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I recently attended SAS’s European analyst event, where I went to focus on new developments around customer intelligence, an application of big data that SAS includes in its high-performance analytics and visual analytics. SAS offers an amazing number and range of products that is hard to keep track of, so I was glad to get a sense that now it is focusing more on business solutions built with data visualization and discovery, big data, data management, cloud computing, marketing analytics (which appears to be the new branding for customer intelligence) and enterprise decision management. It appears that the European event followed closely the lines of the U.S. event my colleague Mark Smith attended; he offers an analysis of the company’s wider messages.

In my areas of interest SAS showed some pertinent developments. As I mentioned, it is now marketing customer intelligence as marketing and customer analytics. Last year its customer intelligence product focused on bringing together as much transactional data related to customers as possible and building from it complete pictures of the customers and their relationships with the company using the software. SAS appears to accept that in the future marketing departments will “own” the customer, and so it is bundling the products it acquired with Assetlink and customer analytics to help users build targeted marketing campaigns and track the success of those campaigns. I am not one of the analysts who subscribes to this view of Marketing’s dominance. In my opinion most CMOs don’t watch ads on TV, they don’t read newspapers so they don’t see print ads, they see email as a file transfer mechanism rather than a true communication tool, and they don’t realize that direct mail has become just junk. This isolation creates challenges in keeping up with consumers’ broadening communication preferences, which take away the main channels of old-style marketing. What is important now is the customer experience, at every touch point. These touches occur across the organization, and so I believe that we must see customer analytics in a wide perspective.

When it comes to big data, during an executive Q&A session SAS CEO Jim Goodnight was dismissive of the trend, saying it is nothing new and that SAS has been analyzing big data forever. To a large degree, I agree with him. Companies have always had lots of customer data – financial transactions, CRM records, letters, email and so on – and have managed to process it. What has changed, again, is the importance of the customer experience in conjunction with the much larger volumes of data customers generate because of their communication preferences. Despite pronouncements to the contrary from pundits and vendors, consumers still make millions of phone calls to companies. The information in these communications has largely gone unused, but companies now realize they contain valuable insights about customers, products and services that they want to discover. Then of course there is social media. The volume of posts has exploded, and companies need to find the tiny amounts that relate to them and to use those insights also to address customers’ issues and likely actions. Including phone calls and social media in customer data brings us into the realm of big data and the need to process the data in real time. Many customer experiences happen in real time – the phone call, the chat session, the post to social media – and to properly respond to interactions, companies need to know the customer and put the interaction into context so they can provide consistent, personalized responses. During one of the event sessions, we were shown how the SAS architecture lends itself to processing large volumes of data and producing the results in near real time, and thus is ideally placed to support the customer experience. SAS has planned product announcements for later this year, and when they arrive I hope to see that SAS has added processing of call recordings to the product.

Another big change has happened in the last year or so: We have all gone crazy for smartphones and tablets. It seems as if no one wants to sit at a desk any more, and everyone wants to work on the move. Vendors have to realizevr_ngbi_br_mobile_device_deployments that they need to provide capabilities for people to work while mobile. The SAS visual analytics product is its version of what my colleague Tony Cosentino calls mobile analytics which is continuing to grow according to our next generation business intelligence research and deployments . It enables access to the outputs of analysis on a smart device, typically an iPad. The demonstration we saw shows that such outputs can be visualized in just about any way users require, and users can click on a display to see the detail behind the information. What is different is that it also provides capabilities to build customized analysis models on the smart device using point-and-click techniques.  Results of the custom analysis are delivered back to the smart device, and the user can choose for the results to be updated as the back-end system data changes or to wait until rerunning the analysis. Once more the importance of gaining real-time insight into customer experiences makes these types of capabilities a “must have” in today’s competitive markets.

SAS is a very successful company, as was illustrated by its impressive financial results, growing employee numbers and an even faster growing ecosystem of partners. Its huge range of products can be built into solutions for specific customers or market segments. As it focuses more on solutions, especially around the customer, I hope to see less emphasis on marketing and more on broader customer-facing activities and the customer experience. SAS has the products, with the current exception of speech analytics, to build what is commonly termed the “360 degree view of the customer” and which my research shows is something many companies lack as they try to support these vital customer-facing activities. Given the plans we heard about for the coming year, SAS should be one of the vendors on companies’ short lists to support such initiatives.


Richard J. Snow

VP & Research Director

In never ceases to amaze me, the number of new terms and acronymsvr_inin_types_of_interactions_in_contact_center the contact center market generates. Just as everyone is getting used to the fact that customers interact with companies through multiple communication channels (multichannel for short), someone invents the term omnichannel and we all have to get our heads around what this means. My research into the contact center in the cloud shows that companies now support on average nearly five communication channels, and although the traditional channels are still the most common, as the chart shows, there are signs that new channels such as chat (used by 37%), social media (29%), text messaging (22%) and video (5%) are on the increase.

The term omnichannel connotes “all in one,” and in this context it implies that companies need to integrate all these channels to give customers the same experience regardless of the channel they use. But I can think of three reasons why this is almost impossible today. The first is that each of these channels uses different devices, and try as companies might, they can’t achieve the same experience on a small mobile device, a laptop, in a text message, in 140 characters, face-to-face, or during a video call. Second, many companies still operate legacy communication systems, especially on-premises, proprietary ACDs, and integrating these with new channels is too costly in today’s economic climate. Emerging contact-center-in-the-cloud vendors such as EchopassEnghouse Interactive, Five9Interactive IntelligenceLiveOps and NewVoiceMedia offer a solution as their services typically include integrated multiple channels of communication. Even so, companies are often faced with deciding how to integrate these with their existing systems. Third, my research also shows that interactions are increasing handled by people in the lines of business, which are spread across the organization and typically have their own processes, systems and customers; therefore customers are likely to get different information depending on the line of business they interact with.

Another important factor is that many companies don’t truly know their customers. My research into customer relationship maturity shows that fewer than one in three (31%) companies produce a single report and analysis of their customers that is shared across the organization. This means that the lines of business are acting on different information, another reason why it is almost impossible to provide a single, consistent experience at all touch points. As companies add more channels of communication this challenge becomes greater, especially when they need to integrate more and more unstructured data into their customer analysis – the big data effect. Adding more channels of communication introduces yet another challenge. Typically each channel uses a unique identifier, and business applications have additional keys; these include, for example, a phone number, an email address, a Twitter handle, an account number or an order number. To truly know a customer companies therefore must link all these identifiers so they can, for example, identify that a current caller is the same person who posted a tweet and sent an email.

To deal with these challenges, I recommend that companies take the following steps:

  • Improve the quality and consistency of their customer data so they have one up-to-date master customer record.
  • Apply customer analytics to every possible source of customer data, including transaction, interaction and event data, structured and unstructured data, and historic, real-time and predictive analysis.
  • Use this analysis first at every touch point to know the customer.
  • Use this analysis also to put the current interaction into the context of previous interactions and the overall relationship with the customer.
  • Use this analysis in combination with rules-based logic to make the response personal to the customer and relevant to the issue raised, and therefore likely to result in the desired business outcome.
  • Above all else, companies need to ensure that they provide consistent information across channels and lines of business. Otherwise they face the prospect that customers will channel-hop until they get the information or outcome that suits them best. Such a process is likely to cost companies customers and sales.

I am not sure such an approach will produce an omnichannel customer experience, but it provides a practical, achievable process that is likely to improve the customer experience and outcomes. I would welcome comments on how others view the concept of omnichannel customer experience and how they intend to achieve it, so please come and collaborate with me.


Richard J. Snow

VP & Research Director

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