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Big Data Spurs Internet of Things and Makes What You Know Valuable

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“Knowing your customer” has always been good advice for both sales and support organizations, whether through handwritten index cards or automated CRM systems with popup screens tied to your phone system. It helps to offer a personalized customer experience. But there’s more than just a customer’s profile that sales and support executives should be aware of.

What if you knew what your customers wanted even before they knew it themselves? That’s the promise of Big Data-driven predictive analytics.

Big Data fuels the Internet of Things (IoT), which enables connectivity of people, things, process and data. What makes a product valuable isn’t the quantity of data it provides, it’s what the product does with that data.

Newly evolving customer support models deliver two distinct opportunities. First, reduce costs through support automation, and second, provide better service through knowledge management.

The support automation component handles routine, day-to-day requests – those that can be fulfilled through either entry-level staff or self-service knowledge bases. A majority of support requests are similar in nature and, with an organically growing knowledge base and mechanisms of automated support delivery; they can often be resolved using automated tools. Information collection may not be the only area gaining a benefit – it’s also possible to automate the process of pushing an app or a bug fix to a customer in response to a specific need or request.

The industry is learning that not all support requests can or should be addressed through these new automated mechanisms. When a request is simple, most customers appreciate a quick and automated fix, but the real value of this system is demonstrated when the support center can provide meaningful, live staff time to requests requiring more time and attention.

In either case, a support organization driven by Big Data, analytics, and the cloud has distinct advantages. When a customer calls, it is possible to know details in advance, on two fronts:

1. Customer-specific data, such as whether a caller is likely to need an upgrade, more supplies, or may have made a recent purchase that needs a support contract; and

2. Trend-specific data, which allows agents to identify broader analytics that are likely to predict what the customer may require.

This information centered approach to customer support takes more than a stack of index cards. To accurately gather detailed and predictive data, large amounts of information must be gathered, analyzed, and applied. Gaining deeper insight into each customer has two positive outcomes – it creates an environment where the customer is better served, and generates opportunities for additional revenue streams by revealing what the customer may likely want or need.

Know your customers better to serve them better

By knowing the current asset profile of your customers in advance, service requests can be mapped to the best available resource. This also does away with the need to repeatedly ask customers about the configuration of their machines or seek other information. So, you can speed up the resolution time and offer a more satisfactory service experience to customers.

Generate new revenue streams

IoT is enabling organizations to engage with their customers in whole new ways and to create new business models. Enterprises can target customers with marketing strategies to upsell products on the basis of their present asset profile or by predicting what they may require in future. Monetize out-of-scope opportunities and increase profitability through new and incremental revenue streams. You can also analyze the usage behavior of your customers to cross-sell value-added services, bundled offers, and lots more.

So, by knowing more about your customers, you can not only enhance the CSAT but also earn more by leveraging new revenue opportunities.


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