Last week I wrote a blog post about “The blueprint for building a customer-centric organization”. This got so much internal and external feedback, that I thought I’d explain it a bit more.

The claim in the post that raised eyebrows was the following:

How come? Of course everyone should strive to become customer-centric – right? Right?

Understanding the CX Maturity Matrix

Before we tackle that question, let’s quickly go over the CX Maturity Matrix. It’s a framework that outlines five levels of growth. Starting with ‘Reactive’, where customer interactions are hit-or-miss and feedback is rare. And ends in ‘Customer-centric’, where everything the organization does, revolves around customer experience (CX). Moving from one level to the next requires better tools and tech, but also a deeper dedication from the whole organization to putting customers first.

Why customer centricity isn’t for everyone. 

The High Stakes of High CX Maturity

Levelling up your CX Maturity is no small feat. It requires substantial investments in technology, human resources, and perhaps most challenging of all, a shift in company culture. The allure of reaching the ‘Customer-centric’ status is undeniable. But is it viable?

For many companies, particularly those with limited resources or those in niche markets, the investment needed to meet and sustain this level may not align with their strategic or financial realities.

Thus the decision to pursue high CX maturity should not be made in isolation, but should instead be a reflection of a company’s overarching strategic objectives. In scenarios where a business enjoys a monopolistic advantage in a niche sector, or where its business model is product-based or commoditised, the necessity for a high level of CX maturity may not be as pressing.

However, it’s crucial to keep your eyes open; a significant CX gap can become a foothold for competitors.

The Monopoly Exception and the Dynamics of Competition

In particular, niche monopolies present an intriguing case. Such companies might operate quite successfully without the need for intense CX focus, at least in the short term. Yet, this does not warrant complacency. Markets are dynamic, and today’s monopoly could become tomorrow’s battleground for customer loyalty. Thus, even in monopolistic scenarios, a baseline level of CX that meets customer expectations is indispensable.

Adapting to the Flow of Business and CX Needs

The CX journey is far from linear. Companies might find themselves moving back and forth across the maturity spectrum as their strategic priorities evolve. Flexibility and adaptability in CX strategy allow businesses to respond to market changes, technological advancements, and shifts in customer behavior.

Some common scenarios where a need for a larger shift might come:

• New or updated business strategy
• New senior leadership
• Sales lagging
• Sales flying
• Churn increasing
• New funding round
• A sudden shift in tech (think e.g. AI)
• Market dynamics change with a new player coming in or old one leaving

As you can see, there are both internal and external forces that might push you towards rethinking your CX Strategy. There is no shame in moving up, down or even staying where you are. Your business strategy dictates your CX strategy, not the other way around.

Toward a Balanced CX Strategy

In conclusion, while the pursuit of CX excellence is commendable, it is not for everyone. Companies must carefully examine their strategic goals, market position, and resource capabilities to determine their optimal position on the CX Maturity Matrix. A balanced, strategic approach to CX — one that aligns with the company’s unique circumstances and aspirations — is key to fostering meaningful customer relationships and achieving sustainable success.

Engage and Reflect

As we wrap this up, I invite you to reflect on your company’s CX journey. Where does your business currently stand on the CX Maturity Matrix, and more importantly, where does it aim to be? Feel free to contact one of our CX experts to discuss your unique situation and how we can help you achieve your goals.

I was reminded of the importance of the customer experience while watching this video of Steve Jobs at Apple’s Worldwide Developers Conference in 1997. In the video, Jobs appears to be responding to an attack but is actually doing something much more interesting. He thinks carefully and makes a critical philosophical point about his – and Apple’s – approach to creating new products.

It’s five minutes long and worth watching ..

Here are the juicy bits ….

Question: I would like, for example, for you to express in clear terms how, say java, in any of it’s incarnations, addresses the idea (inaudible). And when you’re finished with that, perhaps you could tell us what you personally have been doing for the last 7 years.

Steve: You know, you can please some of the people some of the time, but…. One of the hardest things when you’re trying to effect change is that people like this gentleman are right in some areas.

The hardest thing is: how does that fit in to a cohesive, larger vision, that’s going to allow you to sell 8 billion dollars, 10 billion dollars of product a year? And, one of the things I’ve always found is that you’ve got to start with the customer experience and work backwards for the technology. You can’t start with the technology and try to figure out where you’re going to try to sell it. And I made this mistake probably more than anybody else in this room. And I got the scar tissue to prove it. And I know that it’s the case.

And as we have tried to come up with a strategy and a vision for Apple, it started with “What incredible benefits can we give to the customer? Where can we take the customer?” Not starting with “Let’s sit down with the engineers and figure out what awesome technology we have and then how are we going to market that?” And I think that’s the right path to take.

Apple embodies this philosophy throughout the customer lifecycle, including being exposed to the product, buying the product, implementing the product, upgrading the product, and getting help with the product. It is Apple’s competitive advantage.

Another leading figure in the tech industry known for their forward-thinking approach to customer-centricity is Satya Nadella, CEO of Microsoft. He has been instrumental in transforming Microsoft’s culture and products around the concept of empathy and understanding user needs. He summarizes it nicely:

“Empathy makes us better innovators. If you look at the most successful products we have created, it comes from us having a deep sense of empathy about the unmet needs of our customers.”

Some companies embody this philosophy deeply in their culture. Slack, Spotify, and Tesla immediately come to mind. The entrepreneurs running these companies are completely obsessed with the consumer experience of their products. At Surveypal we strongly believe that real innovation is driven by consumers, not by large enterprises. This means that if you are working on a product or service, you must also be obsessed with the customer experience.

In an era where consumer expectations are at an all-time high, the question isn’t whether delivering exceptional customer experiences (CX) is essential. It’s how your organization can master this to stand out in today’s competitive landscape. 

But what does the path to genuine customer-centricity look like? And is reaching the ultimate level of customer focus the right goal for every company?

We created a CX Maturity Matrix to serve as a roadmap, outlining five distinct levels of maturity that companies meet on their CX journey. By honestly evaluating where your organization currently stands, you can set realistic goals for continuous improvement. However, achieving higher levels of CX maturity demands more than just adopting the latest tools or technologies. It requires a shift in mindset and a longer-term commitment to customer-centricity. And it should align with every aspect of your business strategy and operations.

The five levels of the CX Maturity Matrix:

1. Reactive: Customer interactions are ad-hoc and transactional. Feedback is infrequent and rarely utilized for improvements. VoC efforts are non-existent or manual with no clear ownership.
   
2. Tactical: Basic CX practices like collecting feedback exist but are siloed within departments. Efforts to address issues are tactical versus strategic. VoC is owned by a single team.
   
3. Strategic: Multiple departments align on CX, using insights to improve specific functions. Continuous feedback captures quantitative and qualitative data. VoC insights are reactively shared across the organization.
   
4. Foundational: A holistic view guides CX initiatives through the customer journey. Predictive capabilities emerge from integrated feedback systems capturing multi-dimensional data. Dedicated CX teams systematically operationalize insights.
   
5. Customer-centric: CX is a core strategic driver across the organization. Deeply embedded customer insights from integrated data to optimize individualized experiences. Cross-functional roles ensure end-to-end accountability.

The Non-Linear Path of CX Transformation

While this CX Maturity Matrix provides a useful framework, it’s important to recognize that the journey is not always linear. As an organization’s business strategy shifts, it may need to move between maturity stages to realign its customer experience approach. Goals and priorities can change, requiring flexibility to adapt CX efforts accordingly. In both directions.

Furthermore, achieving the “Customer-centric” level is not and should not be the ultimate goal for every company. This level of maturity demands significant investments in resources, technology, and cultural transformation. Organizations must carefully evaluate if such comprehensive customer-centricity aligns with their overall strategy and is viable for their specific context.

The Core Challenge: Cultural Shift Towards Customer-Centricity

Regardless of the desired maturity level, the biggest challenge doesn’t lie in implementing tools or policies. It lies in fostering a cultural shift toward customer-centricity. Tools and technology can act as a catalyst, but not the sole driver.

This transformation requires commitment from senior leadership to embed CX principles into the organization’s DNA. It’s a continuous journey of empowering employees, breaking down silos, and ensuring customer insights are consistently used for decision-making across functions.

Attempting to take shortcuts will likely undermine the entire effort. Achieving true CX excellence takes time, grit, and a willingness to adapt strategies as needed. Lasting changes demand a realignment of culture, processes, and mindsets throughout the company.

Conclusion: Embracing the CX Journey

Understanding your current level of CX Maturity and where you aspire to be is just the start. Setting achievable goals, and embracing the tough yet fulfilling journey of strategic change and cultural shift is key for companies. This way, they can create their unique route to providing top-notch customer experiences. Successful companies will build strong relationships with their customers. They will not only meet but also surpass expectations, leading to lasting success.

Have you ever felt overwhelmed by the sheer volume of data in Zendesk, unsure of what to make of it? You’re not alone. 

In most software platforms, data is analyzed through various views, such as brand, contact reason, channel, team, or agent, especially in the case of Zendesk. While these views provide insights, they often miss a crucial component for addressing customer friction – Context.

Without context, gaining a holistic understanding of customer experiences becomes challenging.

Wait a minute! Sebastian, isn’t there already several software providers doing NLP (Natural language processing) to auto tag incoming tickets?

Yes, there is, but not in the way we do it. We put our own spin on it designed specifically for Zendesk users.

Our innovative approach integrates contextual topic analysis with Zendesk metrics, offering a comprehensive view of customer outreach and pinpointing the exact areas of friction. It’s one thing to know what is talked about, its a whole other thing to know the impact it causes.

Understanding the metrics and their impact on resourcing

Having a clear understanding of where resources are being allocated is essential, especially when it comes to customer support.

The first four metrics in the Conversations view provide a snapshot into this: for any specified time frame, they answer crucial questions such as how many tickets were created, the total time spent on them, the estimated costs, and the average price we’re paying per ticket on a particular topic. These metrics not only offer a quantitative perspective but also hint towards qualitative improvements.

Whether it’s identifying product issues or process bottlenecks, the data provides a clear picture of the financial implications. For instance, it quantifies the cost of not addressing a product flaw or the potential savings from rectifying a process inefficiency.

In discussions and decision-making, data-driven insights always hold an edge over mere hunches, ensuring that voices are not just heard but also heeded.

Evaluating process and knowledge gaps + automation opportunities

The metrics of average replies and assignees serve as a barometer for the efficiency and effectiveness of our ticket resolution process. Essentially, they shed light on our capability to address and resolve issues associated with any given topic.

A high average in these metrics often signals underlying challenges, be it in our processes or potential knowledge gaps among our agents. For instance, if a ticket frequently gets escalated from one agent to another, or even a third, it prompts us to question the efficiency of our routing process. Are there inefficiencies in how we’re directing tickets? Might there be knowledge gaps that need addressing? Or perhaps, are there restrictive policies hindering our agents from resolving issues promptly?

Conversely, if the metrics reveal low averages, it paints a different picture. When tickets are consistently resolved with minimal replies and non-existent agent handovers, it indicates a streamlined and effective resolution process. Such efficiency often hints potential for automation.

If we can solve a majority of tickets with just one reply, it’s a clear indicator that these processes are ready for automation. Implementing automated solutions in these areas can further optimize the workflow, reducing some of the workload from our agents and ensuring even swifter resolutions for our customers.

The power of reopen rates

The reopen rate, often overshadowed by other metrics, serves as a crucial indicator of our effectiveness in addressing customer concerns. A high reopen rate for a particular topic suggests that our solutions may not be meeting customer expectations or fully resolving their issues. This not only impacts customer satisfaction but also creates a cascading effect on our support system.

For instance, if out of 679 conversations, 5% were reopened, that translates to an additional 33 tickets. While this might seem manageable, imagine the strain on resources when the rate escalates to 20%. Such a surge in reopens means an added flow of tickets that ideally shouldn’t exist, further straining our agents and potentially compromising the quality of support.

Gauging customer sentiment

While operational metrics provide insights into performance, metrics like CSAT (Customer Satisfaction Score), NPS (Net Promoter Score), CES (Customer Effort Score), and FCR (First Contact Resolution) offer a direct window into the customer’s perception post-service. Integrating these metrics with specific topics allows us to pinpoint not only our strengths but also areas of potential concern.

Especially in scenarios with high ticket volumes, such granularity becomes invaluable. It enables us to identify and address specific friction points in the service experience, ensuring that we’re not just meeting operational benchmarks but also consistently aligning with customer expectations and sentiments.

Predictive performance scoring

The predictive performance score, though still in beta testing, aims to address one fundamental question: if every customer was to rate us, what would that collective score look like?

Often, feedback is limited to a small subset of interactions, leading to the question of its representativeness for the broader customer base. Our current approach looks at a combination of over 10 distinct metrics, focusing particularly on the performance aspects of each ticket. By modeling this against your unique dataset, we generate a score that offers a more holistic and representative view of customer experience.

Summarizing it all

Making sense of your Zendesk data can feel hard and chaotic. Yet, with ‘Conversations’, we’ve crafted a solution that brings calm to the chaos. By emphasizing context, we ensure that every metric, every feedback, and every interaction is seen through a lens that truly understands the customer. It’s not just about numbers; it’s about the stories they tell.

Your Next Step

Feeling intrigued by the potential of ‘Conversations’? Why not give it a go? Experience firsthand the synergy of contextual topic analysis and Zendesk metrics.

Request a free trial and discover the difference context can make in your customer insights journey.

I joined Surveypal as a Sales Manager in October 2022, and it has proven to be a highly rewarding experience. Right from the start, I was impressed by the company’s straightforward approach to recruitment, which resonated with my own values. I particularly appreciated the transparency and openness surrounding the role, making me feel confident in my decision to join.

During the onboarding process I was warmly welcomed by a friendly and supportive team. Their willingness to lend a helping hand made the transition into the organization smooth, allowing me to feel valued and motivated from day one.

Something that truly stands out at Surveypal is the emphasis on collaboration. The team’s open communication fosters an environment of trust and camaraderie. I am grateful for the level of trust and autonomy given to me, enabling me to take ownership of my work and contribute my ideas to the company’s growth.

As a team, we celebrate victories together and tackle challenges as a united front, learning from mistakes and setbacks along the way.

While my journey at Surveypal has been predominantly positive, like in any other workplace, we every now and then encounter challenges. However, the support and encouragement I have received from my colleagues have helped me face obstacles head-on, leading to personal and professional growth.

My experience as a Sales Manager at Surveypal is a fulfilling journey of growth, team spirit, and overcoming challenges. I am excited to continue on this journey and look forward to what the future holds for both myself and the company.

Outside of work, I find solace and inspiration in various hobbies. Hiking allows me to connect with nature, art exhibitions ignite my creativity and appreciation for human expression, and yoga keeps me centered and mindful. Moreover, my passion for traveling has led me to explore 25 countries, embracing diverse cultures and broadening my perspective on life.

Customer service can often seem like a ‘black box’—a complex, intricate part of your business that demands a deep dive to understand. It’s not only a crucial touchpoint with your customers, but also a gold mine of untapped data. In this blog post, we will simplify these complexities and highlight how you can transform customer service into a strategic advantage.

Box 1: Navigating the Operations Maze

High-volume companies know customer service to be a fast-paced world, bustling with immediate tasks and metrics. From the top levels, it may seem overwhelming and distant, a maze of daily operations. Yet, remember, it’s often the first (and sometimes only) interaction your customers have with your business.

Customer service is more than just extinguishing fires—it’s an opportunity to build lasting relationships and shape the customer experience. Start by acknowledging its dual role: immediate problem-solving and strategic relationship building. Integrate this understanding into your broader business strategy.

Promote a culture of sharing customer service experiences and insights across all departments. Celebrating instances where customer service teams have enhanced customer relationships can inspire a mindset focused on elevating the overall customer experience.

To quantify the impact, convert customer service outcomes into business metrics like CSAT scores, FCR rates, and customer retention rates. These numbers not only represent your service performance but also showcase their direct influence on business success. For instance, improved CSAT can increase loyalty and repeat business, higher FCR can lower operational costs, and better retention rates can boost customer lifetime value.

Box 2: Harnessing Hidden Data

The second ‘black box’ is a sea of underutilized data. Just as an airplane’s black box records every tiny detail of a flight, customer service data is a treasure trove of insights. These are more than just feedback from structured mechanisms like surveys—they are subtle behavioral signals from your customers.

It’s time to value passive data. Insights from all customer interactions, like the frequency and types of issues customers encounter, and the sentiments expressed during the resolution process, can offer a comprehensive understanding of your service’s effectiveness.

Leverage analytical tools to transform this data into actionable insights. Identify patterns and trends and convert them into metrics such as average resolution time, sentiment scores, and churn prediction. When these are presented in terms of their financial implications—potential revenue losses or gains—they become powerful tools for strategic decision-making.

The Road Ahead

Customer service, once seen as a complex set of black boxes, can actually be a significant source of strategic insights. Recognize its dual role—both operational and strategic—and utilize both active and passive customer data to unlock its potential.

By turning these overlooked aspects into clear, quantifiable business metrics, we redefine the role of customer service in the organization. This shift not only paves the way for exceeding customer expectations and fostering strong relationships but also steers your business towards growth.

Now it’s your turn to unbox these treasures in your organization. Step back, observe, and listen—let your customers guide you towards continuous improvement and success.

As digital technologies transform the world we live in, personal interactions with customers are becoming increasingly rare. This makes it all the more critical to capture and understand every customer voice. But when faced with a mountain of unstructured data, how can companies ensure they’re not missing out on valuable insights that could drive business growth and customer satisfaction?

This is where Surveypal comes into play.

For the past 17+ years, Surveypal has been evolving beyond a feedback management pioneer towards the forefront of customer intelligence. But how exactly do we make that happen?

We combine unstructured data from customer service tickets with structured performance metrics to paint a complete, accurate picture of what’s really going on in customer facing departments. When something meaningful happens, we make sure companies don’t just know about it, they understand the why behind it.

This is the next step in the road towards customer intelligence and a powerful way to make data, insights and most importantly voices, come alive and be heard beyond departmental silos.

However, we believe that understanding is just the beginning – the real power lies in action. Thus, Surveypal helps customer service and experience team leaders turn their high-volume contact center data into insights, and insights into data-driven decisions. As one of our customers recently shared, “With Surveypal, we get great insights at a glance and can dig deeper than ever before.”

But why is this important? And why now?

We’re living in an era where survey response rates are declining. Yet, support tickets are filled with valuable real-time and historical information about customer concerns and pain points. Traditional methods of capturing the Voice of the Customer (VoC) have proven tedious due to the sheer volume of unstructured data, resulting in searching through generic tags and and ticket fields to find meaning.

Typically, these tags and contact reasons are then translated into word clouds or exported to spreadsheets for a time-consuming data massage session to get some form of idea of the magnitude of issues. This approach, however, fails to deliver real value reducing many VoC programs from a “must-have” to a “nice-to-have”.

That’s what makes Surveypal different. We believe there is value in every single customer voice – surveyed or not. We’re not just about delivering satisfaction scores or core metrics. We enable companies to understand both the surveyed and the silent customers, using these insights to drive meaningful change. At scale.

The rise of AI from a niche technology available to the few and canny, towards becoming accessible to nearly anyone, has provided companies with an opportunity to make sense of their customer data in ways never before possible. Harnessing this computational power, Surveypal can help companies turn structured and unstructured data into actually actionable insights, ensuring no customer voice goes unheard and no opportunity for improvement overlooked.

Why Surveypal then?

At Surveypal, we stand on three pillars – inspiring collaboration, encouraging valuable feedback, and fostering a growth mindset.

Translated into our promise to our customers

• We aim to break down organizational silos and combine performance and quality data to help departments collaborate towards better customer experiences.
• We provide valuable insights on the data, may it be structured or unstructured.
• We are your partner of success to help create value for your customers.

As a leader, you need tools that allow you to validate your gut feeling and enable you to share valuable information across the organization.

Skip the vague “We have constant request from customers complaining about feature X”. And confidently go to something more concrete; “We spent 56 hours last month assisting through the account verification that should be automatic. This single complaint came up 124 times and costed us roughly 2765€ plus results in poor customer experience that costs us additional churn”

See the difference when going from vagueness for concrete values? The second one makes you heard across departments.

Ready to listen better?

Discover the power of listening better, understanding deeper and acting decisively with Surveypal. Together, we can amplify your insights and take action to ensure a future where every customer voice is recognized, understood, and valued.

Customer support is integral to business success. Customers expect elevated experiences when interacting with a brand, so they readily do business and even recommend brands that meet their expectations.

Text analysis is one technique helping brands meet customers’ expectations in today’s business environment. It allows you to listen to everyone wherever they are, giving you critical feedback to act on to improve the customer experience and the overall quality of your customer service. 

How do you implement text analysis for customer support? 

What is Text Analysis?

Text Analysis is a machine-learning technique that automatically extracts actionable insights from unstructured text. It is about using computer systems to digest online data and documents to extract meaningful information you can respond to and act on.

Text Analysis helps you to efficiently process multiple text-based sources (like documents, product reviews, service desk tickets, emails, social media content, etc.) as a human would.

Gone are the days when customers were giving feedback only via surveys.

In today’s business environment, customers will reach you via email or other approved channels and discuss you on review platforms and social media.

Being everywhere simultaneously to listen to what your customers may have to say and take on issues that may come up is next to impossible.

But with Text Analysis, you can go through millions of text sources, using specific keywords such as names or company information to identify when a discussion should concern you. For example, you can monitor brand mentions on social media and get real-time alerts when anyone mentions your brand.

You can, also, automatically sort and classify the information extracted from text data to identify sentiments, patterns, relationships, and other actionable insights. Or, categorize customer sentiment into positive or negative and further separate issues into specific topics, such as order issues, service issues, etc.

Thus, Text Analysis helps you turn unstructured data into structured data, so you’ll know what your customers need.

The different types of text analysis techniques 

There are different types of text analysis techniques, as follows:

Sentiment Analysis

Sentiment Analysis is about understanding the emotions your customers express about your brand or product/service experience. 

Sentiment analysis uses Natural Language Processing to analyze customer sentiments from customer interactions across a variety of sources. 

In its simplest forms, it tracks brand mentions, extracts customer sentiment, classifies the sentiment (as positive, negative, or neutral), and scores the sentiment to show you the real value of customers’ emotions (“the product is very good” will have a higher score than “the product is good”).

Tracking your customers’ emotions helps you make data-driven decisions to improve customer experiences and maintain brand loyalty.

Topic Modeling

Topic modeling is the process of identifying related keywords in pieces of information extracted from textual sources and grouping them into topics or themes.

Topic modeling sorts the unstructured, heterogeneous data into themes. For example, a topic modeling algorithm analyzes specific mentions to identify whether the customer’s needs fall under product quality, pricing, orders, service, etc.

Text Classification 

Text classification is the process of assigning tags to text data based on pre-defined categories. The text classification algorithm relies on a set of tags to structure and summarize unstructured data extracted from the web.

For instance, if we have the statement, “I am happy with my XYZ hoodie. The quality of the material is so good,” the text classifier will take it as input, analyze it, and then use relevant tags such as “happy,” “product quality,” and “good” to summarize it. 

By reducing the extracted information into relevant tags, text classification makes it easy to classify them into topics, sentiments, etc.

Text Clustering 

Text clustering groups textual data so that similar texts are put together.

Through this process, the algorithm analyzes data and determines whether similar objects exist in the group. If if does detect similar objects, it will separate them into clusters. 

Named Entity Recognition

Named Entity Recognition (NER) is an NLP method that involves identifying and extracting specific information from unstructured textual sources.

Named entities are key subjects of textual data (such as company name, product name, locations, etc.) that concern your brand.

NER delivers key information that can help you improve customer experiences. For example, your support service can use it to detect when a customer leaves a review on a platform or mentions you on social media.

Text Analysis starts with named entity recognition. You must have a piece of information before you can analyze it to extract business insights. Named Entity Recognition scours the web and brings you information that concerns your brand.

Benefits of Using Text Analysis for Customer Service

Using Text Analysis for customer service benefits your brand in many ways, such as:

• Improved response times
• More accurate issue resolution
• Enhanced customer satisfaction
• Identifying customer sentiment
• Targetted responses to customer queries
• Pinpointing trends and pain points
• Driving product and service development

In the following paragraphs, we’ll dive a bit deeper into those benefits.

Improved Response Times

Text Analysis alerts you of customer comments/ complaints on different platforms in real time.

Thus, you can swiftly respond to customer issues and offer immediate solutions, reducing your average handle time.

More Accurate Issue Resolution

Text Analysis uses different algorithms to classify extracted information by topics and customer sentiments accurately. 

This helps you streamline the process and offer more accurate issue resolution. For example, classification helps your support agents understand the customer’s needs, while sentiment analysis helps them measure customers’ true emotions.

Enhanced Customer Satisfaction

Customer satisfaction depends on meeting customer expectations, and text analysis helps you meet or exceed customer expectations.

For example, 12% of Americans rate “lack of speed” as their number one service frustration. Text analysis tracks textual data for customer complaints in real-time, allowing you to offer immediate solutions and have happy customers.

Identifying Customer Sentiment 

Text analysis helps you determine how customers feel about the products and services you offer them and the experiences they receive from your brand.

Effective text analysis does not just classify customer sentiments into negative, neutral, and positive. But it scores each sentiment, helping you understand the strength of the customer’s emotions and respond appropriately.

For example, consider two pieces of customer feedback, “I am not happy with the ABC model” and “I am so angry that you guys shipped me a piece of shit as the new ABC model.”

While they are both negative sentiments, the “piece of shit” comment shows an angrier customer (and will have a weightier score).

Thus, sentiment analysis helps your agents know the type of customers they’re dealing with, how to prioritize tickets, etc.

Developing Targeted Responses

Text Analysis helps you to structure qualitative data, pointing you to the real issue in customer complaints, giving you a glimpse of the type of customer, etc. This helps you provide tailored responses addressing customers’ concerns and emotions. 

Identifying Trends and Pain Points

When you track customers’ interactions on review platforms and social media, you can spot common pain points and issues before they begin trending.

Text Analysis dives deep into information extracted from textual sources and analyzes the said and the unsaid to understand what a customer really wants or expects. This can also help you predict customer behavior and be ready to meet them, increasing customer satisfaction. 

Drive Product and Service Development 

The first step to solving a problem is identifying it.

Understanding how your customers feel about your product and service helps you take steps to improve your offerings.

For example, consider that your analysis shows dissatisfaction with an aspect of your product’s quality. Then you know that to provide an excellent customer experience, you must enhance or add features to improve that quality aspect.

How to Implement Text Analysis: a Step-by-Step Guide

Many text analysis platforms have easy-to-use interfaces, allowing you to run your data and visualize results without adding a single line of code.

The simple steps for using text analysis software include: 

• Choose a template. Text analytics tools offer different templates for running analysis. The first step is to choose an appropriate template.  
• Upload your data. The next step is to upload your data. Tools generally accept a CSV file.
• Match your data to the right fields. 
• Name your workflow: Set a name for your workflow.
• Run your data. The tool automatically processes your data.
• Visualize your data. The tool presents your analytics result using easy-to-understand dashboards. You can then visualize the result to spot trends, patterns, and other actionable insights.

How to Implement Text Analytics for Customer Support

No matter the type or size of your business, you can implement text analytics to improve customer service productivity. Implementing text analytics for customer support requires the following:

Data Collection

The first step is to collect customer support data, including chat or chat transcripts, email communications, social media interactions, and customer feedback surveys.

Collecting a significant amount of data is important to ensure accurate analysis. So, gather data from internal and external sources.

• Internal data are those internal to the business that you generate every day. Sources include emails, chats, online support tickets, etc. You can export it from your platform as a CSV or Excel file or connect to an API to retrieve it directly.
• External data is data about your brand all over from all over the web. Sources include news articles, online reviews, online forums, and social media posts. You may need web scraping tools to collect external data. Many of these platforms have their own APIs that you can use to search their archive and collect users’ comments.

Data Preparation

Once the data has been collected, it needs to be prepared for analysis. This involves cleaning the data, removing irrelevant information, and ensuring it is in an easily analyzable format. 

Data preparation happens via several text analytics techniques, which include the following:

• Tokenization. Breaking the raw text into semantically meaningful parts. For example, the text “Their gadgets are good” is tokenized into: “their,” “gadgets,” “are,” “good.”
• Part-of-speech tagging. Attach grammatical tags to the tokenized text. For example, the PoS tags for the tokens above are, Their: Pronoun, Gadgets: Noun, Are: Verb, Good: Adjective.
• Parsing. Establish a meaningful connection between the tokenized words (using the grammar of the language the text is written in) to help the text analysis software visualize the relationship between words.
• Lemmatization. Simplify words into their dictionary form by removing affixes (suffixes, prefixes, etc.).
• Stop-word removal. Remove words with little or no semantic context (such as a, and, for, etc.).

However, your text analytics tool handles most of the data preparation automatically, and you won’t even notice it happening. 

Text Analytics Tools

Next, you should choose a text analytics tool that can analyze customer support data.

Any decent tool should allow the detection of named entities from text, grouping content into themes, and extracting meaning from text.

Good tools should offer pre-trained text analysis models and also allow you to create custom models for analyzing text and extracting valuable insights.

Text Analytics Techniques

Always choose the text analytics techniques best suited to your business needs.

As mentioned earlier, these techniques may include sentiment analysis, topic modeling, named entity recognition, text classification, and text clustering.

Implementation

After selecting the appropriate text analytics tools and techniques, the fun part begins – the analysis process.

This involves running the data through the text analytics tool and applying the selected techniques to gain insights into service desk interactions, open-ended customer feedback, brand mentions, reviews, etc. 

This process will enable you to categorize keywords and assign sentiments.

Analysis and Insights

Once the analysis is complete, you can begin to analyze the results and gain insights from your customer support conversations. This can involve identifying trends, common issues, and customer sentiment.

Visualization tools can help you turn text analysis results into easier-to-understand formats. They present analytics results in striking dashboards (graphs, charts, and other visual elements), making it easier to understand your results.

Act on Insights 

Insights gained from text analytics can help extract meaning from customer intractions and make informed decisions to improve customer support. But any success depends on taking actionable steps.

For example, if analytics show that customers complain of slow response time, you should implement strategies to improve response times.

Other insight-driven actions may include addressing common issues, updated the content of your knowledge base, and developing targeted responses.

Challenges of Using Text Analytics for Customer Support 

Using Text Analytics for customer support comes with challenges relating to data quality, data complexity, interoperability, and data privacy.

Data quality

Text data can be incomplete, ambiguous, and full of noise. That is, the data often contain spelling errors, abbreviations, slang, and ambiguous words, so understanding the data can be challenging. 

For example, consider the customer remark, “imo, ur delivery time of 2 weeks does not make sense”

The Text Analytics tool will have difficulty understanding that

• imo = in my opinion
• ur = your
• does not make sense = too long.

Data cleaning and preprocessing helps you overcome data quality issues to successfully implement text analytics by removing noise, errors, and irrelevant information.

It also helps clear ambiguity and standardizes extracted data. Some data-cleaning techniques for making raw data easier to understand include tokenization, lemmatization/stemming, stop-word removal, and encoding.

Data Complexity

Customer feedback/complaints and other data that will interest your support teams may reside in source systems not created with analysis in mind, making extracting the data or textual analysis challenging.

For example, unstructured data can come in types or formats such as video, audio, and images. Extracting such data for textual analysis can burden the performance of the source system and take a long time. Integrating and combining textual data with other data types can also be difficult.

Data transformation and representation helps overcome data complexity issues, making it easier to combine different data types for analysis.

You can do data transformation using vectorization, embedding, and dimensionality reduction.

Interoperability

Your text analytics tool becomes part of your data infrastructure, so having software that easily integrates with your existing systems makes for seamless data consumption. 

A text analytics platform incompatible with your data infrastructure can make data transfer challenging, whether transferring raw data to the tool for processing or transferring analytics results to your data system to drive action.

Overcoming interoperability issues requires choosing a text analytics tool that works well with your data infrastructure. 

Privacy Concerns

Some privacy laws prohibit the disclosure of an individual’s private records without their consent. Since unstructured data may contain personally identifiable information, you risk breaching privacy laws when you do text analysis and index documents in search solutions.

Overcoming privacy concerns 

PII redaction is a technique that can help you overcome privacy challenges and implement text analysis successfully without breaching privacy laws.

PII redaction automatically detects and removes personally identifiable information (such as names, contact details, addresses, etc.) from your data. Thus, the individual’s privacy is protected even when you index documents in search solutions.

Wrapping up

Text analytics enables you to dive deep into your data to identify the root cause of your performance issues and find solutions that prevent them from escalating and impacting customer satisfaction.

Using Text Analytics helps your business in many ways, including improving response time, developing targeted responses, providing more accurate issue resolution, identifying customer sentiments, enhancing customer satisfaction, identifying trends, and driving product improvement. 

SurveyPal is a trusted tool for businesses implementing text analysis to improve support performance and quality. It delivers automatic text analytics insights allowing you to focus on your customers.

Poor customer service has a devastating impact on your company’s bottom line. The cost of bad customer service is significantly more than just lost sales or angry customers. It affects your company’s reputation, employee morale, and even threatens its long-term viability.

68% of consumers say they’ll pay for products and services from a company that offers good customer service experiences. 93% say they’re likely to make repeat purchases from a business that provides excellent customer service. So, why are so many businesses failing to provide excellent customer support? What is the actual cost of poor customer service?

Let’s explore this critical issue and discover why every business should prioritize delivering exceptional customer service.

What are the Causes of Poor Customer Service?

There are several potential reasons the support in your company might be lacking:

• Inadequate training: Your customer service representatives have not received proper training on how to handle different inquiries or how to use the technology and software needed to do their jobs effectively.
• Poor communication: Communication breakdowns between your support team and customers are resulting in misunderstandings and frustrations.
• High turnover rates: Because agent churn is high, your remaining inexperienced and overwhelmed customer service representatives cannot provide quality service.
• Insufficient resources: A lack of resources, including staffing, technology, and tools, is making it difficult for your customer service representatives to provide timely and effective solutions to customers.
• Unresponsive management: When management is unresponsive to customer complaints or fails to address issues within the contact center, it leads to a hostile work environment and poor customer service.
• Inflexible policies: Your customer service representatives are limited by rigid policies that prevent them from providing satisfactory solutions to customers.

Examples of Bad Customer Service

Customers have strong preconceived perceptions of the support experience they should get from a company. There are many ways you can disappoint them:

• Long hold times: When customers call a call center, they expect to be connected to a representative quickly. If they’re forced to wait on hold for an extended period, it’s frustrating and makes them feel undervalued.
• Unhelpful representatives: If the representative on the other end of the line is unhelpful, rude, or dismissive, customers feel angry and unheard.
• Transfers and escalations: When customers are transferred from one representative to another or escalated to a supervisor, it’s confusing and tiresome, especially if they have to repeat themselves several times.
• No follow up: If a representative promises to follow up with a customer or resolve an issue but fails to do so, it will erode trust and confidence in the company.
• Lack of empathy: Customers want to feel understood and heard. When representatives lack empathy, it leads to a negative experience.
• Inconsistent service: When different representatives provide different information or resolutions, it creates confusion and frustration for customers.

What are the Consequences of Poor Customer Service?

The importance of customer satisfaction can’t be overstated. Bad customer service experiences have potent effects on your customer base and can significantly affect your company’s bottom line.

Disappointing customer experience

Customers who have a disappointing customer service experience are left feeling that your company doesn’t value them. These negative emotions will create a lasting impression and discourage them from doing business with your company again.

Poor customer service creates a sense of detachment between your customers and your company.

Around three out of every five consumers say good customer service is vital for them to feel loyalty to a brand. Customers who receive poor service will feel that the company doesn’t care about their needs, leading to a breakdown in trust and loyalty.

Negative word of mouth

Customers who have a bad customer service experience with your company are likely to share their experience with friends, family, and colleagues, both online and offline.

Customers are more likely to share their negative experiences than their positive ones. Negative experiences are emotionally charged and create a lasting impression. Promotors or your brand have a customer lifetime value between six and 14 times higher than a detractor.

Bad reviews

When customers experience poor service, they are likely to feel frustrated, angry, and let down. They may express their dissatisfaction through online reviews, highlighting the issues they encountered.

Negative reviews have a ripple effect, as they will reduce the number of customers willing to engage with your company.

Customers often turn to online reviews when making purchasing decisions, and a company with many negative reviews is seen as unreliable and unprofessional.

Bad reviews are hard to address, as they quickly spread online and are seen by a wide audience.

Low team morale

Poor customer service creates a negative working environment for agents. When customers are dissatisfied with the service they receive, they are more likely to express their frustrations to the agents, resulting in a hostile and stressful work environment.

Agents may feel unsupported, undervalued, and unappreciated. When agents cannot provide satisfactory service, they feel demotivated and demoralized. Agent engagement drops, increasing employee churn.

Loss of business

Bad customer service affects your current customers and your prospective customers.

Increasing customer retention rates by 5% through better customer service can see a 25-95% increase in profits. A bad customer experience can see an existing customer turning to your competitor who can offer better service.

Without a top notch help center, you won’t get new word-of-mouth business. Your company won’t rise to the top of review sites for your customer service, resulting in fewer views. Those who seek out your company will find negative reviews that turn them away.

Inefficient customer support has a massive snowball effect on your number of clients, and it’s vital to get customer service right.

Loss of profit

You’re leaving potential profit on the floor when you offer poor customer service experiences to customers. 89% of customers have stated they are likely to make a repeat purchase after a positive customer service experience.

Customers remember the service they receive much longer than the price they paid.

Spending more to improve your customer service while raising prices to accommodate will ultimately result in much better long-term profits for your company.

5 Ways to Improve Your Customer Service Experience

1. Reduce wait times

Analyzing call volume data will help you identify peak call times and adjust staffing levels accordingly. You can be sure enough representatives are available to handle the volume of calls and reduce wait times.

Technology such as interactive voice response (IVR) systems can answer common customer inquiries and reduce call volume. This will help to reduce wait times for customers who need to speak with a representative.

Offer self-service options such as FAQs, knowledge bases, and online resources so customers can get the information they need without calling your contact center. This will help to reduce call volume and wait times.

Streamline processes, such as call routing and call handling, so representatives can handle calls more efficiently and reduce customer wait times.

Monitor wait times to identify areas for improvement and adjust staffing levels or processes as needed.

2. Improve your first contact resolution rates

First Contact Resolution (FCR) is an essential metric for call centers as it measures the percentage of customer issues resolved during the first contact with the representative. Improve first contact resolution rates by:

• Providing adequate training: Coaching and training on problem-solving, active listening, and customer service helps agents handle customer issues more efficiently and effectively.
• Using data analysis: Analyzing call volume data helps you identify common customer issues and provides representatives with the information and resources needed to resolve the problems during the first contact.
• Implementing knowledge management systems: These systems provide representatives access to information and resources to quickly resolve customer issues.
• Performing call monitoring: Monitoring calls and providing feedback to representatives helps you find areas for improvement and training opportunities to improve FCR rates.
• Providing incentives: High FCR rate incentives will motivate agents to resolve customer issues during the first contact.
• Reading customer feedback: Soliciting customer feedback after their interactions with representatives helps you identify areas for improvement.

3. Make it easy for customers to reach a human agent

When customers call a contact center, it’s essential to provide explicit instructions that are easy to follow on how to reach a representative.

Interactive voice response (IVR) systems provide customers with the option to speak with a representative by selecting a specific option from the menu.

Offering customers the option to receive a call-back can help reduce wait times and ensure a shorter time before the customer speaks to a human.

Providing self-service options for common inquiries will reduce call volume and make it easier for customers to reach a human agent when needed. Offering multiple comminication channels such as email, social media, and chat also reduces call volume so customers who need to speak to a human can more easily get through.

4. Don’t force customers to repeat information multiple times

Customer relationship management (CRM) software stores customer information and previous interactions. Keep all customer information in a central system. This can help representatives quickly access customer information and avoid asking customers to repeat themselves.

If you’re delivering omnichannel customer service, ensure the CRM you use consolidates information on customer interactions from all channels, so agents can see all previous discussions regardless of how the customer contacted you in the past.

Recording calls can help representatives to review previous interactions and avoid asking customers to repeat themselves.

When possible, assigning a single representative to handle a customer’s issue from start to finish can help avoid repeating information. Smart IVR systems can route customers to the same agent each time if they’re available.

5. Don’t sacrifice quality for speed

While customer service performance metrics focusing on the speed and efficiency of calls are important, the quality of your customer service is more important.

Providing excellent customer service to drive customer satisfaction sometimes means spending more time on calls. Incentivizing quick calls often results in customers having to call multiple times to get a resolution, a terrible result for customer satisfaction. Ultimately, it’s more expensive than if the issue had been resolved on the first call.

Focusing solely on speed reflects poorly on your brand when customers don’t get the service they expect. They feel rushed and undervalued.

Employee satisfaction, motivation, and engagement will also drop if they feel they must rush to complete as many calls as possible. You will instead build better agent engagement by allowing them to deliver the best customer experience possible every time.

The Final Word

Poor customer service will decimate a business. We’ve looked at some of the most common types of bad customer service and how they can destroy your company if not addressed.

By taking steps such as reducing wait times, improving your first contact resolution rates, giving customers more options, and providing your agents the tools they need to deliver excellent customer service, your business will see immense gains from better customer satisfaction.

Until recently, customer service was a less pronounced aspect of business, and not much thought was put into making it a value-add. The thinking behind this was that customer support was only useful for receiving complaints from begrudged clients. 

Accordingly, CFOs considered it a cost function — hire customer service reps and fund their operations, and try to cut down such funding as much as possible while at it! 

Much like how people dashed the West for the California Gold Rush, CFOs are now striking gold with customer service as a revenue function — a key touchpoint where they can gather valuable data and insights on customers to identify new business opportunities. 

There’re different approaches to customer service that uncover value-add for companies looking to generate more revenue. Direct (tangible and explicit) value-adds would typically entail increased renewal rates, easy upsells, and customers that stick around for the long haul (increased average customer lifetime), as more sales trickle in. But it’s not just about the numbers. 

Value-add can also be tacit – indirect, or come in intangible forms gleaned through interaction and experience, making it unseen until shared. For instance, a delightful all-round customer service experience that differentiates a brand from the competition, thereby enticing prospects during marketing or sales; Or, more insight into customer needs to aid the product development (R&D) process. 

Whichever way this value comes to play, it looks like CFOs are readily riding this wave: TSIA’s The State of Customer Success 2020 reported that CFOs would rather fund customer success resources with direct monetization than throw resources at customer service. As such, monetization can also be a way to prove ROI. 

But maximizing the input from customer service to acquire more clients and expand profit margins is no walk in the park. It takes careful analysis, planning, and time.

Things to Consider Before Introducing the “M” Word

Thinking about monetizing your customer service? Bright idea! But before you take the plunge, there’re a few things to consider.

Introducing a new cost structure to your customers without proper preparation can lead to a spike in churn rates and put a lot of pressure on your team.

It’s crucial to make sure everyone is on the same page and fully trained to handle the transition. 

Depending on your product, process, and organization, you might need a new team structure or additional training for your monetization strategy. You may also need to develop new marketing communications, education initiatives, and onboarding processes to ease the transition.

Ultimately, to ensure long-term success, both your organization and your customers must be prepared. The key to success is finding the best monetization strategy for your business. But before you make that big decision, take a deep-dive analysis of your customers, their needs, and how you’re currently filling those needs (the value you bring them).

It’s important to remember that as your offering evolves, so does your customer. The last thing you want is to jump in with both feet and lose a chunk of customers. Get ahead of the game by gathering intelligence on your business, with an outside perspective for prospects looking in. 

Strategies for Monetizing Customer Service

One of the best things about customers’ insight is that it presents the most reliable, unbiased information about them. Your customer base is a storehouse of knowledge and feedback on your value proposition you can harness for a successful launch.

With that in mind, we’ve cherry-picked 8 of the best strategies to adopt to give you a headstart in successfully making a money-spinner of your customer service: 

Embrace Artificial Intelligence (AI)-powered tools  

The disruptive power of AI is finding its way into industries, and customer service is no exception. The stats echo this sentiment: This Gartner report finds that by 2020, customers will manage 85% of their relationships with companies without interacting with humans.

If you’re ready to make a big impact in the customer service industry, the secret to success is embracing technology, and AI is leading the charge.

High-class businesses are using AI to elevate their service to new heights, and if you want to make big bucks, you can’t afford to miss out on the AI revolution.

This entails using cutting-edge tools like Chatbots and Assist Agents to quickly respond to customers and provide immediate, on-demand assistance, also giving customers the option of self-service. 

Analysis firm Juniper Research found in a recent research that chatbots alone are expected to cut back on labor and operational costs by $8 billion+  every year from 2022. The costs being saved can be pulled back into R&D processes to innovate a better product for customers.

With AI, your company can track customer queries and issues automatically, saving you the cost of hiring additional customer service agents. 

Focus on the customer experience 

According to Microsoft’s Global State of Customer Service Report, 90% of consumers think customer service plays a pivotal role in their choice of and loyalty to a brand. 

This research done by Havard Business Review also points to the direct link between customer experience and annual revenue. In the report, it was claimed that customers with the best experience spent 140% more than others with a bad or less-than-great experience. 

It’s not an oddity to see customers dreading having to return with an issue because they are either put on hold or flat-out ignored.

Since customers are already not in the best of moods when they contact support, it’s your duty to make sure they leave feeling satisfied. 

Remember that great customer service will lead to referrals, so ensure that you focus on making their experience with your company nothing less than phenomenal. In choosing your support team, avoid going for square pegs in round holes — onboard agents that are equipped to provide the right solutions for the relevant customer queries without delay.

A team like that will win the hearts of these customers, enabling them to spread the word about your company’s exceptional service (positive word-of-mouth).

Use customer support as a springboard to streamline internal processes

Service desks are busy and under pressure. And so, they often struggle finding time and resources to make changes that could streamline company-wide processes. 

However, recent advances and innovations in both communication technologies and service management have enabled support teams to cost-effectively streamline operations while meeting support demands and stakeholder expectations. 

The best bit? These changes can be made quickly and without breaking the bank. Harnessing the power of integration and automation, teams can deploy technology to share data about customers with other departments and let them know what challenges they face as well as what is working well as they learn and improve.

Streamlining helps you align customer service with company goals. Since customer service metrics are now largely tied to revenue targets, you need internal consistency — across all departments, from sales to marketing to product management and R&D — to work as a coordinated unit and deliver results throughout your business. 

Use customer service to drive product development

Often, customer feedback is a rich repository of game-changing innovation for product development. With the gift of insight into customer pain points, companies can establish collaboration between the customer support team and the product teams — a strategic partnership where they exchange customer data to bring the company’s products closer to customer expectations.  

By carefully mining data from customer support channels, your company gets first-hand insight into the minds of the clients and can then come up with tangible ideas for product development to drive more sales and increase adoption. Plus, product improvements like these make the customers feel like their concerns are being heard, thereby driving customer retention and a positive image. 

Feed support insights into your marketing engine 

Successful marketing campaigns draw potential new clients into the sales funnel. A big part of making your marketing successful is knowing exactly what appeals to your target audience and applying it. What better way to know what’s running through customers’ minds than through the customer support system? 

The desire to solve product problems is mostly what informs search intent. As such, taking a closer look at the concerns raised and questions asked by customers, you’re likely to find that a gold mine of product issues you could deploy for content marketing. 

This way, you create useful on-site content that answers customer questions and speaks from their POV to resonate more deeply. To go for the kill, power your marketing activities with these customer insights and watch your engagement levels and traffic skyrocket for more ROI. 

Provide proactive support 

Providing proactive support is one of the surest ways to keep your customers in your corner. Keep the communication lines open and establish a presence across all platforms so that whenever a customer chooses to contact you, they get a prompt response. And do not be limited to swift responses only. Take proactive steps to anticipate some of the needs of your clients before they even realize that they need it and suggest it to them. 

One such step is subscribing to the “call avoidance” principle to streamline support models, saving time and money.

This approach focuses on using technology and processes to eliminate the need for end users to contact the service desk in the first place!

Why is this important? Well, as many in the industry know, telephone contact is often the most time-consuming and costly communication channel for support. But, thanks to advancements in self-service and self-help capabilities, call avoidance support structures have been a staple in the consumer marketplace for years.

Think about it: providing a live person-to-person communication channel for every contact is unrealistic and unsustainable. Instead, self-service portals have become a “one-stop shop” for end users, offering everything from password reset facilities to global system outage updates. This way, users only need to contact support when self-help cannot assist.

And it’s not just theory. In reality, self-service is already relatively widespread in the IT service desk industry. But there’s always room for improvement and lessons from the consumer marketplace can point us toward a more holistic approach. As service desks are increasingly pressured to do more with less, professionals need to take note of these consumer-space successes and apply them to their support models.

Do not overlook the employee experience 

Your employees are a reflection of your company — and by extension, its relationship with customers. While you’re activating tools to enhance customers’ experiences, don’t abandon that of your employees. 

Only a happy and well-treated agent can pass on the company’s values when interacting with customers on any platform.

A begrudged employee sends the wrong message to customers and limits the inflow of valuable insights from the support interaction. 

Make sure your employees, particularly those at the customer-facing front, are not being made to perform in an unhealthy work environment. Invest in employee satisfaction and watch them go above and beyond in smashing customer service KPIs, leading to a happy customer base.

Turn successful support interactions into selling opportunities 

Imagine your customer having to drive 2 hours to the next town to return an item. For every customer complaining about the distance to reach a supplier of your product, you’ve lost so many others who must’ve been too discouraged to bother. 

When offering support, be sure not to lose sight of the bigger picture. The immediate solution might be a refund, but the long-term solution could be an opportunity to extend your marketing & sales footprints to a new demographic — or roll out an exciting new feature to significantly cut back on future refunds! 

The possibilities are endless, but you only find out after a successful support interaction. To avoid a backlash, you also want to be wary of upselling while the customer issue is still pending. There’s always plenty of room for promotional efforts after the issue has been resolved. 

It doesn’t have to be an out-and-out attempt to close a sale on the customers; why push a tedious sales pitch when a subtle, yet effective, strategy like a cleverly placed promotional link in the footer of your closing emails can be the gentle nudge needed to seal the deal?

Summing Up

Calling all businesses! Whether you’re a small startup or a big corporation, we all know that customer service is the true ruler of the land. But, who says delivering great experiences has to break the bank? 

From cutting costs to increasing revenue, the sustainable strategies we’ve outlined here’ll help you create and maintain a connection with your customer base that boosts your bottom line, while strengthening your brand image to place you firmly among the key players within your industry.