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4 ways advanced analytics can help exceed customer expectations

 | 5 min read
4 ways advanced analytics can help exceed customer expectations

In 2020, companies across countries and industries scrambled to stabilize operations, ensure the health and safety of employees, and find ways to continuously deliver. But in the wake of all this uncertainty, one thing remains crystal clear: customer engagement is more crucial than ever.

After all, with uncertainty comes doubt. Customers may be on edge, and they need reassurance that organizations will continue to meet—and exceed—their expectations. This calls for more proactive strategies and technology.

Advanced analytics, for example, lets you monitor key metrics and anticipate common issues to keep customer satisfaction in check. This way, you can make consumers feel reassured, safe, and cared for—even after the pandemic.

4 customer-focused strategies powered by advanced analytics

Organizations have long relied on advanced and predictive analytics to transform businesses. Using machine learning, these methods turn raw data into actionable, valuable insights that can help you make better, data-driven decisions. Essentially, not only will these insights answer the question “what happened?” but also “what will happen” and “what should you do?”.

To explore this in more detail, below are 5 ways you can leverage advanced analytics to improve experiences and inspire customer delight across touchpoints.

1. Providing personalized experiences

You might have an ideal customer, a target persona with set attributes and preferences. But no matter how niche your market is, there will always be key differences between your buyers or clients. No two consumers are the same, so you should avoid the batch-and-blast approach if you want to exceed their expectations.

Your goal then is to incorporate personalization into your campaigns and strategies. Research shows that when a customer has a personalized shopping experience, 44% is likely to become a repeat buyer and 39% is likely to share their experience with their friends and family. By providing targeted experiences, you’re letting customers know that you understand them, know their preferences, and are willing to provide them with what they need. In other words, your customers will feel heard.

Cluster analysis dashboard: You can segment customers based on various attributes.

Personalization starts with creating customer segments. Using clustering machine learning models, create segments based on geography, time, channels, behavior, and other dimensions. This means that you’re grouping customers into several buckets, with certain attributes to distinguish the clusters.

Segmentation not only allows you to provide hyper-relevant content, services, and promotions, but it also lets you zero in on certain customers. For example, if you’re looking to maximize acquisition costs, you can choose to focus on segments with high customer lifetime values, a high likelihood of engagement, or a high propensity to purchase. If your goal is to successfully introduce a new product, you can target segments who purchased similar offerings or those whose usage patterns denote interest.

All in all, advanced analytics enables you to provide the right offerings to the right people at the right time.

2. Anticipating customer behavior and needs

You gain customer’s trust and loyalty when you provide expected solutions. But you can take this even further by being one step ahead of them. Anticipating what they need is one of the best ways to let them know that you have their best interests in mind.

Deliver products, features, or solutions even before these are expected, and this will do wonders for customer retention. And remember: just a 5% increase in retention can already go a long way. It can actually lead to as much as a 95% increase in profits.

To anticipate customer needs, you need to keep track of key metrics. And it’s not enough to just monitor these through regular business intelligence reports, which is why you’ll need to leverage more advanced analytical methods. Utilize predictive analytics to get foresight in terms of these metrics, and this will allow you to either improve experiences proactively or avoid critical issues or complaints.

One metric you can focus on is churn. Using data from past interactions, predict likelihood to churn by determining the factors that significantly affect abandonment risk. This way, you can identify those who are likely to cancel their subscription, abandon their shopping cart, or even close their account. Use this foresight to provide extra attention to these high-risk customers through targeted offers and timely communication.

3. Improve customer service accessibility

The pandemic has led to disruption everywhere, whether you’re in aviation or retail. This might have caused a lot of frustration for your customers: they may have to deal with cancelled flights, they may have lost internet connectivity, they might be growing impatient with shipping delays, or they may just need access to information.

While it might not be possible to solve every customer’s problem or issue right away, you can at least ensure the availability of your customer service department. Call volume drastically increased during the pandemic, with an 800% growth compared to normal levels. Your agents are probably bombarded with more inquiries and issues than they can handle. So, how do you ensure that consumers can contact your organization when they need to?

An advanced analytics dashboard that shows predicted customer churn
An advanced analytics dashboard that shows predicted customer churn

Through forecasting algorithms, you can avoid underestimating or overestimating call volumes. Anticipate specific time periods when a higher inbound call volume is expected and make optimal staffing and scheduling decisions based on this foresight. Managers can determine strategic agent start times, end times, and break times. This way, you can ensure that calls do not exceed your contact center’s capacity and that it is equipped to handle an in-surge of calls.

With operations streamlined and inefficiencies reduced, you can reduce call waiting time, boost customer satisfaction and protect company reputation.

4. Creating delight with high-performing staff

Agent performance goes hand-in-hand with customer satisfaction. Aside from making sure that there would be enough agents to handle a high call volume, you can take this a step further and ensure that the right agents are available.

For example, not all agents will be able to resolve refund requests or service modifications. As you make staffing and scheduling decisions, ensure that agents with the appropriate knowledge and skill levels are available to provide the required resolution.

To optimize agent performance through advanced analytics, you’ll need to look at two key metrics: average handle time (AHT) and first-call resolution rates (FCR). The former is the average time required to handle a call and the latter is a measure of how well customer issues are resolved the first time they call. Both metrics can help gauge customer satisfaction. The lower the AHT and the higher the FCR, the more satisfied your customers tend to be.

Using advanced analytics to improve first-contact resolution rates.
Using advanced analytics to improve first-contact resolution rates.

Leverage predictive analytics to determine factors that drive up AHT and reduce FCR. Unlock insights that will help you discover inefficient processes and identify roadblocks in agent performance. Not only will these insights help reduce repeat calls and abandonment rates for a smarter contact center, but they will also inspire confidence in agents to handle interactions efficiently and effectively.

Happy customers = better business outcomes

One important thing to remember is that both happy and unhappy customers tend to share their experiences. The question is, which experience about your company would you like broadcasted to the public? Improve outcomes and protect your brand reputation by making customer success a priority. Your business has readily available tools to take control and leverage advanced analytics. Get the foresight needed to deliver contextually relevant experiences across touchpoints, stay on top of crucial customer complaints, and respond to their needs at a pace they expect.

About the author

Fiona Villamor

Fiona Villamor

Fiona Villamor is the lead writer for Sryas, a global technology company that delivers powerful insights and business transformations at scale. In the past 10 years, she has written about big data, advanced analytics, and other transformative technologies and is constantly on the lookout for great stories to tell about the space.

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