalization platform needs customer preference and customer behavior for a particular product. And for the same, Artificial Intelligence is used to personalize marketing messages for users and to assist them with real-time experience. 

AI proves as a more significant competitive advantage and boosts the baseline of the business.

To help your company recognize how AI in data analysis can benefit your production line and overall business, we have curved up some examples of smart implementation. 

Let’s see some insights from the professionals, and business use cases to give you the track for advanced data analysis yourself. 

Let’s start with Google, who is investigating AI algorithms for each development cycle for mobile application features like speech translation, natural language processing, and search ranking and prediction systems. 

Now, a question arises, what impact would AI have on future marketing?

You must have heard or read opinions of AI implementation that increases marketing and got concerned about it.

Let’s see how AI impacts your work and business process as well and how to tackle it with intelligence?

Many people are not aware of machine learning aspects. So, let me clear that ML is a part of AI and overall a part of the automation process.

Here is the example of a chatbot that works with the help of AI by using ML algorithms. It mainly works through algorithms and logic that has been proved by AI-powered systems. And as per the latest research, ML and AI are creating more demand for employees.

Furthermore, AI helps drive a significant outcome and an unbelievable ROI:

  • For 75% of organizations, using AI has helped drive customer satisfaction by 10% as well.
  • 9 of 10 organizations that have implemented AI and successfully gained more than 10% boost in sales.
  • Finally, as per the report exposed, businesses using AI to power data-driven insights in marketing that helps for data prediction growing to $1.2 trillion in just two years. 

How brands use AI in marketing – examples of AI-powered marketing campaigns

  1. Personalization:
    Myntra, as a known retail brand, assists their customers with real-time services by suggesting some products based on customers’ previous purchases. AI-based algorithms are used to facilitate such services and to predict fashion and user preference based on data.

    Spotify as a digital music service provider analyzes data to facilitate users with a personalized experience. They identify a history search and recommend other songs, playlists or artists that match their flavor of music.  
  2. Dynamic Pricing:
    To determine with most competitive pricing, we use AI to monitor trends and cost determination. Mostly the pricing aspect is used for rental services and for eCommerce business. 

    By doing so, organizations win customers’ hearts by recommending prices based on external factors and their buying trends as well.

  3. Dynamic Product Recommendations:
    We all have experienced product recommendations so far but unknowingly not aware of AI aspects helped in marketing the same. 

    Amazon is widely using AI with its own team and customized algorithm to recommend products for users.
  4. Customer Service
    All we need is easy access to products or services with minimal support and ph calls. Here, AI helped brands to aid diminish the customer service and cost behind it. 

    Businesses these days are using augmented messaging, and chatbots for the fast reply and customer support messages to reduce waiting time.
  5. Email Marketing
    As we talk about personalization, demand for it in Email marketing is a big challenge. Since the day, email marketing is done equally to all, and thus customers don’t’ react to frequent emails that are not specialized for them. 

    And here AI played a significant role by analyzing customers’ behavior and their interests in segmenting the mails. 

    As a solution, increasing the relevancy of any messages is a must. Dynamic email content and tailored receipt are examples of AI-powered customer emails.
  6. Content Marketing with AI
    AI aspects help marketers to enhance content base and information. From crafting the relevant subject to the perfect ad copy, lots of services are focusing on taking the pain out of copywriting.

    You are thinking of how AI can help in content marketing, right? 

    But there are various tools available that help to analyze the audience’s interests. And based on that, content topics are created that help Google to crawl and attract the audience.
  7. Content Analysis and Improvement
    To facilitate information is not enough. A range of AI-powered solutions permits analysis of content that benefits with user-friendly content, enhance the content, and improves to market it. 

    The best example to quote here is small SEO tools and Grammarly that helps to find spelling mistakes, grammar correction, and styling errors. You can even set content goals as per the targeted audience.
  8. Marketing Performance Analysis
    · AI-powered business analytics tools help uncover unprecedented insight from the company’s data.

    · Understanding anomalies in campaign performance to help identify and overcome potential issues.

    · Forecast business performance. And with such insight, help set realistic expectations, KPIs, and more.

Hence, AI helps marketers in various ways through ML algorithms where big data get to visualize and predict future trends and promotional activities. From analytics to forecasting and endless optimization potentials, your marketing ROI will be a lot different since the time of implementation.

Opportunities for Artificial Intelligence in Business

Yes, there are challenges associated with every new technology, and when data comes to picture, the scenario gets waste for the business. But, as we know without challenges and new implementation, there are no opportunities as well. AI has several opportunities and has proved a power booster for businesses. 

Many known enterprises hire dedicated AI developers and dedicated data engineers to get the best out of opportunities associated with AI. Let’s discuss some smart implementation and opportunities:

  1. Track Competitors with AI
    Are you thinking about tracking your competitor’s activities? Yes, it’s a significant aspect to keep track of what your competitors are doing. But most businesses fail to do so. 

    A shut looks into any competitors’ next move and marketing activities such as promotions, pricing, and more is a must in the world of digitalization. 
  2. Marketing with AI
    Marketing campaigns and increasing ROI is the dream of every organization. Strategies are planned well, and research is done on budgets to implement marketing activities. 

    As we know, all these activities are time-consuming and vary channel to channel across media, and it asks for experts, research and result oriented aspects. 

    Here, the job of AI marketing solutions comes in! Let’s see how?

    · This machine learning-enabled layer analyzes live campaign data with the help of response analysis algorithms.

    · AI facilitates platforms such as Acquisio to help in supervision marketing operations, various crosswise channels like Google Adwords, Facebook, and Bing.

    · It computerizes regular bids and monitors overall marketing costs so that business owners can reduce the time spent on tracking marketing campaigns.
  3. Make light work of Big Data
    Each and every business wants to take advantage of online and offline data to make an organized and data-driven decision. 

    As per the research, the most meaningful thing about AI-powered tools is fitting well in the manufacturing process and workflow and provides close insights that are applicable.

    Monkey Learn as a know AI business tool incorporates and analyzes data from corner to corner various channels and achieves time-saving analytics and reporting like sentiment analysis in Google Sheets, CSV, and more.
  4. Customer Support Solutions-AI integrated 
    Automated chat systems as one of the known chat for websites assist small businesses to update their customer service and releases resources.

    · It helps to enhance the responsiveness of your customer service team.

    · A reduction in time is one of the benefits of AI. 

    · AI customer service solutions like DigitalGenius automate answers to incoming customer questions.

    · It classifies help tickets and direct inquiries or messages to the appropriate department.

  5. Artificial Intelligence in CRMs
    CRM as the most needful software to handle numerous tasks is the way to smooth your work. AI helps the software to classify all necessary functions to the next level. 

    Get valuable insights from business through a CRM platform that is AI embedded to show your clients with precise information. 

    For real-time data analysis, AI functionality is used in order to provide future predictions and recommendations based on customer data.

From the above AI implementation to business processes, we initiate that AI’s time may have finally started and here is the time for your business to boost with enhancing strategy and sales. 

Data-driven and AI development companies help to get your requirements to visualize data for smart implementation. Furthermore, we got through more AI opportunities and challenges that businesses face. If you are thinking about predicting future sales by using past data, AI and ML is your next door to walk around for better business decisions. 

Meghavi Vyas

Meghavi is Sr. Technical Writer and exploring the knowledge in Big Data and Analytics. She is passionate about new technology and got her hands on writing technical terms and data aspects. She loves to explore the bleeding edge of tech stuff as an early adopter to Data Science.