Swyft Offers Low-Cost Interaction Management Software as a Service

Summary: Swyft offers a Software-as-a-Service real-time interaction manager. It costs less than traditional versions of those products but has similar features.

Last month’s post on Oracle Real Time Decisions offered a brief overview of real-time interaction management products. I won’t repeat that here, except to summarize that these systems use data from multiple source systems to feed centrally-managed, real-time decisions to multiple touchpoints. The most common application has probably been product recommendations in customer service call centers, where there’s a substantial opportunity to sell something to a customer once you’ve solved their problem. Another frequent use has been selecting offers on Web sites, such as the familiar book recommendations on Amazon.com.

You’ll note that both of these are single-channel examples. That may seem odd, since coordinating treatments across channels is a key selling point. I believe the explanation is that most buyers purchase interaction management systems to get more powerful decision engines than those provided with their call center and Web site products.

Indeed, effective interaction management requires a sophisticated mix of predictive modeling, business rules, flow management, response capture, data integration, real-time processing, simulation, and analytics. The simple scripting and personalization engines built into call center and Web products don't provide all this. Equally important, the results of an interaction management deployment are immediately and precisely measureable – so it’s clear when one product works better than another. This means specialist vendors with superior products have a good chance to survive.

But you’ll also notice that these products don’t have many customers. I haven’t done a proper census but doubt there are five hundred implementations among all vendors combined. One reason is the sophistication itself: only a highly knowledgeable set of users can deploy the required rules and models effectively. Another is cost: you’re looking at the price of a 50 foot yacht (about a quarter million dollars if you haven’t bought one lately), plus a sister ship or two for implementation. Few firms with the resources and business volume needed to justify this expense.



(Alternate interpretation: the tools built into standard call center and Web applications are pretty good, so dedicated interaction managers offer only a small percentage gain. A company must be quite large for this to cover the interaction manager's cost.)

Swyft provides a low-cost alternative – more like a 30 footer (around $100,000).


The comparison is inexact because traditional interaction management systems are sold as licensed on-premise software, while Swyft is a Software-as-a-Service product, billed monthly. Pricing for agent-based applications (call centers, field sales, etc.) runs about one dinghy per user ($50 to $80 per month). But even small clients buy a fleet of 100 or more. Web site applications are priced on number of customers but come to roughly the same total.



Implementation is around $15,000 to $25,000, with data connections handled through standard Web Services. The company says a typical deployment takes 30 to 90 days, usually closer to 30.

Functionally, Swyft offers a pretty full set of interaction management capabilities. Decision rules can take into account capacity constraints such as call center workload; customer propensities; current and previous interactions; channel distinctions; offer eligibility; and event-based triggers. Interactions can kick off complex back-end workflows for follow-up treatments.

Call center integrations monitor agent activities and flash an alert if the system has an offer to make. The system then guides the agent through transition statements, probing questions, objections, offers, closing statements, and disposition capture. It can present different messages depending on the agent’s skill level. Web site implementations can present offers, collect data, and run champion/challenger and multivariate tests. The system will automatically adjust offer frequencies based on test results.

One feature that Swyft lacks is built-in predictive modeling. The company says it has found that most clients already have models in place. Rules can use model scores as inputs.

Like other interaction managers, Swyft relies primarily on data stored in external systems. Again like other products, it creates its own database of offers made and responses received for each customer. Less typically, it also stores marketing contents internally and provides a content builder to create these. The system can import and store additioinal information if real-time access is not appropriate.

The current version of Swyft lacks an interface that lets business users create their own rules. The company addresses this largely by doing the work for its clients, providing a “concierge” service that includes content and rule management as part of the base price. Clients do have the option to do this work for themselves; the company says it can be done after a couple weeks of training. A simpler end-user interface is planned for future development.

Swyft was founded in 2004 and launched its product in 2006. It has about ten clients spread among financial services, insurance, communications and media. The largest are mid-sized firms, with a several million customers. Intriguingly, the company offers its product on the Salesforce.com App Exchange, specifically offering a smartphone-enabled version that can use geolocation to identify a salesperson’s current location and recommend the most efficient prospects to visit. It has not yet deployed this at an actual client.

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Oracle Real-Time Decisions Empowers Business Users

One of the few dependable rules in the software industry is that Suites Win. When a market first develops, it is filled with “point solutions” that do one function – say, send emails or analyze Web traffic. Over time, products emerge that combine these functions and displace the individual point solutions. Even though the point solutions may be better at their particular task than the corresponding suite components, the time, cost, and risk savings of preintegrated products are irresistible to most buyers.* This is especially true when IT departments, rather than end-users, control the purchase process.

The only reason that companies haven’t already ended up with a single mega-system is that new applications appear constantly. It takes time before the existing suites can expand to assimilate the new features. This is especially true in customer management, where new touchpoints – Web, mobile, social, etc. – appear at a dizzying pace. In the real world, nearly all companies run multiple customer contact systems and probably always will.

What this means in practical terms is that companies wishing to coordinate customer treatments across channels need to knit together their separate touchpoints. A class of systems to do this has long existed, loosely labeled as “interaction managers” or “decision engines”. These systems manage outbound campaigns and real-time interactions using a combination of business rules and predictive models. Examples include Infor Interaction Advisor, IBM Unica Interact, Pegasystems Recommendation Advisor, SAS Real-Time Decision Manager, eponymous thinkAnalytics, and Oracle Real-Time Decisions.

These systems are all broadly similar in that they connect to external systems for customer data, marketing content, and message delivery. This contrasts with standard marketing automation and customer relationship management systems, which maintain their own customer databases, store content internally, and deliver messages themselves. Interaction managers and other types of customer management systems do share decision management capabilities including multi-step process flows, logical rules, and predictive models.

Interaction management vendors compete on the power of their rules, automated model generation, user interface, scalability, and analytics. To some degree they also compete their ability to connect with data sources and touchpoint systems. But every vendor I've spoken with says this integration is easy, so it doesn’t seem to be a major point of differentiation.

I caught up last week with the Oracle Real-Time Decisions (RTD) team, who released their latest version earlier this month. RTD is based on the SigmaDynamics product, originally built in 2002 and purchased by Oracle in 2006. Oracle now sells it as a general purchase decision platform, positioned as one of its business intelligence and middleware products. But although some clients do use it for customer service, sales, and operations management, 90% of implementations are still for marketing decisions, primarily to select offers for Web sites and call centers.

RTD’s particular strengths are automated learning and sophisticated decision rules. Users set up process flows, define decision points within each flow, and connect to touchpoint systems to capture events at those decision points. The system then automatically correlates event outcomes with creative, channels, offers, customer attributes and other factors. This happens without users specifying which factors to track -- a significant labor saving. The scope of data lets the system predict behaviors based on the full context of a situation, not just the customer’s identity. The data also provides the foundation for in-depth reports on the factors driving results, in addition to standard campaign reporting.

Decision rules can incorporate multiple goals, each assigned a relative weight, and multiple choices, each assigned a value towards reaching each goal. The system scores each choice by adding up the value it contributes to each goal, adjusted for the probability that the customer will accept that choice if offered. Users can also weigh goals differently for different customer segments: for example, retention might be more important for high-value customers, while cost reduction could be a priority for customers who are less profitable. The same goal definitions can apply to multiple decisions, reducing work and ensuring consistency.

Although RTD has always been powerful, its user interface was designed for technical users. The latest release changes this, introducing role-based security that allows different business users throughout an organization to control different functions. This means offers could be controlled by one person, campaigns designed by someone else, and touchpoint placements by a third party. Different users can also be presented with different views of the underlying objects, so they can see information organized in ways that make the most sense for their own purposes.

The new version of RTD is still aimed at large enterprises. Pricing depends on the type of deployment but it's a safe bet you won't get started for less than a couple hundred thousand dollars.


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*True believers might argue that Software as a Service upends this rule by making integration very simple. I’ll grant that SaaS makes it easier to add new components on top of a standard platform such as Salesforce.com’s Force.com. But I'd argue that the platform itself is the functional equivalent of the suite, so the rule still stands.

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