The Future of CX: 5 Ways Data Science Outsourcing Helps You Boost Customer Experience

Published: December 14, 2023
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The importance of data science is undeniable. All organizations, from emerging startups to powerhouse companies, benefit significantly from using data when making crucial business decisions – particularly for improving customer experience.

As the global business landscape becomes increasingly competitive, more brands are turning to data science outsourcing for guidance in elevating their CX strategy.

But what is data science, and how does it help companies improve their decision-making, particularly regarding customer experience? Let’s dive deeper into the role of data in today’s CX initiatives.

Starting With the Basics: What Is Data Science and Analytics?

Data science combines statistical analysis, specialized programming, artificial intelligence (AI), and machine learning (ML) to extract actionable insights from mountains of data. 

As technologies advance, companies of all sizes and industries have realized the potential uses of data science for their daily operations, helping them accelerate digital transformation and streamline business processes.

Much like business analysts, data scientists must have a deep understanding of the specifics of a business, including the particular pain points and challenges of an industry. However, data scientists have specialized knowledge beyond typical business acumen, applying their expertise in machine learning algorithms, programming languages, and computer science to real-world problem-solving.

The Role of Data Science in the Customer Experience

Brand interactions have become increasingly digital in the modern world, from AI chatbots to algorithm-powered product recommendation systems. Through a human-centered AI design, every customer touchpoint can be streamlined through technology and then measured and examined for insights.

Businesses can gain robust insight and information by analyzing data from a customer’s digital footprint. How often does a particular demographic check your website? What specific products or services are selling well in a precise location? What are the characteristics of the customers who are loyal to your brand? These are all questions you can answer through data science.

Once you’ve answered your most pressing questions, you can use the insights you’ve extracted to refine your CX strategy, tailoring experiences to your consumers’ particular needs and wants. Data science outsourcing enables companies to leverage customer data to create a better overall customer experience.

Limitations of the Traditional CX Model (and How an Outsourced Data Scientist Can Help)

Before we address the advantages of data science outsourcing in enhancing the customer experience, let’s first delve into how businesses used to measure CX. Previously, companies relied on surveys and customer feedback forms to assess whether their CX improvement efforts worked. Here are the limitations of this method:

Traditional CX is reactive rather than proactive.

Before the rise of advanced technologies, businesses used surveys and traditional feedback methods to learn what customers think and feel about their products and services. The problem with this approach is that brands can only know that something isn’t working once customers have expressed their disappointment.

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With traditional CX, buyers only provide feedback after interacting with your business. Still, if you wait for customers to reach out to you only after they’re frustrated or angry, you will have failed to win their business. 

According to a McKinsey study, nearly two of three business leaders prioritize acting on CX issues in real-time. Still, only 13% believed their companies could facilitate proactive customer service.

With help from an outsourced data analyst, businesses can become more proactive in improving their CX initiatives. They can utilize predictive analytics to identify, anticipate, and prevent possible problems a customer may experience during their interactions with your company.

Traditional CX is limited in scope.

Not every customer likes to answer surveys or provide feedback. Many dissatisfied consumers quietly turn away and bring their business elsewhere, leaving you wondering where you went wrong.

The same McKinsey study found that only 7% of a company’s customers answer surveys. So, businesses gain a minimal view of their client experience, with the small sample size not representative of the majority’s thoughts, feelings, and brand perceptions.

Thankfully, data science is different because it collects every digital footprint your customers leave when interacting with your brand, from how many times they’ve viewed your website to how often they have purchased your products. By working with these more extensive data sets, businesses can make more informed decisions about what most consumers genuinely want.

Traditional CX relies too much on guesswork.

Another problem with traditional CX methods is that they can be too ambiguous, failing to uncover the root causes of customer satisfaction and dissatisfaction. Survey scores vary depending on various external factors, including location, time sent, and even survey length.

According to a 2023 State of Surveys Report, the length of a survey affects how willing people are to complete it. As such, nearly half (48.8%) of all surveys in the U.S. were one page or less to encourage more customers to answer them.

However, short surveys won’t give you in-depth insight and information about your customers’ thinking. Even when you convince enough people to provide feedback, it will still be challenging to analyze why they rated something a certain way or how you can improve their experience.

The McKinsey research mentioned above found that only 16% of business leaders say surveys are enough to help them analyze and address the root causes of their CX performance. With more thorough data collection and analysis, companies can stop relying on guesswork and instead listen to what the numbers say.

How Outsourcing Data Analysis Enhances the Customer Experience

Now that we’ve discussed the limitations of traditional CX let’s delve into how data science outsourcing helps companies enhance their customer experience initiatives. Here’s how utilizing data can help you gain a competitive edge:

An infographic discussing how data science outsourcing helps revolutionize your customer experience.

Facilitates Hyper-Personalized Consumer Experiences

As data becomes more readily available for businesses, consumer expectations are changing to keep pace with them. Knowing that brands are collecting their information, more customers now expect their digital footprint to be put to good use, mainly for giving them more personalized experiences.

According to a 2023 Statista report, customers expect companies to improve personalization when they provide more data (74%), when technology advances (73%) and when they spend more money on products and services (64%).

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A different study echoes these findings, stating that 73% of buyers want brands to understand their unique needs, and 56% expect all offers and messages to be personalized and relevant. 

Businesses can tailor a customer’s experience to their past behaviors and interactions with the brand using insights generated through data science outsourcing.

Real-Life Case Studies

Here’s an example everyone may be familiar with: Netflix, the streaming giant, uses your viewing history and demographic to recommend movies and series that you might enjoy. 

Leveraging predictive modeling, their recommendation system uses a complex algorithm that helps viewers easily find new shows relevant to their tastes and interests. It reduces time spent endlessly scrolling through and searching the app while improving customer experience and satisfaction.

The health and beauty retail company Boots UK is another real-life example of a company using data science to improve personalization. They collected data from 15 million Boots Advantage Card users, building algorithms to recommend the next best action for customers based on their purchase history and preferences.

Their data-powered loyalty program was a resounding success, leading to a 70% rise in personalization and a visible increase in customer loyalty and spending.

Predicts Customer Behavior and Satisfaction

Surveys and other traditional CX methods can help businesses understand past consumer habits but cannot predict what customers might do in the future. Using AI and machine learning models, companies can use existing datasets to identify trends, make intelligent predictions about future behavior, and use these insights to create a roadmap for success.

One real-life example of a company using data science to predict customer behavior is Amazon’s “anticipatory shipping” method. Before a customer even orders, the e-commerce giant can expect what products will be in high demand (based on previous orders and other relevant factors) and ships the packages to its fulfillment centers.

This strategy aims to cut down on order fulfillment times by stocking their shippers’ hubs with products they know will be highly anticipated by shoppers. So, once a customer purchases the item online, the package will be ready and available for delivery as soon as possible.

Provides Deeper and More Detailed Customer Insights

As we established in previous sections, the traditional CX model is limited in that only a few customers answer surveys, and many may phrase their feedback in vague terms, leading to possible misinterpretations.

With data science, there is less room for ambiguity. Data engineers and other data science professionals can sift through mountains of raw, measurable data and extract clear, actionable insights.

Ideally, businesses will use their collected data to achieve a 360-degree customer view, allowing for a more holistic understanding of consumer behavior, trends, and preferences. With more profound and comprehensive insights, companies know what customers need and understand what’s driving their behavior and shaping their preferences.

Identifies Business Strengths and Areas for Improvement

Before business leaders make a decision, they need to clearly understand the risks and rewards and have a logical approach to planning. After all, any new move you make – whether adding a feature on an app or creating a brand-new product – will affect the overall customer experience.

According to a PwC survey, only 39% of companies consider themselves “highly data-driven” when making decisions, but those who leverage big data often increase profitability and performance. 

A BARC study supports these findings, reporting that 69% of businesses make smarter strategic decisions thanks to data science, 54% can control their operational processes more effectively, and 52% understand their customers better.

Instead of relying on gut instinct when launching a new product, service, or feature, businesses can draw from the available consumer data to make educated predictions about how their target base may respond to the changes.

Investing in an outsourced data science program can also help businesses identify the obstacles and challenges customers face when interacting with their brands, helping them to create opportunities for improving consumer satisfaction.

Addresses Customer Pain Points

Understanding and addressing customer pain points, the frustrations or challenges buyers may encounter when interacting with your brand, is essential to providing a top-notch experience. Whether dealing with a confusing payment process or lack of transparency in deliveries, customer pain points can shape how consumers feel and think about your brand.

By collecting and analyzing data, businesses can identify possible pain points in their processes and address them before customers even get the chance to complain. Predictive models can also help them continually develop innovative strategies to improve and refine their CX initiatives.

Leverage the Power of Predictive CX Through Data Science Outsourcing

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Ready to take your customer experience to the next level? Partner with SuperStaff for data science outsourcing.

Utilizing AI and other advanced technologies, our professional data scientists extract actionable insights from raw information to help clients understand their business’s strengths and pain points.

We aim to empower you to maximize relevant data in your strategic decision-making and planning, helping you provide your customers with the best possible experience. Connect with us today to get started!

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