Deciphering Marketing Potential using New-Age Marketing Technologies 

The growth of data analytics, business intelligence, and artificial intelligence has made it simpler for marketing professionals to approach every circumstance with a dash of technology. These solutions use inputs, the data generated in an organization, and experiences to produce “new insights”. Some can even help determine right and wrong to create new content.

Advancements in Marketing Technology

The days of managing marketing initiatives manually are long gone. Marketing technologies now make it simpler than ever to improve a company’s marketing efforts. Using data-driven and AI-powered solutions helps marketing executives in a great way to transform their industry. According to McKinsey & Co., companies that use data-centred marketing strategies see a 15-20% increase in return on investment. And using technology is the only method to optimize effective data management.

Another study reveals AI as another marketing technology that is advancing the fastest. The report conveys about experts in the field predicted that it will advance by 55% in the next years. The study also confirmed one of the main advantages of AI: “it may transform marketers from “reactive to proactive planners,” helping them to plan operations more effectively, particularly when doing customer segmentation, behaviour monitoring, and keyword tagging into account. Generative AI and reinforcement learning are two examples of such advanced versions.

How to reap success using these ‘New-Age’ Marketing Technologies

Here are some benefits marketing professionals can make by using advanced and trending technology for the marketing industry. 

1. Knowing your customers

   The more customer data gathered, the deeper a marketing professional can understand their customer. This makes them discover more about what their leads are looking for when they approach. This, in turn, helps marketers be prepared and provide for their needs anytime. Solutions like predictive intelligence help in foreseeing their future behavior pattern and purchasing trends.

   Predictive intelligence establishes a casual relationship by analyzing historical data and current patterns. According to a report by Mckinsey, harnessing predictive insights helps connect closely with their customers, predict their behaviour, and identify issues in real-time.

2. Building personalized messaging

   Generative AI is in fashion now. Gartner has declared generative AI as one of the most disruptive and rapidly evolving technologies in their 2022 Emerging Technologies and Trends Impact Radar report. Generative AI is a machine learning that uses algorithms to create new data, such as images, texts, or sounds. It may resemble an online anonymous creative head producing creative work. But, in reality, it’s simply a group of brilliant algorithms behind the scenes. 

   Chat G P T, a sizable language model, is one of the most discussed generative AI models. Although GPT had been included in several SaaS solutions for more than a year, adding a user-friendly interface and a potent language model that builds on requests in a conversational way made this an instant hit. 

   Generative AI can aid in customer segmentation by forecasting how a target audience will react to commercials and marketing initiatives. This might be a useful tool for businesses looking to increase sales and particular target groups. Also, you may artificially create outbound marketing communications to improve upselling and cross-selling tactics. A marketing professional may use it to receive customized messages based on the brand’s position in sales, marketing, customer service, or any other field.

3. Product pricing

   For most marketers, figuring out how to deal with pricing changes, especially price increases, can be quite difficult. Most marketers frequently make mistakes when implementing the changes, even after anticipating customer reactions, which leads to expensive regrets. Reinforcement learning, on the other hand, enables professionals to model consumers’ actions in the future and accurately forecast their responses to changes in the pricing structure.

   But what is Reinforcement Learning (RL)? Machines are taught to interact with their surroundings and gain rewards for doing the proper actions until they complete their task through reinforcement learning. Like how the human brain makes decisions depending on the positive or negative outcomes of prior choices, RL accomplishes the same thing more quickly, precisely, and broadly.

4. Fill Gaps in the Buyer Journey and Lifecycle

   The buyer journey might seem like a blind alley for marketing and sales professionals. However, understanding how and when customers react to their campaigns is crucial for marketing professionals. 

   Analyzing customers’ reactions, queries and needs is crucial while curating new strategies. Key components of customers’ conversations can be easily used with the help of conversational analytics. This can be used to understand client intents, measure customer service performance in novel and useful ways, and evaluate the overall quality of services and goods.

5. Addressing your customer needs 

   Although businesses can develop real-time ideas, they might not have the necessary technology to implement them. In addition, companies might not be able to use their consumer data if the right procedures and measurements are not in place. Therefore, a clearly defined analytics solution for recording and distributing real-time consumer feedback is essential for marketing success.