How to Use Data Analytics to Improve Customer Support

Your team should always look to make improvements to your customer support efforts. Customer data analytics is key to ensuring the improvements you make have a positive impact on your audience.

Straight up:

The level of customer support you provide can make or break your customer relationships — and your business as a whole.

According to data curated by Nextiva:

• 70% of consumers choose to do business with companies that offer the best service and support
• 56% of consumers will stop doing business with a brand after a poor service experience
• 40% of consumers will tell others to avoid a brand after a poor service experience

It’s not enough to deliver a high-quality product or service to see your customers succeed, either.

To truly ensure your customer’s success, you need to offer laser-focused support at every step of their journey with your product and your brand.

This goes right along with BusinessDictionary’s definition of customer support, which explains that such support includes the “planning, installation, training, troubleshooting, maintenance, upgrading, and disposal of the product”.

Injecting support initiatives throughout your user experience (and overall customer experience) keep your customers engaged and productive whenever they use your products. The more successful they are in their efforts, the more likely they’ll be to stay loyal to your brand.

In short: Delivering high-quality customer support is vital to your customer’s success, and to that of your business.

Here, we’ll discuss how to use customer data analytics to determine how to deliver this support to your audience.

What is Customer Data Analytics, and How Can It Improve Customer Support?

Customer data analytics, or customer analytics, refers to the analysis and assessment of your customer’s behavioral data in order to better understand their needs, preferences, motives, and actions.

With regard to customer support, customer data analytics focuses specifically on product usage data.

Overall, It’s about understanding the behavior of your customers like how they use your products or what they do “behind the scenes” to help them get the most use out of them. By understanding what your customers do — or what they expect to be able to do — at different points along their journey, you can inject support initiatives that can supercharge theirefforts at each touchpoint.

On top of that, customer data analytics allows you to not only identify problems within your user experience, but can also help you determine what needs to change in order to fix them.

(As we’ll get to, “delivering exceptional customer support” often means “making improvements to the product to better enable the user”.)

With that said, let’s take a look at how to use behavioral data analytics to improve your customer support efforts across the board.

Analyzing Pre-Usage Data to Deliver Proactive Support

The customer experience doesn’t begin when they start using your product.

And it doesn’t begin when they first hear about your brand.

Rather, the customer experience begins the moment they realize they have a problem that needs to be solved.

Your goal, then, is to provide support to your potential and current customers the moment they reach this point. If you don’t provide support through these means, your customer’s experience with your brand will stop then and there — and your competition will likely pick up the slack.

In order to provide this support, though, you need to know what your customers are doing before they decide to use your product. This will give you a clear idea of where to focus your initial support efforts — and what needs to be done to engage and convert prospective customers.

One effective way to figure all this out is to reverse-engineer your current customers’ initial experiences with your brand.

Here, you’ll be looking to identify critical engagements that spurred the customer to take further action. Perhaps it was a well-timed email, or a quick-yet-thorough reply via live chat. Whatever the case may be, it’s important to know which support structures your target audience are relying on — and to focus on optimizing these structures over time.

You can also work with your current customers to determine what you might have been able to do better throughout their initial experiences with your brand. Here, you can survey your customers, looking for answers to questions such as:

• What do you know now that you wish you knew before you started using our product?
• What information may have made your purchasing decision easier?
• How could we have better prepared you for the next steps in your journey?

This can help you pinpoint opportunities to provide support that you’d previously overlooked (and that may be causing hesitation on the part of your prospective customers).

For example, after analyzing their audience’s path to purchase, software company RocketLink realized they weren’t providing enough information to first-time site visitors about their tool’s features.

To fix the issue — and provide better support to future customers — the team simply added descriptors of their tool’s most-used features to their homepage:

Needless to say, these added descriptors provide much more information for new prospects — making it much easier for them to move forward with a purchasing decision.

Your content’s performance data can also give you great insight into how to better support your customers before they convert and/or even use your products.

Think about:

• What content has generated the most engagement?
• Which gated content has the highest conversion rate?
• Which knowledge base or FAQ pages are getting the most traffic?

Look to your most popular blog posts and knowledge base articles, your highest-converting gated content, and other content initiatives. This will determine what topics your audience is interested in, and what information they consider “need-to-know” for productive use of your product. In turn, you can continue creating content focused on these areas — providing proactive customer support for current and future customers alike.

(In getting “meta” with your analysis, you’ll also want to identify ways to optimize your current content to enhance your customer support efforts, as well.)

Finally — and perhaps most importantly — you’ll want to assess any data related to your user onboarding processes. The goal is to identify where your new users were able to do what they set out to do — and where they needed more support.

Note: Session recordings allow you to easily pinpoint these critical onboarding moments in order to improve them as needed.

On just the surface, this will allow you to optimize your customer onboarding experience as needed. Whether this means adding supplemental information, being more clear with instructions, or even just making changes to the UI, it’s all about guiding your new users through correct use of your product.

On a deeper level, understanding where your customers struggle during onboarding shows that further support in this area is likely needed across the board. This goes back to the idea of creating in-depth, informational content to proactively support customers through problems they haven’t even faced yet.

Again, your customer support efforts should begin well before your customers convert.

(Really, without these initial support efforts, you probably won’t even get a chance to deliver more value to them.)

By looking at what’s worked — and what hasn’t — for your current customers along their path to purchase, you’ll know exactly how to support your new prospects as they begin their own journey with your brand.

Analyzing Product Usage Data to Enhance Real-Time Support

Understanding how, when, and why your customers use your product is essential for providing both proactive and ultra-reactive customer support.

The goal is to make improvements to your product and UX that allow your users to receive even more value while putting in less and less effort.

Again, session recording and analysis is key, here.

With LiveSessions, your support and design teams can gather in-depth insight into your customers’ hands-on experiences with your product from both a high-level and granular vantage point.

Looking at your entire audience, you can assess overall engagement with your product:

From there, you can identify surface-level anomalies (e.g., shorter-than-average sessions, inactive sessions, etc.) — and dig deeper to identify where problems may have occurred.

As you dig into your product usage data, you’ll be looking to identify:

• The features and functions your users rely on — and the ones they have trouble with (or avoid altogether)
• Their success rate for completing specific tasks, and the average time it takes to reach certain milestones
• Where engagement tends to drop off and session terminations spike

The next step is to figure out how to increase the amount of support you provide at these critical junctures to better equip and enable your users.

How you do this depends heavily on the situation.

In some cases, it may be that your interface needs to be tweaked for better usability. If you notice instances of “rage-clicking”, hesitation, or session termination increasing during a certain task, you’ll know to focus on improving these processes within your product.

Remember: “Customer support” isn’t always about providing additional help. Often, it’s about ensuring your users don’t need hands-on assistance to accomplish the task at hand.

In other cases, it may be necessary to provide additional support to your users.

(For example, you may find your users avoid a specific feature simply because they aren’t sure how to get the most use out of it.)

In such cases, the level of support needed will determine how you proceed.

If possible, you’ll want to deliver the necessary information or assistance directly within your product. Pop-ups, overlays, and the like can deliver quick, focused tips at the exact moment your users need them.

Similarly, a live chat or chatbot option can allow your users to get the help they need without having to navigate away from your tool:

For these cases, your focus will be on preparing your live chat team as well as effectively building your chatbot to efficiently deal with these critical issues as your users encounter them.

(Of course, you should also continue to streamline these processes for the user in the first place.)

You’ll also likely find spots where your users need much more assistance than can be given directly in-app. This, to be sure, is the nature of SaaS tools: There will always be something more your users can learn about how to best use your product.

At any rate, failing to provide further resources at these moments can cause users to become confused and frustrated — and may even be the reason they churn.

And, it’s not enough for these resources to exist, either.

A huge part of customer support is making this support as accessible as possible for your users — to the point that they barely have to even search for the answers they’re looking for.

Take project management software Monday, for example.

For novice users, an in-app video delivers the basic info needed to get started with Monday’s software. However, for users that want to get started right away, clicking a project item provides them with additional information to ensure customer success

Once again:

To deliver such structured, anticipatory support to your users, you need to have clear visibility into how they use your product, and into everything that goes on as they use it.

With the right data in hand, you’ll know what your users will need before they even come close to needing it. In turn, you can create the features, content, and other support structures necessary to lead your customers to success.

Using Post-Usage Data to Deliver Supplemental Support

Knowing what your users do after engaging with your product can allow you to enhance your customer support initiatives, too.

Really, the simple act of staying in touch with your users when they’re not using your product is an act of support in itself.

At the very least, you’re making clear to your customers that you see them not just as users of your product, but as individuals looking to accomplish certain goals. And, you’re showing them that you’re prepared to do whatever you can to help them reach these goals.

More than that, though, understanding where your users’ paths lead after they use your product (and in-between uses) can allow you to both fill gaps within their current experience and lead them to further success.

For your successful users, the questions you’ll be looking to answer here include:

• What were they able to accomplish after using your product successfully?
• What improvements have they noticed since using your product?
• What blockers are they still facing that may be keeping them from their true potential?

For users who may not have experienced success with your product, you’ll want to know:

• What were they unable to do when using your product?
• What gains did they expect to realize, and how did they fall short?
• What do they wish they knew about your product before they started using it?

The answers to these questions again lie in your users’ session data, as well as any feedback you collect from your customers over time.

Source: Refiner

Post-engagement feedback forms, bi-annual surveys, even exit surveys — when analyzed alongside your product usage data — can all provide valuable insight as to how to better support your customers moving forward.

Thinking of your successful users, your goal is to expand on the support you currently provide to help supercharge their efforts moving forward.

Depending on your users’ goals and experiences, this may mean:

• Creating more informational and practical content to help them become “power users”
• Adding advanced features to supercharge your power users’ efforts
• Developing entirely new tools or tiers of service tailored to specific user segments

For your unsuccessful users, your goal will once more be to add support structures throughout your user experience as needed.

This can take any number of forms, such as:

• Triggered pop-ups, push notifications, or emails delivering vital information at just the right time
• More focused, step-by-step directions delivered at critical parts of the user experience
• More effective and efficient person-to-person customer service

Your customers’ post-use actions and outlook, along with all other data you’ve collected on them thus far, should give you a crystal clear idea of where they need more support — and what you need to do to give it to them.

Wrapping Up

Customer data analytics is key to improving your customer support initiatives in an impactful way — and minimizing your audience’s need for hands-on support in the first place.

By gaining better insight into how your customers use your product and engage with your brand, you’ll be able to focus on delivering support — proactively or upon request — whenever it’s needed most. Moreover, you’ll be better equipped to optimize your support efforts at these critical junctures, which in turn will make your users more likely to persevere (and less likely to churn at the slightest bump in the road).

While there are many ways to analyze your customers’ behavioral data, LiveSession’s recording and analytics tools allow you to actually see these behaviors in action. In turn, you’ll then be able to identify areas where more support is necessary — and can start making the necessary improvements to deliver it as needed.