11 Trends in AI and Data Analytics for 2022

AI will help marketers delve deep into emotions and needs to enhance the customer journey throughout 2022 and beyond 

Key takeaways:

AI can help companies plan and predict developments in customer behavior

AI can improve the customer experience

AI combined with data opens a world of marketing possibilities

AI can contribute to actionable data, more convenient data, database as a service, continuous intelligence, cleaner data, NPL, hyper-automation, AI and IoT combined, stories instead of dashboards, new data leverage ops, and predictive analytics

Artificial intelligence (AI) allows machines to learn from experience, adapt to new input, and perform tasks that are usually done by humans. Essentially, computers can learn to accomplish specific goals through AI by processing large amounts of data and recognizing patterns in that data.

Data is the lifeblood of AI. Through AI data mining and modeling, businesses have been able to predict and plan for developments in customer behavior as well as market conditions. These methods are also essential for leveraging AI to solve day-to-day business problems and strategize for long-term growth.

Organizations are bringing together AI and big data in a variety of ways for faster learning, challenge management, and more efficient task completion. This will result in dramatic changes in the way many companies function and market themselves, as well as provide endless opportunities for innovation.

Both AI and marketing need data, and putting those together opens a world of possibilities for better targeting and a better customer experience. In 2022, brands will use AI to better anticipate customer needs with actionable data, more accessible data, and more automation. Also expect to see a greater convergence of AI and the Internet of Things (IoT) to provide deeper insights into customer behavior.

Let’s look at 11 trends to watch in 2022.

1. Actionable Data

For 2022, businesses will focus on AI-powered analytics to extract actionable data insights that will help them make a myriad of business decisions. 

With AI coupled with Machine Learning (ML), marketers can narrow the scope of their data to focus on things consumers are actually engaging with and probably will engage with in the future.

2. Data at your fingertips

Unifying the sources of data has always been a problem, but AI will make big data much more useful and accessible to the different ways you must use it, such as visualization and analysis. Only AI can process the massive data lakes companies have collected and find actionable insights swimming in them.

3. Database as a Service

Database as a service merges big data analytics solutions to meet the fast-growing needs of customers. This goes beyond simply using cloud technology to give users and applications on-demand and remote access to information.

4. Continuous intelligence

By integrating real-time analytics with operations, continuous intelligence makes recommendations for actions based on historical and real-time data to provide decision-making automation or support.

By 2022, Gartner predicts more than 50% of new business systems will utilize real-time context data to optimize decision-making and improve customer support.

5. Cleaner Data

Poor quality data presents a number of problems, including clutter, incorrect data, and slower data retrieval, as well as high costs in terms of both money and time. In 2022 expect AI and ML to automate more effective and efficient data cleansing processes.

6. Natural Language Processing

Natural Language Processing (NLP) is a branch of AI dedicated to helping humans talk to machines. NLP means computers can understand, interpret, and manipulate human language, as well as extract keywords and phrases, understand their intent, translate that to another language, or generate a response.

In 2022, NLP will provide instant information retrieval from big data repositories. It will help increase access to quality information and can even prompt the system to provide the business-related insights needed to move forward. NLP also gives organizations access to sentiment analysis, so they know, at a much deeper level, how their customers feel about their brand.

7. Hyperautomation

Hyperautomation combines robotic process automation with AI to automate processes in ways that are more impactful than traditional automation.

By uncovering and automating formerly inaccessible data and processes, hyperautomation brings enhanced visibility to the interactions between processes, functions, and key performance indicators to automate the complete customer journey.

8. AI and Io

2022 will see the combination of AI and IoT offer even better access to consumer data, including buying habits, how consumers interact with devices, better insights into the buying journey, real-time interactions, POS notifications, and targeted and fully contextual ads. These insights will also lead to faster resolution of customer service issues. 

9. Stories instead of dashboards

Wave goodbye to data dashboards, which force users to do manual work to gain deep insight and understand the story behind the data. AI and ML will produce data stories that provide the required intelligence without the work. By 2025, it’s predicted that 75% of data stories will be generated by this analytics method.

10. New data leverage opportunities

Applying AI to data in video, audio, vibration, text, emotion, and other content analytics will open new opportunities most companies haven’t fully leveraged this type of data. 

11. Predictive Analytics

Predictive analytics allow businesses to detect potential customers and expected responses by using personalized data they’ve built over time. AI algorithms integrate the ability to detect these key emotions to provide insights that make seeking potential buyers more effective by giving access to sales data on thousands of customers and the items they’ve bought.

BDEX quality data from the start

The tools at BDEX help you get the quality data you need, right when you need it. Reach who you want to reach when, where, and how they want to hear from you.

We have over 6 billion unique IDs, over 5,500 data categories, more than 800 million mobile ID-to-email matches, and over 1 trillion data signals. With BDEX, you’re empowered to create your own custom audience. So, all you have to do to get your messages in front of the right people at the right time is to build your ideal customer to target and activate the data.

BDEX data is always clear, high-quality, and current, which isn’t easy to find in the ever-expanding world of big data.

To improve your ROI, you have to get the most out of your data. Otherwise, you’re wasting time, money, and resources by marketing to the wrong audiences at the wrong time with the wrong messages. BDEX can give you the right data you need to better connect with the person behind the data signal.

Make real human connections with BDEX. Contact the team today to get started transforming the quality and accuracy of your data.