Artificial intelligence is revolutionizing the way businesses approach digital marketing. We enable businesses to select and implement these technologies in their sales and marketing technology stack to drive results.
AI-Driven Business Intelligence
AI business intelligence uses predictive analytics as a powerful tool that can help digital marketers forecast future trends of user behavior and make data-driven decisions that drive conversions. By leveraging statistical models, AI predictive analytics can identify patterns in user behavior, such as when users are most likely to convert or which channels are driving the most engagement. This information can then be used to develop more effective marketing strategies and campaigns that are tailored to the unique needs and preferences of different user segments.
With AI predictive analytics, digital marketers can stay ahead of the curve, anticipate changes in user behavior, and make data-driven decisions that deliver measurable results.
Conversational AI and Lead Generation
The ubiquitous chatbot has been given new superpowers with the inclusion of Conversational AI. A 24x7x365 expert in your brand that can automatically execute on your business processes is a game-changer in many ways.
With CRM Integrations, Conversational AI can automate lead nurturing and follow-up from multiple sources and add your Marketing Qualified Leads (MQL) to your Sales Pipeline. This ensures that your sales team is always working on the most promising leads, while the AI handles the rest.
Internationalization is another advantage of Conversational AI. With the ability to automatically communicate in multiple languages, you can reach a global audience and provide a personalized experience to customers in different countries.
AI-Driven SEO optimization
Using AI to optimize a website’s SEO can be highly advantageous. With its advanced natural language processing capabilities, AI can conduct initial keyword research and generate a list of relevant keywords to get you started. Once your keywords are identified, AI can use your topics to automatically generate meta tags, featured snippets, and even schema markup code that can help search engines better understand the content and structure of your website. Overall, AI can be a powerful tool for optimizing a website’s SEO and improving its online visibility and reach.
AI-Driven Intelligent Customer Data Platforms
By using AI to empower customer data platforms, businesses can achieve personalized campaign journeys, gain valuable campaign insights, and perform hyper-segmentation of their audience. AI-powered customer data platforms can analyze vast amounts of customer data to provide insights that help businesses understand their customers better, target them more effectively, and create personalized experiences that increase engagement and ultimately drive ROI.
Additionally, integrating AI with marketing automation tools brings several advantages. AI can automate time-consuming tasks such as lead scoring, email personalization, and content creation, freeing up time and resources for other important tasks. AI can also provide valuable insights and recommendations for optimizing marketing campaigns based on real-time data, leading to data-driven decisions that achieve marketing goals more efficiently.
Enterprise AI Sales and Marketing Applications
Enterprise AI application development is an emerging paradigm that involves utilizing various technologies and techniques to build secure and accurate systems that help organizations achieve their business goals.
One essential aspect of these AI applications is their user interface, which can include chat and Q&A interfaces for natural language communication to provide a level of trust so that user agency is never lost. To ensure the trustworthiness of the responses provided by the AI, developers can use citations to back up the information presented.
Unstructured document data embedding of PDFs and PowerPoint files are another crucial component of enterprise AI applications, enabling the system to extract insights from large volumes of existing workplace documents. Data document security and privacy must also be considered throughout the development process to create a “walled garden” between you and publicly trained Large Language Models to ensure that sensitive information remains protected.
Additionally, orchestration of AI responses can be managed using frameworks like LangChain, a tool that helps automate the process of adding proprietary “plugin” functionality to your application independent of a Large Language Model (LLM).