How to Design the Framework for Your AI Marketing Strategy

Before you can build artificial intelligence into your marketing strategy, it must first be part of your marketing framework. Your marketing framework details how you will execute your marketing plan and deliver your content to your audience.?You will want to think about how AI can be used to enhance your existing products and services, create new products and services, and build relationships with your customers.

?Marketers can integrate AI into existing systems or design an independent program. Either way, AI can ease the burden of repetitive tasks while also performing critical machine learning.

Save Time and Money With AI Automation

AI can be used to perform repetitive, structured tasks that require relatively low levels of intelligence. For example, chatbots, auto-generated e-mails and buying decision trees. However, AI can’t discern a customer’s intent or provide a customized response, and it doesn’t learn from these interactions over time. We still need humans for these tasks.

?Increase Intel and Sales With AI Machine Learning

?Machine learning is already widely used in online advertising and search engines and customer relationship management (CRM) systems because it is a powerful marketing tool – delivering convenience for customers and intel for marketers. AI algorithms use large quantities of data to make relatively complex predictions and decisions, learning over time.

The Difference Between the 4 Types of Marketing AI

Standalone ?and Integrated Task Automation Apps

Standalone task automation software refers to a system or device that can operate independently, without relying on external connections or other devices or networks. Standalone software often gives you in-depth reporting capabilities and advanced functionality as required per your business needs. This app is typically designed to perform a specific task within a system like inventory management by tracking sales and stock levels. The beauty of standalone task automation software is in its ability to specialize.

An integrated task automation system, however, integrates a suite of software applications bundled together to operate as one cohesive system. Multiple software solutions like customer support, inventory management, and invoicing would all fall under a single banner. The advantage of this is that you are able to streamline real-time data sharing and business process integration. There is no need to juggle work on multiple standalone applications. Also, manual data entry is eliminated. With integrated software, data entered in one module is immediately updated across all other modules in real time, fostering an environment of consistent, accurate, and up-to-date information. This is particularly helpful when analyzing business trends and making data-driven decisions.

While standalone task automation software may excel in its ability to focus on one area, integrated task automation software shines in its ability to offer a big-picture view of the entire business operation that is holistic, providing an interconnected understanding and management of your business.

Standalone? and Integrated Machine Learning Apps

Standalone Machine Learning Apps (also known as a desktop application) refer to a system or device that can operate independently, without relying on external connections or other devices or networks. Standalone software often gives you in-depth reporting capabilities and advanced functionality as required per your business needs. Some examples are Notepad, Calculator, Microsoft Word, Adobe Photoshop, and Google Chrome.?

Integrated Machine Learning Apps on the other hand incorporate computer systems that are able to learn and adapt using algorithms and statistical models to analyze and draw inferences from patterns in data. Some examples are facial recognition, product recommendations, e-mail automation, SPAM filtering, voice to text, and social media optimization.

While AI has made significant inroads in marketing already, its practical use is really just beginning. Given AI’s enormous potential, it is crucial marketers have a strong understanding of the four types of marketing AI applications currently available. By understanding these four AI marketing systems, marketers are in a better position to plan and sequence the introduction of new uses to improve marketing strategy.