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Now they're becoming services-backend infrastructure used to fully automate customer-facing systems (e-services and ASP-hosted services) and solutions used to leverage strategic consulting services.

Function aside, when you sort out the marketing hype and acronyms, the transformation of the use of analytic applications is really just indicative of a larger transformation having to do with the way business and customer intelligence solutions are being used. Companiesdepend on them and they are critical to their business. Companies rely on these tools not just to fill up data and crunch numbers but rather help analysts and decision-makers provide the insight necessary to solve important business problems.
Analysis efforts involving customer intelligence and business intelligence, moreover, are not isolated disciplines within an organization. Companies need customer intelligence to help determine who their customers are, what they need, and when they need it, and companies need business intelligence to respond and deliver effectively to their customers. The two disciplines not only feed off each other but are inextricably linked.

When all is said and done, analysis techniques (not software applications) will continue to drive innovation, and this year's bevy of analytic applications will morph into something else next year. To help decipher the future of analytic applications, we offer a few predictions for the road ahead.


We told you so

Delano Technology's announcement of its acquisition of Digital Archeology should come as no surprise. It is the latest announcement in a series of marriages that are taking place between analytic application vendors and customer interaction solution providers. The acquisition continues to reinforce the trend that we wrote about last year between providers of customer intelligence (CI) solutions and CRM vendors. The only difference is that, this year, the mergers have gone one step up the analytics food chain.

Last year we saw traffic analysis and personalization solution providers buying data-mining consulting firms and analytic applications in the quest to improve their online intelligence capabilities. Now we are seeing analytic applications vendors get together with campaign management, e-mail marketing, e-mail response, and even call center vendors to put those analytics into action-identifying optimal offers, segmenting mailing lists, and routing calls and messages to the most appropriate agents.

But it is going to go much farther than that! Now that the online marketing analytics loop is closing, the next quest is integrating the call center and other customer interaction touchpoints such as wireless gadgets and the amorphous Customer Interaction Portal (CIP) (which replaced the omnipresent and much-hyped Enterprise Information Portal [EIP]). This sets to the heart of why E.piphany bought both RightPoint Software and Octane Software, why Delano bought Digital Archeology, and why Broadbase Software bought Servicesoft Technologies. The injection of advanced analytics into CRM and Customer Interaction Management (CIM) systems will facilitate stronger integration of marketing, sales and service strategies, and tactics into a more holistic practice of customer interaction management.

The Internet and e-business are pushing companies into more intimate contact with their customers, forcing them to be individually responsive to the needs and desires of their customers throughout their relationships and across all touchpoints. This means that analytical applications should become integrated with the operation of business processes providing ranking, categorization, and profiling services to any process that needs them. With this kind of operational customer intelligence, businesses can structure customer interactions, not just according to static understandings of the customers identities are and their stated preferences but by up-to-the-minute understandings of customer behavior. Analytic applications can provide the operational basis on which to decide what steps to take. These steps include when to contact customers, how rapidly to respond to their inquiries, what media to use, what offers to make, and what content to render to them based on both real-time analysis and a process-oriented, scenario-driven understanding of the state of individual customers' relationship with the businesses.


Analytic Applications' Key Capabilities

Analytic applications provide CRM and CI solutions with three key capabilities:

1. The Ability to Quantify the Value of the Customer Interaction.
The analytic applications' reporting solutions help quantify the value of the customer interaction. The metrics tracked and reported can help guide e-businesses with their CI and CRM strategies. For example, call center managers, sales managers, and marketing managers can determine the number of customers that interact and purchase at particular touchpoints. They can also determine which touchpoint is best suited for doing business with customers (e.g., whether John Smith responds better to an e-mail campaign or Mary Jones prefers telemarketing).

2. The Ability to Set Thresholds to Trigger Rules and Events.
The results of the calculations that analytic applications provide can be used to set thresholds that can trigger business rules and events, which in turn automate the delivery of specific content (such as personalized offers and product recommendations). The analytic application can then be used as the "brain" to help facilitate real-time interaction and personalization. For example, I spent $500 buying books on line at books.com one week, and the site's analytic application calculates the average order size on a weekly basis. The analytic application could then compare my purchases against the average purchase rate metric and, if it's greater than the average, could trigger a special discount or coupon for future use.

3. The Ability to Help Qualify Customer Information.
Analytic applications can also be used in tandem with CI and CRM solutions to help sort out and qualify customer information, thereby enriching a company's customer intelligence data-gathering activities. When James Weston calls the customer service department to find out when the video that he purchased online will arrive at his house, the customer service department can then ask him what kind of delivery service he typically prefers. The information about the call can be entered into a CRM system and analytic applications can help determine how Jim's delivery preferences affect the company's current delivery services model. In this example, analytic applications could help the company determine if Jim's delivery service preference is profitable for the company.

Each of these capabilities fits into the gather, analyze, strategize, and act framework for delivering customer intelligence and ultimately fostering the development of a deeper mutually beneficial relationship between the customer and the company. This is, after all, the main goal of CRM.


B2C or B2B? Ho-Hum!

If these three capabilities seem like old hat to you and you are yawning at this point, you may have joined the ranks that find B2C boring! After all, B2B is where the action is. Dynamic pricing, e-markets, exchanges, virtual supply chains-this is really where the opportunity lies for e-intelligence, right?

It does seem to be where many analytic applications vendors are heading. The same crowd that ventured into CRM and campaign management last year have aggressively entered B2B e-markets this year. And, since these folks have gone B2B, guess how they're leveraging their analytic applications?

The same way they're used in B2C! The only difference is that the analytic applications track a broader range of business intelligence measures-especially in the supply-chain arena-and as a result of the increase in breadth are used to help support the decision-making in complex business processes rather than simple offer generation.


Shift from Analysis to Business Processes

The focus has shifted from marketing-centric data management and analysis to supporting and facilitating customer-oriented business processes. What does this mean for the players in the market? Again, we see several major trends:

1. Analytic Applications Are Becoming Services Rather than Standalone Enterprise Software Applications.
As Ray Lane, (former president of Oracle) recently noted, in the next five years enterprise application vendors (like Oracle and SAP) that currently sell business intelligence solutions won't be selling packaged software applications. Instead they'll be selling services over the Internet. "Software companies will be services suppliers. They'll innovate on order processing or on selling the intellectual capital needed to upgrade or change corporate business systems" Analysis fuels these hosted services, consulting services, and automated e-services. Whether the services take the form of a hosted services model, an ASP, or pure consulting services will depend on the nature of the service and the demands of the customers rather than the whims of the vendor. (If you believe that Microsoft will dictate the playing field for these models, you can probably ignore this point.)

2. Customer Intelligence Equals Business Intelligence.
In B2B commerce the complexity of decision-making mitigates the need to balance an understanding of the customer's needs and role in the decision-making and business processes with an understanding of the operational activities and business processes. This is where CI and BI become symbiotically linked. Companies need to understand who's making the key decisions (CI) as well as how to make the right decision (BI).

Depending on your perspective, the term customer intelligence may seem redundant, especially if customer intelligence equals intelligence for customer-focused companies. Given that it will take many companies time before they become truly customer focused, the term customer intelligence will still be useful for these folks so that they don't confuse the process of analysis for operational efficiency with the process of analysis for understanding customers.

3. Metrics Have Been and Will Continue to Be More Strategic than Tactical.
In and of themselves, metrics are not magic bullets. Any company that elevates them to received knowledge typically becomes the subject of a Dilbert comic strip. Metrics are used to guide strategy, but they don't make or implement the strategy-people do. Hence they will always be a tool for helping people to think, plan, and act. As a service, applications that deliver metrics can be used to help automate decision-making processes and facilitate consulting engagements in which the experts help companies understand what the metrics mean.

Companies that offer analytic applications are now offering strategic e-business planning and metrics analysis services. We are seeing, however, that many companies on the lower end of the analytic applications food chain-those vendors that have evolved from Web traffic analysis-have gone more into the metrics, strategic planning, and consulting service area than in the broader, automated customer interaction area. While it may be that consulting can inevitably foster these vendors' own internal product development, it may be difficult for them to catch up with the other analytic applications vendors that ventured into the customer interaction area this year. Time will tell.

4. Statisticians and Analysts Are Not Out of a Job;
There Will Continue to Be a Strong Need for Modeling and Analysis. No matter how much automation we have, we still need someone on the other end of the pipeline who can assess the analysis. This person needs to be able to understand not only what is being reported but how it was calibrated.

Also, no matter how much stuff is reported in real time, companies will also need to take a step back and do the trend analysis and predictive modeling that enables them to check their current strategies and steer successfully forward. Again, to do this you need skilled analysts who are trained in modeling and statistical analysis.

5. Analysis Techniques, Not Measures, Will Drive Future Automation and Innovation in Product Offerings.
Want to be able to improve customer retention rates through better target marketing? The solution may lie in how you define and select the segment model, not in how you net out the metrics used to calibrate retention. Metrics by nature are inherently historical and linear. You gain understanding by adding up the numbers and then calibrating what has occurred. Models, on the other hand, have dimensions, are complex, and their goal is often to predict what can occur based on historical data.

Just as you've learned in driving school, you can't go forward by constantly looking in your rearview mirror. You need solutions that can help you look ahead. Predictive models help you do this. And like metrics, both the models and the tools used to create the models are designed to solve critical business problems.

Consequently, the solutions that help companies create predictive models will continue to thrive and be a vital part of a CI and CRM infrastructure. Companies such as Lands' End and Ithena, for example, have developed tools that can help improve segmentation modeling, which is based onconjoint analysis techniques and set theory modeling. These analytic solutions are then applied and used with other software to improve online campaign management and personalization.


Conclusions and Pragmatism

How do these predictions affect your plans? If you are in the process of evaluating your current customer intelligence infrastructure, you will need to consider whether you are investing in an analysis application or analytic infrastructure for your business. Given the state of the market, you may need a strategy to bridge your plans for the present and the not-too-distant future. Your timeline for investing in these solutions may also be affected.

Some of these trends may also help sort out the hype that you've been hearing from marketing and sales presentations. If you're hearing that you only need a solution that can provide metrics and reports, you may want to do some research in how these solutions fully address some of the more difficult issues underlying your business and customer intelligence systems performance. Just because you're working in an e-business doesn't mean that you have to reinvent the wheel of analysis. Analysis is a learning process. It builds on what you've done and learned before.

Sometimes the obvious is mostly pragmatic. Perhaps these predictions aren't far-reaching but merely a summary of the present and the near future? As we race through the fall towards the end of the year, we'll definitely have a few more points to add to the trends list, points (perhaps to belabor) for the end of the year wrap-up and the year 2001 predictions.

Like any facet of business, incorporating analytic technologies into the planning, management, and operations of your business is a learning process. You may find that, at this time, taking full advantage of sophisticated reporting and a few key metrics is the most important focus for your business. Or you may want to create a focused, measurable personalization strategy that you can apply to both your online and bricks-and-mortar outlets. Either way, your company must be ready to take advantage of the technology before you can reasonably implement it.

But take it from us, the technology and services that stem from today's analytic applications will not only become an incredibly valuable management tool, they will be an integral part of making e-businesses work, day to day, minute by minute, customer by customer. As you reshape your business, you must consider and prepare for the ways you can use these technologies to improve your ability to find and exploit the opportunities your customers offer.