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.

Coremetrics Offers a Foggy View of Lifecycle Analysis

I stumbled over an Adexchanger interview yesterday with John Squire, the Chief Strategy Officer of IBM Coremetrics. It first caught my eye because the headline read “IBM’s Vision for the Marketer”, which is always a topic of interest. Then I noticed it was touting new reporting feature called Coremetrics Lifecycle, which the company describes as “the industry’s first application geared to enable online marketers to track and understand how customers progress through long-term conversion lifecycles.”

This was intriguing. On one hand, I’ve seen plenty of systems that track customers through the buying process, including Eloqua, Marketo, Leadformix, Clear Saleing, C3 Metrics, and Encore Media Metrics. So the claim to be first is questionable. But, on the other hand, seeing another vendor offer this sort of analysis reinforces the importance of the concept.

But a closer look at Lifecycle itself was disappointing. The product does allow tracking of individual Web site visitors over time, which is the foundation of lifecycle analysis. But, in my opinion, a lifecycle tracking system reports on movement of customers across stages within the lifecycle. That is, it shows conversions from one stage to the next. This implies reports that show the previous stages of customers who enter a new stage (“where they came from”), and show the destinations of customers who leave a stage (“where they went”). These are typically represented as a matrix showing all combinations of previous and current stages, or a flow chart that highlights the most common before-and-after pairs.

Lifecycle does none of this. Rather, it lets users define any number of segmentation schemes and count the number of customers in each segment. It does report how many customers entered each segment during a specified time period, but not where they came from. In fact, there is no requirement for a logical progression from one segment to the next, which to me is what a lifecycle implies.

Lifecycle has some other useful features. It can report on the most common marketing treatments received by people who moved into a segment, giving some insight into treatment effectiveness. It calculates the average number of days and Web sessions that customers spend in a segment, which is a limited velocity measure. It also lets users select segment members and send them messages through Coremetrics’ products for email, display ad retargeting, and Web site personalization, although it's not clear the process can be automated.

But a proper lifecycle analysis tool would go much further. It would calculate the end-to-end completion rates, show the drop-off from one stage to the next, estimate the incremental impact of specific treatments, project future segment counts, and show changes in these measures over time. So while I’m pleased that Coremetrics is promoting the concept of lifecycle analysis, I’m disappointed that its product doesn’t deliver a real lifecycle measurement solution.

Addendum - June 19, 2011

After the original post and IBM's comment on it, I reviewed the Lifecycle product with the Coremetrics team. This uncovered no substantive errors in the original post, although a couple of points could have been stated more clearly.

- the system supports two types of lifecycles, one requiring that customers progress through the stages in sequence and one that does not. Users specify the type when they set up a new lifecycle. In both cases, the stages are defined by selection rules created by the user.

- there is a limit of six stages per lifeycle.

- for sequential lifecycles, the system will warn the user if the selection rules are not inherently sequential. (An inherently sequential rule might be based on the number of purchases made; you can't make three purchases without having previously made two. Other stage definitions, such as downloading a white paper or leaving a comment, might come in any order and, therefore, are not inherently sequential.)

- in a sequential lifecycle, the system will not allow customers to advance outside of sequence even if the definitions would allow it. Nor does it report on customers who would qualify for a later stage but cannot reach it because they didn't qualify for a previous one.

- the system's primary report shows the number of customers within each stage during a specified date range. Think of this as an inventory. A "Migrator" report shows how many customers entered their current stage during the report period: for example, there were 500 customers in stage 3, of whom 200 first entered stage 3 during this period. This gives some sense of movement, but it's not the classic funnel analysis showing the percentage of customers in each stage who eventually move to the next stage.

- users can run the standard reports against "segments", which could be defined as anything including a cohort of customers who entered the system during a specified time period. A Lifecycle inventory report for such a cohort would show how many customers reached each stage and got no further. This is the information needed to build a classic funnel analysis, although users would have to extract the data and manipulate it to produce an actual funnel report. This would be done outside of Coremetrics, because there is no end-user report writer.

- reports show the average number of days and Web sessions it takes customers to reach each stage (i.e., since they first entered the system), not the number of days and sessions spent in each stage, as I wrote originally.

- users do have the option to create a recurring process that automatically selects customers in a particular stage and sends them an email or other message. The system could apply a few rules to this process, such as eliminating people who had been selected previously. But more sophisticated controls would be handled outside of Coremetrics, in the message delivery system.

- the system can profile customers in each stage against many attributes (products purchased, geography, social network membership, etc.) in addition to marketing contents received. But, as I wrote originally, the reporting only shows the percentage of customers in each stage who match a particular attribute: this is far from measuring influence, for reasons I'll explain in a future post.

- we confirmed that the system doesn't do projections of future inventory counts, report on out-of-sequence customer movements, or allow customers to migrate backwards into lower-ranked stages (as might happen if stages were based on recency or ratios).

I'm happy to have clarified these matters but none of this changes my original assessment: Lifecycle is a useful product that falls far short of serious life stage analysis.

Oracle Integrates On Demand Marketing with On Demand CRM

Summary: Oracle has integrated marketing automation with its on-demand CRM product. Will competitors do the same?

If I were more on the ball, I would have noticed that May 25 marked a full year since Oracle bought the intellectual property* of high-end B2B marketing automation vendor Market2Lead. I was actually briefed on May 17 by the Oracle team handling the resulting product but hadn’t noticed that the anniversary was approaching. I wonder if they had cake?

I hope so, since they’ve clearly been working hard. In February they released the first “Oraclized” version of the product, now Oracle CRM On Demand Marketing. This included a redesigned user interface that matches the look, feel, and terminology of Oracle’s on-demand CRM product, is available in the same 20 languages, and allows unified user IDs and log-ins.

The new system uses the same data structures as the rest of Oracle CRM On Demand. It shares many physical tables as well, but keeps the major contact tables separate yet synchronized. This is largely because Marketing systems typically contain many more leads than Sales wants in CRM. Marketing systems also run large, complex queries that would interfere with CRM performance if both systems used the same physical files.

The unified data structure allows unified reporting across the customer buying process. Although Oracle doesn’t use the term, this is very consistent with the revenue management concepts described by other B2B marketing automation vendors. Oracle’s new Marketing system supports this with a separate analytical database, which is essential for advanced revenue reporting such as time-series analysis.

Except for improved reporting, the features of the new Oracle product are pretty much the same as the old Market2Lead, which I last reviewed two years ago. This was, and remains, one of the most powerful in the industry. Important capabilities include “adaptive” program flows, which vary depending on customer behavior; advanced Web pages and forms; automated content recommendations; and several types of asset templates. These are mostly relevant to large companies, which fits nicely with Oracle’s customer base.

In fact, most On Demand Marketing sales are part of an Oracle CRM On Demand installation, either at current Oracle CRM users or at clients buying both CRM and marketing automation simultaneously. It doesn’t hurt that On Demand Marketing is the only choice for companies who want a Software-as-a-Service marketing system from Oracle. The company’s other big marketing automation product, Siebel Marketing, is on-premise software.

All this makes Oracle a poster child of sorts for the proposition that CRM and marketing automation should be part of a single system. I’ve argued this for a long time but it’s still a minority view, especially (and for obvious reasons) among the vendors of stand-alone marketing automation products. Oracle itself has announced an initiative for “cross channel customer experience management” which incorporates its products for CRM, marketing, loyalty, real-time decisions, and ecommerce.

It will be interesting to see whether Oracle’s integrated marketing-plus-sales product leads its not-so-friendly competitors at Salesforce.com to respond with an integrated solution of their own. Or, more broadly, whether IBM sticks to its position that it doesn’t need a CRM product to dominate the integrated marketing world. The B2B marketing automation vendors are definitely mice at an elephant dance. It’s a dangerous but exciting position.

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* It wasn’t an outright acquisition because Salesforce.com wouldn’t permit integration with an Oracle-owned product. So existing Market2Lead clients remained with the old company until it could migrate them to other marketing platforms. Once this is done, Market2Lead will complete its shutdown.

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.

Pirates, Train Wrecks, and Marketing Automation

Summary: Selecting a marketing automation system is an adventure. Here's the screenplay. Ready when you are, CB.

I spent most of this week at the inaugural DemandCon conference in San Francisco. My presentation, How to Avoid a Marketing Automation Train Wreck, was based largely on the Marketing Automation Vendor Selection Workbook I released last month (available for free on the RaabGuide Web site). But the heart of the Workbook is a series of checklists like the one below, whereas DemandCon asked presenters to avoid long lists of bullet points. So I had to rethink the format.


After some pondering, I decided it would be more memorable to structure the presentation as a story. This made sense: deploying a marketing automation system is literally a quest, and one that can end in either triumph or the train wreck of my title. Although my actual delivery was marred by a few technical hiccups, I liked the result enough to offer a version of it here.

Prologue

A good adventure begins with a map. This one starts with our hero, a young prince, accidentally uncovering a box containing a map of the marketing technology landscape, showing where B2B marketing automation fits among other types of customer management systems. Since any story is better if you add pirates, this is a treasure map, where X marks the spot. (Sadly, one of the technical hiccups meant the DemandCon audience never saw this image, but I personally find it hilarious. Note the pirate-style headline.):

The box also holds a chart that lists the features of different types of marketing automation systems. I didn't have time to reformat it, but in the story these are presented as clues to identifying the treasure.


He also finds a set of puzzle pieces that, when assembled, present a flow chart of standard B2B marketing tasks: program setup, lead generation, nurturing, scoring, transfer to sales, and reporting. This teaches him that marketing automation is a process, not a technology.


Our Story Begins...

The young prince is intrigued by his discovery, but reluctant to take on the quest. He is moved to action by a village of marketers and salespeople crying out for more leads and better nurturing. Specific benefits include replacing point solutions with an integrated system; running larger numbers and more types of marketing programs; less reliance on non-marketing resources to manage Web content and process data; and closer integration with sales. Who could resist?

After the hero announces his decision, he is warned about the perils ahead by a wise old consultant. These include:

- buying without concrete objectives
- choosing systems based on who has the most, best, or coolest features
- only considering industry leaders
- not using scenarios to test systems against your needs
- ignoring the information you can gather from references
- not investing in training, planning, program design, content, and other resources for successful deployment

Thus forewarned, our hero starts his quest. He starts by making a plan, which means he identifies the business benefits expected from this project. These should be quantified and linked to marketing programs that will deliver them. Then he defines the requirements implied by these programs, by listing the tasks to be completed for each project and the system features needed to execute these tasks. I represented requirements as a kitten who “requires” a bowl of milk – except that now it’s a pirate kitten (my second-favorite slide in the deck. Yes, I am easily amused.)

Planning complete, the hero sets out on his search. Along the way, he meets several companions with different traits. Recognizing that he can't succeed alone, he knows he must choose one of them to help him find the treasure. His task at this stage is choosing the right one. (We somehow seem to have lost the pirates. Pity.)

These companions represent the different marketing automation systems. To choose wisely, the hero must understand the type of product he needs. I divide the B2B marketing automation world into three segments: systems serving “micro-businesses” (very small firms where marketing is a part-time job, often for the owner); small to mid-size business (a separate marketing department but typically in one location and serving one product line); and enterprises (huge companies with dozens of marketers serving multiple markets and products). Each type of business has different requirements and is served by different vendors: I won’t list the details here but they’re in the Workbook.

The Journey

Our band of travelers now faces a series of challenges, escaping from traps, crossing rivers, and beating off attacks by wild animals. At each stage a different member demonstrates his special skills. In concrete terms, this means defining scenarios based on the goals you have set for your marketing automation system. What matters is seeing how well the systems perform the tasks you need, not the ones the vendor likes to demonstrate. This means the real challenge is understanding your requirements – our hero must learn about himself before he can complete his quest. It’s a cliché but how else can I sell this to Disney?

Now the scene switches: it’s the tavern after a day of adventures, and our little group are warily eating together, trying to decide who they can trust. In other words, they’re checking references. You’ll remember that skipping references is one of the dangers I warned against. It’s true that the company will hand-pick happy customers, but you can still learn a lot if you ask the right questions:

- why did they pick the system (maybe the cared about something that’s not important to you);
- what do they see as strengths and weaknesses;
- are they using the system the same way you expect to;
- are their skills and resources similar to yours.

If a vendor can’t connect you with a reference whose situation matches your own, be very cautious.


And while we’re on the subject – don’t think social media queries replace reference checking. What comes back is typically a “yes, we love it” from highly motivated fans. Apart from dedicated grudge-holders, few businesspeople will volunteer negative feedback in social media: they can only get in trouble and there’s nothing in it for them. If you do rely on the social media, contact the people who respond and have an in-depth conversation asking the same questions you would ask the vendor’s own references.

Back to our story. The hero still hasn’t chosen on a single companion, and now the group faces the final test: it must cross the desert, storm the castle, and find the treasure. Who will stay and who will run away? Who will is a good long-term partner? The only way to find out is to move ahead.

In marketing automation terms, this means setting up a trial so you can understand the day-to-day details of working with a system. Most vendors will give you a trial license if they know you’re seriously considering their product. The trick to an effective trial is to test the system thoroughly: this means setting up programs are as demanding as those you’ll actually run once you own it and then running them from start to finish.

Here’s where all that early planning and goal-setting comes in handy, since you’ll have defined those programs already. If that sounds like too much work, bear in mind that you’ll need those programs after deployment anyway. So you might as well do the work a bit sooner and have the programs available to help make the right selection.

Triumph and Return

The group now wins the final battle and finds the treasure, only to meet a new crisis: there’s only enough water for two people to recross the desert. The hero must finally choose. In our story, this is easy because everyone else has failed or died nobly – oh, and it turns out that the remaining companion is really a disguised princess, with whom the hero has fallen in love. Didn’t see that coming, did you? Even better, she’s a pirate princess. Disney’s gonna love it.


But the real world isn’t a fairy tale. You may actually find several qualified vendors. Do what you can to make a rational choice – the Workbook provides a list of criteria to consider. But even if there is no clear winner, make a choice and get on with it. Remember your real goal is to get value from using the system, not to run the world’s finest selection project.

Epilogue

The story doesn’t end with the hero’s triumphant return. Treasure is only valuable if you spend it wisely; relationships don’t end with the wedding. It’s hard work to live happily ever after. So we have an epilogue showing how the happy couple used their riches to improve the lives of the villagers for years to come.

In marketing automation terms, this means avoiding the final mistake of underinvesting in deployment. Be prepared to spend money training your staff, developing content, cleansing data, and measuring results. Expect to spend time on organizational changes and coordinating with sales, finance, and IT departments. Hire consultants and agencies if you don’t have the necessary skills in-house – which few firms do when they start. And don’t get stuck in a rut: make a long-term plan to steadily expand use of your system after your initial deployment.

The End

I have to admit this isn’t exactly what I presented at DemandCon, although I wish it had been. The one thing I’d still want to change is to give more emphasis to the section on deployment. It’s problems with process, content, data quality and staffing that cause most marketing automation train wrecks, not the technology.

Do I smell a sequel?

DIGIDAY:TARGET, or, Yogi Berra Meets Data in the Online World.

I was scheduled to attend the DIGIDAY:TARGET conference on May 4 but wasn't able to be there. (Download the conference agenda and presentations.) Happily, my colleague and big-data guru Matt Doering was able to take my place. Here are Matt's thoughts:

Yogi Berra meets data in the online world.

At the recent Digiday:Target conference (Park Central Hotel, NYC, May 4 2011) a moderator posed the question “Which is better: More Data, Consistent Data or Data Expertise”. Not surprisingly there was a wide variety of opinions both from the panel as well as from many attendees I talked to later in the day. Many I listened to were really intrigued and conflicted by this question. To understand the real answer let us first review the pros and cons of the three possible answers.

Background

More Data – Large volumes of data from varied sources.
Pros:
• Richer data content from any given data source.
• Data sources tend to enrich each other, if properly managed.
• More likely to find the outliers that many times can be the real profit makers.

Cons:
• Many companies don’t have the resources to handle very large volumes of data.
• Lack of Metadata about data sources.
• No real experience with merging multiple data sources with different element codes and timeframes.
• Data hygiene can be an issue if you are working with a data set that is new to your organization.

Consistent Data – All data conforms to some industry standard. Any data not conforming to the model is discarded or reduced.
Pros:
• All data is easily understood and documented in a Metadata stack.
• Data hygiene is easy to define and enforce.
• Data processing performance profiles are well understood. This makes it very easy to scope a system or project.

Cons:
• Let’s admit it; all homogenized milk tastes the same. Where is the differentiation potential?
• In the process of conforming to a standard more detailed data is lost. For example if the industry standard requires that age elements be bucketed into 10 year breaks what happens if for your product offering you need 6.5 year breaks?

Data Expertise – Deep experience with very large data sets.
Pros:
• Small data, large data, inconsistent data are not a problem. Expertise can handle all these issues.
• These resources understand the role that standardized data plays in data analysis (like a good coat of primer on a wall) but also know that the real value is in what is different.
• Most data experts love to teach so the entire data IQ of you organization increases.
• Able to distinguish between dirty data and gold nuggets.

Cons:
• These resources can be hard to find. It’s not a matter of having the right degree its more of who they are. Just as simply having a degree in fine arts doesn’t make you an artist a degree in stats doesn’t make you a good data scientist. In fact one of the best data scientists I know never took a stats course.

“Its déjà vu all over again”

Yogi had it right. If, as I strongly believe, data expertise is of critical importance for the media world it’s not the first industry where this is true. A number of industries over the past 25 years have had to deal with the “big data” problem. Early examples of this are the classic CPG scanner data, pharmaceutical detailing data and financial services direct marketing data sets. All these industries faced large and diverse data issues and they all succeeded in overcoming the problem with technique not CPU.

Now it might be tempting to claim that our space generates significantly higher volumes of data or more diverse data, but is that really true? At first this appears to be true, but when you factor in the computing power available at the times it is not that far fetched to say the adjusted data volumes are actually very similar. Keep in mind that the data scientists of those days were working with computers with less horse power and memory then the average iPad used by the majority of attendees at Digiday:Target.

So where do you find this expertise? Look to the industries named above. Membership of the Direct Marketing Association and those who attended the NCDM (National Center for Database Marketing) is a good place to start. Look for people from the telecommunications industry who helped build systems to analyze Call Detail Records (CDRs). Experience in genome sequencing and pairing should grab your attention. Do these people know clicks from conversions? Probably not, but on the other hand for them more data is the breath of life. We need to recruit the talent that is out there into the industry and avoid having to reinvent it “all over again”.

Silverpop's Latest Release Targets Sophisticated Marketing Automation Buyers

Summary: Silverpop has continued to extend the marketing automation capabilities of its Engage platform. The latest release adds features that are most important to enterprise marketers.

More than a year has passed since Silverpop merged its email and marketing automation systems into a single product, Engage 8. The combined product offered advanced email but was missing some capabilities available in the previous marketing automation product. These included revenue reporting, anonymous visitor lookups, marketing calendars, and advanced scoring features such as caps on points from one event type. Clients who needed those features had to remain on the previous system (Engage B2B). Prospects who wanted them had to look elsewhere.

Silverpop has been steadily enhancing its new product since that time. The latest version, Engage 8.3, was released last month. It still doesn’t offer all the features of the oldl B2B product because Silverpop decided that some were not worth duplicating. But it does offer other capabilities that are improvements. Here are some highlights from the latest set of additions:

- multiple scores per lead. This is important in large companies that need to score leads against multiple products. It also allows different scoring rules for different customer segments. Scoring models can now include data values, such as a score that was calculated externally and imported.

- progressive profiling. Online forms can automatically remove questions a visitor has already answered and replace them with new questions in a user-specified sequence. Silverpop's form builder handles this quite elegantly, without requiring the user to embed rules or a scripting language.

- social sharing. The system can publish directly to Twitter, Facebook, and LinkedIn accounts. Content can include sharing buttons for a wide range of other systems. The system can track the number of shares and reshares for each message and identify traffic from those shares. It also captures the identity of the original sharer although this is not currently exposed.

- revenue tracking. Engage still relies on Salesforce.com to produce revenue reports. But it now feeds Salesforce all campaigns that touched the lead and flags both the original source and the campaign that generated contact information. This will allow advanced attribution analysis.

- Salesforce.com integration. Users can now embed campaign codes within a URL link, making them easier to capture. They can have the system create Salesforce.com tasks when a new lead is created, use Salesforce.com opportunity stages within campaign rules, and add leads to a Salesforce.com campaign at any step in a marketing automation program.

- enhanced security. Silverpop suffered a widely-publicized security breach in December 2010. The new release tightens access in several ways, including user-specific IP restrictions, challenges to log-ins from new IP addresses, two-factor authentication, and narrower restrictions on administrative rights. Given subsequent breaches at other firms, most recently Epsilon and Sony, it's possible that vendors and marketers will start paying more attention to security issues.

- email controls. Merging the email and marketing automation systems does have the advantage of giving B2B marketers access to features developed for Silverpop’s advanced email business. These include send-time optimization, which automatically sends campaign emails at the most effective time of day, and a “snooze” option that lets recipients halt email messages for a specified time period instead of opting out completely.

These are all valuable additions to Silverpop’s B2B capabilities. But Silverpop faces an uphill battle in regaining lost momentum and competing with the advanced analytics now touted by several competitors. Silverpop may be positioning itself to serve the upper end of the market, where companies with multiple products and world-wide organizations need advanced features like multiple scores, dynamic content, enhanced security, and high scalability. That’s a plausible strategy, although it means competing against both high-end B2B marketing automation vendors and B2C products like Neolane and Teradata/Aprimo. Given the costs of product development, it would be tough to remain a first-tier system by selling to large enterprises alone.

Intuit / Salesforce.com Alliance Is No April Fool's Joke

Am I the only one who missed the April 1 announcement of a strategic alliance between Salesforce.com and Intuit? Given our industry's endless nattering about whether Salesforce.com will move into marketing automation, this should have attracted more attention (or, at least, enough attention that I would hear about it sooner than I did).

In case you too missed the news, it comes down to this: Salesforce.com will be available on Intuit’s App Center and be deployed so that the Intuit and Salesforce.com databases are synchronized. For those of us used to thinking of Salesforce.com as the 900 pound gorilla, it’s disorienting to see Salesforce on the Intuit App Center, rather than the other way around.

But it does make sense. Intuit has more than 4 million customers, compared with 90,000 for Salesforce.com. The revenue differential isn’t as large ($3.5 billion for Intuit vs. $1.7 billion for Salesforce) and Salesforce.com actually has a slightly higher market cap ($17.5 billion for Salesforce.com vs. $16.5 billion for Intuit). But Intuit represents a gateway to the small business market for Salesforce.com, so it’s clear who needs whom.

What has this to do with marketing automation? Pretty much everything, I’d argue, at least for companies like Infusionsoft, OfficeAutoPilot, and Genoo, who target “micro-businesses” at the lowest end of the market. Those vendors base much of their appeal on the convenience of using one system for marketing, Web pages, CRM, and even order processing. The one thing they don’t offer is accounting, in good part because Intuit’s QuickBooks has such a dominant position.

The lack of accounting data is an important gap, because the accounting system is the ultimate source for information on customer identities and transactions. That data is important for effective marketing. Having it automatically available to Salesforce.com makes Salesforce a much more attractive marketing option for small businesses.

I suppose I should backtrack a bit here and acknowledge that I’m talking about marketing to customers – that is, people who have already made a purchase – rather than marketing to prospects or leads. Business-to-consumer marketing automation systems manage relationships with both groups, while B2B marketing automation is concerned primarily with just prospects and leads. The “micro-business” marketing automation vendors are more like B2C systemsbecause they do deal with customers as well as leads and prospects.

In other words, the Intuit / Salesforce.com alliance poses a very large threat to the “micro-business” marketing automation vendors but doesn’t have much impact on the rest of the B2B marketing automation industry, which sells to larger companies. Indeed, those larger firms are typically not QuickBooks clients at all.

But here’s the thing: let’s say that Salesforce.com does succeed in selling to a lot of Intuit clients, and in the process adds marketing automation features to serve them better. Those marketing automation features will be available to all sizes of Salesforce.com clients, including the larger ones who currently purchase marketing automation systems. Even if those firms continue to use marketing automation just to target leads and prospects, they’ll suddenly have a stronger reason to adopt Salesforce.com as their marketing platform. So marketing automation vendors who thought the Salesforce.com / Intuit deal didn’t apply to them, might want to think again.

MakesBridge Offers Powerful Features to Small Business Marketers

Summary: MakesBridge offers a full set of marketing automation features with some special strengths that will appeal especially to small companies.

I’ve written quite a bit recently about marketing systems for very small businesses – a category I’ve tentatively labeled “micro-business” and pegged at under $5 million revenue. This group of marketers has different needs from even slightly larger companies. In particular, they want a highly-integrated combination of standard marketing automation (email, landing pages and individual-level Website behavior tracking) with customer relationship management (tracking personal and telephone contacts with individuals). Leaders in the space are Infusionsoft and OfficeAutoPilot, which both also provide integrated shopping carts for e-commerce. HubSpot also has many micro-business clients but is not focused on them exclusively and – probably as a result – has a slightly different feature set: more Web traffic generation and no built-in contact management or shopping cart.

There are plenty of other vendors serving micro-businesses. I’ve previously reviewed Genoo, which supplements the standard marketing automation features with Web hosting and built-in CRM but no shopping cart. Canterris , NurtureHQ , and mKubed all provide email, Web visitor tracking, nurture campaigns, lead scoring, and CRM integration ((Salesforce.com for Canterris and NurtureHQ; its own CRM for mKubed) for under $500 per month. Canterris and mKubed also host Web forms and landing pages but NurtureHQ apparently does not. See my List of Demand Generation Vendors for other options.

MakesBridge is another contender. The company started in 2001 as an email service provider and still offers a $29.95 per month email product. It greatly expanded its features in 2010 and now offers a marketing automation system starting at $500 per month. This includes the full rig: outbound email, multi-step nurture campaigns, landing pages and forms, lead scoring, Web visitor tracking (licensed from VisiStat and quite impressive), and a sales automation module that can work as a stand-alone CRM system or integrate with Salesforce.com, NetSuite, Google Apps, or Capsule CRM, a $12 per month per user system also aimed at small business. There’s no shopping cart or Web site hosting but I don’t yet consider those standard features, even for micro-business systems.

MakesBridge does a particularly good job of taming the mass of Web pages that are critical to reacting to lead behaviors. It does this by letting users write rules that reference sets of Web pages rather than individual pages. This can be done by either assigning a shared label to several pages or by assigning page attributes and selecting on those. This is a helpful middle ground between rules that treat all pages the same (e.g. “visited any Web page”) and those that require users to list a specific page or several individual pages. These rules can be used in segmentation, lead scoring, and sales alerts.

The system also has a solid campaign engine, which breaks campaigns into steps and allows multiple options within each step. Each option has a filter that determines which leads are eligible, in addition to actions and an execution schedule that apply to those leads. Users can view reports on performance for each step and for each option within the step. A “circuit breaker” enforces limits on the total number of emails sent during any time period, alerting the user and limiting the damage from what MakesBridge calls "automation run wild".

MakesBridge also supports automated direct mail production, another feature favored by micro-business marketers. For this, the company has integrated with Cloud2You, a Salesforce.com App Exchange partner that loads selected records directly into templates to produce personalized mailing pieces. Cloud2You handles the actual printing and mailing without any additional effort by the user. Mailings can be triggered by steps within a MakesBridge campaign,

The sales automation module gives salespeople access to detailed information about their leads, including their current campaigns. Salespeople can remove a lead from a campaign, suspend the campaign, or skip a particular message. Although MakesBridge is designed to integrate with external CRM products, some clients use its sales automation module as their primary CRM system.

Pricing of MakesBridge is based on the modules used, number of users, email volume, and number of leads in the database. The system currently has more than 150 clients. Most are small businesses but some are large corporations.

Argyle Social Helps to Track Social Media Results

Summary: Argyle Social offers social media marketing with above-average features for tracking results.

I’ve had a couple of conversations in recent months with Argyle Social, one of the zillions* of companies offering social media marketing tools. Argyle’s particular focus is making social media measurable. It does this in two ways:

- embedding trackable URLs in social messages. The system provides a social media publishing tool that automatically creates links with embedded Google-Analytics-compatible identifiers for campaign, content, and source. This overcomes the fact that social media traffic often can’t be tied to a referring Web site. The identifiers can also include custom parameters for other Web analytics packages. The URLs are sent to an Argyle-controlled destination which logs the traffic before redirecting the Web visitor to the original target page.

- adding cookies to visitors’ computers when they view Argyle-generated social media content, and checking for those cookies when visitors reach a “conversion” page (i.e., make a purchase or take some other targeted action). The conversion pages can be created outside of Argyle but must contain Argyle tags. Results are used to identify visitors who are "influenced" by social media.

Argyle uses its tracking features to generate reports on direct responses to social media campaigns (i.e., clicks on Argyle-generated messages) and on influenced responses (i.e., conversions of visitors whose cookie shows they previously saw social content). Although this is far from the ideal of measuring the true incremental impact of a campaign, it's a step in the right direction. It also provides data that could be the foundation of a more sophisticated analysis.

These features are not technically difficult, so it's quite possible they're available in some other social media systems. But that matters less than knowing they're available in Argyle if you need them.

Argyle's tracking features are combined with a publishing interface that lets users set up accounts, create posts, and deliver them immediately or on schedule. It can currently post to Facebook, Twitter and Linked In. It can also scan for social messages containing specified keywords and store these messages for future reference. The publishing features don’t yet include enterprise-level capabilities such as response templates, approval work flows, case management, or relationship tracking, although these are on the horizon. A rules-based inbox filtering feature will launch tomorrow.

Argyle launched its product at the end of last year and is nearing 100 customers. A basic edition (three users, ten social properties, one conversion goal, one inbox filtering rule) is priced at $149 per month and the advanced edition (five users, unlimited social properties, five goals, ten advanced rules) costs $499 per month.


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*at last count. Here are the first three lists I found via a Google search, plus others whose authors were SEO-savvy enough to find a nice, round 100, and one with a cool infographic:

[INFOGRAPHIC] What Are The Best Social Media Monitoring Tools?

22 Social Media Marketing Management Tools (Lee Odden)

42+ Social Media Marketing Tools (Joe Pulizzi)

List of Social Media Management Systems (SMMS) (Jeremiah Owyang)

100+ Social Media Monitoring Tools (Pam Dyer)

Top 100 social media monitoring tools (juanmarketing)

Step-by-Step Guide to Selecting the Right Marketing Automation System - Part 2

Yesterday' post described the first three steps in Raab Associates' vendor selection process: defining requirements, researching options, and testing vendors against scenarios. This post lists the four steps needed to complete the task. As before, there's a worksheet for each step that can be a model for your own, more detailed version. And remember, the complete set is available for free in our Vendor Selection Workbook in the Resource Library at the Raab Guide Web site.

4. Talk To References

This is an often-overlooked source of insight. The question isn’t whether the references are happy, but whether your situations are similar enough that you’re likely to be happy as well. Find out whether the reference is using the system functions you care about, how long they took to get started, the amount of training and process change required, what problems they had, and how the vendor responded.

Issue	Questions to ask
System fit vs. my needs	What kinds of programs do you run with the system?
	How many programs do you run each month?
	How many people at your company use the system?
System reliability	How often has the system been unavailable?
	What kinds of bugs have you run into?
Ease of use	How much training did you need to use the system?
	What kinds of tasks need outside help to accomplish?
	How long does it take to set up different kinds of programs?
Vendor support	How well does the vendor respond when you ask for help?
	How quickly do problems get solved?
	Does the vendor ever offer assistance before you ask?
	What help does the vendor provide with email deliverability?
Cost	Did you negotiate any special pricing?
	Did you pay extra for implementation and on-going support?
	Were there any unexpected costs after you started?

5. Consider A Trial

Nearly all marketing automation vendors will let you try their system for a limited period. Trials are a great way to learn what it’s really like to use a system, but only if they are managed effectively. This means you need to invest in training and then set up and execute actual projects. As with scenario demonstrations, you may still rely on the vendor to handle some of the more demanding aspects of the project, but, again, make sure you see how hard it will eventually be to do them for yourself.

What you can learn from a trial	How hard it is to install the system
	How hard it is to set up a campaign
	How hard it is to make changes and reuse materials
	What features are available or missing (if you test them)
	Quality of training classes and materials (if you try them)
What you can’t learn from a trial	How the system handles large volumes of data, users, etc.
	Results from complex or long-running campaigns
	Accuracy of scoring and reports
	Quality of customer service and support
	Quality of vendor partners (agencies, integrators, etc.)

6. Make A Decision

Don’t let the selection process drag on. Selection is a means to an end, not a goal in itself. Unless you have very specialized needs, there are probably several marketing automation systems that will meet your requirements. Look at your key criteria and assess how well each vendor matches them – bearing in mind that a system can be too powerful as well as too simple. Once you’ve found one that you are confident will be sufficient, go ahead and buy it. Then you can start on what’s really important: better marketing results.

Selection criteria	Key factors	Vendor Fit
		Too Little	Appropriate	Too Much
Functions	Outbound email
	Landing page and forms
	Web behavior tracking
	Lead scoring
	Multi-step campaigns
	Sales integration
	Reporting and analysis
Usability	Easy to learn
	Efficient to use
Technology	Easy installation
	Flexibility
Cost	Direct (software and support)
	Indirect (staff, training, services)
	Predictable
	Expansion costs
Vendor	Staff resources
	Product plans
	Financial stability

7. Invest In Deployment

Marketing automation systems allow major improvements in marketing results. But those improvements require more than just a new system. If you don’t already have a formal description of the stages that prospects move through to become buyers, build one and instrument your systems to measure it. Use the stages as a framework to plan, design and develop a balanced set of marketing programs. Invest in the staff training and content to execute those programs successfully. Document and improve internal marketing processes. Work closely with sales to define lead scoring rules, hand-off mechanisms and service levels, and ways to capture results. Build measurement systems and use them to hold marketers at every level of the department responsible for results they control. Bring in outside resources, such as agencies and consultants, when you lack the internal expertise or time to do the work in-house.

Goal	Tasks
Balanced set of marketing programs	Define lead lifecycle (buying process and buyer roles)
	Map existing programs to process stages and identify gaps
	Prioritize new programs to close gaps
	Execute programs and measure results
	Refine programs with versions for different segments
Measurement	Track leads through stages in the buying process
	Import revenue from sales systems
	Link revenue to lead source (acquisition programs)
	Measure incremental impact (nurture programs)
	Project future revenue from current lead inventory
Process management	Define processes to execute marketing programs
	Identify tasks and responsibilities within each process
	Define measures to capture task performance
	Assess existing processes and possible improvements
	Monitor execution, test improvements, check results, repeat
Sales alignment	Identify key contacts between sales and marketing
	Agree on process for lead qualification, transfer to sales
	Agree on measures for lead quality, revenue attribution
	Deploy agreed processes, monitor results, review regularly
Staff training	Define skills needed to deploy new system
	Assess existing staff skills and identify gaps
	Plan initial training to close gaps
	Plan on-going training to maintain and expand skills

Step-by-Step Guide to Selecting the Right Marketing Automation System - Part 1

Choosing a marketing automation system is a major decision. A disciplined selection process is essential to make a sound selection. This series of posts presents the seven-step methodology we use at Raab Associates, along with related worksheets. The first three are below.

For a complete list of the steps, worksheets, and background materials, visit the Raab Guide Website and download the Vendor Selection Workbook from the Resource Library (registration required).

1. Define Requirements

Create a list of your goals in buying the system. Relate these to financial values when possible. Then define how you’ll use the system to meet these goals, being as specific as you can about the actual processes involved. Be sure to include processes beyond what you do already: one of the reasons you’re looking at marketing automation is to expand what your department can accomplish. Your requirements are based on the tasks you must perform to meet your goals.

Goals	Related Requirements
Generate more leads	Manage online and offline advertising campaigns
	Import email address lists and send personalized emails
	Monitor and publish to social media
	Build and deploy landing pages to capture responses
	Use IP address to identify the company of Web site visitors
More effective nurturing	Capture the source and Web site activities of each visitor
	Create Web forms to gather information about visitors
	Score visitors based on form responses and Web behaviors
	Execute multi-step campaigns tailored to different groups
	Use visitor behavior to trigger campaigns and other actions
Better sales integration	Synchronize data between sales and marketing systems
	Send leads to sales based on lead score and actions
	Send alerts to sales based on Web site behaviors
	Report on revenue generated by leads from marketing
More efficient marketing operations	Store marketing materials and share across programs
	Track planned and actual costs of marketing programs
	Manage tasks and approvals during program development

2. Research Your Options

Raab Associates’ B2B Marketing Automation Vendor Selection Tool (VEST) provides a good starting point for matching possible vendors to your requirements. In particular, match the scale and sophistication of your marketing operations to the different buyer segments used in the report. Bear in mind that company size alone doesn’t necessary predict the depth of your requirements: small businesses can run complex marketing programs, and large business programs may be simple.

Company Type	Key System Features
Micro-business	Outbound email and multi-step nurture campaigns
	Landing pages and forms
	Built-in sales and service features
	Built-in or integrate with third party ecommerce and shopping cart
Small to mid-size business	Outbound email and multi-step nurture campaigns
	Landing pages and forms
	Web site visitor tracking
	Lead scoring (one score per lead)
	Integrate with external sales automation system
Large business	Outbound email and multi-step nurture campaigns
	Landing pages and forms
	Web site visitor tracking
	Lead scoring (multiple scores per lead)
	Integrate with external sales automation system
	Manage marketing budgets, program tasks and approvals
	Add custom tables with data from many sources
	Limit different users to different tasks and programs

3. Test Vendors Against Scenarios

Develop scenarios that describe actual marketing projects you expect to run through the system, and have the most promising vendors demonstrate how they would execute them. Scenarios based on your own needs are critical for understanding how well each system would function in your own environment. Be sure that some scenarios describe your more complicated processes, since these are most likely to highlight differences among systems. If vendor staff executes the scenarios for you, be sure to understand how much the vendor built in advance. This ensures that you get an accurate sense of the total work effort involved.

Scenario	Steps
Outbound email campaign	Import list from CSV file, from Excel
	Compose personalized emails with embedded graphics
	Create landing page with data entry form
	Set automated email response to form submissions
	Set rules to score leads and send qualified leads to sales
	Report on results: sent, opened, clicked, completed form
Nurture campaign	Set start and end date for campaign
	Set rules to select leads, based on attributes and behaviors
	Set priority of campaign vs. other campaigns
	Define multi-step flow with wait periods between steps
	Set rules for different treatments for segments within steps
	Set rules to score leads and send qualified leads to sales
	Create emails, landing pages, and forms
	Report on results including leads to sales and revenue
Revenue reporting	Define stages in lead lifecycle
	Define rules to assign leads to lifecycle stages
	Report on movement of leads through lifecycle stages
	Set up process to import revenue from sales system
	Define rules to link revenue to campaigns
	Define rules to estimate incremental revenue per campaign
	Report on revenue generated per campaign
	Capture campaign costs
	Report on campaign revenue vs. campaign cost

The next post in this series will present additional steps in our process.

[x+1] NexTargeting Conference: Cross-Channel Attribution and Online Ad Scalability Remain Hot Topics

Continuing my adventures in online ad measurement, I attended [x+1]’s NexTargeting Summit last week. This reinforced and refined my conclusions from last month’s OMMA Metrics conference, which identified the burning industry issues as:

- better understanding of the interactions between online and offline events (both advertising and results), and

- better scalability for successful online advertising programs.

The online / offline connection was covered by MarketShare CEO Jon Vein, who presented studies that showed including the “indirect impact” of online display ads can dramatically improve their reported return on investment. He also said his firm has found that marketing mix models with complete data can explain as much as 98% of the variance in revenue, while optimization based on mix models can typically improve marketing effectiveness by 10% to 15%. Although I don’t recall Vein mentioning it during his actual presentation, he did tell me in a side conversation that his firm purchased JovianData last year in order to expand its ability to work with individual-level data. MarketShare and [x+1] announced an alliance last month to combine MarketShare’s cross-channel analytics with [x+1]’s digital targeting.

Scalability was covered [x+1] itself, which announced extension of its Media+1 audience targeting platform to combine information from direct media buys and ad exchanges. The relationship between that extension and scalability is a bit complicated, but it boils down to this: combined information lets marketers control the number of ads served to individual consumers across both types of media buys, which segment-level purchases do not. This means that marketers can expand their budgets by targeting ads to new individuals (=effective scaling) rather than bombarding the same people with more messages (=ineffective scaling). That this mimics the reach and frequency measures used in traditional mass marketing (i.e., television) is a happy bonus.

I’ve skipped some of the subtleties of the Media+1 product. These include tracking the degree of overlap between the audiences of different direct-buy Web purchases; identifying optimal message frequency by customer segment; using direct-buy Web sites to establish a base of impressions and then supplementing these on a customer-by-customer basis through real time bidding on ad exchanges; and using scorecards to track performance after initial customer acquisition. The bottom line on Media+1’s beta client was reallocating 40% of the online ad budget to achieve a 20% improvement in results.

[x+1] also used the conference to announce an even broader product, called [x+1] Origin, scheduled for release this summer. This will build a customer-level data hub that combines data and sends targeted messages across display ads, Web site, email, and mobile. I asked [x+1] CEO John Nardone whether it’s actually possible to identify the same customer across all those channels, and he said it’s not an issue in many cases, since you can often give the customer a reason to log in or otherwise identify herself.

Of course, the big exception is acquisition, which seems like a pretty big exception indeed. (“Other than that, how did you like the play, Mrs. Lincoln?”) But tracking mechanisms do get better all the time and there’s plenty of value in better treatment within existing customer relationships. So it’s definitely a good start.

Whatsnexx Manages Customer States, Not Campaigns

Whatsnexx offers itself as a radically easier way to manage customer and prospect interactions than conventional marketing automation. I agree that it's radically different: it works without a central marketing database and tracks customer states rather than assigning them to campaigns. Whether it’s radically simpler is another question.

Some perspective is in order. Although Whatsnexx was launched just last year, state-based systems have been used in marketing before. Previous products include Verbind (later purchased by SAS), Elity (eventually owned by Unica), and Harte-Hanks Allink Agent (still around in some form). The concept is intriguing: instead of creating campaigns that predefine paths a lead can follow, you define the actions to take when customers are in a particular situation. The advantage is you can think in terms of new customers, loyal customers, disgruntled customers, etc., and specify how to treat each group after common events such as placing an order. Most marketers find this easier to conceptualize than a massive campaign with separate branches for each contingency.

Anyway, that’s the theory. In practice, defining customer treatments in Whatsnexx didn’t look much easier to me than defining them in other systems. (You can judge for yourself by viewing several how to videos on the company's Web site.) The process is this: users first define “scenarios”, which are customer processes such as acquisition, retention or complaints, and "states", which are customer types such as new, high value, or disgruntled. They then define the flow of events within each scenario, with the possible responses for each event for each customer state. Terminology aside, I don't find this much different from assigning customers to segments, assigning the segments to multi-step campaign flows, and assigning treatment rules to each step.

But maybe I’m missing the point. Whatsnexx’s Jacques Spilka says he finds huge time savings in the analysis stage that precedes the campaign set-up: instead of taking a week to understand client needs and processes, he can do it in a few hours using the state-based technique. Most of the time setting up any system is spent on analysis, not the mechanics of the campaign design. So savings of that magnitude would be significant. On the other hand, you still have to create the actual content, which is probably the biggest expense of all.

The other main difference between Whatsnexx and conventional marketing systems is that Whatsnexx doesn’t rely on an independent marketing database. This isn’t an inherent feature of state-based systems: other products do work with a database of their own. Indeed, even Whatsnexx maintains a central database of customers and their states. But Whatsnexx doesn’t import all the events that occur in other systems and it doesn’t send messages by itself. Rather, users configure "Infogates" that let existing systems send alerts to Whatsnexx when specified events occur. These alerts (technically, XML messages via a SOAP protocol) include whatever contextual information is needed for Whatsnexx decisions. Whatsnexx receives the alert, applies its logic, and returns a message telling the external system how to respond. The company has existing Infogates for Salesforce.com, Constant Contact, Deliva and CakeMail. It will add new Infogates as required by customers.

It seems to me that this approach is actually a more important differentiator for Whatsnexx than its state-based logic. As the company points out, it lets marketers continue to do their work in their existing systems. This saves the effort of learning a new tool and potentially needing to rewire their current infrastructure. It also lets them avoid building a central marketing database – although I suspect that many will need one anyway for data consolidation and analysis. Still, even deferring that need could remove a barrier to immediate adoption. This is especially true as marketers add data sources that are not built into standard marketing automation products, which are often limited to Salesforce.com and perhaps a tagged Web site.

Whatsnexx was developed by Montreal-based email company Komunik over several years. It was formally launched in late 2010 and has four current customers. Pricing is based on the client’s activity level and starts at $500 per month for up to 100,000 transactions.