Tag: Customer analytics

Customer Analytics

A Comprehensive Guide to Customer Analytics and How it can Benefit B2B Companies

Advantages of Big Data in The Finance Sector (2)

What is Customer Analytics?

Customer analytics is the process that companies use to gather and analyze the data of their customers to make better and wise decisions. Customer analytics help companies with actionable insights into the behaviors of their end-users. These insights empower businesses to improve their marketing, sales, and product development efforts. Additionally, such data can be used to build solid predictive models to determine potential customers. Research shows that companies that focus on customer data analysis are more profitable than ones that do not utilize such services. Therefore, it can be safely assumed that the lack of accurate customer data skews customer profile. It, consequently, leads to lost opportunities, lost customers, poor use of analytic solutions, and unnecessary costs for business, affecting the outcome.

Precisely predicting future buying behavior of customers is not an easy task for businesses. Channel optimization and targeted marketing may hold the key to success. Get in touch to know more about the benefits of our customer analytics solutions.

Why do Companies Use Customer Analytics?

Companies can break big problems into manageable answers by leveraging customer experience analytics solutions. Furthermore, customer analytics has the potential to help businesses gain insights into customer behavior. Customer analytics also unveils their actions and make them easier to understand for business leaders. This helps companies to make wiser and better decisions on pricing, promotion, and management.

Companies that use customer analytics systematically outpace their rivals in terms of profits almost twice as often as companies that do not.

A good consumer analytics platform can help companies improve:

  • Customer retention
  • User engagement
  • In-app purchases

Today, companies have realized the potential of analytics and have started relying on it more than ever before. It helps them keep pace with customers who are increasingly sophisticated. 85% of the customers today expect a seamless experience and faster responses. Analytics is the key for the companies to provide desired customer satisfaction and enhance customer experience.

With customer analytics, companies can:

  • Improve customer loyalty, response rates, and, ultimately, ROI by targeting the right customers with highly relevant messages and offers at the right time.
  • Minimize the costs of campaigns by targeting those customers most likely to respond.
  • Reduce attrition by accurately predicting customers most likely to leave
  • Deliver the right message by segmenting customers more effectively and the better understanding of target populations.

How to Implement Customer Analytics?

In the competitive landscape, companies are benefiting from customer journey analytics significantly across all channels. This is because results are immediate, real, and have a lasting effect. Customer analytics encompasses a completely new approach to analytics, which requires business leaders to become more customer-obsessed. Following are a few steps to implement customer analytics that you must follow in order to obtain the maximum result:

Steps to Implement Customer Analytics

Step #1: Define the scope of the project

Start a customer analytics project by specifying its scale and scope. While defining the scope of the project to implement customer analytics, you need to consider basic parameters like size, complexity, function, and goals. Additionally, it is important to note the quantitative goals like customer retention, churn, acquisition, upsell, cross-sell, the rate of renewable and purchase.

Step #2: Determine Goals

Since customer analytics involves multiple stakeholders, it is crucial to set goals and define what success will look like. One of the most important benefits of using customer analytics is that it connects individual customer behavior to important KPIs and quantitative metrics that you and your business are measured by. Therefore, the key lies in selecting the appropriate KPIs and metrics to monitor and improve, based on the insights generated by your customer analytics platform. You need to choose a mix of customer, financial, and operational metrics.

Customer Metrics:

  • Net Promoter Score (NPS)
  • Customer Satisfaction Score (CSAT)
  • Customer Effort Score (CES)

Financial Metrics:

  • Growth of revenue
  • Upsell and Cross-sell Revenue Growth
  • Churn Rate

Operational Metrics:

  • First Call Resolution (FCR)

Step #3: Create a plan for data integration

Data integration is the spine on which a successful customer analytics initiative rests. Before preparing the plan for a successful data integration, it is important to understand the basics behind it. Whether you are working with a consulting agency, firm, agency or the customer success team of the vendor for implementation, it is important to understand and identify the customer data sources that you want to integrate into the customer analytics platform in order to obtain the required insights.

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Step #4: Identify key use cases

It is important to identify a use case that addresses the most important pain points being faced by your business. At the same time, you should also be careful that you are addressing the issues being faced by all the stakeholders involved in the customer analytics project.

How to pick your use cases?

Here is a framework that can help you pick the best use cases for your initial implementation of customer analytics. This framework describes six types of customer analytics use cases in the order of growing complexity. Most business problems would fit in one of these six types.

  • A-B Testing
  • Optimization of conversion rate
  • Impact analysis
  • Behavioral segmentation
  • Goal optimization
  • Journey discovery

Step #5: Make your organization ready for customer analytics

Customer analytics deserves the time, effort and resources you invest in it. But to derive the best outcome and truly reap its benefits, you need to integrate it seamlessly in your organization. This integration goes far beyond technology and data. You can do this by:

Change Management

Multiple teams and departments might get affected by the results of customer analytics, so it is important that they understand the whole initiative. This is where the support and influence of the stakeholders prove beneficial.

Employee training

Training of employees is an important part to ensure that your organization is ready to successfully implement customer analytics. To ensure usage and adoption of your new customer analytics platform, you need to make sure that the users are properly trained.

Governance

Large organizations have a central governance team in place. This team is responsible for fostering communications, setting project quality standards, and sharing best practices. The governance board is responsible for improving the success rate of customer analytics projects undertaken by the company, while at the same time takes into account the risks involved.

We understand the challenges companies face in identifying and curating high-value customers to develop marketing strategies and initiatives to maximize profitability. Our analytics solutions provide best-in-class frameworks to identify factors for customer churn and develop effective strategies that will increase customer retention. Request a free demo below for more insights.

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Customer Analytics

Customer Analytics: A Step-by-Step Guide to Drive Customer Satisfaction and Revenue

With the rapid growth of companies in today’s technologically inclined world, it becomes very difficult and tricky to understand customer needs. Companies struggle to engage effectively with their customers due to the dramatic change in customer behaviors. As much as they would like to reach out to their customers, there’s no pragmatic way to it, as that is how the cookie crumbles. In fact, this is the biggest challenge that companies face today due to which delivering the best quality products and services along with the best customer experience have become a tedious task.

Failing to provide the best customer experience and analyzing customer data are prime factors behind the unsuccessful stories of businesses in this customer-centric era. So, companies need to recognize the patterns and trends of their customers’ behaviors while utilizing the massive amount of data they have. This is where customer analytics solutions help. Customer analytics results in better all-around decision making and paints a more precise picture of the different touch points in the customer journey. Companies need to unearth both opportunities and shortcomings to leverage into better strategies. Customer analytics solutions can dive into complex use cases with the use of machine learning and big data. Consequently, actionable roadmap to achieve desired outcomes and sharper predictions about the future falls into place.

At Quantzig, we understand the impact that customer analytics solutions can have on your business. And to help companies stay ahead of the curve, our team of experts has provided a detailed guide and useful tips on customer analytics that can assist businesses at any age.

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banking services

Is Customer Analytics the New Kingpin for Banking Services Companies?

For modern banking services providers, understanding the customers is the foundation for a sustainable competitive advantage. The internal and external data sources available to banking services companies can be great sources for guiding product development, customer communication, innovation, and growth. This data can be further meticulously analyzed using advanced capabilities such as customer analytics through which banking services companies can get to know their customer at a more granular level. Furthermore, it can help in effective customer segmentation that reveals specific intelligence that could otherwise be obscured by the sheer volume of data. These insights aid banking services companies identify messaging strategies for marketing and customer service strategies and also gain a better understanding of the customer lifecycle and predict customer behavior.

Why is customer analytics important in banking services?

It is high time for banking services companies to up their game in customer analytics. Here’s why:

Analytics is the new normal

 As a result of low-interest rates, moderate fee revenue, onerous regulation, and a less than robust economy, the banking services providers are expected to remain revenue challenged for the foreseeable future. So, it will be more important than ever for banking services providers and credit unions to focus on all possible strategies that would help them reduce costs and increase revenues. Some of these strategies that can be achieved by customer analytics include:

  • Better management (and measurement) of sales leads across channels
  • Inclusion of custom customer incentives/rewards to influence behavior
  • Improved targeting of customer segments
  • Moving from a product focus to a customer focus 

Achieve customer centricity

Customer delivery and communication channels are expanding. This means that more customers interacting with their financial providers and banking services companies are using online and mobile channels, making it easier to gain insights into real-time sales and services. Analytics can respond to this rapid migration to digital channels by:

  • Integrating sales and service tools within a new digital environment
  • Improving branch efficiency and effectiveness
  • Helping to drive high value, high touch traffic back to branches

Technological changes

Customer analytics is no longer a domain that can be used and accessed solely by highly skilled specialists. Today, these solutions can be easily accessed and used by marketers and other business users to answer complex inquiries. Improvements include:

  • Increased number of specialized vendor solutions and expanded talent
  • Collapsing of product silos and ability to process increased data sources
  • Cloud-based solutions

Establishing analytics as a true business discipline can help banking services prContact USoviders to grasp the enormous potential. Get in touch with us to know how we can help banking sector clients in establishing a customer analytics program to suit their organizational requirements.

How can customer analytics help banking services?

We at Quantzig have identified six levers that make customer analytics a core component for banking services companies to consider:

Customer Insights

Most financial marketers are highly interested in the ability to gain a better insight on current customers. Demographics and current product ownership form the foundation of customer insight. However, behavioral and attitudinal insights are gaining in importance as channel selection and product use have become more differentiated. Take the instance of sentiment analysis and social media analysis that are helping companies analyze in-depth about their customer emotions on social platforms. Furthermore, scoring models such as FICO is especially useful for banking services companies to analyze consumers’ credit history, loan or credit applications, and other data to assess whether the consumer are likely to meet their payment obligations on time in the future.

Business strategy

Customer analytics proves to be highly useful in banking services companies for product and channel development as well as economic forecasting, business improvements, risk analysis, and financial modeling.

Managing customer experience

Using customer analytics for customer experience management (CEM) helps banking services providers in delivering personalized, contextual interactions that will assist customers with their daily financial needs. Moreover, if done correctly, customer analytics enables the real-time delivery of product or service offerings at the right time, thereby ensuring a better customer experience.

Risk management

One of the more common uses of ‘big data’ today especially for banking services companies is in the area of risk and fraud management. The applications of data mining have expanded well beyond providing internal purchase and balanced insights. It now even includes transaction patterns and social media interactions that can provide a leading indicator of potential losses or fraud. The integration of structured and unstructured data in banking services can also be leveraged for traditional risk management including pricing decisions.

Marketing

Another traditional use of customer analytics in financial services is the ability to increase the effectiveness and efficiency of sales and marketing. The ability to derive insights on the likelihood of purchase based on the available information on individual customers has ushered in a seismic shift in marketing from product centricity to customer centricity. Banking services companies and credit unions are now able to make unique, timely, and relevant offers based on available customer insight rather than offering products and services based on what the financial institution would like to sell. This allows banking services providers and financial marketers to significantly improve the efficiency of marketing spending and the close rate of sales leads.

To learn more about how Data analytics solutions work in banking sector companies, request a proposal.

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Implementing customer analytics for banking services

The future is already here. The only drawback is that it is not evenly distributed. Banks services and companies in every other industry are already deploying advanced analytics to move their businesses forward. Quantzig has identified that almost every top bank lists advanced analytics among its top five priorities. Most plan to invest further in these techniques. A few banking services companies are already seeing the rewards. By establishing data lakes and centers of excellence and using machine-learning techniques these leaders have already built substantial foundations for their business.

 How do you know what analytics capabilities to invest in for your business? All you need is an analytics expert that can guide you on leveraging the available data by avoiding pitfalls in banking services and accessing the broad set of opportunities. At Quantzig, we understand these needs of our clients and are committed to helping them bolster their analytics capabilities. Request a demo to know more about our analytics solutions.

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sentiment analysis

Why Is Sentiment Analysis Fundamental for Modern-Day Companies?

What is sentiment analysis?

Sentiment analysis is a way to evaluate written or spoken language to determine if the expression is favorable, unfavorable, or neutral and the degree to which they are so. In the modern world, businesses run on the internet, which has made the role of sentiment analysis critical for business. It is vital for companies as it helps to see what customers like and dislike about them and their brand. Customer feedback that is collected from social media, the company website, the company’s call center agents, or any other source—contains a treasure trove of useful business information. But, this often proves to be insufficient to know what customers are talking about. Businesses must also know how customers feel. Sentiment analysis is one way to uncover the feelings of customers. Here are some of the key benefits that sentiment analysis can offer to companies:

Upselling opportunities

Effective sentiment analysis helps companies analyze their customer’s emotions towards their business. Happy customers are more likely to be receptive to upselling efforts made by companies. With sentiment analysis, you can easily identify customers that are delighted with your business. This helps companies recognize the target audience that might be receptive to spending more, as well as avoiding upsetting disgruntled customers with any unwelcome sales pitches.

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Chatbots

The benefits of sentiment analysis can extend beyond helping the human agents of the company. Chatbots can also prove to be highly beneficial too. That’s because chatbots can be trained to recognize, and respond to, customer mood. For instance, sentiment analysis can easily decipher when a chat needs escalating to a human agent or route an engaged prospect through to a sales team.

Identify critical emotional triggers

Emotional triggers are what drives discussions between customers and the company. Using sentiment analysis, companies can easily identify the messages and conversations that act as emotional triggers that can change customer mood. Perhaps the use of certain phrases like “Please wait”, often triggers customer annoyance. On the other hand, using emojis can have a positive effect on the conversation’s overall tone. Understanding the messages that have the power to trigger certain emotions customers can help provide better service and is also useful for creating effective marketing materials.Request Proposal

Live insights

The mood of customers can change at any point during a customer service interaction, and this is often ambiguous. With sentiment analysis, not only can businesses see the mood of each customer in a session, but visual indicators also have the ability to display how this mood changes in real-time. They can get live insight into how well a chat is going, and the ongoing mood of even the flightiest customers.


Know more about Quantzig’ s analytics solutions for business

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media industry

4 Huge Big Data Use Cases for Modern Businesses to Zoom Ahead

Organizations now have access to more data than ever before, but unless companies decipher how to bring this data to work it proves to be absolutely useless. Understanding the benefits of big data is not as simple as putting all the data in one place. Their real value can be harnessed only through specific big data use cases and applications. Those applications tend to vary widely across departments and industries. While there are several technical challenges associated with integrating and managing all of this data, organizations should first take the time to identify and crystallize the right benefits of big data for their business. Let’s delve into some of the key big data use cases for modern businesses that we have identified with several successful customer deployments:

Top big data use cases for business

E-commerce personalization

With hundreds and thousands of search queries and customer databases, it often becomes difficult for e commerce companies to optimize their customer’s shopping experience. This daunting tasks of collecting, processing, and analyzing shoppers’ behavior and their transaction data open up a plethora of opportunities for big data in e-commerce. Using a powerful search and analytics platform e-commerce companies can clean and enrich product data for a better search experience on both desktops and mobile devices. They can also use predictive analytics and machine learning to predict user preferences through log data, and then personalize products in a most-likely-to-buy order. This would ensure maximum conversion. Quantzig’ s customer analytics solutions provide customer insights to drive sales and improve revenues through acquisition, growth, and retention.  

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customer centric marketing

Top Customer Analytics Tools That Every Manager Must Consider

Today’s business landscape is highly customer-centric. The more an organization gets to know about their customers, the more are the chances to keep them happy. This is the main idea behind using customer analytics tools. Customer analytics refers to the systematic examination of a company’s customer information and customer behavior to identify, attract, and retain the most profitable customers. The ultimate aim of customer analytics is to create a single, accurate view of a customer to make decisions about how to acquire and retain customers, identify high-value customers, and proactively interact with them in the best manner possible. In the absence of aRequest Proposaln adequate amount of accurate data, any insight derived from analytics could prove to be inaccurate. Here are some of the top customer analytics tools that are widely used today:

Top Customer Analytics Tools 

Customer lifetime value analytics

Attributing the lifetime value to each customer helps organizations to immediately identify the most valuable and important customers to the business. In this method, customer analytics tools are used to determine how long a customer is likely to stay a customer, how often they are likely to buy during that period, and how valuable they are across that timeframe rather than merely of looking at transaction profitability. This allows businesses to focus their marketing attention on the most valuable customers. If correctly done, this analytics can be valuable in identifying ways to increase the length of the relationship and the value of the customer.