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The Real Low-Down on Real-Time Analytics

The Real Low-Down on Real-Time Analytics

The Real Low-Down on Real-Time Analytics

By Donna Fluss
1to1 Magazine

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The emerging real-time analytics market is confusing. There are many offerings coming from many market categories with nearly indistinguishable marketing messages. To make sense out of the confusion and find the value obscured by the marketing hype, let’s define analytics.

Real-time analytics should help companies make quick and accurate decisions by collecting and processing all relevant information – such as structured and unstructured customer data, transactions and inputs – from multiple sources, including telephone conversations, in “almost” real time, to provide immediate and practical feedback that can be used to improve performance and profitability.

This sounds hauntingly similar to what the CRM movement set out to achieve and hasn’t. Some people have asked, “Could real-time analytics be a replacement for CRM?” I say no. Companies who have invested millions of dollars in relationship initiatives are not going to throw them away, nor should they.

It’s a business strategy

At the risk of defying the prevailing wisdom, analytics is not reporting and not data warehousing, although it can use data from both these sources. Nor is analytics business intelligence (BI), decision support (DS) or personalization, although it may very well use these capabilities as well.

Here’s the bottom line: Just as CRM is an enterprise business strategy and not an application (as there can never be one application that addresses all enterprise systems needs for sales, marketing and customer service tools), neither is analytics simply a product. Rather, analytics is a business strategy that uses enabling applications including data warehousing, data marts, BI, DS, OLAP, modeling, personalization and reporting to achieve its goals.

If analytics is a business strategy, then real-time analytics is its logical extension that facilitates immediate action in all areas of the enterprise. The tools to enable this strategy are in their infancy. And because the uses for real-time analytics are varied and growing, the applications are coming from many market categories.

For instance, pharmaceutical companies need real-time analytics applications to collect and analyze feedback from drug trials in order to meet federal reporting guidelines. Telecom providers concerned about retaining profitable customers can user real-time analytics to quickly identify at-risk customers and address competitive challenges.

Financial-services firms seeking to optimize the effectiveness of their marketing channels (print, Web, email, broadcast and phone) can quickly identify their most successful medium and move marketing dollars accordingly. Retailers can rapidly assess customer satisfaction with products and services to speed up product enhancements and customer loyalty.

Sorting out the software

There is an important similarity in all the products entering the real-time analytics market, regardless of their functional category. Whether the market is survey software, data warehousing, BI, reporting, e-service, search, content management, knowledge management, quality assurance, speech recognition or text retrieval, all use a form of artificial intelligence – a text categorization engine – to interpret inputs from customers.

The underlying technologies of the text categorization engines are different and are suited for different needs. Which technology used matters, and the enterprises should carefully review the product they choose for compatibility with their environment. But the overall business application, implementation and ease of use are much more important and this is what prospects should prioritize.

Putting it in perspective

Enterprises need timely, useful and actionable information about their customers, and they need it at ever-increasing speeds. Yet, real-time analytics can only be as good as its underlying technology, which is still evolving. However, these applications provide a more accurate and timely view of customers than any other existing set of products. By converting large amounts of raw data into useful information in a matter of minutes, real-time analytics give an enterprise an advantage over competitors who continue to labor with unwieldy customer databases or even larger data warehouses.

Finally, real-time analytics isn’t’ a perfect name for this category, but it creates a “buzz,” and the excitement is driving positive change in corporations.

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