How machine learning delivers new dimensions to marketing and customer experience

Atman Rathod -

While advanced technologies helped mitigating the differences between online and physical stores, the biggest value addition has been the data-centric approach of knowing customers and getting access to valuable insights that can be utilized to target them for promotion and marketing. This is why both artificial intelligence (AI) and machine learning (ML) seems to be the era-defining technologies to improve customer experience (CX) and help online as well as mobile marketing.

The question is, are businesses really ready to utilize the potential of AI and Machine Learning for improving their customer experience and marketing. We will try to answer this in this article.

How machine learning will help marketers meet customer expectations

According to the latest report from a Gartner research, by 2020 nearly 85% of the customer relationship across businesses will be handled without the intervention of human beings. From this it is quite evident that AI and ML will play a big role in shaping the customer service and relationship management by using intelligent automation. Let us now explain some of the ways Machine Learning will help knowing customers better to help marketers with lot of useful and actionable insights.

  • Helping Customers to Find What They Need

AI and Machine Learning are two technologies that based on previous user data and user behavior can detect what the customers really want and can serve them accordingly. Even when the customers really do not have any idea of what they want or just know it vaguely in the form of an image, the latest image recognition capability of AI can help them search with the image and get in touch with what they want.

  • Delivering You Meaningful Insights Through the Gathered Data

We already know that customer data is the gold mine for the marketers as the data-driven insights produced by analytics tools help them taking faster, precise and more customer-centric decisions. Naturally, too much data is no longer a challenge but a raw material for decision making processes.

AI and Machine Learning can take such data-driven insights to the next level simply through robust capability of handling multifaceted data to produce most useful and contextual insights. AI and machine learning is not only able to handle a vast amounts of data but they can quickly decipher patterns and analyze for producing most useful insights for the respective context. 

  • An Always Active, Round the Clock Customer Service

Most small businesses suffer from lack of resources and money power to offer a fully operative customer care center with manpower and tools. An intelligent AI powered chatbot can do the work for them with much precision. The intelligent chatbots can now handle most queries that come from the customers on a day to day basis and they always get better over time as they learn from customer inputs and behavior.

  • It Shows Marketers What Works for Them and What Doesn’t

AI and Machine Learning based upon the data-driven insights and learnings about the customer behavior over time can provide lot of useful insights to the marketers about how their campaigns work and where they really not generate traction.

  • Helping Marketers to Personalize Their Campaigns

AI is also a great technology to help marketers with data-driven insights about the buying behavior and past decisions of the customers. Based on such insights, consumers can be offered product recommendations that suit them. Personalized product recommendations are already proved to be useful to drive sales and business conversion and AI and Machine Learning technology can play a great role in it.

How and why customers prefer automation more in marketing endeavors

It is also important to understand the customers point of view regarding these two technologies. Do they make their shopping experience better? Why customers should prefer automation instead of human inputs to their queries? Well, let’s try to find out some credible reasons.

  • AI based automation tools like chatbots help solving customer queries faster.
  • AI and Machine Learning together help product search easier than ever before.
  • AI based automation tools for security and authentication helps processing requests and payments faster without compromising on security.
  • The automation simplifies the entire customer journey while using a mobile app or a website.

5 automation marketing rules from Google that will transform customer experience

Google recently came up with 5 specific rules that every marketer should follow while using automation for their campaigns. Let us have a look at the best practices prescribed by Google to utilize automation for online or mobile marketing.

1. Focusing on Customer Experience and Growth-hacking

While efficiency has long been the focus area of marketers to drive results, modern-day marketers focus more on the growth-hacking to secure revenue gain at faster pace. AI and Machine Learning together take a holistic approach to customer service and overall customer experience to boost business conversion.

2. Right User Acquisition

The biggest concern for most marketers is to ensure right acquisition of customers who are more likely to respond to their marketing tactics and approaches. This can actually minimize the drainage of resources while ensuring optimum outcome. To reach more valuable customer with ease you can use Machine Learning insights. 

3. Build Meaningful Customer Relationship

Machine Learning technology can easily show you what your existing customers are most likely to respond to. AI and ML will also provide you lot of insights about the particular triggers for making investments and choices. When you address your customers on the basis of inputs from AI and ML, you are more likely to build a meaningful relationship.

4. Connecting Customers Creatively

In marketing automation, there is no dearth of generic tools and approaches that apart from doing the job faster completely miss out on personalization and customer-centric approaches. With AI and Machine Learning the automation tools on the other hand can be more well-informed about the customers. Based on relevant insights such tools can actually serve each customer in a way that suits them.

5. Native Mobile Apps are Must

Lastly, prioritizing mobile experience is a must. There cannot be a better way give priority to mobile users than rolling out native mobile apps. A native mobile app will help a business delivering a fast-paced, visually engaging and customer-centric experience. Even when you are utilizing automation tools like chatbots, think of developing the same for the context of native mobile app.