Customer service and data analytics go hand-in-hand. Without accurate and reliable customer-centric data, marketers cannot hope to make impactful decisions that drive growth and boost user satisfaction. Here’s what the research tells us:
- Data-driven organizations are 23X more likely to acquire customers, 6X as likely to retain customers, and 19X as likely to be profitable as a result.
- In an Econsultancy and Adobe survey, 65% of respondents expressed that “Improving data analysis capabilities to better understand customer experience requirements was the most important internal factor in delivering a great future customer experience.” You can read the full report here.
- Another survey suggests that “The top needs for improving customer experience personalization are more real-time insights (46%), gathering more customer data (40%), and greater analysis of customer data (38%).”
The writing is on the wall: If you’re not using data analytics to drive powerful customer service, you’re already falling behind the competition and losing your edge.
Now that you have a solid foundation of the integral role data analytics plays in driving a stellar customer experience, let’s look at the benefits it poses and key strategies businesses can leverage to advance their organizational goals.
4 Proven Ways to Use Data Analytics & Improve Your Customer Service
1. Helps Identify Forthcoming Trends:
“When customers share their story, they’re not just sharing pain points. They’re actually teaching you how to make your product, service, and business better.” – Kristin Smaby, “Being Human is Good Business”
When unearthed and analyzed, data allows brands to redirect their focus towards a more meaningful customer experience. How so? Businesses can:
- Anticipate the user’s needs and wants, and pivot their offering accordingly at different points in the user’s journey.
- Access a 360-degree view of the user–from their pain points and past behavior to their motivation and wants. This is also known as the buyer persona:
- Data analytics basically allows companies to move ahead with clear direction and clarity, and drive on-point communication.
- Understand how their offering doubles up as the solution to the user’s unresolved issues and/or unrecognized problems.
Lance Gruner, Mastercard’s executive vice president of customer experience and care says, “Data analytics aids his company to ensure it has the right amount of support in place to address customers’ needs promptly and then exceed their expectations. In addition to forecasting the volume of inquiries so that we can resource accordingly, we are also using advanced models to predict the complexity of the inquiry.”
To get inside the heads of its customers’ heads, AT&T Business has executed a customer experience machine learning system. This technology intakes hundreds of exclusive data elements- literally petabytes of data – throughout customer lifecycles. “It predicts based upon customer effort, cycle time, retry rates, etc. if a customer will stay as a promoter or if they start sliding towards neutral or detractor territory,” explains Sorabh Saxena, AT&T Business’ president of global operations and services.
The system generates predictive alarms that drive the next-best-action recommendation, either automatically or through system assist to ensure that the customer remains a promoter. “The best part is that it is constantly learning and fine-tuning the algorithms as it gets more experience,” he says.
The learning: To boost organizational growth, high-quality data is key. It enables organizations to stay one step ahead of their competitors by leveraging accurate, reliable, and evidence-based consumer insights.
2. Provides Deeper Insights & Deliver a Hyper-Personalized Experience:
Tying back to the previous point, data translates to insights. And insights help drive customized experiences, which in turn, ensures customer satisfaction.
Customers today actively demand personalized offers, products, services, and experiences. In fact, according to McKinsey:
“Today’s consumers do not buy just products or services — more and more, their purchase decisions revolve around buying into an idea and an experience.”
This is where high-quality data analytics lends a helping hand and allows brands to foster a meaningful relationship with the user. On the ground, it also helps marketers to address powerful questions such as:
- Which digital channels are most used and/or least liked by their existing client base?
- Which keywords should the brand use to encourage content consumption across digital platforms?
- Are customers liking ads or do they value testimonials that are displayed on the social media channels or the company’s website?
- What parts of the website are the customers spending the most amount of time in?
And so on.
At the end of the day, data empowers marketers to come up with strategic and personalized offers, and deliver an impactful and positive experience.
Imagine a world in which retailers know exactly what a shopper wants even before arriving at a company’s website or app. That’s what predictive analytics can provide. “Through data-driven technology, we can create a personalized collection, incorporating thousands of products every single day – a customer experience that is truly relevant and engaging.” Bindu Thota, vice president of technology for online clothing and accessories says, “That’s the human touch.”
For the first time in history, we are seeing social media and other online avenues enabling marketers to interact with people anytime and anywhere. “This provides an unparalleled opportunity to discover emerging patterns that assist companies to marshal their resources and direct their energies more effectively,” explains Adam Lichtl, founder of Pacific Data Science, a data consulting firm.
“By accumulating all these small points of data around the customer experience and integrating them we can get a fair picture of the customer journey – before, during, and after they engage with the company.”
The learning: Today, mass marketing finds no appeal and has no place–be it in the marketer’s mind or the user’s. A “one-size-fits-all” strategy for communication will no longer cut it, making data integration a priority for organizations of all shapes, sizes, and types.
3. Helps to Adjust the Pricing:
One of the biggest concerns for customers posts the customer experience is pricing. All said and done, competing on fair pricing also provides brands with an undue advantage. However, it is impossible to understand what your users might not like regarding the pricing strategy. Data can shed an insightful light here. Considering that your customer’s needs are ever-evolving, particularly in the scenario of an ongoing pandemic, being flexible and agile with your pricing model might unlock opportunities for expansion, profit, and user satisfaction.
Here’s a quick and useful process that brands can follow:
Step 1: Gather real-time user data–from psychographics and demographics to purchase history and buyer intent.
Step 2: Analyze the current product/service and compare it with the anticipated trends in buyer needs and demands.
Step 3: Identify gaps as well as areas of improvement for figuring out windows of innovation, growth, and differentiation.
Step 4: Make customer-centric R&D an ongoing and integral part of the company’s mindset and culture.
For the standard growth of a business, it is imperative to maintain a proper balance between customer satisfaction and price. With the help of data analytics, you can pinpoint the perceived value for pricing your products and services. Through the data accumulated from past sales records, market trends, and individual buying patterns, data analytics enable businesses to device product prices that best suit their business.
The learning: Data-powered assets such as buyer persona, behavioral reports, transactional history, and so on have emerged as a key tool for driving meaningful product improvements, especially when it comes to pricing.
4. Helps in Decision-making:
With a treasure trove of priceless user data that you can analyze and leverage using a Business Intelligence tool, marketers and leaders automatically become better-positioned to make informed decisions on factors such as sales, pricing, communication, organizational goals, etc. Moreover, marketers can drive important decisions such as establishing a knowledge self-service tool for instance–a go-to channel for more than 6 out of 10 U.S. consumers today.
BI removes the guesswork and enables you to make informed decisions based on the data in front of you. Your dashboard enables you to see which channels are most successful at converting your customer. It helps you to adapt your strategy or change your approach to maximize your return on investment (ROI). For example, imagine your sponsored LinkedIn posts are responsible for more conversions than your PPC campaign and you have to make the decision whether to change your keyword strategy or channel more of your marketing budget into LinkedIn instead.
The learning: Contrary to popular opinion, data-powered technology can help humanize a brand and empower decision-makers to move ahead with agility, confidence, and motivation. With the right kind of leadership in place, customers are bound to experience the benefits–be it speedy delivery, personalized offerings, efficient customer services, and so on.
In Conclusion: Data is an Intellectual Asset for Brands Today
Businesses today have become customer-obsessed and for good reason. With information comes power and this adage holds for any customer-facing business. Whether it’s driving personalization or catering to the customer’s needs, data plays a central role in helping brands connect with users on an emotional level–a winning strategy in today’s competitive landscape.
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About the author
Surya Ranjan Pandita is a digital marketer at Acquire. He is always on the lookout for new optimization strategies and loves to create actionable content. Feel free to ping him on surya.pandita@acquire.io or on LinkedIn
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