Data Analytics Role in Improving Customer Experience | 3Pillar Global (2022)

Forrester previously predicted that organizations either need to learn to leverage customer insights and quantify the business impact of customer experience (CX) initiatives or find themselves in a vulnerable position. Another report from Adobe revealed that companies considered “CX leaders” were three times as likely to have exceeded their business goals. While many forecasts are little more than an alternate reality, Forrester, Adobe, and others are spot on about CX. Customer experience is a competitive advantage in every industry, from finance and insurance to healthcare, logistics, and retail.

Big Data is critical in creating the personalized experiences customers have come to expect—at scale, without friction, and with the human element intact. Companies are ramping up investment in smarter CX tools powered by AI, machine learning, and advanced analytics that help them understand customers—through how they shop and what they buy—to improve the customer experience.

In these next few sections, we explain how customer-centric data analytics strategies are the new competitive advantage.

Growing Datasets Enables Better Customer-Centric Data Analytics

According to Salesforce, 80% of customers say that the experience a company provides is as essential to them as a brand’s products or services. But capturing, analyzing, and acting on customer insights has long been a challenge for organizations. While so-called “small data” has been accessible for years in the form of sales reports, web analytics, and social media reporting dashboards, many companies struggle to connect transactional insights with the emotional.

And as companies have become more digitized, the amount of customer data available has increased exponentially in just a short time. Mobile app usage, location data, chatbot interactions, and social media feeds can now be combined with data from phone calls, transaction histories, chats, email conversations, and in-store interactions.

These channels combine to capture tons of raw data containing valuable insights into where and how customers like to engage with brands. Here are some examples of how brands use Big Data analytics to improve customer experience:

Understand Evolving Consumer Expectations. Customer behavior and expectations have changed dramatically over the past few years. In the midst of the COVID-19 pandemic, consumers evolved in response to the uncertain, unprecedented time.

(Video) How Big Data Analytics Can Be Used to Improve Customer Experience?

  • Tear Down Customer Experience Silos. Today’s marketers, sellers, and customer service professionals face tremendous pressure to reimagine traditional roles, break down silos, and apply new technologies to provide differentiated, digital-first customer engagement. According to Salesforce, 69% of marketers say traditional marketing roles hinder customer engagement. As a point of reference, only 37% of marketers felt that way in 2018.Traditional organizational models often had marketers focused on one stage in the sales funnel or one area like email marketing or lead generation, while sales and service teams each did their own thing. Now more than ever, it’s critical for all customer-facing teams to have a cohesive understanding of a customer’s journey to ensure a consistent end-to-end experience.
  • Using Big Data Analytics to Improve Service. Customer feedback can be used to inform processes for handling issues moving forward or for improving products and services. This Convince & Convert article mentions a credit reporting agency that analyzed their database to determine which complaints made customers most unhappy. The agency then measured those impacts against their impact on the organization’s bottom line. From there, they were able to prioritize issues based on magnitude.
  • Personalization. According to McKinsey, personalization can increase revenue by 5-15% and marketing efficiency by 10-30%. Big Data analytics allows brands to use online behavior insights to create customized landing pages, email campaigns, and offers, and to serve up personalized recommendations to drive more purchases.

Customer Experience and Data Analytics Are Essential for Understanding Customer Needs Throughout Complex Journeys

According to the Adobe report mentioned above, CX leaders are increasingly prioritizing content strategies that align with the specific touchpoints in the buyer journey. Big Data analytics removes the guesswork when it comes to understanding customer needs, pain points, goals, and interests, and it creates total visibility into the buying process.

Companies can now review thousands of data points in real-time that help them understand their customers in context. For example, AI-enabled analytics tools can reveal why some products are more popular with millennials vs. baby boomers, or why marketing campaigns aren’t generating as many leads as anticipated.

Organizations can also gain complete visibility into the buyer journey by drawing on transaction data, purchase histories, social media insights, as well as things like market trends and environmental conditions. This lends insight into which factors triggered certain events. Companies now create super-specific customer segments and target each group with precision, optimizing customer interactions by serving up personalized content and communications at every touchpoint.

Customer-Centric Data Analytics Helps Brands Prioritize and Act on Issues Based on Revenue Impact

A McKinsey report highlights an important point. While many executives understand the benefits of embracing a customer-centric strategy, they often fail to quantify what great customer experience is actually worth and how it can generate value. According to KPMG, the relationship between CX and financial gains can hit a point of diminishing returns.

For example, companies often overspend on efforts to attract or delight customers, which typically cost more than improving retention rates or taking advantage of upselling and cross-selling opportunities. Big Data analytics tools can help organizations make sure they allocate their resources where they will have the most significant impact.

Another report from Deloitte offers a framework for measuring the business value of CX and breaks it down as follows:

  • Does the customer realize business value? What external factors (positive reviews and referrals) indicate this?
  • Is the customer experience positive? Here, you look at complaints, review interaction data, NPS scores, and surveys to gauge sentiment.
  • How are products/services performing? How are products selling? Are certain products/services linked to more positive experiences than others?
  • Internally, you want to measure revenue, churn rate, and average order size, as well as how much you’re spending on marketing efforts and processing returns.

Big Data allows organizations to connect what customers say to what they do and analyzes satisfied, neutral, and dissatisfied customers to identify what factors into a good or bad experience. Big Data can also be used to target and acquire customers who share characteristics with a company’s most profitable customers. This allows sales and marketing teams to focus their efforts on audiences with the highest propensity to buy and the highest potential lifetime value.

(Video) Data, Analytics and Improving the Customer Experience

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Exceptional customer experience (CX) is possibly the most important competitive advantage for businesses today. This guide sets out the fundamental principles to help you prioritize, analyze, and improve your organization’s customer experience.

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How AI & ML Change Customer Experience and Data Analytics

Artificial intelligence has changed the way brands connect with customers, making it easier to create personalized experiences and nurture long-term relationships. According to Adobe’s 2020 Digital Trends in Asia Pacific report, more companies are embracing AI and ML as a way to bridge the gap between the high-volume, high-velocity data being generated and the ability to use that information to engage customers in real-time.

For marketers, bringing more automation into the mix is huge. The report touched on an important point: over the past several years, marketers have amassed more and more customer data, along with a growing list of responsibilities. As AI-enabled platforms become more accessible, there’s an opportunity for marketers to gain some of their time back by eliminating ad-hoc manual efforts that prevent them from creating real value for consumers.

The Salesforce 2020 State of Marketing report found that AI adoption has grown by 186% since 2018, and 92% of marketers now have an account-based marketing (ABM) program. AI tools allow organizations to leverage real-time insights to engage customers as they browse a brand’s website. Brands might serve up content that speaks to specific pain points. In sales, AI is becoming an essential tool for lead scoring, and can also help determine the best steps to take next based on what tactics have historically been successful at various stages in the sales cycle.

In financial services, banks use Big Data analytics to improve the customer experience by tracking milestones like weddings, births, college, home purchases, and retirement, and then using those insights to deliver relevant offers. In healthcare, Big Data analytics are being used to provide personalized patient journeys and improve health outcomes.

(Video) How Retailers Can Use Data to Improve Customer Experience

Customer Insights and Data Analytics Set the Stage for Success

Technology is redefining the current relationship between brands and consumers. As customer expectations continue to reach new heights, a data-driven customer experience is no longer the exclusive domain of tech giants and well-funded startups.

Organizations in banking, retail, insurance, healthcare, and countless other sectors are now competing on experience. Without Big Data analytics, rising to emerging CX challenges won’t get any easier.

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FAQs

How does data analytics improve customer experience? ›

It helps you 1) understand who your customers are, how they shop, what they buy, and how they prefer to engage; and 2) build better, more intelligent tools to serve and retain them. Better data security can also elevate the customer experience for new and existing clients.

How does analytics improve customer service? ›

4 Proven Ways to Use Data Analytics & Improve Your Customer Service
  • Helps Identify Forthcoming Trends: “When customers share their story, they're not just sharing pain points. ...
  • Provides Deeper Insights & Deliver a Hyper-Personalized Experience: ...
  • Helps to Adjust the Pricing: ...
  • Helps in Decision-making:

Why is data so important for customer experience? ›

The more data the company has, the more personalized and engaging the customer interactions become. For instance, the CRM system your team uses can make it easier to see which channels your clients use, so you can make sure that there are always agents available when a customer needs service.

What do we do and how do we use data to improve customer experience? ›

How to Use Data to Improve Customer Experience
  1. Collect an Inventory of Current Customers. ...
  2. Determine Where You Stand With Your Clients. ...
  3. Map and Analyze Customer Profiles. ...
  4. Put Data Into Practice to Appeal to Clients. ...
  5. Measure Customer Satisfaction Results, and Make Changes Accordingly.
28 Jul 2020

How is data analytics used in customer service? ›

Customer service analytics is the process of collecting and analyzing customer feedback to discover valuable insights. It can help you better understand your customers' needs and expectations, lead to improved customer experience (CX) strategies and increase customer loyalty and retention.

What are customer experience analytics? ›

Customer experience analytics is the collection and assessment of customer data – such as the reviews customers leave on your social media accounts or frequency of purchases on your website – that enable you to understand them better and consequently make their experience interacting with your brand more delightful.

How data analytics can improve organizational operations customer experience productivity and performance? ›

Data analytics help to improve business management by helping leaders assess the effectiveness of current workflows, analyze the outcomes of the processes, automate new workflows, and refine them over time. Data also allows leaders to determine if processes are burdensome, draining the budget, or challenging to use.

Can data analysis or data analytics introduce customer service improvements? ›

By using advanced data analytics you can understand your consumer base, deliver on or exceed expectations and proactively identifying opportunities for improvement. Your business can establish a connection with customers that has the ability to stand the test of time.

How do you approach customer service from a data analytics perspective? ›

Below are four key strategies the customer service manager can implement to leverage analytics to maximum effect.
  1. Differentiate the customer experience. ...
  2. Deliver personalized service. ...
  3. Develop a singular view of the customer. ...
  4. Deliver consistently exceptional service.

What is a CX data analyst? ›

The work of a CX analyst is the intersection of customer service and business/data analytics. These analysts focus their work on collecting and parsing data, specifically focused on customer service and experiences. They then turn that data into something useful.

What is data analytics in simple words? ›

Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain. Increasingly, data analytics is done with the aid of specialized systems and software.

How can you provide effective customer service by capturing data to track interaction? ›

The key to effective quality monitoring includes six crucial steps:
  1. Listen to your customers by monitoring interactions. ...
  2. Capture all of your customer feedback channels. ...
  3. Ask your customer what they think. ...
  4. Use quality monitoring to help agents improve skills. ...
  5. Do not view agent development as a one-off activity.
11 Feb 2013

How data can improve customer relations? ›

Data makes it possible to understand what customers have to go through and where the friction points are without real-time interaction. Data allows you to watch behaviors and trends that lead up to, occur during, and happen after purchases, giving you better insight into the purchase journey.

How do you optimize your customer experience? ›

How to Optimize for Customer Experience
  1. Ask customers how they feel. It's easy to make assumptions about customer preferences based on their actions within your product. ...
  2. Create a journey map. ...
  3. Understand why they made their purchase. ...
  4. Do user testing and session recording. ...
  5. Don't neglect mobile. ...
  6. Emphasize consistency.
25 May 2021

What are the most important factors in building a great customer experience? ›

There are many factors that contribute to a great customer experience, such as the quality of the product or service, the convenience of the purchase process, the friendliness of the staff, and the overall atmosphere of the business.

Why is customer analytics important in business? ›

By uncovering customer needs, the right analysis can help you develop new products and services; ones your customers may not even know they need. The new product lines you develop in this manner could drive sales and profits even more, helping you build an even better business.

Is customer analytics key to marketing world? ›

Conclusion. Customer Analytics is very important in today's digital world. Properly implemented analytics helps to predict customers' reactions to marketing and AD campaigns, their brand adaptation, and their understanding of the customer experience.

What are the different types of customer analytics? ›

There are 6 different types of customer analytics: customer journey, customer experience, customer engagement, customer lifetime, customer loyalty, and voice of customer.

Which analytics allows you to develop a quality and customer experience for all customers? ›

Customer Experience Analytics – Definition

Customer experience analytics is the systematic examination of a company's customer data to understand the customers, their pain points, and their experiences which will, in turn, give you the confidence to update and optimize existing customer experience solutions.

What are the activities in customer analytics? ›

As the backbone for all marketing activities, customer analytics comprises techniques such as predictive modeling, data visualization, information management and segmentation.

What is customer engagement analytics? ›

Customer Engagement Analytics: Defined

Customer engagement analytics focuses on using analytics to improve customer engagement by helping businesses analyze structured and unstructured customer data obtained from various channels.

What is a key benefit of data analysis? ›

Better Decision-Making

One of the main benefits of Big Data analytics is that it improves the decision-making process significantly. Rather than relying on intuition alone, companies are increasingly looking toward data before making a decision.

How can data analytics benefit a company? ›

Businesses collect customer data from many different channels, including physical retail, e-commerce, and social media. By using data analytics to create comprehensive customer profiles from this data, businesses can gain insights into customer behavior to provide a more personalized experience.

Why is data analytics so important? ›

Data analytics is important because it helps businesses optimize their performances. Implementing it into the business model means companies can help reduce costs by identifying more efficient ways of doing business and by storing large amounts of data.

What is predictive customer analytics? ›

Predictive customer analytics helps businesses identify customers at high risk of churning. To identify customer attrition before it happens, look at the traits of customers who have churned in the past using churn rate cohort analysis. You can also look at a customer's lifecycle for clues about who will likely churn.

Who is a customer success analyst? ›

A customer success specialist develops and maintains long-term business relationships by serving as an internal advocate and client liaison. Typically a “people person,” by nature, they have a hybrid of soft and hard skills required to master technology and manage customer relationships.

What does customer experience specialist do? ›

The role of a customer experience (CX) specialist is to ensure that the marketer follows a buyer-centric approach and delivers a smooth, unfragmented and consistent customer experience across all touchpoints and at all stages of the buyer journey.

What does a customer insight analyst do? ›

Generally, a customer insight analyst or manager's job is to look at and analyse trends. Being commercially aware of their market as whole is key, as they need to think outside the box and ask questions of the data they collect, to transform it into actionable insights for the business to grow.

What are the 5 types of data analytics? ›

5 Types of analytics: Prescriptive, Predictive, Diagnostic, Descriptive and Cognitive Analytics - WeirdGeek | Data analytics, Data analysis tools, Data science.

Why is data analytics the future? ›

Data Analytics is being increasingly leveraged by startups, SMEs, and large organizations to reduce costs, improve customer experience, optimize existing processes and achieve better-targeted marketing. In addition to these, many companies are showing interest in Big Data due to its ability to improve data security.

Why data analytics is the future of everything? ›

Organizations can use the insights they gain from data analytics to make informed decisions. Thus, leading to better outcomes and customer satisfaction. 2. Better Customer Service: Data analytics allows you to tailor customer service according to their needs.

What are the five ways to monitor your customer service? ›

Analyze service interactions across all channels
  • Ask customers for their feedback. Asking your customers for feedback on their preferred channels is a great start. ...
  • Consult with agents to improve practices. ...
  • Offer regular employee training and mentoring. ...
  • Provide regular channel maintenance.

How can you contribute to improving customer service delivery? ›

How to Improve Customer Service
  1. Understand customer needs. ...
  2. Seek and promote customer feedback. ...
  3. Set and communicate clear service standards. ...
  4. Delight your customers by exceeding their expectations. ...
  5. Capture and share examples of great service. ...
  6. Create easy and effortless customer service. ...
  7. Personalise your customer service.

How can customer interaction be improved? ›

11 ways to improve customer interactions
  1. Show empathy. Make an effort to show empathy to every customer you interact with. ...
  2. Be transparent. ...
  3. Communicate across a variety of channels. ...
  4. Express your gratitude. ...
  5. Use your authentic voice. ...
  6. Follow up with every customer interaction. ...
  7. Consider using a checklist. ...
  8. Rely on customer feedback.
18 Oct 2021

What are the uses of data in the hospitality industry? ›

Data analytics in the hospitality industry can help hoteliers to develop a strategy for managing revenue by using the data gathered from various sources like the information found on the internet. Through analysis of these data, they can make predictions that will help owners with forecasting.

How could insights from that data solve a problem? ›

Rather, data and the insights it provides are powerful tools used to identify, assess and resolve business problems in real-time. In this way, data science can be applied to business problems to improve practices while reducing inefficiencies and redundancies – strengthening customer satisfaction.

How data and analytics strategy is a great place to start addressing some of the roadblocks that can pop up between you and your customers? ›

A data and analytics strategy is a great place to start addressing some of the roadblocks that can pop up between you and your customers. Meeting your customers' expectations, being where they are, and providing seamless support is an easy call to make when your data nudges you in the right direction.

What is a customer experience strategy? ›

What is a customer experience (CX) strategy? A CX strategy comprises the plans you put in place to provide positive experiences at each customer touchpoint along the customer journey and the purposeful ways to measure those experiences – both online and off.

Why customer experience optimization is important? ›

Customer experience optimization is so crucial because it increases customer satisfaction and improves KPIs for businesses. Happy customers and better KPIs usually means more revenue and growth.

What is customer experience excellence? ›

It's a term that measures how a customer feels after interacting with a product, service or brand as a whole. Likewise operational excellence, relating a company's costs to the value it delivers to customers.

What are the 3 main components of customer experience? ›

The three main components of customer experience are:
  • Discovery. This component is all about how companies contact customers and how they make that contact relevant and meaningful. ...
  • Engagement. This component is about how customers interact with the company and company products. ...
  • Delivery.
13 Feb 2022

What are the four elements of the customer experience model? ›

- To truly understand customer experience we have to understand the four components required to build one. There are archetypes, activities, interactions, and principles. An easy way to remember these is to think about the different parts of a relationship.

What are the 7 qualities of good customer service? ›

7 Must-Have Qualities of a Stellar Customer Service Rep
  • Problem-Solving Skills. The number one skill you need to excel in for good customer service is problem-solving. ...
  • Clear Communication. ...
  • Friendly Attitude. ...
  • Empathy. ...
  • Business Acumen. ...
  • Product/Service Knowledge. ...
  • Strong Time Management.

What are the uses of data in the hospitality industry? ›

Data analytics in the hospitality industry can help hoteliers to develop a strategy for managing revenue by using the data gathered from various sources like the information found on the internet. Through analysis of these data, they can make predictions that will help owners with forecasting.

How could insights from that data solve a problem in data analysis? ›

Data analytics is a sub-field of data science and plays a major role in problem-solving. It makes it easy for us to extract and gather information from various sources and combine it to use it in our solutions effectively. More the information we can gather, the easier tackling the problem gets for us.

What is data analytics in simple words? ›

Data analytics (DA) is the process of examining data sets in order to find trends and draw conclusions about the information they contain. Increasingly, data analytics is done with the aid of specialized systems and software.

How could insights from that data solve a problem? ›

Rather, data and the insights it provides are powerful tools used to identify, assess and resolve business problems in real-time. In this way, data science can be applied to business problems to improve practices while reducing inefficiencies and redundancies – strengthening customer satisfaction.

What is the significant role of data analytics in hospitality industry? ›

Data analytics in the hotel industry is key to marketing strategy, building customer loyalty, and enhancing productivity. It enables hotels to personalize experiences for their guests, introduce better hotel pricing strategies, and expand their customer base.

What are the benefits of having data analytics in hospitality industry? ›

Proper data analysis can allow the hotel industry to build a tailored marketing strategy plan that is targeted to specific customer types and maximize revenue. This enables advertisers to build a more personalized user experience. They can identify key consumer groups and develop more content to serve their needs.

How data analytics is beneficial to tourism and hospitality industry? ›

How Data Analytics Benefits Hospitality Industry. Data Analytics has a wide range of applications in the hospitality industry and the hospitality and travel companies are leveraging it to enhance business operations, create unique marketing strategies, understand occupancy rates and yield, among others.

How important is data analysis? ›

Data analysis is important in business to understand problems facing an organisation, and to explore data in meaningful ways. Data in itself is merely facts and figures. Data analysis organises, interprets, structures and presents the data into useful information that provides context for the data.

Why is it important to use an analytical process when solving problems? ›

Why are analytical skills important? Analytical skills are important because they allow you to find solutions to common problems and make informed decisions about which action to take next. Understanding problems and analyzing the situation for viable solutions is a key skill in every position at every level.

Why is business analytics important in solving business problems? ›

The Benefits of Business Analytics

Assist businesses to understand their customers more precisely. Business uses data visualization to offer projections for future outcomes. These insights help in decision making and planning for the future. Business analytics measures performance and drives growth.

What are the 5 types of data analytics? ›

5 Types of analytics: Prescriptive, Predictive, Diagnostic, Descriptive and Cognitive Analytics - WeirdGeek | Data analytics, Data analysis tools, Data science.

Why is data analytics the future? ›

Data Analytics is being increasingly leveraged by startups, SMEs, and large organizations to reduce costs, improve customer experience, optimize existing processes and achieve better-targeted marketing. In addition to these, many companies are showing interest in Big Data due to its ability to improve data security.

How do companies use data analytics? ›

Businesses collect customer data from many different channels, including physical retail, e-commerce, and social media. By using data analytics to create comprehensive customer profiles from this data, businesses can gain insights into customer behavior to provide a more personalized experience.

How data analytics can curb business risk? ›

Through data analysis, businesses can identify weaknesses in their current assets and the kinds of risks their liabilities impose on them. With this information, businesses will be able to use their assets more efficiently.

How data analysis can aid problem solving and decision-making? ›

Increases consistency. The use of data in decision-making processes ensures that the business agrees on results. This approach helps people understand how decisions are made. They can determine the implications of the data being collected and analyzed, and take appropriate action.

What are the common problems that data analysts encounter during analysis? ›

Top 5 Data Analytics Challenges
  • Lack of skilled resources with understanding of Big Data Analytics. ...
  • Gaining meaningful insights using Big Data Analytics. ...
  • Bringing extensive data to big data platform. ...
  • Uncertainty of Data Management Landscape. ...
  • Data Storage and fast retrieval.

Videos

1. Better Customer Experiences with Data Analytics
(Snowflake Inc.)
2. Video 3: Improving Customer Experience with Machine Learning and Analytics
(Liferay)
3. Using Real-time Data Analytics to Improve the Customer Experience
(PEX Network)
4. TI Media - Creating data-driven decisions to improve the customer experience
(Snowflake Inc.)
5. Think CX, Part 19: How to use analytics to improve the customer experience
(Evolv AI)
6. How Telecom Companies are Improving Customer Experience with Customer Journey Analytics
(Pointillist)

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