Customer Analytics Deserve More Than Spreadsheets

I recently completed two closely related benchmark research reports, on next-generation customer engagement and next-generation customer analytics. The  research on customer engagement shows that companies on average engage with customers through seven or eight communication channels and that almost every business unit except IT engages with customers. To provide customers with personalized, in-context and consistent experiences across these channels, companies need an up-to-date, complete view of their customers that gives those who interact with them the information they need to decide how to respond. However, the customer analytics research shows that the majority of companies don’t have access to such information and analysis. The most common analytics tool for more than half of companies is spreadsheets in 52 percent of organizations. Although spreadsheets meet individual users’ needs for ad-hoc analysis, they are inadequate for enterprise processes such as customer analytics. Almost three-fifths (57%) of companies in the research said that using spreadsheets makes it difficult to produce accurate and timely customer analysis.

We have identified key steps in any analytics process: setup and maintenance of the data to be analyzed, preparation of the data, analysis of the data, interpretation of the results and action. As my colleague Robert Kugel has often noted, most spreadsheet users are self-taught, and setting up and maintaining spreadsheets can be time-consuming tasks. Those with limited skills may stick to the basics and so miss out on more complex analysis. Indeed, my benchmark research finds that only 15 percent of companies said their employees have excellent analytics skills, and more than one-third (35%) of business users said they don’t get enough support from IT in using customer analytics.

In addition, companies are now generating enormous volumes of customer data, much of it unstructured, including call recordings, text messages, chat and Web scripts, CRM notes and social media posts. For spreadsheet users, extracting insights from so much various data requires considerable amounts of manual effort. For example, someone must listen to calls to extract customer sentiment from call recordings and then input the content. In addition, given the sheer volume of these types of data, many companies cannot process it all and therefore can’t produce a complete view.

Because of the lack of skills and the limited visualization capabilities of spreadsheets, most users settle for simple 2-D charts such as graphs, pie charts and line diagrams. Our research shows that almost three-quarters (72%) of companies are content to limit outputs to such charts and therefore potentially miss out on insights that could be uncovered through advanced forms of visualization. As many people before me have said, there is little benefit to producing information and analysis if you don’t use it to take action. Spreadsheets are limited also in capabilities to share outputs, and so most companies put that data into PowerPoint slides and share the results through email. Under such circumstances, it is likely that not everyone is using the same customer analysis, which in turn raises the likelihood of employees making decisions based on inconsistent information.

However, if spreadsheets are not the answer, what is? Our benchmark research shows that one in four (26%) companies have adopted a dedicated customer analytics tool and that those businesses have achieved on average nearly six benefits. The chief benefit is improvements in the customer experience, which 55 percent have realized. This is closely followed by seven other benefits, achieved by an almost equal number of companies: better analysis across a range of business needs (52%), better alignment across business units (51%), better sharing and communication across business units (49%), improved productivity (49%), improved efficiency of business processes (47%), faster responses to opportunities (47%) and enhanced competitive advantage (47%). All of these benefits are compelling reasons to change, but our research doesn’t show this happening: Only about one in three (29%) participants said they intend to change in the next 12 months.

This of course begs the question, Why not? The benchmark research finds the answer in a lack of focus on producing a compelling business case for change. It seems companies’ primary concern is the presentation of the business case, not the potential value of investing in customer analytics, finding the budget for such an investment and gaining executive sponsorship. Given that companies see spreadsheets as “free,” producing a case for spending money is not a priority for most. However, customers are the lifeblood of all businesses, so having a complete view of them is essential to marketing, sales, customer service and financial success. As such, I urge companies to look at the benefits others have gained using dedicated customer analytics tools and use them to build a case for change.

Regards,

Richard J. Snow

VP & Research Director

SAS Expands Business Relevance in Using Analytics

After the SAS analyst event last year, I wrote that it is hard to keep track of everything SAS has to offer because it had so many products and developments in the pipeline. Back from this year’s event, I can report that 2011 was successful, its revenue and worldwide presence are up, and SAS continues to expand its channels to market. On top of everything I saw last year even more products and developments are in the pipeline, but the theme and focus remain the same: enabling business analytics.

With a little help from some experts, CMO Jim Davis and CTO Keith Collins presented how all these products are being focused on five key areas in which SAS is enabling business analytics: high-performance analytics, business visualization, information management, decision management and cloud computing. Each profile included an impressive array of capabilities and roadmaps that showed SAS is not resting on its laurels but has an extensive R&D program with many new releases planned during the year. An important message was that high-performance analytics is the SAS approach to managing big data, which was mentioned often during the event. As CEO Jim Goodnight explained in simple terms, bringing high performance to analytics involves not just Hadoop or other big-data processing software, but executing analytics in memory and thus producing results much faster. For SAS, Hadoop and similar technologies provide data sources that its software can pull into memory and thus include in analysis. For a layman like me on this subject, the demonstration looked impressive. In my area of specialization, customer and contact management, the key point was that SAS works as well with unstructured data as is does with structured data, so it supports fast analysis of text and social media.

The second highlight was visualization. My research into contact center analytics and customer analytics shows that as well as needing analysis in near real time, users want systems to be easy to use, and more want to see results on their tablet devices. Judging from the demonstration, SAS has put a lot of effort into these areas, and I felt that with a little help from IT to set up the data sources, even I could learn to run sophisticated analysis of almost any form of data. And users can not only see the results on a tablet, but the mobile technology is interactive, so users can drill down into underlying information.

One area I still have questions about is SAS’s cloud strategy; for example, during question time Jim Goodnight was dismissive of the hype around the cloud. While SAS showed development in services supported in the cloud and promised more to come, I was left with the feeling this is something management feels it needs to do rather than embraces as a strategic direction pursued with the same vigor as other vendors.

Another session showed how SAS is channeling its products and developments into three key business areas: customer intelligence, fraud management and risk management. Several presentations illustrated capabilities in all three areas and roadmaps for multiple upcoming releases.

When I wrote recently about new developments in customer intelligence, I failed to note that the DataFlux subsidiary has now been fully integrated into SAS, which strengthens the company’s overall capabilities in two key areas. My recent research into customer relationship maturity shows companies struggling to manage multiple sources of customer data (both structured and unstructured) and thus are unable to produce a single set of reports and analysis about their customers. The combination of DataFlux’s customer data management capabilities and customer intelligence can address both issues in an integrated way. In particular, as organizations introduce more channels of customer communication, these combined capabilities enable them to produce the cross-channel analytics our research shows many companies are looking for.

Events like this always include customers presenting their own success stories. One analyst questioned the value of these because all the case studies are bound to be glowing; if they were not, SAS would choose other customers. This proved to be the case in my one-on-one session with a customer that had deployed some of the marketing products, the picture he painted was not as rosy as in the public presentation. There had been ups and downs during the project, but in answer to the crucial question, “Knowing what you know now, would you still choose SAS?,” the answer still was yes. The customer said his users love the product, and it is producing the business benefits his company was expecting. He also confirmed plans to extend its use of SAS products.

In summary, the event confirmed that SAS has lots to offer companies looking to improve their use of analytics. In my area of interest, SAS has the tools to help manage customer data, and to produce reports and analysis using data from multiple business units and data produced by multiple channels of communication –things that my research shows company struggle with but increasingly want to resolve.

Regards,

Richard J. Snow – VP & Research Director