Customer Data Analytics

Through customer data analytics, you can collect and analyze your clients’ data to get insights about their needs, wants, interests, and other valuable factors that affect their relationship with your brand. Using that information, you can build an informed marketing and sales strategy to maximize your engagement with your customers while increasing your sales.

Types of Customer Analytics

There are 4 different types of analyses you can use to sift through your customer data. All of them are extremely useful, so the best strategy is to combine them to better understand your clients.

Descriptive Customer Analytics

A process that explores historical and real-time customer data to understand a particular phenomenon that has happened or that’s currently happening. Example: Checking a website traffic and its sales on a particular month.
Diagnostic Customer Analytics

An analysis focused on understanding why a particular customer-related problem happens using a combination of techniques. Example: Delving into the website data while combining with other customer data (e.g., data from sales and marketing teams) to understand the website’s traffic and its sales.
Predictive Customer Analytics

A technique to anticipate potential changes in customer behavior, which often uses data mining and machine learning to make estimations based on historical and real-time information. Example: Analyzing the data from previous months and years, comparing it to current data, and extrapolating averages and medians to offer estimations on possible future scenarios.
Prescriptive Customer Analytics

A method to lay out potential courses of action based on the estimations of possible future scenarios made with a predictive analytics tool. Example: Suggesting adjustments to the website to prepare for a projected increase in traffic due to seasonal spikes. Example: Analyzing the data from previous months and years, comparing it to current data, and extrapolating averages and medians to offer estimations on possible future scenarios.

How To Collect and Store Customer Analytics Data

Thanks to the widespread digitalization of business processes, companies of virtually every industry can quickly gather and store customer data from a wide range of sources. However, having so many ways of collecting data can be daunting, which means you’ll need a proper strategy to make sure you’re gathering relevant information in the most efficient way possible.

How can you build that strategy? By taking into account the following suggestions.

1. Define the type of data you’ll collect and the channels from which you’ll gather it from.

Though it might seem like collecting tons of data is the best course of action, the reality is that doing that can lead you to an overwhelming amount of useless information. That’s why you need to define 3 essential things before you start collecting data:

Customer data origin. Customer data has 3 main origins. First-party data is the information you collect through your own channels and tools. Second-party data is the information that comes from another organization’s first-party data. Third-party data is the information you might buy from a data aggregation service. You need to decide which combination of the 3 is best for you, depending on the data you’re able to collect yourself, the partnerships you have with other companies, and the data availability in your industry.

Customer data type. There are plenty of different types of data you can collect: website traffic, total sales, leads, social media engagement, answers to surveys, clicks on buttons—the list goes on and on. Before collection, you need to define what data type will better inform your business needs.

Customer data sources. If you end up choosing first-party data as your information’s origin, then you need to determine which sources are best to gather your selected data type. Thus, you might need to collect information from your website, POS system, social media, market research, review sites, surveys, in-store interactions, or apps, among many others.

2. Lay out your collection process.

After identifying the data you’ll be collecting, it’s time to choose the tools that will help you gather it. There are plenty of customer data analytics tools available in the market, so which ones you end up using depends on the type of data you’ll be focusing on as well as your existing digital infrastructure.

For instance, you can analyze website traffic through Google Analytics, social media engagement through native analytics tools provided by the social platforms themselves, and marketing efforts through marketing platforms like HubSpot or specialized services like SurveyMonkey.

You should also consider adopting a customer data platform (CDP), a tool that allows you to centralize different types of data coming from different sources and origins. In that way, you’ll have easier access to relevant information and will gain the ability to work with it in a single place.

3. Store the data properly.

Since you’ll be collecting a lot of data, knowing how to store it correctly is a must to avoid bottlenecks, availability issues, and data losses. That’s why you need to understand that data storage involves more than just dumping data into a database. You need to define the storage format, determine if you need to apply some sort of standardization before storing, and build the right infrastructure to gather it all.

You could say that a customer data platform is enough to centralize all data, but things aren’t that simple. While a CDP can certainly help you, picking the right one can be tricky. That’s because you need the best CDP, one that can seamlessly integrate with your data sources and orchestrate them in ways so that you won’t lose data in the migration. Another option is adopting data warehousing services, but that’s a complex solution that’s best suited for big companies.

A word of caution

Customer data collection is a thorny subject. There are plenty of regulations and norms that govern how you can gather information from your customers. Those normatives aim to protect the privacy of client data, which is why it’s very important for you to have a deep understanding of all applicable data regulations to make sure you’re respecting them at all times. Failing to do so can lead to considerable fines and a loss of trust from your customers, which will definitely impact your reputation.

How Does Your Company Analyze Customer Data? Customer Data Analytics Tools

Once you have your data properly stored, it’s time to analyze it. Again, this will depend on the type of data you’re working with and the business insights you’re trying to get from your datasets. Both of those things will determine which kind of customer data analytics tool you’ll need from one of the following:

Customer analytics tools. Takes numerous criteria into account to create groups of customers that are then analyzed for highly targeted marketing campaigns.
Business intelligence solutions. Converts raw data into insights that suggest improvements, pinpoint issues, and help streamline operations.
Digital experience platforms (DXP). Uses data to help manage and deliver optimized digital experiences.
Customer data platforms (CDP). Brings data from multiple sources together into a centralized hub that guarantees accessibility and provides analytical features.
Customer journey mapping solutions. Dives into data related to the customer life cycle with your company to provide a bird’s-eye view of their history with you.
Customer journey analytics platforms. Uses customer maps to analyze different touch points in search of improvement opportunities.

Best Tools in the Market for Customer Data Analytics

We’re living in the golden age of data, where companies can gather customer information from a myriad of sources to gain insights that directly translate into a competitive advantage. Given that context, it’s not surprising to learn that there are countless tools for customer data analysis. How can you pick the right one? It’ll all depend on your business goals. However, there are a handful of essential tools that you should consider adding to your digital infrastructure.

Google Analytics

Free tool that helps you analyze web traffic and user actions on your site. One of the best things about it is that you can customize certain parts of the analyses to better understand different audience segments.
Microsoft Power BI

One of the most popular business intelligence tools in the market, Microsoft Power BI deeply integrates itself with other products of the Microsoft family to offer visual-based data discovery and augmented analytics through powerful dashboards.
Tableau

This tool allows you to connect spreadsheets, databases, and big data tools so you can access comprehensive insights through visual dashboards. It leverages smart algorithms to better organize the data and provide easier access to insights.
AWS Data Analytics

This service from Amazon can help you create a data lake where you can unify data and guarantee its governance. You can expand its basic offering through the integration of other Amazon services, such as Redshift’s cloud data warehousing or EMR’s processing platform at scale.
Adobe Analytics

This encompassing platform can collect data from multiple sources (including websites, mobile apps, and in-store systems) to later provide insights to improve the customer experience. It’s a great tool for hyper-personalized marketing campaigns.

Customer Data Analytics Platform Development

While you can always go for an off-the-shelf customer data analytics platform to manage your client’s data, there’s also the possibility of developing your own. While that might seem like an unnecessary option, the reality is that a custom data analytics platform can provide you with even better insights for your company.

The benefits of developing your own customer data analytics platform include:

Seamless integration with your entire digital infrastructure, especially your data sources.
Highly customizable features to get tailor-made results.
Increased flexibility regarding updates and upgrades.
Complete ownership of the data with reduced privacy concerns.
Most cost-efficient solution in the long run.

It’s true that a custom-built customer data analytics platform isn’t for everyone, as it’s a best fit for companies with complex operations and multiple data sources. Yet, if you’re steadily growing or you are part of an enterprise, then relying on a custom solution can provide you with a competitive advantage that off-the-shelf alternatives won’t.

Ready To Start Your Customer Data Analytics Project With BairesDev?

Whether you want to implement a customer data analytics platform, boost your existing implementation, or build a new one from scratch, BairesDev is your best option. We have decades of combined experience working with data collection software and analytics tools, so we can offer you expert guidance and an in-depth roadmap to lead your project to success.

Our data engineers can examine your needs and help you define the data types you need to understand how to better engage with your customers, create successful marketing campaigns, and increase your clients’ overall satisfaction. Our teams will also aid you in leveraging the customer data technologies available so you can get the best results in the most efficient way.

Have a customer data analytics project in mind?