You may be wondering, what is dark data? It’s essentially all the data that’s collected but never analyzed or used. Sounds like a waste, right? Wrong!

This overlooked treasure trove of information holds the key to understanding your customers’ needs and pain points and can help you provide personalized, effective support.

But don’t just take our word for it. We’ll also provide examples, tools, and actionable steps for leveraging dark data for customer support in your own business. Trust us; your customers will thank you for it.

So, are you ready to unlock the power of dark data and boost your customer support strategy? Let’s get started!

What is dark data?

As a business owner, you know the importance of gathering and analyzing data to make informed decisions. But have you ever stopped to consider the vast amount of data that goes unused? 

This is what we call dark data – the untapped gold mine of information that holds the key to improving customer support, enhancing customer experience, and driving business growth.

A recent study showed that 73% of collected data goes unused. Can you believe it? That’s a lot of missed opportunities. But it’s not too late to change that. You can gain valuable insights into your customers’ needs, preferences, and pain points by leveraging dark data. 

This can help you provide more personalized and effective support, leading to improved customer satisfaction and loyalty.

But it’s not just customer support that can benefit from dark data. This valuable resource can also be used to optimize marketing efforts, improve supply chain management, and optimize product development. The possibilities are endless.

Where does dark data come from?

You might wonder where this mysterious dark data comes from. The explanation is that it originates from various sources. Log files, which record activity on a company’s website or app, are one typical source.

Because of their enormous bulk and complexity, these log files are frequently disregarded even though they might offer insightful information about client behavior.

customer behavior and feedback are other forms of dark data. These can offer insightful information about client requirements and preferences, but it’s common for organizations to gather this information without ever analyzing it.

Dark data might even come from social media. Consider all the shares, likes, and comments that occur on websites like Facebook and Instagram. Businesses can enhance their marketing initiatives and gain a better understanding of their clients by evaluating this data.

However, the idea of dark data is not anything new. Actually, scientists from the University of California, Berkeley were the first who invented the phrase in the 1990s.

And, since then, there have been enormous increases in data collection, creating more and more potential for corporations to use dark data.

How to utilize dark data for customer support?

So, how do you get started with Dark Data (the gold mine for improving customer support)?

The process may require some digging and the help of specialized tools (we’ll tell you about those tools in a bit, hang on!). Here are a few steps that you can follow to utilize those Dark Data for customer support.

1. Identify sources of dark data

Finding the information’s origins is the first step in utilizing dark data. As we’ve already discussed, some typical sources are social media data, consumer reviews, polls, and log files.

Review the data that your company is gathering but not using, and think about how it might be useful for enhancing customer service.

2. Establish a plan for analyzing and using the data

Having determined the sources of the dark data, the following stage is to create a strategy for its analysis and utilization. This can entail bringing in some specialized equipment or recruiting a group of people with knowledge of data processing.

Moreover, it’s critical to have a clear understanding of the goals you have for the data. For example, recognizing trends in customer behavior development, creating a customer segmentation model, establishing a customer onboarding process, and identifying pain spots that require attention.

3. Analyze the data and extract insights

Now that you have a fixed strategy, it’s time to begin work with data analysis and extraction of insights. Searching for patterns or trends may include going through a lot of data.

Besides, it’s important to consider the context of the data collection and how you can apply that to your company.

4. Implement changes based on the insights

Now, it’s time to put the dark data insights into practice after you’ve retrieved them. This can involve modifying your customer service strategy, to offer more assistance and support or deal with common problem issues.

It’s crucial to monitor the effects of these adjustments and keep studying the data to find more room for growth.

You may effectively use dark data to enhance your customer service and experience by adhering to these measures. Moreover, with an increase in sales and money, it will also boost customer satisfaction and loyalty.

Some popular tools for dark data mining 

You can utilize a variety of tools for dark data mining in customer support or customer care. Some possibilities are:

1. Text analytics tools

These tools enable you to extract insights from and spot trends in vast amounts of text data from surveys and customer comments. Lexalytics, Adobe Analytics, and IBM Watson are a few examples.

2. Social media monitoring tools

You can collect and analyze social media data such as comments, likes, and shares with the help of these tools. Also, you can learn more about the customer behavior & their preferences. For example – WP Social Ninja, Hootsuite, Sprout Social, Brand24, etc.

3. Data visualization tools

It is simpler to extract insights and spot patterns thanks to these tools’ assistance in visualizing and communicating data in a straightforward and understandable way. For example – Tableau, Google Charts, and D3.js.

4. Customer relationship management (CRM) systems

Now, many CRM systems include impressive capabilities of data analytics for analyzing customer data and extracting insights from there.

Popular examples of CRM systems – FluentCRM, Salesforce, Zoho CRM, Microsoft Dynamics, etc.

5. Help desk plugins & software

You can monitor customer contacts, examine customer data, utilize machine learning techniques, evaluate customer feedback, and reviews using a support desk plugin or software.

You can learn more about client preferences and behaviors. Spot typical difficulties, problems, and enhance the customer experience by doing this. Examples – Desk.com, Salesforce Service Cloud, Fluent Support, and others.

It is important to keep in mind, that these are just a few of the vast approaches for dark data mining in customer service or customer support that are available now in the industry. However, the right tool will depend on the particular requirements and objectives of your business.

Machine learning AI for utilizing dark data 

Suppose, to mine dark data; you’ve decided to turn to machine learning AI.

Using various natural language processing techniques, the AI will be able to extract useful information from these unstructured data sources. Also, this will identify trends and patterns that may be impacting the customer experience.

For example, the AI may find that a large number of customers are experiencing difficulties with a certain product or that there are recurring issues with a particular part of the customer journey.

Armed with this information, you can take steps to address these issues and improve the overall customer experience.

In addition to analyzing dark data, you can also use machine learning AI to predict customer behavior and identify potential issues before they arise.

This proactive approach can help your customer support team to address problems before they become serious, resulting in a better experience for your customers.

Machine learning AI can analyze customer interactions and identify areas where the customer experience can be improved.

By streamlining processes and providing more detailed information, you can make the customer journey smoother and more enjoyable for your customers.

Dark Data: The gold mine for customer support

As the old saying goes, “Knowledge is power.” Therefore, when it comes to customer support, having a deep understanding of your customers and their needs can make all the difference in providing exceptional service. That’s where dark data comes in. 

So, if you want to take your customer support to the next level, don’t let your dark data gold mine go to waste. Start mining for insights, utilizes them, and watch your business thrive.

Thank you for reading this blog and for your interest in learning. We hope you found it informative and helpful. And wish you the best in your efforts.

The post How to Leverage Dark Data for Customer Support appeared first on Fluent Support.

Every business goes to extra lengths for that customer. Companies are investing big money to create and improve their customer experience. No one wants unhappy customers to share their frustration on social media about their bad customer experience.

A happy customer is more likely to become a loyal customer. Only a positive customer experience can make a customer happy.

But what is customer experience? How can any business with limited resources provide a great customer experience for its customers? How can they balance the pressure of customers’ expectations and other business goals while doing this?

In this blog, we will cover the definition of customer experience, why it is important for your business, the difference between good & bad consumer experience, and how you can measure customer experience to increase your revenue. 

What is customer experience?

Customer experience (CX) is everything about how a customer feels about your brand, products, and business.

The main ingredients of customer experience are products and people. It focuses on the relationship between your business and your customers. No matter how small or big the interactions are, everything is included in the CX.

When a customer views your advertisement, reads your website copy, emails, or other text from you, contacts your support for help, or calls, these customer contacts are what we call customer experience. How customers view these interactions defines your business customer experience. Every exchange between customer and business creates great (sometimes bad) long-lasting relationships. The deeper the relationship goes, the more the brand gets customer loyalty.

Customer experience happens in these ways-

• Customer perception about your brands before they buy anything
• Their sales experience when they buy your product
• The quality of your products or service
• Customer support or service experience after purchase

A great customer experience is a key factor for a business’s success.

Importance of customer experience

Customer experience directly influences 3 business metrics:

1. Customer retention
2. Customers lifetime value
3. Customers loyalty toward your brand

In a competitive market, connecting with customers and retaining them is more challenging than ever. Excellent customer experience can help you sustain and accelerate growth. It also promotes brand advocacy and increases loyalty among your user base.

Present-day, the internet favors customers hugely. Now anyone can share their experience with millions of people through one Facebook post, tweet, youtube video, or a viral TikTok. Virality can amplify anything, from a great interaction with brands to a bad customer experience. One bad experience goes viral and puts a wrong impression on your brand reputation.

Now customers crave personal connections with brands. You can quickly lose to your rivals who understand client experience if you are not focused. Customers have unlimited options and one click away to choose; they want more than quality products or services. If they try to reach your customer service or support and can’t get in touch or face a bad experience, they will not hesitate to turn to your competitors.

A great customer experience will increase customer satisfaction, positive reviews, and organic growth through word-of-mouth marketing. But how can a brand provide an amazing customer experience to its customers? 

First, get a clear picture of good & bad customer experiences.

What is a great customer experience?

What makes a customer interaction a good customer experience? You should make it easy for your customers to do business with you. How can you make it a great customer experience? Make it seamless for customers to do what they want to do with your products and services.

Every positive customer experience has these elements which make every interaction great:

• Your products or services serve quality instead of just a cheap market alternative. Quality always wins. If it can’t fulfill customer needs, then the whole experience will be crushed. Your product design should be intuitive. Your service benefits should be appealing and valuable if you are offering services.

• Your marketing is realistic, aligning with customers perceptions. Every business should have realistic expectations about its products.

• Your self-service tools are available online. Make them searchable and resourceful. Help your customers to help themselves quickly access your knowledge base, documentation, and guides.

• Focus on proactive support. Identify issues before customers face them and provide solutions before they ask.

• Your pricing is visible in every sales copy, website, or cart. Transparent sales are the best way to influence buying intended customers.

• All your teams are in the loop in every customer interaction and can quickly access information about any customers in real time. It helps your teams avoid conflict and reduce customer frustration over repeating the same information to different persons for every inquiry.

• Customer support is the center of attention for your business. It is the central part of the company, and every team plays the part of the support team. Everyone is aware of customer experience in every user’s onboarding process & makes sure customer needs are taken care of.

What is a bad customer experience?

Bad customer experience happens when a customer faces a problem onboarding to your business. Then, if they can’t reach your support for help, it will be an even more frustrating experience for them. Bad customer experience happens from poor customer service. We wrote about thirteen bad customer service examples in our previous blog. Here are a few reasons make most of the bad customer experiences:

• Long wait times over the phone and many agents-to-agent touchpoints.
• Employees without proper understanding of customers problems.
• Overused automation without human contact points.
• Not enough coordination among teams makes customers repeat information every time they connect with different persons.
• No visible contact option on your website or brochure.
• Ignores customer complaints and never reaches them for solutions. Do not take customer feedback seriously.
• Rude employees and no empathy for service.
• No personalization on customer support. People feel like talking to bots.

How to measure customer experience?

Customer experience can make you stand apart from your competitors. But to achieve great customer service, you have to measure and analyze ongoing customer experience to the teeth continuously.

There are no tangible ways or frameworks to measure and analyze consumer experience. Every industry is different, and its customer demographics are too. You have to deep dive into data, analyze little pieces, and run numerous experiments on the go.

Here are some ways you can start your customer experience by measuring and analyzing:

1. Run customer satisfaction surveys

Start your measuring experiment by collecting data directly from your customers. Run customer satisfaction surveys right after closing a support ticket or call. You should get a clear insight into your customer satisfaction score (CSAT) and Net Promoter Score (NPS). 

CSAT will give you an understanding of customer satisfaction through different touch points. NPS will give you an insight into customer perception about your brand and how likely they will recommend it to their connections. It will help you decide your future steps. You can use the data to follow up with customers later time.

2. Calculate customer lifetime value

How much a customer spends money with your business is an important metric you should always calculate. We wrote about customer LTV in our latest blog. Read it; you’ll learn why it is vital for your business and how you can calculate your customers lifetime value. 

3. Analyze your churn rates

Churn rates tell you how many customers you lose in a certain period. If your churn rate is higher, something terrible happens with the customer experience. Keep an eye on your churn rates. Learn what causes churn rates and how you can reduce it.

4. Learn more about customer effort score (CES)

CES is a customer service metric, and it tells you how many touchpoints a customer has to face to resolve an issue. It gives you insight into your support system and how you can make it fast for customers to reach suitable people for solutions.

5. Use community forum for customer feedback

Community forums can be a great resource for businesses to collect customer feedback. You can access everything from feature requests to customer’s pain points, support problems, and organic customers suggestions about your product/service. You can use the community forum as your focus group to test new changes and get feedback instantly.

6. Time to resolution (TTR)

TTR gives you insight into the time needed for your customer support team to resolve a customer issue or close tickets. Find out how much time a customer needs to wait for an answer from your agents. Measure the average time. Most customer frustrations happen over long wait times. The shorter your TTR time, the more remarkable will be the customer experience.

7. Analyze Support data

Customer support data can be used to measure and analyze CX further. If recurring issues regularly come through tickets, you should review the problems and provide solutions immediately. It will save time for both your support agents and customers. A streamlined process will decrease support tickets and provide an excellent client experience.

Conclusion

Companies are now investing a lot in great consumer experience. In today’s world consumers hold more power than the sellers. Client experience revolves around how your business interacts with them, how fast you’re solving their problems and how easy it is to onboard with your product or service.

Measure customer experience by collecting customer feedback, running customer surveys & gathering customer support data, and analyzing it. It is a never-ending process. You have to keep analyzing and improving customer experience every day. Because one bad customer experience can affect your brand image. Investing time and money in a good CX experience will attract loyal customers in the long term, thus increasing revenue.

The post What is Customer Experience & Why It’s Important? (And How to Measure It) appeared first on Fluent Support.

In this post, we’re going to look at what proactive customer support means and briefly discuss how you can implement a Proactive strategy.

What is Proactive customer support?

Let’s get one thing straight. Proactive support isn’t one single feature or tool that improves your support. It’s more of a strategy for approaching customers’ needs. The core of this strategy is to offer support, even before a customer asks for it. 

In simple words, Proactive support is a strategic practice of identifying, resolving, and communicating potential issues before your customers identify them and seek help.  

But what’s the benefit?

Why invest in Proactive customer support?

While good customer support improves customer satisfaction rates and enables a better customer experience, it also reduces costs. Proactive support, on the other hand, doesn’t directly reduce customer support costs, but smoothens customer onboarding and saves time for your agents.

A few of the key benefits of Proactive customer support are,

1. Reduces Queries

By offering proactive support you can reduce the number of queries that are submitted to your support inbox. This reduces the amount of pressure on your agent. What it also does is reduce the number of moving parts your agents have to deal with.

2. Saves Time

Proactive customer support means preparing the solutions to questions your customers haven’t asked already. Having resources and solutions prepared for common or expected questions frees up time for your agents. This time can be used to answer complex problems that require expertise.

3. Improves customer retention

By far the best benefit we imagine is the improved quality of your customer experience. As your customers feel prioritized and get stellar CX from your business, your satisfaction ratings improve. More satisfied customers that think you care about their needs are easier to retain, improving your retention rates as well.

Great, so we know the benefits of proactive customer support. Aside from the general benefits, proactive support is important because 87% of customers expect a proactive strategy from brands.  Now let’s check out the core differences between normal and reactive support. 

Reactive vs. Proactive customer support

Reactive support is the average support strategy where you wait for customers to come to you with their problems or questions. Most of the support process begins after customers create a ticket and take out the time to elaborate on their problem.

Proactive support on the other hand is preemptively provided. Its purpose is to reduce the number of redundant questions customers might ask. 

Don’t get us wrong here, reactive support is just as important. One is not meant to replace the other. Rather it’s about creating a process where customers can get help for truly complex problems while the solutions to typical problems are right in front of them.

In contrast to reactive support which boasts your team’s knowledge of the technical know-how, proactive support highlights your understanding of the customer’s journey.

5 tips for proactive customer support strategy

Now that we’ve got the basics out of the way, let’s check out how you can implement a proactive customer support strategy.

Ask for feedback

Customer feedback is a goldmine for your business. Single well-defined customer feedback can make up for months of market research. Asking for feedback is not something you do to improve your products or services. It’s actually a huge part of crafting a customer experience more in line with the art of customer follow up. 

This not only gives you insight into what the customers are facing while doing business with you. It also highlights the aspects where you can implement proactive solutions.

Track online conversations

Your customers are everywhere on the internet. Sometimes looking at feedback and most common ticket issues isn’t enough. While they are good sources of insight they are hardly complete. 

To get an even better idea you need to track what your customers are saying about you. For instance, your customers might have detailed conversations online about what they love or hate about your product. Being a part of this conversation means you can get a clear picture of what your customers love about your products.

Notify before Solving

If you have traced an issue before customers have faced it, it’s kind of your responsibility to clear it up. Whether it be a notification, a social media post, or an email newsletter. Keeping your customers up-to-date on what’s going on with your product is a crucial part of proactive support. 

It doesn’t matter whether you have already fixed the problem or not. The important bit is letting your customers know that they might face issues using your product or service. This gives them time to prepare for the complications and buys you time to develop a reliable solution.

Plan out your resources

The best way to offer proactive support is to prepare resources to solve typical problems and make them easy to find. A good addition to this is having Knowledgebase suggestions. The way this works is your ticketing system can check what customers are typing in real-time. 

In turn, it can show related articles to the terms a customer uses to explain their issues. This is the essence of Proactive customer support because it offers probable solutions before a customer submits their tickets. 

Utilize automation

Last but not the least, you can automate first responses for tickets using automation, such as Fluent Support’s automated workflows.

WorkFlows let you automate customer support processes such as sending template responses, offering relevant solutions and even submitting solutions automatically, based on the contents of the ticket.

Even with basic information such as the product priority, you can automate actions without having to commit agents from the start. For instance, Fluent Support lets you trigger workflows on ticket submission and on customer responses.

Wrapping Up

Proactive customer support is not just about offering support. It’s actually part of a larger whole called customer experience. Proactive as a strategy complements other common support strategies. Not only does it reduce the overall stress on your agents, it actually smoothes out the support process from step one.

All you need to do as a support manager is pick the right support ticketing system that is optimized to offer proactive support.

The post What is Proactive Customer Support? appeared first on Fluent Support.

Then you can more precisely target your customers with this information. Putting the customer first can lead to growth for your business. But what types of customer data should you collect, which data is super valuable and how can you collect those data?

The answers to these questions are easy to find when you know where to look. In this post, you will learn about various types of customer support data, why it is crucial to collect them and how to collect them.

Types of customer support data

There are many types of customer support data. These are divided into two groups:

• Structured data: Data you can visualize and present to others.

• Unstructured data: Data could not be visualized and presented, connected with people’s sentiments.

Most types of data we use in our day-to-day are structured data. Structured data can be measured and can have a direct impact on business. You can collect information through surveys, and put that in a graph or diagram. These data are structured.

But when you ask your customers how they feel about your product, the answer is unstructured data. You can’t put that in diagrams. Both of these data are important for your business. They help you determine your business’s customer service objectives.

Here are 8 best customer support data you should collect from your customer support team:

1. First Contact Resolution

Find out how your agents handle the customers who opened support tickets for the first time. “First Impression” always matters. If your support agents are not handling your first-time customers properly, it will harm your business. An unsatisfied customer will be clueless about their problem’s solution. Most of the time, they will not return to repurchase anything. Your re-targeting will be worthless. And they may share this negative experience with others.

When first-time customers are satisfied with your support team, they will most likely buy more from your business and tell others about their positive experience with your business. Try to collect data on everyday support queries – 

• How many first-time customers opened a ticket?
• How many replies did the support agent make to resolve the ticket?
• Average handling time on these tickets?
• What is the response from users after the ticket survey?

You can use your findings based on your industry. If the answers are negative, then you should take time to talk with your customer support team. Help them train them to better at service and answer customers.

2. Customer Satisfaction Score (CSAT)

Try to find out how satisfied they are with your support agent’s answer and the support they received. CSAT, short for ‘Customer Satisfaction Score,’ can help you in this situation.

A customer satisfaction score is a widely used method to determine performance indicators for customer service and overall product quality. You can define customer satisfaction in percentages from 0% to 100%.

You can use one or two questions to ask your customers some options and collect this information. 

• Are you satisfied with the support agent?
• Are you satisfied with overall support?
• Do you find the solution to your problem?

You will find various examples on the net, or you can use free templates available using a simple google search. Use them in your business, collect data and analyze your CSAT regularly. Always try to collect CSAT after a resolved ticket. You can also collect CSAT after a refund or cancel the subscription or a product return. 

Use this formula to get a percentage score:

(Number of satisfied customers/ Number of survey responses) x 100 = % of satisfied customers

3. Net Promoter Score (NPS)

Net promoter score is one type of customer satisfaction metric. It is about how many of your customers are ready to promote your products and service. NPS collects data about referrals. Loyal customers are a business’s brand promoters. The more loyal customers you have, the more new customers you can reach. 

Your target should be to gain as much as a promoter using your outstanding support. This will help you expand your market and sell more to new users. Cultivate a relationship with your customers through your support team. Your support team knows your user’s pain points. They are the ideal data point to communicate and collect information. Identify your repeat customers and ask them questions-

How likely is it that you would recommend our Product/Service to a friend or colleague?

You can offer options ranging from 0 to 10 to rate the answer. Collect the answer and analyze the promoter, neutral, or Detractors (below five ratings). You can track everything from business to products/services with Net Promoter Score. Create an NPC survey associated with your industry for better results. 

NPC is a strong indicator. It will provide you with an overall look at your business and help to improve or monitor products and services. The more data you can collect and analyze along with your NPS score, the better you can determine where to improve your customer experience. It will help you prioritize your improvements to make the most significant impact.

4. Customer Happiness Metrics

A strong product, a sound customer support strategy, and a team are not enough sometimes. You have to analyze and use your Customer Satisfaction Score (CSAT) and Net Promoter Score (NPS) to determine how to reduce churn and optimize the customer experience.

This information will help you understand customers’ emotions and how they feel about your business. You can also monitor how customer sentiment is changing at a certain point in time. You can set your future marketing funnels and content basis on that customer sentiment. This will give you better conversion and ultimate customer satisfaction. 

Every business should collect customer happiness metrics from time to time. They are easy to collect. Train your support team to do the work and ask the right question for the correct answer.

5. Support Ticket Data

Support ticket data is the most structured data you should prioritize collecting and analyzing. You will get an overall idea of your customer happiness from your support ticket data. You should collect these data for future analysis:

• Ticket volume on a certain period (on the day, week, month basis)
• Tickets around certain topics
• Time to resolution
• Last ticket submitted by the customer
• First ticket submitted by the customer
• Average handling time on new customers
• First touchpoint activity
• Number of tickets by customer

You can use automation to collect and organize support ticket data to save time. Use this information to find out customer churn reasons and churn risk (more on that later). Use efficient customer support tools which help you collect these data without any headache.

Create an instant trigger with your automation on selected events like when a new customer opens a ticket, then selected instructions are shown in ‘Internal Note’ on how to handle the customers for new assigned agents. There are limitless possibilities with support automation available. 

6. Customer Churn Reason

When a customer opts out of your service or applies for a refund, you should collect the reason for their decision. The business has a high priority to getting repeat customers and cultivating loyal customers for the long run.

That’s why every business must find out customer churn reasons. Find out-

• Why do users are optin out of your service?
• Why are customers applying for a refund?
• What problem are they facing, so they have to open support tickets?

Try to collect as much structured data about why a customer is optin out. Ask a simple question like these, keep the process easy for your customer, and analyze how to reduce future churn risk.

7. Customer Churn Risk

Businesses should analyze customer happiness metrics to evaluate customer churn risk. Find out churn reasons and solve the issues one at a time. Use data to determine which customer has a high churn risk and have specific instructions for your support team for the specific demographics.

8. Customer Happiness Reason

Like finding out a customer’s frustration reason, find out why a customer is happy with your business. Collect positive reviews from your repetitive customers. Ask questions like –

• Why do they love your brand?
• Why do they use your service or product?
• Why do they choose to promote you?
• How to improve the product or service?

Customers with high NPC scores are the ideal profile to collect this information. Learn about your customer’s emotions, and transfer that information unstructured to structure data through accurate survey questions and simple processes. Implement your learning into new customer interactions and hostile customers to improve relations, reduce churn risks, and better customer satisfaction.

Why should you collect customer support data?

Collecting support data is a mandatory process for businesses. But they are sometimes overshadowed by the hype of big data. Big data is a hot trend right now. It is good to invest in big data. Before investing in big data, you should ask some questions yourself first-

• What is the goal of my data collection?
• How is it going to improve my business?
• Is it going to create problems in the normal process?
• How can I improve my process to collect the correct data?
• How am I going to use the data throughout company teams?

These are the starting question you should answer first. Data helps you visualize your company’s progress, a certain status, and the performance of teams. You can present data in company meetings or share your data across teams.

Data gives you the ability to set performance goals based on your present success. You can get insight into how your teams are doing and what they lack. Data helps you to fulfill the lackings.

Robust data will help you evaluate recruitments, marketing budgets, and ongoing expenses. You can invest more precisely without wasting time and money. By presenting data to your teams, you can inspire them, and show them how they are contributing to the business and how they can hey improve their performance. Positive data will make team members more engaged and motivated toward their work.

How to collect customer support data?

The best sources to collect customer support data are those you are already using to serve your customers. Here are six ways you can collect customer support data-

1. Helpdesk software

What tool you are using to serve your customer support is the best source to collect customer support data. It should be your primary source. Choose a suitable help desk software for your support operation from the start. Do not hesitate to invest in the right tools. You should these things consider while buying a help desk software-

• Does it help me track individual and team reports?
• Does it show daily ticket volumes, waiting time, and resolve time?
• Does it show first reply time and average handle time?
• Does it have multi-channel support features?
• Does it have a pre-built dashboard for both admin and agents?
• Does it have custom tag, priorities, and product abilities?
• Can I run automation on this?
• Can I connect my favorite applications through webhooks?

These data are essential to collect and use; your support solution should provide features to collect these data. Dashboards with visuals are a high priority for a good support ticket system.  

2. Knowledge Base

Knowledge base software is another source of customer support data most business sometimes ignores. You can find out which of your documentation page are getting the most view and optimize it to get better results. You can also get an insight into which topic is most searched on your site, then research that topic-related questions or problems and write a depth blog or do video tutorials showing users how to solve the problems.

3. Customer Surveys

Customer surveys easily collect user responses on particular services, products, or specific things. You can collect customer satisfaction (CSAT) and net promoter score (NPS) surveys and run surveys after a ticket close. If your support ticket software has the options, you can automatically send surveys triggered by specific events.

Use precise words to ask questions in your surveys. Make it easy to understand your customers so the support agent can collect the correct information using the survey.

4. Business Tools

Tools like Google Analytics, Kissmatrics, or Heatmaps can give you rich, valuable data about your business, website, and customer behavior. They can provide you with in-depth information that your support system may miss. Integrating these tools with your support desk can improve ten-fold customer support data collection.

Sometimes these tools can be difficult and time-consuming to use. Measure your time and money if you don’t need these tools immediately.

5. Community Forums

Online user forums are another unstructured data source you should consider collecting. Invest some time to research community forums related to your industry. You will find all kinds of posts from your customer demographics, go through them and learn about their problems. Use that knowledge in your business operation.

Often time users share their experiences with others in these forums. Know where your customers are hanging out. Train your support agents to be there and handle questions, reviews, and user posts about your business.

6. Online Reviews

Review sites are excellent sources of customer support data. These sites often give people the ability to rate products. Find out where people are writing and rating your products/ services. Learn how people are reacting, expressing and what they are sharing about your business.

Collecting these data regularly will be time-consuming. It’s not worthwhile to collect support data from these websites every day, so try to do it on special occasions and projects.

Wrapping up

Collecting, maintaining, and using customer support data is a regular task. Tracking your customer support data can give you knowledge about improving areas in your business. Always keep solving these issues and monitor the customer support data matrics constantly.

Make sure you have a clear objective on what data you want to collect, why you want to collect them, and how you will collect them. The more accurate customer support data you have, the easier it is to make decisions about marketing, sales, support, and overall business.

The post 8 Types of Customer Support Data & How to Collect Them appeared first on Fluent Support.

Your support team knows about your customer better than anyone. They are in touch with your frustrated customers daily; they know their pain points and how they react to your products or services. They have a more significant impact beyond support. This knowledge is valuable for your business operation, such as marketing, re-targeting, and improving your products.

When used in a proper way, customer support data can help your company achieve unbelievable customer happiness metrics and gain a new customer market.

But what is customer support data and how can you make the most of your customer support data? In this post, we will explore seven ways to make most of your customer support data effectively.

What is customer support data?

Everything related to customers and how they use your products or services collected through your business’s support team is customer support data.

This data includes your customer information, their interest, what they are buying, what their problems are, and much more.

Customer support data can be differentiated into many types. Businesses can collect customer information based on metrics like customer happiness, support ticket data, user churn risk & reason behind it, and customer satisfaction.

You can analyze and research the collected data for robust re-targeting, offer related customer service, and a better marketing plan. Customer support data can help businesses create new strategies to strengthen their marketing and support goals. You can use this data to predict your customer’s future actions and set your re-targeting process to get a positive result.

How to collect customer support data?

Collecting your customer support data is super important from day one. Businesses must have a process to collect the correct information using the right tools.

The best way to collect customer support data is to have super responsive and feature-rich helpdesk software. Most of the support ticket solutions have built-in data-collecting features nowadays. Using tags, automation, and custom priorities, you can collect different types of information about your customers in a support system like Fluent Support or Awesome Support.

You can use your knowledge base to determine which topics are most searched and the main reason for new tickets. You can also research online reviews to learn about customers’ pain points and run surveys to determine customer satisfaction.

Tools like Google Analytics, Kissmatrics, and Heatmaps are some business intelligence tools widely used to collect customer data. You can implement these tools to get deep customer support data for future use.

How to make the most of customer support data

Customer support data is gold when you put that into action. It would be best to use customer service analytics to evaluate your support team’s performance and identify problems to solve them immediately. You can use this information in other ways too. Here are 7 ways you can make the most of your business’s customer support data-

1. Know your customers

Enough customer support data can help you identify your ideal customers. If you know your customer’s demographics, you can adequately segment them. It can help you connect to the right customers when necessary. You can also create a suitable marketing funnel for your specific customers or re-target a particular group.

Customer experience data will help you understand your demographic behavior. You can use that understanding to apply the right tone and training to your support team. So they can improve themselves, give better support experience to customers and boost customer satisfaction.

Collect customer support data from your support team and ask them these questions to identify your demographics-

• How are customers connecting with support?
• What is their pain point?
• What products are they buying? Are they buying other products? 
• How are customers behaving from one product to another? 
• Is there any churn rate?
• How many customers leave after checkout?
• What is the behavior of customers while in the refund process?
• What is the problem customer trying to solve with your products?

You can ask many questions you can ask your industry. Choose wisely. Collect data on your intention to use the data for analyzing present and future customers. You can use this information to provide feedback to your first buyer. You can collect how they react and use that to create onboarding messages, email campaigns, and help documentation for users.

2. Follow the right metrics

Choosing the right metrics while collecting data is the most crucial step. When you are collecting data, follow the right metrics. This will help you focus on specific topics and tools you should use.

Try to figure out the customer’s first touchpoint with your support. How are they behaving with your support? Are they getting the right answer when connecting with your support team? Most of the time, customers’ first contact with support determines their relationship with your brand long-term. When they get immediate solutions for their problem from your support or even satisfaction, it leaves a positive image on them about your products. These customers are most likely to buy again or tell their friends & family about your brand.

The second metric you should follow is how they are satisfied with your customer support team. Try to figure out this question. The answer will tell you a lot. You can use this data to figure out how to evolve the support team or how much you need to invest in support.

The third metric is how likely your customers will refer your business to others. This data will help you analyze customer retention and determine what your brands lack in terms of customer needs.

You should also consider other metrics like time to first response, average handle time, resolved cases, etc. But always follow the mentioned three metrics first.

3. Review team performance

When collecting and analyzing customer support data, you should consider reviewing your support team’s overall performance. Because everything depends on the connection between your support agents and customers.

Put the right people on your team. Try to avoid all kinds of bad customer service. Train your people to handle your customer with empathy.

Keep in mind while reviewing your support team-

• How are they communicating while engaging with users?
• What are the waiting time data on average tickets?
• What are the average closed tickets by individual agents?
• How do customers react after refund requests?
• How many tickets closed at first touchpoints?

You should review performance weekly, monthly, and quarterly to ensure quality support data. Use your support data to get an overall look into your support team’s performance. Your collected data will be worthless and not actionable without a good support team.

4. Define business goal

Using customer support data, a business can define its goal for the long term. When it comes to business goals, all things are defined by revenue and cost.

To run a business, the main goal is to increase revenue and decrease costs. You can use support data to know what is costing you money or what you need to improve to increase revenue per customer.

Every business should have a clear data strategy. Data strategy means how your business uses data to implement proper processes toward fulfilling its business goal. 

Analyze customer support data about your product or services; if one feature is costing you more customers, you should focus on improving the feature and benefits to improve customer satisfaction, thus increasing customer retention. The proper use of customer support data will risk going in the wrong direction—or stalling out completely—if you don’t have a solution for using data to guide your decisions and actions.

5. Evaluate data tracking

Data tracking is hard work when you are tracking lots of data. Sometimes businesses lose track of data because often they collect so much event data that they don’t know where to start. That’s why you should have a clear answer on how and why you are tracking and using your data.

Constantly evaluate your data tracking. If you are unsure where to start, try finding your immediate questions answers. What data do you need to track these answers? You will then know how to start the right process.

Use tools (Google Analytics, Kissmatrics, etc.) to track your events and goals, name them properly for future use. Analyze and evaluate overall progress to determine which needs your immediate attention.

6. Store data for future

Businesses should start planning to store data privately from their start. In the early stage, free analytics tools will do the work, but as the business grows, it is will helpful for the future to company invest in data storing and analysis.

Nowadays, it is easier to store data. As a business, you should always think ahead. In this era, data is like a goldmine. It is far more valuable than money to businesses sometimes. Data is useful when you make it easy to access your team. It is only possible in your own dashboard. 

You can make charts, diagrams, and information with metrics visualized into a dashboard accessible to everyone in your company. Storing your data on your own and making it easy to find for everyone will make your data more valuable. It will help them make the right decision backed by actual customer data.

7. Use support data on marketing

Your all customer is not here to stay forever. You will lose users every day. But with customer support data, you can analyze metrics like customer satisfaction and support ticket data to find out the customer churn rate. You can use that information to improve your marketing funnel to re-target those customers repeatedly.

Support data can be helpful in marketing to target new users. Because you already know about your existing customers, you know about their age, what they like, their pain points, and their problems through your support data. Use that data to target the same demographics and personalized marketing materials for better conversion.

You can use support data to provide content based on users’ first purchases and keep up good retention. Apply that to a follow-up email, checkout text, or message too. Your knowledge of support data can help your marketing team gain engagement, and retention, decrease customer churn rate and increase back-to-back product sales.

Conclusion

Customer support data is one of the most valuable data types you can use in your business growth. Not only is it helpful to increase profits and customer retention, but customer support data can also give you ideas on how to make your products or services more effective. In some cases, it will lead to new product or service ideas.

Businesses can identify their support representatives’ performance and customers’ needs by using customer service analytics. They can utilize these data for marketing or content to retain old and gain new customers.

You should not just store customer support data. You can follow any of the above methods to use support data wisely in your business and keep your team productive all the time.

The post 7 Ways to Make Most of Your Customer Support Data Effectively appeared first on Fluent Support.