How Data, Analytics and Insights Can Improve Customer Service

This blog, co-written with Thanneermalai Krishnappan (Technical Manager, Apexon), draws on their joint experience in the data and analytics environments.

The 24/7 nature of the connected society has taken the idea of what customer service should be to a new level. As digital experiences have evolved, so too has the requirement for an effective and efficient customer service as a must-have business optimization strategy.

According to a recent report from Gartner there is a defined shift towards technologies that are focused on the customer, with the analyst noting that business leaders must be aware of how customers interact with the numerous digital channels that are available. In fact, the next two years will see the most anticipated (and, by association, valuable) tech solutions revolve around the customer, the report said, with companies investing both time and money into ensuring that customer service and support is a priority.

The customer journey is the perfect place to integrate next-gen technologies such as AI and advanced data analytics, Gartner said, even more so as the insights gained from customer behavior become key to leveraging competitive advantage. The caveat is that – in many cases – defined time-to-market pain points have been less about the amount of raw data that is visible to companies and more that the data generated is not effectively translated into actionable insights.

“It is crucial that leaders understand how customers interact with digital channels in order to contain customers within them, and improve their overall customer experience,” said Connor Seidenschwarz, principal, research in the Gartner Customer Service & Support Practice, in a press release. “In fact, most customer service leaders we surveyed view investments in analytics as an investment in improving their self-service capabilities.”

Taking that into account, this blog post will look at the challenges, trends and solutions that decision makers must be aware of when leveraging data and analytics to deliver the optimal customer service experience.

To do this, we must also understand why eliminating guesswork is a critical part of the process and, importantly, why the adage that the customer is always right remains as relevant today as it has always been.

Customer Service has an Impact

Customer service should always be a priority, but we must accept that this is both a business optimization strategy and a reflection on the brand itself.

Understanding your customer’s needs is a given, albeit that the ability to deliver on promises made in the pre-sale phase of a product lifecycle should also be high on the list. For that we should consider what we – as consumers – expect from the plethora of companies and brands that we interact with on a regular basis.

The phrase “caveat emptor” – literally translated as “buyer beware” – is based on the principle that the customer (or buyer) is responsible for ensuring that the goods and/or services that they are paying for are of a sufficient quality to be acceptable.

This becomes even more important when you factor in the move away from purely physical customer touchpoints and the increased adoption of digital channels. In fact, there is an argument that digital transformation has flagged up not only why customer service matters but also the impact of getting it wrong. Recent history is filled with examples of brands that failed to appreciate the impact that poor customer service can have on the bottom line, so it is critical to ensure that all bases are covered from day one.

If we take this one step further, then the information that can be gleaned from these defined and digital touch points should be used to find the answers to the following questions:

• How well do you know your customers?
• Do you know what makes them buy your products and services?
• What channels are they using to engage with the brand?
• Are there any pain points or choke points that prevent the customer from getting the response they want?
• What is the ratio of satisfied to unsatisfied customers?
• How high are your retention levels?
• Are you using the data to gain competitive advantage or for damage limitation?

To reiterate, there is a rich seam of data that can come from customer service, but if you don’t know how to use this information then the insights it can give are of little actual value.

Data-as-a-Service (Daas) has seen significant traction in the data and analytics sector, providing companies with the tools they need to both make sense of the information available and integrate data-driven solutions. Apexon’s recent acquisition of Gathi Analytics, for instance, was driven by a need to ensure that decision makers understand the synergies between actionable insights and customer behavior, especially when it comes to ongoing business optimization strategies.

It also should be noted that there is increased awareness of the importance of data to the overall customer experience, with a recent report from IDC predicting that global spending on big data and business analytics (BDA) solutions will hit $215.7 billion by the end of 2021. If that is indeed the case, it is reasonable to assume that companies investing in BDA are taking a 360-degree view of their customer service and engagement strategies.

Collecting the Customer Insights You Need

Ten years ago, the consensus was that software was eating the world, but there is little doubt that data has taken its place.

Customer data is a tradable commodity that brands seek out, to not only understand what the customer wants at any point in time but also what works in terms of purchase behavior, needs, likes, dislikes and preferences. The ability to use this information to optimize the overall engagement experience itself is a key differentiator, albeit that the companies that do it well – Amazon, Apple, Starbucks, to name but three – are often using the same playbook.

There is an expectation that people will turn to the official customer service channels of brands to resolve an issue as a first option.

In recent years, this has become an increasingly convoluted area for companies to either manage or (in some cases) police. The use of various non-company resources to report, self-resolve or flag up a problem with a product has (no surprises here) become more popular, with third-party party channels – Google, YouTube and other social media channels, for example – all becoming a preferred means of customer engagement with a brand.

According to another recent Gartner report, this is not only generational but also marks a defined shift towards a so-called “voice of the customer” mentality amongst end users.

Millennials and Gen Z prefer to deal with a brand’s customer service offerings indirectly, while Baby Boomers and Generation X are more likely to go the more traditional route. This split is not a surprise, the younger generations have been digital natives since birth.

On the plus side, the digitalization of customer service offerings – and the 24/7 mentality that comes with the connected society – allows companies to mine a treasure trove of data that is generated directly from all these interactions, and that gives them the requisite insights into not only customer behavior but also where engagement happens. Often, it is customer services that offer up the most valuable data.

What is important to remember is that the data gleaned from effective and efficient customer service is not a product of digitalization. In the past, companies would turn to tools such as surveys, focus groups or market research to get the behavioral information they wanted. This element of a brand’s engagement with the consumer audience has been part of the product delivery lifecycle for decades, digital transformation has merely raised the bar as to how, when, and why they engage.

In fact, the shift from long-standing means of both assessing customer satisfaction and buying habits to a more tech-related approach can be traced to the simple fact that outreach is not only virtual but also conducted on a 24/7 basis. Customer insights don’t just happen, they need to be collected, that is where data and analytics comes into play. Depending on what information you want, your customer service function can be adjusted accordingly.

Trend analysis, for example, is based on geographic location, time framed and customer behavior patterns, which allows companies to predict the future based on what is happening now. Custom surveys will give you an idea of customer satisfaction. Market analysis – which should be the basis for any product launch – and focus groups provide more detailed insights into the customer journey, providing a quantitative and qualitative assessment of customer segmentation and purchasing patterns.

All of these are methods of gaining the insights you need have been a part of the awareness landscape for years. Where the digitalization of society really comes into its own is through the adoption of tools that are specific to the collection of the right data.

Social listening, for instance, is a consumer-focused AI technique that trawls social media for customer references of a product or service. To make this even more appealing, you get to track your competitors as well. And the increased adoption of predictive analytics does exactly what it says on the tin – studying historical and/or real-time data to predict what should happen in the future.

Without wishing to hammer home the point, data and analytics are the key to effective customer insights. Data is not only information, but a valuable resource (companies like Facebook and Amazon would not be the tech behemoths that they are without it) and companies that are serious about improving the overall customer service experience should consider the following questions:

• What are the best tools for the job?
• How important is big data and business analytics to your overall optimization strategy?
• What techniques to leverage customer information have been successful and what have not?
• Do you have a customer insight strategy?

Right Questions = Relevant Answers

Customer service is the platform on which a brand’s reputation and continued consumer awareness is built on. Good products may draw an interested person in, but it is the overall customer experience (CX) that companies must pay attention to.

The practice of using CX analytics, for example, is showing increased adoption rates. This is targeted information that can allow for the visualization of the customer journey, the identification of patterns or trends, access customer feedback, improve service and eliminate guesswork

Although these tools are useful in revealing the questions and answers, it is important to understand that the data provided must lead to actionable insights. If you are not reading the data right, you will not get the insights that you need.

Customer feedback, for instance, should be the building blocks for a better overall journey. Companies that don’t take all the different or potential experiences into account when designing a product are missing an opportunity for continuous improvement.

By the same token, if a decision maker does not replicate the digital journey as a “customer,” the nuances and chokepoints of how an end user interacts with a business might not be revealed – a cumbersome purchasing process or a poorly-designed website could be forcing people to cut the engagement short … or worse.

For those reasons alone, being able to leverage all the digital information that is available remains a key part of business optimization strategy. In other words, data and analytics can (according to a Salesforce blog) provide insights that will allow you to pinpoint opportunities and critical issues, stay on top of customer satisfaction, build communities, understand workloads and improve service efficiencies.

Insights should be available to companies simply by asking the right questions at the right time. These would include knowing what you want for the business, where and how you are gathering data, the allocation of responsibility for customer insights (and service), effective outreach to a target audience and the mapping of the customer journey itself.

It’s not rocket science but the answers to these questions will determine the data-driven roadmap that you would do well to follow.

Data and Analytics Matter

Getting the right blend of customer experience and customer service remains a challenge for companies of all sizes. And brands are acutely aware that the digitalization of society has ushered in business workflows that draw heavily from proactive and not reactive attitudes.

Customer satisfaction is both a pre-requisite and a barometer for success, with brand loyalty often dependent on how effective the overall experience is. The establishment of global village means that data is collected at every digital touchpoint, so it makes sense that the companies that know how to use that information effectively will be the ones that come out on top.

Long gone are the days when the only way for a consumer to register their happiness/displeasure was through a visit to a physical location or a phone call. Data collection has always been part of the customer journey and product lifecycle, but technology has made it easier for decision makers to see what they are doing right (or wrong). This information is even more relevant as the business community becomes ever more dependent on digital channels to deliver the customer service that people expect.

Data and analytics eliminate the guesswork across the full spectrum of the experience, strengthening the bond between customer and brand. Even the simplest of data collection projects can provide companies with the insights that they need to move forward. And that can be the differentiator between the brands that succeed and the ones that are left in their wake.

Customer service has always been a key component of how brands engage, and the digital world has merely raised the bar. Apexon’s digital engineers are well-equipped to solve the toughest challenges that companies face, so don’t delay and reach out to us to find how we can help alleviate your pain points.

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