Ventana Research Analyst Perspectives provide unique fact-based insights and education on business, industry and technology vendor trends. Each Analyst Perspective presents the voice of the analyst, typically a practice leader and established subject matter expert,  reporting on new developments, the findings of benchmark research, market shifts and best practice insights. Each Analyst Perspective is prepared in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable, actionable news and insights.  

SAS Make Customer Intelligence Engaging and Valuable

My colleague David Menninger recently wrote about the SAS Analyst Summit, concluding that “the SAS analytics juggernaut keeps on truckin’.” He observed, as I have done in the past, that SAS has a vast array of products that it regularly updates to keep up with market demand, ensuring it remains one of the premier vendors of data management and analytics systems. Dave’s perspectives provide in-depth insights into what these products do, while I focus on how they help with business outcomes around customer experience. I was therefore intrigued to hear at SAS’s European analyst event that its products support four types of user – data scientist, business analyst, intelligence analyst and IT analyst. The presenter used simple quotes to illustrate the differing priorities of these groups: For the data scientist, the one that caught my eye was “I need the latest algorithms to solve the latest problems”; for the business analyst I picked “I need to get my report done quickly and easily”; the information analyst is about “identifying patterns of interest that can prompt active decision-making”; and the IT analyst is about “issue resolution and redemption” (mainly operational analysis). In short each type of user needs different products and capabilities, hence the array of products. Nearest to my research practice is the business analyst, who wants easy access to reports and analysis to resolve business issues, and this is where the company’s Customer Intelligence product plays a part.

As I previously wrote this system has evolved into what SAS calls its Customer Decision Hub. It brings together a number of products so organizations can capture and synchronize all forms of customer data to “deliver the best customer experience.” The Decision Hub can gather customer data from a variety of sources and synchronize it for a customer. It provides rules to govern what happens to the data and how it is used, and reports, analysis and prompts so that employees can deliver information to users and customers in the most appropriate manner. It also includes an array of other capabilities such as information to drive marketing campaigns, data to support event-based interactions, customer journey maps and a 360-degree view of the customer. The latest version of the Decision Hub improves support and capabilities to better manage Web-based interactions, email, mobile and social media channels of interaction.

The next step in its development is SAS Customer Intelligence 360. It is an enhanced version that has a single HTML5 user interface, additional public and RESTful APIs so that data can be collected from third parties, a single data and decision hub for all things related to customer experience and support for both inbound and outbound interactions across all channels. It is available as a multitenant cloud-based service, but data can reside on the user’s premises. Customer Intelligence 360 includes four components. Master Audience Profile supports collection and synchronization of all sources of customer data, both internal and third-party, to build customer profiles. Workflow and Collaboration support creation and development of marketing content across multiple groups. Intelligent Orchestration manages engagement across channels to ensure that customers receive consistent information and to harmonize marketing programs. Unified Measurement and Optimization helps analyze the outcomes of engagement and marketing programs to optimize them in the future. Together these components enable organizations to build complete pictures of their customers, ensure that business groups coordinate how they engage with customers regardless of purpose or channel, and analyze the outcomes to improve them.

Some of these messages obscure what for mevr_Customer_Analytics_08_time_spent_in_customer_analytics is an important feature – the single customer data hub. Our benchmark research consistently shows that organizations have a diverse set of customer-related data source: business applications such as billing, CRM, and ERP; communications systems such as voice, email, text, Web and chat scripts and social media; and operational systems such as network control that provide event-based data such as calls made, films downloaded or energy used. Managing all this data creates issues for organizations. Indeed, nearly two-thirds of organizations participating in our research into next-generation customer analytics said that the data they need as input into customer-related analytics is not readily available. The research also finds that users spend more of their time preparing and reviewing data than they do analyzing the outputs, which undermines productivity and impedes getting actionable information to decision-makers.

SAS offers a combination of data management and analytics to overcome these issues. Buried inside the data management tools is another key capability – identity management. Our research into next-generation customer engagement shows that companies support an average of nearly seven communication channels, and each of these is likely supported by different systems. In such cases, each interaction record has its own unique customer identifier or combination of identifiers, which are difficult to standardize and use as one. To get close to producing a 360-degree view of a customer or a journey map of channels used, organizations need systems that link all these identifiers so the data can be associated with a single customer. The tools in SAS Customer Intelligence are among the few I have come across that do this; I recommend that companies looking for such analysis should carefully evaluate this product.

I support Dave’s view that the SAS juggernaut is rolling on, and systems such as Customer Intelligence can help companies improve customer engagement. However, as organizations evaluate such products, I caution them not to get bogged down in all the components but to look at the overall system and how it can ingest and manage all the organization’s data and any from third-party sources; scrutinize how easy it is to use for all the different potential users. It is also worth remembering that the early focus for Customer Intelligence was to support marketing, and many of its messages are still colored by such thinking. Everything I have seen and heard in recent briefings shows it is applicable across all customer-facing business groups, including the contact center, so I recommend organizations looking to improve enterprise-wide customer engagement evaluate how SAS can help.

Regards,

Richard J. Snow

VP & Research Director, Customer

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Modeling Revenue Recognition for Contracts to Meet New Regulations

I recently wrote about the challenge some companies will face in planning and budgeting when new revenue recognition rules go into effect in most countries in 2018. It’s important for companies that will be affected to be sure they have the appropriate systems, processes and training to handle the more difficult demands imposed by the new rules. With the change in accounting, the time lag between when a contract is signed and when a company recognizes revenue from it may be more variable and less predictable than in the past. In extreme cases, performance measured by financial accounting will diverge materially from the “real” economic performance of the organization. Consequently, executives – especially those leading publicly listed companies – will need the ability to look at their plans from both perspectives and be able to distinguish between the two in assessing their company’s performance. In companies where the timing of revenue recognition can diverge substantially from current methods, financial planning and analysis (FP&A) groups will need to be able plan using models that incorporate financial and managerial accounting methods in parallel. They will need to be able to identify actual-to-plan variances caused by differences in contract values booked in a period and differences between the expected and actual timing of revenue recognized from contracts signed in a period.

I don’t want to overemphasize the impact the new revenue recognition rules will have on companies’ planning. While some companies need to understand that they will have to alter their planning and review processes, I expect that most will be unaffected by the new accounting for contracts, for at least one of three reasons:

  • A majority of their revenue does not come from contracts. (Retailing is one industry in which many companies do not transact business using contracts.)
  • No single contract or type of contract is large enough to have a material impact on reported revenue.
  • The time lag between signing a contract and fulfilling the contract is short (a month or less) or the time lag between booking a contract and fulfilling it is reliably consistent from month to month or quarter to quarter.

For many companies, tracking individual contracts will be unnecessary, impractical or both. It may be unnecessary because the relative size of contracts matters. Even if an organization’s individual contracts differ significantly in terms of the interval between signing it and recognizing revenue from the transaction, if there are enough of and even the largest represents an insignificant percentage of total revenue, the difference won’t matter. That is, in most cases the difference between expected and actual timing of revenue recognition of individual contracts is likely to be cancelled out. Moreover, tracking individual contracts will be impractical for many organizations because their volume will make it is too expensive and time-consuming to capture the relevant terms and conditions for each contract, which is necessary to be able to isolate the factors driving actual to forecast or budget variances. For FP&A groups the challenge will be in creating models that accurately forecast the average lag between contract signing and when revenue is recognized. Analysts also should confirm that the standard deviation of this lag under the new rules will be small enough to avoid the need to segment contracts into major types. (I’ll return to this point shortly.)

Nonetheless, a significant number of organizations – either entire corporations or business units with revenue responsibility – will need to change their approaches to creating and using planning models in order to accurately measure variances between their plans or budgets and their actual results. This means developing models that enable them to separate variances that are the result of differences in when business was booked and those in which the timing of the revenue recognition process turned out to be longer or shorter than expected. Certain types of businesses that have large, complex contracts with their customers, such as aerospace, construction and engineering, are likely to find that they need to plan and track results by contract – at the very least the 20 percent of their contracts that account for 80 percent of their revenues.

Another type of company or business unit that will need to adopt a more granular approach to tracking contracts  under the new rules is one in which there are significant differences between the timing of revenue recognition for different types of contracts. Even though the value of individual contracts booked in a period is an insignificant percentage of the total, it may be necessary for organizations to segment contract bookings and revenue recognized for each major type of contract. This would be the case if there are significant differences in the timing of revenue between types of contracts and the mix of contract types varies from one month to the next. For example, imagine that Company X has contracts that have three distinct revenue recognition profiles. In one of them, which accounts for one-quarter of annual bookings, there is a consistent one-month interval between when the contract is signed and when revenue is recognized. For a second type of contract (representing 40 percent of annual bookings) it can take up to several months before revenue can be recognized, and then it happens all at once. The remaining contracts are recognized over a year after a contract is signed. Any significant differences in the mix of contract types signed from month to month will make it difficult to reconcile variances and accurately identify differences caused by better than expected or inadequate contract bookings and those caused by timing differences.  So it’s necessary to create and use models that segment revenue by mix of contract types.

It is time for companies to get serious about adapting their business to the new revenue recognition rules. They will have to cut over to new processes and systems in 2017 to comply with the new standards and be able to make year-on-year comparisons when the new methods go into effect in 2018. Financial planning and analysis groups should be considering whether their forecasting, planning, budgeting and reporting models and processes will need to change under the new accounting standards. Those that will have to change should look into acquiring a dedicated planning and budgeting application if they (or affected business units) are currently using spreadsheets for planning. That will include many organizations: Our next-generation business planning research vr_NGBP_09_spreadsheets_dominant_in_planning_softwarefinds that two-thirds (65%) of companies use spreadsheets to manage their budget process. A dedicated planning application will help them prepare better to understand whether a difference was due to the new accounting rules or poor performance using actual data rather than opinions.

FP&A groups should be aware of their company’s exposure to new revenue recognition rules. If the rules will have a material impact on how the company accounts for contracts, they should determine whether it will be necessary to plan and budget for “real” and accounting data in parallel. If so, and if their company currently plans and budgets using desktop spreadsheets, I strongly recommend that they look into acquiring a dedicated planning application. In addition to dealing with increased complexity, this type of software can improve the budgeting and planning processes, making them more efficient.

Regards,

Robert Kugel

Senior Vice President Research

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Rescuing Retail’s Mobile Customer Experience Requires New Technology

One aspect of living in downtown Chicago is that there’s always something going on. But as distasteful as the subject matter of certain local events can be, some proceedings can inspire perspectives on a number of topics. One that occurs to me is how the retail industry can apply the new generation of mobile and location-based technologies not only to shape the customer experience but even rescue it from challenging situations. On Nov. 30, 2015, the Chicago Tribune reported that the Black Friday protests on the city’s Magnificent Mile cost local businesses 25 to 50 percent of their expected sales. While protestors have a constitutional right to free speech, business operators also had an opportunity and a responsibility – to proactively engage customers before, during and after the tumultuous Thanksgiving holiday weekend.

As many of us will recall, the events that led up to the protests in Chicago on Friday, Nov. 27, 2015, were tragic. News was made when a dashboard camera video surfaced showing a Chicago police officer fatally shooting 17-year-old Laquan McDonald. As a result, the officer in question has been criminally charged and is awaiting trial. When the video was released, tensions permeated the city. Emotions ran high, and protests became a part of the city’s downtown landscape. But let’s be clear about that Black Friday on the Mag Mile in Chicago. Retailers and many other business owners in that high-end shopping district knew that protesters would take to the street that day in an attempt to halt commerce. Retail operators also knew that their customers would share that busy street. Nevertheless, I know of no business that chose to close in advance of the protests. Moreover, I’ve yet to learn of any business that made plans to protect their customers’ collective holiday shopping experience, let alone secure the revenue that might accompany it. In my opinion business operators on North Michigan Ave. failed their customers and stakeholders on that Black Friday.

Media reports claimed that the Black Friday protests in Chicago were peaceful, and a festive atmosphere even accompanied one local television reporter’s account, as she proclaimed that the stores were open and people are shopping! But in a few hours, the consumer shopping experience dramatically changed. As seasonal rains came that evening, protestors systematically cut off street-level access to retail locations, leaving bitter customers out in the cold. Stores began to lock their front doors. Many, including globetrotting tourists, stood confused and abandoned. If retail operators had anticipated this scenario, they could have thrown a lifeline to marooned shoppers by developing a technology-assisted customer experience plan that could have rescued the situation and even saved a substantial loss in holiday sales.

The retail industry’s keys to meeting the challenges presented by Chicago’s Black Friday protests should have consisted of five components: segmented and robust customer data; a strategy for mapping local consumer shopping territories via geo-fencing and real-time analytical insight into individual location information; two-way acceptance of mobile communications; a customer-centric technology infrastructure; and a consumer team that possessed the dedication and creativity to respond quickly to rapidly changing market conditions.

As Black Friday events began to unfold, affected retail operators should have executed a communication plan that immediately addressed known local customers. Advisory communications could have been sent via email or text message to local residents, holiday shoppers or not. Those personalized messages could have been reinforced by notices posted to all available social media channels. Moreover, retailer operators in tune with their mobile customers could have reaped the benefits of acting on customer proximity and location analytics. Retailers with robust mobile customer relationships could have utilized geo-fencing technology and intelligent consumer apps to immediately interact with those who were inside the protest zone and in close proximity to one of their stores. Any interactive mobile customer who became locked inside or outside a store, or who was connected to a retailer equipped with beacon technology and a customer experience platform augmented with real-time location analytics, could have been guided down alternate paths to open and accessible locations, optional online services or even a secure personal refuge.

For retail operators interested in the ability to quickly engage customers in the midst of any rapid change in local conditions or market dynamics, the overarching challenge has become threefold: securing a customer base that will opt in to mobile technology in advance of receiving real-time communications; employing talent that can creatively craft breakthrough notifications; and adopting a technology environment focused on making the most of opportunistic omnichannel customer experiences.

Indeed, retail operators who proficiently use next-generation location-based and mobile solutions can make the most out of every individual interaction and stand to benefit from measured increases in sales, service, customer satisfaction, organizational alignment and competitiveness. Vibes Media is one technology provider of products for GPS-enabled, location-aware mobile devices that can access latitude and longitude coordinates near stores in order to trigger important notifications. Contextual marketing tools from Pitney Bowes allow marketers to deliver messages to customers at any time and place, across preferred channels of communication. Moreover, one can imagine how geodemographic segmentation offerings from ESRI could have been used to proactively beat competing Chicago retailers to the punch in the hotly contested local shopping arena. Our benchmark vr_LA_location_analytics_delivers_business_valueresearch on location analytics finds a variety of ways in which such systems can benefit businesses; improving the customer experience is the one most often cited (by 20% of participants).

The pace at which retailers are using the new generation of interactive technologies to revolutionize the mobile customer experience must increase. The volatile situation in Chicago is far from over and may be replicated in other cities. It is only one example of what any retailer anywhere and its customers could face in the near future. Some mobile technology services have been designed to support customer loyalty initiatives, and they should be rolled out in the effort to generate sales and  revenue, as well as being implemented in the service and support of customer communities. For retail operators who possess the imagination and initiative to employ the mobile technology required to adapt to unforeseen business situations, there are no limits to what they’ll be able to do for their customers and accomplish for their business, even under seemingly insurmountable stress. The revenue they’ll be able to source and the customer loyalty they’ll be able to report as a result of these efforts will be proud measures of industry success.

Regards,

Tony Compton

Vice President and Research Director, Sales and Marketing

Follow me on Twitter and on LinkedIn


 

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