Improving Customer Satisfaction with Data and AI

Customer-service leaders have recognized a key ingredient is missing from their strategies: artificial intelligence.

customer satisfaction

2 minutes

Customer satisfaction matters. A lot.

Even small improvements in customer experience can increase likelihood of purchase. By the same token, small losses in customer loyalty can have a major impact on the bottom line. It’s especially true in a digital world where customer opinion can spread across social media, online publications, and rating sites like Gartner’s in seconds.

The challenge is that customer retention isn’t easy. Anyone who’s worked in customer service knows that keeping customers happy is hard. And it’s become exponentially harder as support has moved from an on-premises role to an almost exclusively remote, chat-driven role.

Data: Your Secret Weapon to Making Customers Happy (and Accelerating NPS)

When the only tools you have to interact with customers are a keyboard and a headset, data counts. Data on individual customers and your larger installed base provides a wealth of information for resolving issues. This includes:

  • Customer purchase and deployment records
  • System-level service analytics
  • Ecosystem analytics (how the product is interacting with its environment)
  • Corollary data from other customers
  • Service notices from component suppliers

Combined, this information enables your service teams to resolve issues faster and proactively remediate issues. This can have a massive uplift on customer sentiment and your company’s Net Promoter Score (NPS).

Get more information on NPS and factors we consider at Pure.

Unfortunately, not every organization is at a point where it can harness this data. Call centers, in particular, run into data-related challenges. Customer-service leaders have recognized a key ingredient that can mean the difference between having to push customers through multiple tiers of support teams and delivering a one-step service experience. 

That key ingredient? AI.

Pure Solutions for AI-driven Service Analytics

At Pure Storage®, we understand the need to deliver predictive and proactive support to customers with office locations anywhere across the globe. And we understand acutely what can happen if customers are not happy. That’s what has led us to invest heavily in strategy to deliver an AI-driven data-services platform for storage management. (Visit our Pure1® AIOps page for more detail.)

It’s a strategy that has enabled us to draw insights from across our install base so we can predict and resolve issues before they become outages. It’s a capability that helps our customers—in any industry and any location.

In our solution brief on services analytics, we provide an inside look at how we’ve designed a hybrid-cloud-based monitoring, fault management, and forward planning service for our customers,— backed by Pure Storage products like FlashBlade—that enables us to be more responsive to customers while optimizing costs so that we can invest further in services innovation.

We hope this gives you some unique ideas on how to enhance your own service analytics strategy and demonstrates why you can be confident that offerings from Pure Storage can improve customer satisfaction and your organization’s NPS score.