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Precision Sales and Marketing Strategies Driven by Data and AI
With just a snippet of text, AI can automatically generate images, copy, campaign plans, and even video materials. Just like that, the advent of Generative AI (GenAI) has had a tremendous impact on how enterprises approach the market—transforming methods, strategies, and efficiency.
Over the past decade, vast amounts of data have been accumulated amidst the wave of digital marketing, and today, data acts as the fuel that activates the magic of AI. AI can now swiftly process massive data sets, achieving customer segmentation, personalized recommendations, and even market predictions with efficiency, profoundly influencing front office operations.
So, how exactly is AI changing sales and marketing strategies? What are the important trends and business opportunities behind them? Let’s dig into the details in the following sections.
As of 2024, AI marketing (Artificial Intelligence Marketing) has become integral to enterprise sales operations. AI not only enhances the ability to identify potential users and increase sales, but also addresses customer challenges through natural language processing and sentiment analysis, further strengthening customer loyalty. There are three major trends in enterprises using AI marketing today:
Many companies have already achieved tangible results in marketing using AI.
For example, Coca-Cola's global music platform, Coke Studio, uses a combination of AI image generation and ChatGPT technology as part of its growth strategy. Last year, during an offline music festival, they introduced the AI Studio, where participants could create personalized music, album covers, and music videos after answering a few questions. They were able to download the files instantly online from a dedicated webpage and share them on social media. This hybrid campaign of offline and online interactions increased engagement, helping convey the brand's value to a broader audience.
Leading e-commerce brand Amazon has leveraged AI to build a powerful recommendation system that accurately suggests products based on users' browsing and purchase history, significantly boosting sales. Additionally, Amazon uses AI to optimize logistics and delivery routes, reducing costs.
In Taiwan, several financial institutions, such as Cathay Financial Holdings' "Afa" and CTBC Bank's "Xiao C," are using AI technology to quickly analyze customer inquiries and provide immediate responses. Customers can enjoy 24/7 online consultation services through both computers and mobile devices. Surveys show that in 70% to 90% of cases, AI-powered customer service in the financial industry effectively resolves customer issues without the need for human intervention.
Digital marketing has evolved over the past 20 years, leading us to an era where audience segmentation is crucial as brands fiercely compete for customer attention. To balance cost and efficiency, personalized recommendations have become essential.
On the other hand however, marketers face challenges due to stringent privacy restrictions, which have led to major browsers to limit the use of third party cookies for tracking user behavior. In addition, major players controlling advertising traffic like Facebook and Google frequently update algorithms, forcing companies to continually adjust marketing strategies to comply with new rules. Data silos are also a common problem for companies, where constantly added new marketing systems lead to data gaps between different internal systems.
The implementation of AI can not only solve the pain points addressed above, but also usher in four major changes in sales and marketing strategies.
Change 1: Precise customer segmentation
Unlike the tracking model using cookies in the past, AI can categorize consumers based on behaviors such as website click-through rates, social interactions, customer service queries, and purchase records. It can further predict market trends and consumer demands, painting a picture of customer profiles through digital footprints.
Change 2: Hyper-personalized marketing experiences
After segmenting customers, AI can develop tailored marketing strategies based on individual consumption trajectories, providing the most suitable sales solutions based on the situation of each user. By accurately predicting customer preferences, brands can reach both potential and existing customers more effectively, boosting engagement and conversion rates.
Change 3: Smart sales forecasting and opportunity management
AI can progressively learn and improve its analysis and prediction capabilities using past sales data (sales cycles, amounts, customer sources, etc.). Besides modeling future sales curves, it can proactively identify potential opportunities, saving sales teams significant research time.
It can even dynamically adjust product prices based on market demand and inventory or customize the content and timing of marketing emails based on user behavior, thereby increasing open rates.
Change 4: Sales automation
In the age of AI, sales processes can be increasingly automated. AI chatbots can simultaneously handle large volumes of customer service requests, analyze past market trends, and offer tailored insights and recommendations for each season or specific product. This can enhance the sales personnel's decision-making ability and simplify sales processes. For instance, automated triggers can be set up at each stage, automatically sending product information emails after a cold call, or reminding salespeople to follow up on customer progress a few days after initial contact.
GenAI is known to enhance customer experience, optimize operational processes, and boost employee productivity and creativity. According to a McKinsey report, GenAI has the potential to contribute $4.4 trillion annually to the global economy.
The next step in transforming sales and marketing operations will be closely tied to this potential growth. This shift will not only help businesses address current digital marketing challenges but also bring better results, significantly enhancing efficiency and work quality.
However, a transformation of this kind—encompassing business operations, owned data, and AI integration—requires experience and specific skill sets that cannot be acquired overnight. Selecting the right technical partner is key to success.
This year, Going Cloud has been awarded the AWS Rising Partner of the Year - Technology Partner, for its comprehensive solution framework and advancements in cloud AI projects in the Asia-Pacific region.
Going Cloud offers a suite of solutions that support a wide range of application scenarios. Whether optimizing internal processes, streamlining daily sales and marketing tasks, or analyzing and predicting user behavior, we are dedicated to delivering practical, tailored, and intuitive solutions that meet specific client needs.
Following are examples of the solutions we offer to help empower sales and marketing operations:
The precision of personalized recommendations is key to continually attracting users to place orders.
Going Cloud's recommendation engine first analyzes user behavior over a period of time. Once user preferences are identified, it recommends products the user might like in specific scenarios, thereby enhancing the personalized experience. Furthermore, business logic can be incorporated flexibly to promote specific products/brands to meet seasonal or strategic business quotas.
For example, suppose AI analysis reveals that over the past week, a customer has frequently browsed products related to "beach and swimming." When the customer is browsing a travel blog for itineraries, an e-commerce link to purchase sunglasses can be recommended below.
When the customer begins browsing sunglasses, different styles and designs can be recommended, capturing every upsell and cross-sell opportunity. Through accurate product recommendations and exposure, conversion rates can be increased significantly. Additionally, a personalized product recommendation mechanism can further cultivate customer loyalty to the brand and potentially develop new customer segments.
Technological advancements in AI now enable practical, high-level "human-machine collaboration". This, not only frees up human productivity but also provides better service quality and accelerates the sales process for enterprises.
Going Cloud's AI Chatbot Sales Solution can integrate various data sources, such as Google Drive, Office documents, Salesforce, and ERP, to create a dedicated enterprise product service brain accessible through your preferred user interface or communication platform. Through the integration of large language models (LLM), it quickly identifies customer needs and provides tailored suggestions, speeding up the sales process and initial opportunity assessment by the sales team.
Consider an online travel agency: when a customer inquires about shuttle services from Narita Airport in Tokyo for specific dates, their reservation request is promptly addressed. Simultaneously, their information about the Japan trip is added to the sales database. Later, recommendations for Tokyo accommodation or other travel itineraries can be made, accelerating the product sales process.
Data is the key fuel driving AI, and Going Cloud is committed to empowering enterprises to drive business growth with advanced IT architecture and data-driven strategies.