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How to Develop a Customer Analytics Strategy: Five Trends to Watch

A customer analytics process is a process that helps businesses analyze and improve the customer experience. It allows them to identify areas of their customer base where they can improve. It also helps them understand their customers’ needs and provide them with the necessary information to make informed decisions.

According to Forbes, 58% of enterprises are seeing a significant increase in customer retention and loyalty as a result of using customer analytics.

A good customer analytics process combines quantitative and qualitative data. You can get a deeper understanding of how your customers behave through quantitative data, which are usually collected from various sources, such as web traffic statistics. On the other hand, qualitative data, usually collected from sources such as interviews and surveys, are more detailed and can provide insight into how your customers feel.

Example: Hotjar Surveys embedded for gathering qualitative data

Example: Finteza web analytics report on website visitor activity as a part of quantitative data

The data and analytics industry is rapidly expanding, with new trends emerging at breakneck speed. This implies that you and your company must stay current to optimize it fully. It is not enough to configure data analytics once and then forget about it; rather, it is necessary to adapt to current trends.

The following 5 current data analytic trends will help you develop a strategy and maximize the benefits of data analytics in your business.

1. Creating Actionable Insights

It isn’t enough to simply have insights from data; businesses must also act on them because insights are meaningless without actions. This is one of the major analytics trends of 2022, with its emphasis on acting on actionable insights garnered from data.

Data analytics has traditionally been read-only. Insights are created, but their application is left to the organizations or businesses. However, this is changing, with technological innovations like artificial intelligence and machine learning allowing businesses to take action with business intelligence tools.

Businesses will benefit from artificial intelligence and machine learning in data preparation, processing, and gaining insights from data sets. This can be accomplished by identifying trends and patterns in large data sets. This will boost business sales and operational efficiency while keeping the company competitive in the market. Discovering actionable insights and acting on them is crucial for the growth of businesses and their ability to create a good experience for their customers.

2. Consumer-personalized Data

80% of consumers are more likely to buy from a company that provides a tailored experience. 

It is important to have actionable insights that reflect customer behavior and can adapt to customers and market dynamics. Understanding customers’ behaviors, needs, and preferences through data analytics enable businesses to create approaches that will effectively meet their target market. 

Adding customer names into an email subject line is a simple example of a personalized customer experience. Spotify Wrapped—an annual campaign where Spotify shares a compilation of each listener’s top artists, songs, genres, and more in a shareable graphic—is a great example of mid-tier personalization harnessed for marketing. Strava’s recommendations—which offer suggested activities and challenges based on past activities—exemplify using personalization to drive usage and retention.” — Kiera Abbamonte, Content Writer @

Spotify Wrapped — credit: The Verge

Personalization allows businesses to build a trusted relationship that is always ready to understand and respond to changing customer needs. With it, businesses can improve their customers’ experiences and increase sales.

3. Using Gathered Data Responsibly

Before personal data can be collected, customers’ trust must be gained. And once trust is established, it should not be abused. This brings us to an important rule: data privacy. 

The increasing abuse of data and scandals have made the public wary about sharing personal data with the public. The implication of this is that the unwillingness to share personal data means there will be little data analytics conducted and, consequently no strong, actionable insights.

Businesses must understand the public’s fear and find a way to alleviate it. Their confidence in data privacy will make them share personal data without fear. It is now up to businesses to use the data responsibly while improving customers’ experience.

Some tools or technology are required to guarantee customers’ data privacy. This technology must be able to meet regulatory requirements and provide privacy and policy controls.

4. Data Cloud Migration

One of the prevalent data analytics trends today is the migration of data from on-site to the cloud. The benefits attached to data cloud migration are significant. As a result, businesses are moving their data and analytics from in-house to the cloud.

The chief significance of cloud migration is the speed and ease of data analytics. The cloud enables real-time data ingestion and processing, allowing for faster and more informed decisions when they are required. With the need to quickly execute actionable insights and make data-driven decisions, businesses must understand data on time.

Cloud analytics offers businesses scalable and cost-effective access to high-performance computing or analytics. Businesses can use Google Cloud Analytics, Amazon Web Services, or Microsoft Azure to meet their data analytics needs.

5. Context-enriched Analytics

It is estimated that by 2025, context-driven data analytics, alongside artificial intelligence, will replace more than half of traditional data models. Businesses don’t have to wait till 2025 before they start implementing context-enriched analytics, as it creates in-depth data analysis.

Context-enriched analytics is built on graph technology. With it, companies can have deep data analytics while having an in-depth understanding of data points. It helps businesses to identify or create additional context-enriched analytics based on similarities or dissimilarities.

To implement context-enriched analytics by capturing and storing contextual data, some tools capable of processing varying data types are required.

Data analytics is no longer an afterthought in today’s highly competitive market, but an intentional and necessary activity needed to make actionable insights. Businesses have seen how crucial it is to use business analytics in making actionable insights, fact-based decisions, and data-driven products and services. As a result, the highlighted trends in customer web analytics today are essential for your business if you want to run a successful business and improve your customers’ experience.

Web analytics gives insights into the market by identifying trends and patterns, and also into the behaviors and motivations of customers. The insights garnered from this can give a competitive edge to businesses. This makes it important for companies to be data-driven.

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