RedPoint Offers Broad, Deep B2C Marketing Automation

On days when I have nothing else to be cranky about, I sometimes fuss at how business-to-business software vendors hijacked the term “marketing automation” despite its long and relatively honorable history describing systems for consumer marketing. Oracle’s recent agreement to purchase Eloqua reinflamed that wound, since much of the commentary ignored Oracle’s extensive existing suite of consumer marketing systems.

More productively, the deal also shifted discussion from components within a marketing suite to where marketing systems fit within the larger world of unified customer management. This perspective has always been part of consumer marketing, where the classic description of Customer Relationship Management (CRM) was “marketing, sales and service”. That formula fell out of favor when the most prominent CRM system became B2B-oriented Salesforce.com, whose very name reflects its origins in B2B sales automation.

One reason that B2B perspectives have dominated the recent discussion of marketing automation is that the major B2C marketing automation products have receded from view after being absorbed by larger corporate platforms: Unica is part of IBM, Aprimo is owned by Teradata, Portrait Software is owned by Pitney Bowes, Epiphany is owned by Infor (which last month acquired marketing resource management leader Orbis Global, a bit of news I'd missed), Alterian is owned by SDL, and SAS is owned by, well, SAS. This diminishes most products’ independent profiles (Aprimo is the exception), although they are still selling nicely. Even some of the less prominent B2C products have been acquired recently: Conversen by Experian and Entiera by FICO, although neither of these are enterprise software vendors.

The net result of all this harvesting by big buyers has been to clear the ground for the next crop of B2C marketing automation systems. These fill a demand for powerful but moderately-priced options by both marketing services providers and mid-sized companies. Those buyers often find that systems from big enterprise software vendors become too expensive or require too many ancillary components from their corporate parents.

One vendor taking advantage of this opening is RedPoint. Founded in 2006 by veteran CRM consultants and technologists from Accenture, the firm has created an exceptionally extensive marketing automation product including not just campaigns and content management, but also database maintenance, which isn't usually part of marketing automation.  Although IBM, SAS, and Pitney Bowes provide a similar scope, RedPoint is unique in having built all those components itself and keeping them tightly integrated.

The data features are especially impressive. RedPoint offers a rich set of standard data management features including loads from files, databases, and semi-structured formats like XML and EDI; transformations including regular expressions, file splits, and table joins; batch and on-demand process flows.  There's also a novel option to use Web service calls for on-demand data appending, a particularly noteworthy concept.  Beyond those, the system provides specialized functions to manage customer data including name/address parsing, standardization, and matching. Users can apply the system's built-in rules for these or modify the rules to meet their own preferences. All data functions are managed with a sophisticated workflow engine that allows fast development of new marketing databases -- often in a matter of weeks, not months.  This removes (or at least shrinks) the single greatest obstacle facing many new marketing systems.

The system was also designed to scale.  It can work with standard files and SQL databases, with native connectors for SQL Server, Netezza, Oracle, and Teradata. Support for Hadoop, Hbase, PIG, Hive, Cassandra, GreenPlum and other “big data” technologies is due early this year. Clustering is available at all application service layers and the system supports true multi-tenancy (multiple instances running on the same installation).

Campaign management features are equally deep although less unusual.  A drag-and-drop flow builder allows complex, rule-based branches and can react to behaviors during the campaign. Users can define audiences with batch selections, scheduled processes, and “subscription groups” of anonymous individuals (such as Web site visitors) who match specified behavior profiles. Splits can be based on logical conditions, random selections, or auto-generated cells with all possible combinations of specified variables. The auto-generation feature, which can easily produce segmentations with hundreds or thousands of cells, is a hallmark of sophisticated B2C marketing automation systems. It is used for segmentations such as RFM (recency, frequency, monetary value) cells, age/gender/cluster cells, branch or dealer assignments, and product splits.

RedPoint also provides self-training predictive models.  These are currently used within the data management functions and matching algorithms. They will be soon applied to select offers for Web personalization.

Content management includes an editor to create outputs for email, Web, SMS, Twitter, Facebook, FourSquare, LinkedIn and other formats. Users can build shared templates that are later modified for individual projects. Objects can contain Web forms and dynamic content blocks driven by selection rules or mapped to audience segments. The system can generate Web tags to capture user behaviors and can react to those behaviors in real time. It manages approval workflows, version tracking, and precise control over which users can access different objects and functions.

Pricing for RedPoint is based on a combination of deployment services, software licenses, and hosting fees. A minimum system starts around $60,000 per year. There are more than 100 installations, about half sold directly and half through partners such as marketing service providers. The system can be hosted by RedPoint, by a service partner, or by the client.

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Future of Marketing Automation: Grow or Die

‘Tis the season for industry predictions. I’ve already fielded a couple of requests for my thoughts, which usually requires some pondering before I reply. But this time I was able to answer right away because I’ve just finished a white paper on the future of B2B marketing automation, sponsored by Leadformix and available here for free download.

The question answered by the paper is “What will marketing automation vendors do next?” This is different from the perhaps-more-important question of “What will marketers do next?” I don’t claim any particularly deep insights into the latter: they'll continue to adapt to new media and buying habits, I guess. Like everyone else, I’m seeing greater use of social, mobile, and video; more cross-channel campaigns; closer cooperation between marketing and sales; and expanded use of analytics. If I had to predict one thing that isn’t utterly obvious, it's that B2B marketers will be more involved with managing customer relationships after the initial sale. The reason is that post-sales interactions are increasingly automated and marketers have the best tools to manage automated interactions effectively. The task is really the same as a sophisticated lead nurturing campaign: to monitor customer behavior and respond appropriately.

While my vision of future marketing may be rather broad, I think I see the future of marketing automation in clearer detail. This is what’s covered in the white paper. To summarize the argument:

• marketing automation vendors must grow or die. Today’s B2B marketing automation systems are used primarily for lead nurturing. This means they don’t help other marketers who do lead acquisition and marketing administration (planning, budgeting, project management, etc.). They also have limited interactions with sales and service departments, who own the post-sales customer relationship. Marketing automation vendors who want to expand their business need to service these other groups or risk some other system becoming the central platform for marketing management. If that happens, the other systems will slowly encroach on marketing automation functionality and eventually replace it.

• marketing automation can expand in either direction along the customer path: backward to acquisition or forward to sales and service.  Most expansion to date has been towards sales, in the form of add-ons that give salespeople access to information about behavior of their leads. But CRM systems are deeply embedded in sales departments, so they block growth in that direction.  I therefore expect marketing automation vendors to instead shift toward features for acquisition marketers. These would include not just “inbound marketing” through social media and search engine optimization, but also purchasing media such as online and offline advertising.

• marketing automation can also be divided into layers of delivery systems, campaign management, and platform functions.  Delivery systems manage touchpoints such as Web sites, email, and social media publishing.  Campaign management is the rules and models to select names for promotions.  Platform functions are supporting technologies such as the marketing database, planning and budgeting, content management, analytics, and security. Current marketing automation systems do all three to the degree needed for lead nurture campaigns.  Extending to other users will require more powerful platform functions in particular. Whoever controls the platform can best expand throughout the marketing department.

• marketing automation vendors will increasingly fall into two groups: a handful of big platform vendors and larger number of small specialists. The platform vendors will offer a broad range of functions internally and further extend their range by exposing their platforms to third party developers through “app markets”. The specialists will have narrower scope but be very good at serving companies with specific needs such as low cost, marketing services, or  industry editions (for sports, investments, franchises, etc.)  Both types of companies can succeed although the platform vendors will tend to dominate over time.

• new competition will come from outside the industry, especially from delivery systems. This seems counter-intuitive: delivery systems are by definition channel-specific and function-generic (a term I just invented to mean they serve all functions within marketing, sales and service). This means they are in the strategically weak position of selling commodity products without strong ties to any particular set of users. But the delivery vendors recognize this weakness and can afford to overcome it by investing in campaign engines and platform features. This is exactly what's happening when email vendor ExactTarget purchases Pardot or Web content management vendor SiteCore adds email campaigns and a database. It (almost) goes without saying that CRM vendors are also potential competitors: they already have the platform features; what they mostly lack are campaign engines.

These trends have specific implications for marketers who are selecting a marketing automation system.  You'll need to download the white paper to find out what they are.

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[x+1] Origin Digital Marketing Hub Offers Cross-Channel Decision Management

My recent posts on real time decision systems have all described products from vendors of batch-oriented, outbound campaign management systems. Expansion to real time decisions helps those vendors cement their strategic position as a complete solution for marketing departments. But technically the two sets of systems have little in common: outbound systems create lists for direct mail and email, while real time systems generate recommendations for Web sites and call centers. Knowing this, you might suspect there are other real time decision management vendors with roots in Web marketing. You would be correct.

[x+1] Origin Digital Marketing Hub is one example. [x+1] originally began as Poindexter Systems, which offered real-time Web ad optimization based in predictive models and anonymous user profiles. This was an early form of what now called a Data Management Platform (DMP), which one articulate blogger defined as “a very smart, very fast cookie warehouse with analytical firepower to crunch, de-duplicate, and integrate your data with any technology platform you desire.”

You could also see DMPs as a type of marketing database because they have the key characteristic of being organized around individual prospects and customers. It’s true that DMPs identify individuals with cookies, not a conventional name and address. But both types of systems can still perform the basic marketing database functions of sending messages to individuals and tracking their responses.

That original DMP is still the foundation of the [x+1] suite. But the company has also extended into Web ad buying (Origin Media DSP), Web site recommendations (Origin Site), attribution (Origin Analytics), and cross channel marketing (Origin Digital Marketing Hub). Supporting multiple channels and potentially storing names and addresses puts [x+1] Hub into direct competition with other real-time decision management products.

I’ll assess the Hub against my real time decision management framework in a minute. But first let's look at [x+1]’s features that are not found in a typical real time decision manager. These include:

- Web tag management: the system provides Javascript code to tag Web pages and advertisements, drop cookies on visitors’ computers, and then use those cookies to track visitor behaviors. The system also supports server-to-server connections that capture user behavior without relying on cookies. Most real time decision systems rely on external systems to capture this data.

-Web audience management: [x+1] Hub can integrate Web audience data from external compilers such as BlueKai and eXelate, enabling marketers to use that information for decisions and targeting. In theory, any decision manager could access the APIs of those providers, but [x+1] is designed specifically to integrate their data and manage the associated charges. [x+1] can also help sell the client’s own data to external syndicators.

- Web media buying: [x+1] can manage real-time bids and other Web advertising purchases. Users set up campaigns with budgets, cost targets, date ranges and other parameters for the system to execute automatically. The system can also track media purchases made outside of [x+1]. Reports provide detailed information on reach, frequency, pacing, inventory, and other advertising-specific metrics.

- attribution: the system tracks visitors through user-defined funnel stages, as defined by visits to specified Web pages or media exposures.  It then uses regression analysis to estimate the influence of each promotion and promotion attributes, such as ad size and format, on stage movement . This is much more sophisticated than the first touch, last touch, or fractional attribution methods available in standard marketing systems.


These features make clear that [x+1] Hub isn’t directly comparable to conventional real time decision systems. But [x+1] does offer itself for real time decision applications, and the whole point of decision management is to centralize decisions within a single system. This means that [x+1] Hub is inevitably competing with the other products to be the one thing that rules them all.

So, how does [x+1] Hub stack up against my decision management criteria?

- connecting to external systems. Like other real time decision managers, [x+1] Hub can connect to external systems via Web services and batch file imports.  It can also capture Web traffic via the Javascript tags and server-to-server connections. However, displaying the returned messages on a Web site requires code created outside of the system.  [x+1] Hub has existing integrations into call center, search, mobile, SMS, social, and email products.

Visitor profiles are stored permanently within the system and can contain whatever attributes the user chooses. The base set includes visitor behaviors, http header attributes (browser, operating system, location derived from IP address, etc.), information imported from external data vendors, and a history of messages presented to each individual. The system can link cookies from [x+1], the client, and third party vendors once these are identified as the same person. Partners including LiveRamp, i-Behavior and Datalogix can link online and offline identities.

Web behaviors and imported data can trigger actions including as assigning a visitor to a segment, adjusting a counter, exporting data, and sending a message through an external system. The results of these actions are stored in the [x+1] database where they can be inputs to other decision rules.

- making decisions based on rules and predictive models. Decision rules in [x+1] Hub are organized into two layers: the system first tests a visitor against one or more “targeted experience” definitions until it finds a match; then, it tests the visitor against a sequence of “targeting rules” associated with the winning experience. Each rule returns a specified offer or creative treatment. Offers and creatives can also have their own eligibility rules, which apply across all campaigns.

Rules can include if/then logic or predictive models. If the models are used, [x+1] can generate scores for multiple responses and pick the best option based on response probability, expected value, or other formulas. This lets the [x+1] select the best option for each individual even though the system always selects the first rule the visitor matches. There are also default choices in case the visitor fails to meet any other rule.

The models are set up by [x+1] technicians. Scoring formulas can incorporate external data, such as inventory levels or sales goals, so long as these are accessible to [x+1] via data import or API connections. Users can also specify the percentage of responses that will receive each option, allowing the system to deliver a fixed mix of results even if the models would favor some choices less or more often.

The system can return multiple offers in response to a single request. Users can block these from containing duplicate offers. Users can also set up “creative groups” of incompatible offers and have the system return only one offer from each group.

- integration with campaign and content systems. [x+1] Hub is not part of a suite with its own outbound campaign manager, although it can be integrated with other vendors’ campaign management products. Similarly, the system also doesn’t store or render content but can connect with third party content management systems. [x+1] does maintain a registry of content IDs that are sent back to execution systems, which look up and render the related messages.

- deployment model. The entire [x+1] suite is sold as a subscription. This can include the software only or software plus supplemental services. On-premise deployment is technically possible but no client has yet selected it. Pricing is based on system functions and volumes. It starts around $12,500 per month but can be lower if the client is also buying media through [x+1].

All told, [x+1] Hub seems functionally competitive with stand-alone decision managers. Still, the system’s main appeal will be to marketers who want the DMP, media buying and attribution features. Those marketers should find that [x+1] Hub lets them coordinate real-time customer treatments across all channels without purchasing a separate decision management system.

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Pitney Bowes Interaction Optimizer and Dialogue Offer Unified Inbound/Outbound Marketing Campaigns

In his classic Harvard Business Review article Marketing Myopia, Theodore Levitt argued that railroad companies could have survived the rise of the automobile had they considered their business to be providing transportation, not running trains. Someone at Pitney Bowes clearly got the message.  The postal equipment giant has aggressively moved to become a provider of “customer communication technologies”, making 83 acquisitions costing $2.5 billion since 2000.  Purchases have included Group 1 Software (2004), MapInfo (2007) and Portrait Software (2010), which are now part of a customer analytics and interaction group within the company’s software division.

Portrait itself brought an agglomeration of previous acquisitions, having expanded its original customer relationship management system by purchasing Quadstone analytics in 2005 and Million Handshakes marketing automation in 2008. Their descendants are now modules within integrated Portrait suite, including Portrait Explorer (visualization), Miner (predictive modeling), Uplift (model-based treatment selection), Foundation (data access and integration), Dialogue (multi-step outbound campaigns), and Interaction Optimizer (real-time decisions).

Dialogue and Interaction Optimizer are closely linked, sharing a user interface for campaign definition and both using Foundation to connect with external systems. The interface, called HQ, lets marketers define a hierarchy of campaigns linked to multiple marketing activities, which in turn contain multiple channels and offers. Offers are linked to products, which have customer-level eligibility criteria.

Marketing activities have budgets and response forecasts, which can be set for the activity as a whole or for each channel / message combination (called a treatment). An activity can be assigned an activity type, priority, and scoring rule, which are used to prioritize recommendations during inbound interactions. Activities can also be associated with tasks assigned to the user or others.

HQ provides dashboards showing a campaign calendar, personal and delegated tasks, and results by campaign, offer, and channel. The dashboard can be extended to include external data.

IO connects with touchpoints and other data sources through Foundation, which can accept via Web service calls or SQL queries. Foundation integrates the information it gathers and passes it to IO through a Web services interface. The system usually refreshes the data with each new request, but can be configured to retain data in memory during a multi-step interaction. IO is also integrated with GX Software BlueConic to track and segment Web site visitors. BlueConic-generated events can trigger IO messages and BlueConic-captured behaviors can be loaded to the IO database.

Recommendations in IO are based on marketing activities. Each recommendation has audience and message definitions. The audience can be defined by any combination of static lists, dynamic selections, and scoring rules. Messages belong to a single channel and provide content in a channel-specific format. The content may be an actual message or a pointer interpreted by the touchpoint. IO provides a HTML generator to create messages.  These can be personalized with data from the customer record. Messages can be linked to offers, although this is optional.

When IO receives a recommendation request, it checks against the audience and offer definitions of all active recommendations to identify those that are available to the current customer in the current situation. It sorts the options based on activity type, priority, and scoring results, which can be applied in whatever sequence the user defined during campaign setup. More advanced prioritization could be built into the scoring rules but requires a modeling specialist. After the recommendation is selected, it is sent back to the touchpoint for delivery.

Scoring models can be created and automatically updated within IO or imported from external systems. The self-updating models are less accurate than batch built models but make sense where conditions change quickly or very large numbers of models are needed. External models can be created in Portrait’s own modeling tools or with third party software. Scores are calculated within IO using current data.

IO recommendations are generally called by an external touchpoint but can also be embedded within a Dialogue campaign flow, used to generate outbound campaigns. Dialogue provides a drag-and-drop flow builder with a broad range of capabilities to manage data, direct data flows, send messages, and access social media. Campaigns can execute as batch processes or events triggered by database stored procedures. Other Pitney Bowes product offer additional features for database management, data quality, and message creation.

Both IO and Dialogue are available as on-premise software or hosted by Pitney Bowes. Pricing of IO is based on the database size and number of channels supported. It starts around $75,000 for a 100,000 row database for one channel for a perpetual on-premise license. The system has fewer than 50 installations.

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Alterian Alchemy Knits Together Marketing Components

Summary: Alterian just announced Alchemy, which provides a new interface and tight integration across existing components.

Alterian last week announced a new generation of products called Alchemy. It’s positioning these as “customer engagement solutions” rather than “campaign management” solutions. The general idea seems to be that customer engagement involves digital dialogs while traditional campaign management is mostly about outbound messages.

Happily, there’s more here than new labels. The main changes, set for release next March, are:

- an integrated framework to share customer information and marketing data (campaign plans, contents, etc.) across channels. This is supported by a new capability to read data in Microsoft SQL Server databases without first loading it into Alterian’s own database engine.

- a new user interface built using the Microsoft Silverlight platform. This is highly configurable and includes specific new tools for building queries, campaigns, and dashboards. The campaign builder in particular has been updated to support trigger-driven, multi-step processes in a branching flow chart.

The company also plans to expand integration with KXEN for predictive analytics, although it hasn’t set a release date.

Alchemy will also include revised and expanded versions of Alterian's social media, Web content management, Web analytics, and email solutions. These will be released throughout the first half of next year. A detailed roadmap is available in the Alchemy FAQ.

Pricing for Alchemy hasn’t been announced, but it will be somewhat higher than current Alterian products. The old products will remain available to serve what Alterian now refers to as “traditional” marketers.

Alchemy is a bit tough to assess. It doesn't add many new functions, but Alterian already had an extremely broad set of capabilities. I think what’s really happening is it knits together products that Alterian had previously acquired but not truly integrated. This is delivering on an old promise, not creating a revolution. Still, it should let marketers do a substantially better job at managing customer relationships across all channels. Revolutionary or not, that's an improvement well worth having.

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DataMentors Offers Low-Cost Marketing Database

Summary: DataMentors has launched a low-cost marketing database product with limited functionality. It's an interesting test of what marketers really want.

Marketing database software and service vendor DataMentors last week tossed its hat into the ever-more-crowded ring of marketing automation for small(ish) businesses. The new product, DataPoint, is a limited version of the company’s flagship PinPoint system. Like PinPoint, it combines DataMentor’s DataFuse data cleansing and matching software with a private-label version of SmartFocus campaign management and analysis. The difference is that PinPoint scales to tens of millions of customer records, while DataPoint is limited to 100,000 customers, one million prospects, fifty data fields and quarterly file updates. Pricing is $2,000 per month, probably less than half what most marketing automation vendors charge for a 100,000 name installation.

Wait. Back up. Did I just write quarterly updates? Fifty fields? Warm up the eight track and fluff out my mullet, modern marketing automation products don’t have those types of limits. Nor does DataMentor’s own PinPoint. What's going on here?

Even though DataPoint includes the quite sophisticated campaign management features of SmartFocus, it’s really less a marketing system than a tool for data analysis. Marketers without any access to their customer data will be happy to load their files into DataPoint and do all the cool slicing and dicing that the SmartFocus engine makes easy. They might produce some outbound campaigns as well, but lack of fresh data means these are going to be pretty generic.

It’s tempting to relate this old-school approach to the origins of DataMentors itself: it was co-founded by industry veteran Bob Orf , the “O” is OKRA Marketing, a pioneer marketing database vendor founded in 1987 when small records and infrequent updates were the rule. But DataMentors has kept up with the times: Orf says that most PinPoint systems are updated daily or weekly, and the company even offers real-time, Web service access to its data quality system. And of course DataPoint users can upgrade to a more powerful version if they’re willing to pay.

That being the case, it’s probably more useful to think of DataPoint as part of the market for on-demand business intelligence – competing in some ways with companies like Birst, PivotLink and Oco. Although those systems are more flexible than DataPoint, they share its low deployment cost and focus on analytics rather than marketing execution.

One key advantage DataPoint has over those systems is integration with DataFuse, a highly sophisticated matching engine that was DataMentor’s original product and remains the cornerstone of its business. Another difference is that DataMentors has recently licensed consumer and business databases for its clients to use as prospect lists or to enhance their own files. DataFuse users can access these for an extra $1,000 per month – another highly competitive rate. DataPoint clients will also benefit from the deep expertise of DataMentors staff, particularly in the banking industry.

A configuration like DataPoint is not something I would have expected in today’s market, where continuous updates, flexible data models and near-real-time customer interactions are standard operating procedure. But I have tremendous respect for the DataMentors team and trust them to know their market. It will certainly be interesting to see how well DataPoint works out for them.

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Marketing Automation Vendor Consolidation: Lessons from History

Summary: consolidation isn't new among marketing software vendors. When campaign management systems consolidated in the late 1990's and early 2000's, most were bought by enterprise software companies. The pattern will likely repeat itself.

As I wrote in my June 30 post on consolidation among marketing automation vendors, I expect the number of competitors to shrink fairly quickly as new buyers concentrate their purchases among a handful of leading vendors. This is a natural result of a maturing market, as technology-oriented pioneers are replaced by buyers less likely to research their options in depth.

But what, exactly, will the consolidation look like? Will weaker marketing automation vendors merge with each other to establish a larger market presence? Will they merge with complementary firms to offer a broader range of capabilities? Will they specialize in particular industries to establish a small but profitable niche? Or will they simply be crushed as giants from related industries introduce their own products?

Let’s look at a similar consolidation about ten years ago, among the original marketing automation vendors.* These were campaign management systems including Exchange Applications, Recognition Systems/Protagona, Prime Response, Intrinsic, Unica, Aprimo, Decision Software TopDog/MarketWide, Alterian and SmartFocus.

The pattern is quite clear. A handful of vendors managed to survive as independent firms. The big winner has been Unica, which competes successfully among high-end buyers. Decision Software has remained a small company while Aprimo is most successful in B2B marketing resource management. Alterian and SmartFocus are also still independent, but are sold largely via marketing service agencies.

The rest of the competitors, including the original market leaders, were nearly all purchased as line extensions by much larger firms. Exchange Applications went to Amdocs, Prime Response went to Chordiant (itself recently purchased by Pegasystems), Protagona was purchased by DoubleClick (now part of Google), Ceres ended up with Teradata, Intrinsic was bought by SAS, Epiphany became part of Infor, Paragren was bought by Siebel (now Oracle). Other, less successful vendors simply vanished. There were no mergers of equals and no one thrived as a specialist in a particular industry. Although Unica, Alterian and SmartFocus have purchased complementary products, these were extensions around the campaign management core.

Although the world has certainly changed since the late 1990’s, I see no reason to expect a different pattern among demand generation vendors. A few might survive as independents serving the most sophisticated clients. Eloqua and Silverpop are the obvious candidates. Of the remainder, the stronger firms will probably be purchased by companies seeking enter the demand generation space, and the weaker firms will quietly go out of business or be purchased for their client lists.

The more interesting question is who will be the buyers. The obvious candidates are CRM vendors. Of course, Oracle has already made its move by purchasing Market2Lead's intellectual assets. Salesforce.com is the big question and no one would be surprised to see them make an acquisition. Enterprise software vendors like SAP and Infor are also likely buyers. Microsoft is another possibility, although its Dynamics CRM is sold mostly to smaller businesses than the typical marketing automation system. Speaking of small business suppliers, Google and Intuit are long-shot contenders.

Email marketing is another obvious adjacent space. Again, there was already one transaction: Silverpop/Vtrenz in 2007. The potential margins from marketing automation probably look relatively attractive to email vendors. The problem here may be that the independent email service providers (ExactTarget, Responsys, Vertical Response) are relatively small companies themselves, so it might be hard for them to make a substantial investment. On the other hand, as the consolidation proceeds, small marketing automation companies may get pretty cheap.

Finally, we come to Web marketing companies. These include content management systems (Autonomy Interwoven, EMC Documentum, OpenText, etc.) and Web analytics (Adobe Omniture, IBM Coremetrics, WebTrends). Note that many of these are already part of larger suites whose owners could easily afford a marketing automation acquisition. A couple of smaller Web content management firms (Marqui, SiteCore) have already moved towards marketing automation. One challenge faced by the smaller Web marketing companies is that their customers (Web site managers and analysts) are generally not the buyers for marketing automation. Even “inbound marketing” (search engine optimization, keyword advertising, Web display ads) is often done by someone other than the marketing automation user. This is less of an issue for larger firms, who have relationships throughout their clients’ organizations.

Incidentally, not everyone agrees that smaller marketing automation vendors must vanish. I had a conversation today with one vendor who argued that success still depends mostly on helping new users get value from their systems. In this view, small vendors can succeed by providing excellent service and support, as well as by linking with marketing agencies and consultancies. This could certainly be a niche – remember that Alterian and SmartFocus survived by working through service providers. Still, I ultimately expect that most mid- and large-size firms will purchase marketing automation as part of a larger software suite, and thus that independent marketing automation vendors will find it increasingly tough to survive.

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*Actually, there was a previous class of “database marketing” systems including Customer Insight Company, OKRA Marketing, Harte-Hanks P/CIS, Max$ell and RTMS. These used proprietary, non-SQL database engines. Most were purchased by larger companies and then discarded when adequate systems using standard SQL databases became available. Alterian and SmartFocus, both descended from Brann Viper, still survive.

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ClickSquared System Combines Marketing Database, Campaign Management and Multi-Channel Message Delivery

Summary: ClickSquared is marketing services agency that, unlike most of its peers, has built its own marketing automation system. The main advantage is tight integration of database build, campaign management and message delivery. The vendor has just officially launched its system, which should meet the needs of most mid-tier consumer marketers.

In a post last week, I casually described ClickSquared as a vendor delivering multi-channel messages for external campaign management systems. This was not wholly accurate. Although integrated multi-channel delivery is indeed a key differentiator for ClickSquared, the firm also offers its own campaign management system, called “Click 3G”. In fact, Click 3G was officially launched last week, although the company has been migrating clients to the platform since Fall 2008.

The more important clarification is that ClickSquared is a marketing services agency, offering database management, campaign development, creative, execution and analysis. The company got its start in 1999 as a direct mail house specializing in overnight execution of trigger marketing programs. Since then it has added email and other services through acquisitions and internal expansion. It now offers a relationships relationships ranging from full-service to self-service, with a particular focus on full-service solutions for mid-tier businesses and on special programs for very large enterprises. It sends emails for about 85% of its 150 clients and maintains marketing databases for about half of them.

In other words, ClickSquared competes with firms like Epsilon, Merkle and Acxiom for enterprise clients, and with a host of smaller firms for mid-tier clients. It also competes to some degree with email providers like Responsys, ExactTarget and InfoGroup YesMail, which are themselves expanding into other channels. (Apologies to all for over-simplification. Properly identifying the overlapping spheres of industry competitors would take a post of its own.)

One feature that stands out about ClickSquared is its choice to build its own campaign management system. This contrasts with the vast majority of marketing services agencies, which rely on industry-standard products such as Unica and Alterian. The fundamental argument for using industry-standard software is that continuously updating a home-grown system costs too much for most marketing services vendors, who can’t spread the expense across as many clients as a dedicated software company. Nor is software development a core competency of many marketing services agencies. Ultimately, this line of reasoning concludes, marketing services agencies compete on database management, analytics, marketing strategy and client service, so software is a poor investment for their necessarily limited resources.

To put matters in historical perspective, most big marketing services agencies did create their own campaign management systems when the category first developed in the 1990’s. But once satisfactory third-party products became widely available, the big firms largely dropped their in-house products. So it’s intriguing that ClickSquared (and a few other firms including Entiera , which I reviewed last July) have again chosen to build their own.

It’s much too soon to consider this a trend, but perhaps the cost/value relationship has shifted back in favor of in-house systems. The logic would be something like this: the prices of commercial systems haven't change, while the cost of building in-house systems has fallen because the requirements are well understood and developers can take advantage of third-party components and agile development methods. Thus, in-house development is relatively more attractive.

But in talking with ClickSquared (and Entiera, for that matter), I hear slightly a different story. It’s true that they avoid hefty license fees by using their own software. But main savings seems to come from integrating several capabilities, including customer data integration, message delivery and reporting, in addition to campaign management itself. This reduces both the total software cost and the labor needed to combine the separate systems. For example, ClickSquared says it can deliver a new marketing database in one to three months, compared with six months or more using third party systems.

Of course, an in-house system must still meet business needs for the savings to be worthwhile. Part of the reason that ClickSquared targets Click 3G at mid-tier companies is that their needs are somewhat less complex than enterprise marketers. That said, the system offers a respectable set of capabilities.

- Customer data can be loaded via API posts or self-service file uploads. The system provides automated data cleansing and customer matching capabilities. It can also gather data with an advanced email survey tool that supports for dynamic questions (i.e., questions change based on previous responses) and complex question types such as rankings and allocations. Marketing content can be uploaded and edited within the system and then shared across campaigns.

- Analytics are largely handled outside the system. These is no built-in predictive modeling, although scores can be imported and used as variables into segment definitions and business rules. The system does provide its own Web analytics module, or it can import data from Omniture or Coremetrics. ClickSquared captures online response using standard link tracking and can generate heat map reports showing how often different links were clicked within an email or Web form. Users can execute custom attribution rules during their database build.

- Campaigns are based on business rules. These can be executed in batch or triggered by events posted to the system API in real time. The rules can consider file segmentation, offer selection, channel preferences and limits on contact frequency when selecting messages. Click 3G also supports “distributed marketing” campaigns that allow users such as branch offices to execute predefined programs by setting a limited number of parameters. Campaign outputs can include dynamically-customized content for direct mail, email, and mobile (SMS) messages, as well as messages sent to CRM systems via an API.

- Message delivery for email is handled directly by ClickSquared, which helps to manage ISP relationships, ensures compliance with anti-spam regulations, and can spread large blasts over time. The system provides similar services for wireless (SMS) messages, although (like most marketing service vendors) it works with a third party to integrate with carriers. For direct mail, ClickSquared can handle preprocessing such as NCOA and then deliver a file of printer-ready personalized PDFs. Although campaign manager-to-email integration is more common today than when ClickSquared began, its multi-channel integration is still an advantage.

- The system also provides several “Web 2.0” options. Most notable is “clickShare”, which lets users register and then upload, share and comment on materials in an online forum. Other applications support referrals, mapping mash-ups and product ratings. Activities in these applications are fed into the marketing database, where they can be used for segmentation and triggers.

Click 3G lacks some refinements of the main commercial campaign management products, such as embedded predictive modeling and detailed project management. The vendor argues that its mid-tier clients don’t necessarily need such features, or at least need them less than tightly integrated database building and message delivery. Click 3G’s largest installations are currently in 15 to 20 million customer range, firmly within mid-tier territory.

Pricing for ClickSquared is based on the combination of professional and technical services used by each client. For Click 3G, factors include database size, channels used, message volume and system modules. A self-service client with 50,000 customers and 100,000 emails per month would pay $1,500 per month for the system. A client with two million customers and a proportionate mix of email, direct mail, text messages, surveys and social content would pay $15,000 per month. Clients commit to a contract of one year or longer.

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Entiera Offers Consumer Marketing Automation Software as a Service

Summary: Entiera is a sophisticated consumer marketing automation system, offered as a service and at a lower price than conventional competitors.

Entiera Insight is a marketing automation system primarily for companies that sell to consumers. I’m highlighting this because most of my recent posts have been about B2B marketing automation (demand generation) systems, and the two types of systems are quite different. This means I apply different standards to evaluate them.

My template for demand generation systems includes outbound email, landing pages, lead scoring, nurturing campaigns, and CRM integration, while my template for (consumer) marketing automation has planning, project management, content management, execution, and analysis. There is certainly some overlap: “execution” in marketing automation typically includes nearly all the demand generation functions except for landing pages and Web content management. But consumer marketing automation systems generally have more advanced database, segmentation, planning, project management and analytics. (See the paper Demand Generation vs. Marketing Automation in the Resources section of the Raab Guide site for more on this topic.)

Back to Entiera. Although their Web site is tagged as “on demand marketing automation”, they have in-house staff to build, run and analyze client databases, plus compiled consumer and business files that can provide prospect lists or enhance customer records. This makes them sound more like a “hosted” vendor than “Software-as-a-Service” (SaaS), per the distinction in my July 25 post. But I ultimately classify them as SaaS because they offer self-service versions of their data loading and analysis tools. This is unusual among consumer marketing automation vendors.

Entiera Insight includes modules for campaign management, predictive modeling, marketing planning, reporting, and database management. Content management and project management are handled within the campaign module. Thus, Entiera offers all five elements of my consumer marketing automation template.

Like most consumer marketing automation products, Enteria is primarily focused on outbound campaigns. Users construct each campaign from components including filters (list selections), paths (segment definitions), channels (messages), suppressions and deduplication rules. These are laid out in a half-tabular, half-graphical format based on columns that each contain a single type of component.

For example, the first column in a typical campaign would contain a filter to select a universe; the next column might contain several path definitions that divide the universe into segments; and the third column could contain several channel definitions, each linked to one previous path. A multi-step campaign would contain several columns of channels, with each channel linked to a channel in a previous column. The terminology and interface are unusual, but should work well after some practice.

Filters and suppressions are constructed with powerful query builder that supports multiple statements, calculated values, and different types of samples (fixed quantity or percentage of universe; random, ranked or Nth selects). Records selected in one filter are automatically excluded from subsequent filters in the same column. This is a standard approach in consumer marketing systems, but often missing in demand generation products. Users can save standard queries and reuse them across multiple campaigns – another feature that’s more common in consumer than B2B systems. Entiera is rolling out a new Adobe Flex-based interface that will have similar functionality but with a more flexible, drag-and-drop style.

The channel (message) objects are assigned channel types, start dates and end dates. These dates are separate from the start and end dates of the parent campaign, although the channel dates must fall within the campaign’s date range. Channel objects can either be triggered by a specific event or execute after a specified waiting period. Although one channel object cannot be shared across campaigns, the objects are built with offers and marketing contents (such as a specific email template) that are themselves reusable. The system captures detailed information about offers, including target audience, limits on how many times they can be used and accepted, effective dates, unit cost, and retail value. This is an impressive set of features.

Campaigns are executed outside the system, either through transferring files or by sending messages to an external API. Entiera currently uses Exact Target as its email partner, although it could work with others. Users can build and reuse standard execution templates for specific destinations. They can also manage seed lists and control groups. Each campaign can execute once or on a regular schedule. The system is designed to support real-time interactions, although no client has yet deployed it that way.

Planning in Entiera is largely at the campaign level. Campaigns can be assigned start and end dates and tagged by type, objective, category and products. This lets users analyze their plans and results across different dimensions—an important need in complex marketing programs. Users can also enter actual and estimated figures for costs, revenues, audience count, responses and conversions. They can define fixed and variable costs for a campaign and have the system calculate the total costs based on volume.

Although the vendor is working on an expanded planning system, this is already more features that many marketing automation systems provide. Project management is less impressive, currently limited to campaign-level task lists. Tasks cannot be assigned to specific individuals, although this should be added by the end of 2009.

Reporting is available through a mix of standard and custom reports. Standard reports track performance by campaign, type, and channel, including responses, conversions, revenue, costs, and return on investment. Users can also see results for different offers and creative types, as well as responder profiles based on demographic information appended from the vendor’s compiled files. Custom reports are built in Jaspersoft open source software. Users can access different views of the underlying database, allowing them to work with data that is organized and named in ways that suit their individual needs. Custom reports can be saved, shared, combined into dashboards, and distributed by email on a regular schedule.

Entiera also supports advanced analytics and database management. A graphical interface lets clients create complex data flows to import and combine multiple sources. It can do name/address matching for customer data integration and can easily incorporate the company’s compiled lists. Kxen statistical software is integrated for end-user predictive modeling and scoring.

I trust it’s clear by now that Entiera is designed to support complex marketing operations. Security is also enterprise-grade, allowing different users to access different functions, data sets and campaigns. The interface supports different languages for different users within the same installation, a subtle feature which identifies enterprise systems. Entiera also supports portals (with message boards, document repositories, Wikis, etc.) that can be open to everyone or limited to a particular group.

The cost for all this is not cheap, but still considerably below a traditional enterprise marketing automation system. Part of the difference is that Entiera includes database management, reporting, analytics, hardware and other costs that would be purchased separately with traditional marketing automation software. In addition, fees for Enteria are just not that high: a mid-size consumer marketer might pay $20,000 to $40,000 per month, which is about half the cost of a traditional on-premise system.

Entiera was founded in 2005 and released the first version of Insight in 2006. The company has about a dozen Insight clients, and many more using its other services.

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SiteCore Adds Analytics and Marketing To Web Content Management

Summary: SiteCore has added extensive analytical and marketing features to its Web content management system. The integrated analytics should save considerable effort for marketers. Channel-specific marketing automation is less appealing but should help to keep marketing automation vendors on their toes.

I commented last month that more Web content management system (CMS) vendors are adding marketing automation features. One of my examples was SiteCore, so I can’t point to them again as further proof of that assertion. But I did have a good talk last week with SiteCore VP Marketing Darren Guarnaccia, who clarified why this is happening and made a strong case for the integrated approach.

For those of you who (like me) are unfamiliar with SiteCore: it is an eight year old provider of Microsoft .NET-based Web content management systems, with over 1,600 mid-to-large sized customers running more than 20,000 dynamic Web sites including Sara Lee, Toshiba, Omni Hotels and Dollar Rent-a-Car/Thrifty. In other words, it is a substantial player in a crowded market.

According to Guarnaccia, the company has seen control over the CMS selection process steadily migrate from IT departments to marketers over the past four years. The trend is most pronounced at mid-sized firms, where IT is generally less powerful than at very large companies. During this time, it’s become clear that marketers need features that go beyond editing Web pages, to helping them do a better job of understanding and reacting to customers. SiteCore describes this as closing an “actionability chasm” between analytics and execution.

The chasm is created by the traditional approach of using analytical systems (often sold as externally hosted services) that are separate from the underlying content management system. Capturing detailed information with such systems involves much more than adding one code snippet to a shared page template. At a minimum, each page must be given its own ID and, more realistically, pages must be given multiple tags to facilitate analysis. Companies running several separate analytical systems may need several sets of tags.

The practical result of such an arrangement is that marketers and their Web teams quickly fall behind in their tagging, and end up with incomplete and unreliable analytics. Building analytics into the CMS allows users to avoid some tags altogether and makes it easier to reuse the rest. Integrated analytics also allow the system to track visitors with first-party cookies, which are less likely to be erased than the third-party cookies used by some stand-alone analytical products.

Integration also makes it easier to coordinate activities such as personalization, behavior-based targeting, and tests. The logic for these potentially overlapping functions can be all managed as part of one Web page definition, rather than separately.

For example, SiteCore supports lead scoring by assigning content scores (for technology, marketing, sales, pricing, tech support, etc.) to each Web page or, potentially, to components within a page. The lead score for each visitor’s interest in each category is the sum of the category scores for all the pages that person has visited. The same information can be used to identify the visitor’s business role or assign a persona.

The advantage of page-based scoring is that the scores adjust automatically to new Web contents. Otherwise, the company must rely on one team of workers to add new content and a separate team to incorporate the new content into the scoring rules.

Guarnaccia offered a Web site marketing maturity model that started with traffic statistics and extended to user experience statistics, content profiling, segmentation, conversion tracking, campaign management, sales enablement (using the IP address to identify visitor location and company), testing and optimization, and real time personalization. He said these are all present at no extra charge within the latest version of SiteCore, which was released at the end of June as the SiteCore Online Marketing Suite. An online demonstration confirmed they are indeed available, and at an impressively high level of sophistication.

SiteCore organizes these features around the individual Web pages. Attributes for each page include interest scores already mentioned, plus goals and other events that are logged to the visitor's history profile when the page is viewed. A page view can also trigger actions including test execution, personalization, data updates, parameter setting, sales alerts, and calls to external scripts. The system also captures the usual Web analytics data such as traffic volume, referring and exit pages, and on-site search terms. It can also use the visitor history to play back the sequence of pages viewed during a Web session.

This page-centric view of the world makes sense for a CMS vendor, but it's a pretty big switch from the campaign-centric view of most marketers and most marketing automation systems. In fact, the biggest objection to CMS-based marketing automation may be that it assumes everything is centered on the Web site.

Guarnaccia didn’t see it that way. He suggested that marketers will use separate systems for each channel. I think that SiteCore’s main goal is to replace stand-alone Web analytics and personalization systems, not to provide cross-channel marketing automation. Still, the company does plan move beyond Web marketing by adding outbound email campaigns in a few weeks. It will also support emails triggered by Web page visits.

My own take is that building analytics into the CMS makes sense, but I doubt marketers want new silos in the form of channel-specific marketing systems. If so, SiteCore’s marketing features will be most appealing to companies that interact with customers primarily through the Web. For those firms, the Web site could reasonably be the core customer management system. Systems for other channels then would connect with the Web database in the same way that auxiliary channels are (sometimes) now integrated with a central Customer Relationship Management (CRM) system.

The CMS-based model relates to other industry trends: integration between marketing automation and sales systems, and, more broadly, absorption of marketing automation into operational systems. For companies where the Web site is the primarily operational system, these are exactly the same thing. For companies where the Web and CRM are both important independent systems, marketing automation is an ally they may both wish to annex.

For now, though, SiteCore is working to cooperate with CRM rather than replace it. The system can scan IP address registries to identify a visitor’s geographic location and company, and then use the results to route leads, alert sales people, and aggregate data at the company level. SiteCore has built data synchronization for Salesforce.com and Microsoft Dynamics and will add other systems as clients request them. If further integration is needed, other systems can access the SiteCore databases directly.

This access is simplified because SiteCore is traditional on-premise software, not an externally hosted service. Pricing is based on the number of concurrent users and servers. A single server license starts as low as $15,000, although an average installation runs about $90,000. The vendor provides several days of classes, including about two days for marketing users.

The reasons for CMS vendors to add marketing automation functions are clear: to differentiate themselves and to capture budget now spent on analytical and marketing systems. It makes perfect sense for companies selecting a new CMS to prefer integrated analytics, and in some cases to add integrated marketing automation. It’s less likely that companies will discard an otherwise-satisfactory existing CMS just to get these features. But the normal replacement cycle runs three to five years, according to Guarnaccia, so it won't be long before most marketers find themselves with integrated analytical features and new marketing automation options. Even if marketers don't use all of those features, the possibility will encourage stand-alone marketing automation vendors to improve their own products to keep pace.

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Market2Lead User Interface: Attention to Detail Pays Off

Summary: Market2Lead's revised user interface has plenty of refined details. But what's most important is it offers different ways to build simple and complex campaigns. This beats even the best "one size fits all" approach.

Time flies. I saw a demonstration of Market2Lead’s new user interface last December, and they released it in February. But I’m only now getting around to writing about it.

It’s a good thing that Market2Lead moved more quickly than I did, because the new interface is a huge improvement. Their previous offering was a good example of what happens when technicians design a user interface: you get the thinnest possible skin stretched over the underlying components. It’s all perfectly logical and functional, but makes no accommodation for how users actually work.

For the redesign, Market2Lead had the good sense to bring in a usability consultant who focused them rigorously on intuitive navigation, fewer mouse clicks, presenting options only as they are needed, and accommodating both novice and expert users. The results included:

- tabs structured around user activities rather than system tables
- wizards to lead users through creating campaigns, programs and Web forms
- floating menus that show options related to the user’s current activity
- pleasant and consistent color schemes that highlight the commonly-chosen menu options
- searches entered directly into form fields and allowing advanced syntax such as lists and value ranges
- different interfaces for creating simple and complex campaign flows

These are not especially novel concepts, so what really matters is how rigorously they are executed. One objective metric is mouse clicks: Market2Lead reports these were reduced by 300%. The others are largely verifiable by sight – yep, the wizards and floating menus really exist.

But listing these items doesn’t convey their combined effect. The resulting system simply feels less stressful than the original version. Even though you may not know in advance how it works, the next step is usually clear.

The campaign interface is the acid test. Market2Lead offers three versions, each tailored to a different level of complexity.

- The simplest are static campaigns, which use predefined flows and typically present a single marketing program. The program itself represents a single offer, but may contain a sequence of contacts such as an outbound email, landing page, and confirmation email. These elements are predefined for different program types, and users simply fill out forms to specify the details. There is no visual flow chart for the program.

Static campaigns wrap some additional rules around a program, such as which campaign the prospects should enter next. These rules can have some conditional logic, creating the equivalent of a branching workflow. But the structure of the flow is predefined for each campaign type and users cannot change it. As with programs, they use forms to fill in the details.

- A second type of campaign does allow users to build their own workflow. For these, called "workflow campaigns", Market2Lead has provided a Visio-style flow builder but kept it simple. Decisions can only have two results (true or false), branches cannot merge within the flow, and prospects always enter a new campaign at the beginning. This eliminates some options but avoids the complicated paths that can make conventional flow charts so confusing.


In fact, the drag-and-drop interface offers just five icons: send a program, make a decision, wait a specified number of days, send to another campaign, and exit. As in other systems, users can click on each icon to define its parameters. Market2Lead has posted an online demonstration.

- For really complicated projects, Market2Lead provides “adaptive” campaigns. These are designed with standard work flows, but replace the specific programs with rules that select the most appropriate program for each prospect. This allows one simple campaign to deliver different messages to different prospects simultaneously, and to deliver a sequence of messages to the same prospect over time.

Of course, the user must still define the rules used to make the program selections. But Market2Lead argues, and I agree, that this is easier than trying to build the rules within the flow chart itself. It also opens the way for increasingly sophisticated selection capabilities, such as the automated statistical approaches that I described last month.

Choosing from three different campaign types may sound confusing. It certainly will take some time for new users to learn when to select each one. But the Market2Lead interface makes the options readily apparent, which will help to some degree.

More important, each choice makes building its particular type of campaign about as easy as possible. This is a much more effective approach than trying to build a single interface that is good for everything. For marketers who execute a broad variety of campaigns, ranging from simple to complex, this will ultimately make their jobs easier.

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Marketbright's Campaign Flows Work Well for Serena Software

Summary: Serena Software is pleased with Marketbright's Visio-style interface for complex campaigns. The real work is in designing the campaigns, not setting them up in the software.

(Second of three posts on demand generation interfaces.)

I spoke last week with Marketbright client Michaline Todd, director of corporate marketing at Serena Software, to see how Serena likes Marketbright’s campaign interface. Marketbright uses the two-level approach that I consider an industry best practice: users can build simple linear campaigns with a wizard-driven interface, and embed these in a Visio-style flow chart to manage flows across campaigns.

The short answer is that Serena is very pleased, since the flows make it easier to enforce complex processing rules that were otherwise difficult to define and execute. The long answer adds a few shades of gray to this rosy picture, and these are worth exploring.

- Serena didn’t build the complex campaigns for themselves. The work was done by an outside agency, Maratona Marketing. The reason was not the Marketbright interface: of the six weeks it took to develop the company's first complex flow campaign, setting it up in Marketbright took twenty minutes. Maratona spent the rest of the time on business issues such as lead scoring, process flow and content creation. This reinforces the point that most companies will need help to take advantage of the new opportunities that demand generation systems present.

- Todd felt the campaign flows were “as easy as Visio”. She meant this as praise, although I suspect that many marketers don’t find Visio all that easy. In particular, Todd said the visual diagrams helped to explain the flows to marketing and sales managers who would otherwise find them hard to grasp. Todd also noted that Serena itself sells software development tools, so its staff is already very comfortable with flow charts.

- Serena is now running into conflicts when a given prospect is in more than one marketing campaign. Marketbright handles this now by limiting each prospect to one message per day, storing any additional messages, and sending them later. The vendor plans to refine this approach by letting users prioritize the campaigns so the most important messages are sent first.

Todd cited a couple other features she appreciated. These include a “flight check” of all components before the campaign is executed and an option to view results of active campaigns by clicking on icons in the flow chart. She didn’t mention some of the limits I noted in my Raab Guide analysis of Marketbright, such as a maximum of two splits leading from any decision within the flow or the inability to create random tests without SQL coding.

We did discuss testing in general. Todd said her company doesn’t run formal a/b tests although it does review the performance of different messages to see which yield higher response. She hinted that she might add testing later but was wary of creating too much complexity in the company’s first flows. Marketbright president Erik Bower reinforced this comment, suggesting that most marketers are too busy to analyze results from many tests. Instead, Marketbright plans to add “self-optimizing” capabilities similar to Google AdWords, which will let marketers load alternative versions and have the system automatically select the better-performing option over time.

We also discussed whether an automated lead nurturing campaign can build a relationship between a prospect and the sales rep whose name is on the system-generated emails. Both Todd and Maratona’s Cari Baldwin told stories about prospects who believed the emails werebeing sent personally. This is good news for companies hoping that demand generation systems can compensate for the loss of direct contact between sales people and early-stage prospects. (See my recent white paper Restoring the Balance for more on this.) But the stories also raise a note of caution: in both cases, the prospect approached the actual sales rep at a trade show, and the rep had no idea what they were talking about. Happily, both reps handled the situation well.

(Note: MarketBright was purchased by Act-On Software two years after this post was published.)

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Silverpop Engage B2B Adds Visual Campaign Builder

Summary: Silverpop Engage B2B has added an innovative visual campaign builder that supports complexity without the drawbacks of a Visio-style flow chart. Thumbs up.

(This is the first of three planned posts on updated interfaces from demand generation vendors.)

Silverpop Engage B2B (formerly Vtrenz) on Monday released its first visual campaign builder, finally matching a feature offered by nearly all its competitors. The interface takes a creative approach to the conflict between simple presentation and complex campaign flows, using what Silverpop describes as “horizontal video-production-style features” that lay out each contact stream in a separate row on the screen. Movement between streams is handled by objects that list the destinations, but don’t connect to them with lines like a conventional, Visio-style flow chart. (Click here for a video demonstration.)

Silverpop told me that they had originally planned to use a Visio-style approach but found the diagrams became unworkably complex once they expanded beyond a few branches. Since this matches my own oft-stated opinion, I readily agreed.

It also can’t have hurt that the Engage B2B was already organized around contact streams, which it calls “tracks”, and rules to direct movement between streams, which it calls “track routes”. This fits perfectly with the new interface. In fact, “track” is precisely the term that audio, video and film producers use to describe their synchronized inputs. Think “sound track” or “8 track tape”. But I digress.

The ability to explicitly direct leads from one contact stream to another is what separates the Engage B2B approach from simple linear campaign flows. In the new interface, track routes are objects within the contact stream, and can be opened to edit the decision rules that determine where the lead moves next. The stream can also contain decision objects with a single rule that is tested repeatedly during a specified evaluation period. This allows the system to wait for an event (e.g., allow one week for response to an email) and still react immediately if it happens. If the rule is not met by the end of the evaluation period, the lead can move to the end of the track, to another track within the campaign, or to another campaign.

The interface includes a variety of thoughtful details that have a major impact on usability.

- A track can include placeholder objects, letting users design a campaign before its marketing materials are ready. Since this raises its own risks, the system flags incomplete objects so users know which still need work.

- Users can hover over the list of destination tracks within a track route object and then click on a destination to move to it.

- When events are based on fixed dates, as in a Webinar promotion, the objects in the different tracks are vertically aligned by date. This makes it easier to grasp what happens when.

- Once a campaign is under way, the system displays actual metrics on the track objects (responses, leads currently in the object, leads that have passed through, etc.) so users can see the results at a glance.

- The rule definition interface offers a wide variety of pre-formatted, fill-in-the-blanks statements. This lets non-technical users build complex rules, since it spares them from learning about database details or programming syntax.

Of course, no interface is perfect. There is no visual overview of how leads move across tracks and campaigns, which can make the flow hard to grasp. Nor is there an alternative, more concise interface for simple linear campaigns. The system doesn’t seem to adapt to different user skill levels or to adjust which options are exposed, although I might have missed some of these features.

Still, the Engage B2B interface represents a much-needed fresh look at solving some of the basic issues in campaign visualization. It definitely raises the bar for the rest of the industry.

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Best Practices for Marketing Automation and Demand Generation Campaigns

I enjoyed my little presentation on BrightTalk last Wednesday, which you can still view by clicking here. (If that doesn’t work, go to the BrightTalk site and key my name into the site search function. This will also bring up a roundtable discussion from Tuesday, which I think was interesting as well.) The BrightTalk platform itself worked nicely and was about as simple as possible. They offer a limited version for free (one 30 minute Webinar per month), which is worth considering if you’d like to dip your toe into this sort of thing. The next level up is $949 per month, which is rather pricey compared with $99 per month for Go To Webinar, a platform we’ve used here which does roughly the same thing. I'm not saying they're identical: BrightTalk lets you upload your slides rather than sharing the screen of your PC, which makes it more reliable, and seems to offer some promotional services too. So you’d want to look more closely at both paid services before making a choice.

But I digress. The heart of my presentation on Wednesday ended up as a list of 37 “best practices” for marketing automation / demand generation programs. I’ll probably embed them in a white paper for the Raab Guide Web site in the near future, but for now I thought I’d share them here. (If you want the full slide deck, complete with moderately witty speaker notes, drop me at email at draab@raabassociates.com.)

A bit of context: the presentation listed a sequence of steps for marketing campaign creation, deployment and analysis. The best practices are organized around those steps.

Step 1: Gather Data. The marketer assembles information about the target audience. Best practices here involve the types of data, and, in particular, expanding beyond traditional sources.
• leads, promotions, responses, orders: these are the traditional data sources used in most marketing systems. Best practices would link actual orders back to the individual leads, and do accurate customer data integration.

• external demographics, preferences, contact names: the best practice here is to supplement internal data with external sources such as D&B, Hoovers, LexisNexis, ZoomInfo, etc. More information allows more accurate targeting and better lead scoring.

• social networks: these can be another source of contact names, and sometimes of introductions via mutual friends. A close look at what individuals have said and done in these networks could provide deep insight into a particular person’s needs, attitudes and interests, but this is more an activity for salespeople than marketers.

• summarized activity detail: marketing systems gather an overwhelming mass of detail about prospect activity, down to every click on every Web page. Best practice is to make this more usable by flagging summaries such as “three visits in the past seven days” and making them available for segmentation and event-triggered marketing.

• self-adjusting surveys: once a lead has answered a survey question, the system should automatically replace that question with new one. This builds a richer customer profile and avoids annoying the lead by asking the same question twice. For a bonus best practice, the system should choose the next question based on user-defined rules that select the most useful question for each individual.

• order detail, payments, customer service: the best practice is to gather information beyond the basic order history from operational systems. This also allows more precise targeting and may uncover opportunities that are otherwise invisible, such as follow-up to service problems.

• near real-time updates: fast access to information about lead behaviors allows quick response, particularly in the form of event-triggered messages. This can be critical to engaging a prospect when her interest is at its peak, and before she turns to a competitor.

• household and company levels: consumers should be grouped by households and business leads by their company, division or project. This grouping permits selections and scoring based on activity of the entire group, which may display patterns that are not visible when looking at just a single individual.

Step 2: Design Campaign. The marketer now designs the flow of the campaign itself. Traditional marketing programs use a small number of simple campaigns, each designed from scratch and often used just once. Even traditional campaigns often include multiple steps, so this itself isn’t listed separately as a new best practice.

• many specialized campaigns: the best practice marketer deploys many campaigns, each tailored to a specific customer segment or business need. These are more effective because they are more tightly targeted.

• cross sell, up sell and retention campaigns: demand generation focuses primarily on campaigns to acquire new leads. The best practice is to supplement these with campaigns that help sell more to existing customers and to retain those customers. Marketing automation has generally included these types of campaigns, at least in theory, but many firms could productively expand their efforts in these areas.

• share and reuse components (structure, rules, lists): when marketers are running many specialized campaigns, they have greater opportunity to share common components, and greater benefit from doing so. Sharing makes it possible to build more complex, sophisticated components and to ensure consistency both in how each customer is treated and in how company policies are implemented.

• new channels (search, Web ads, mobile, social): these new channels are often more efficient than traditional channels, and many have other benefits such as being easier to measure. Best practice marketers test new channels aggressively to find out what works and how they can best be used. Even if the new channels are not immediately cost-effective, marketers can limit their investment but still build some experience that will be useful later.

• multiple channels in same campaign: true multichannel campaigns contact customers through different media. A mix of media allows you to reach customers who are responsive in different channels, thereby boosting the aggregate response. Channels may also be chosen based on stated customer preferences and the nature of a particular contact. Marketing automation systems make it easy to switch between media within a single campaign.

Step 3: Develop Content. This step creates the actual marketing materials needed by each step in the campaign design. These are emails, call scripts, landing pages, brochures, and so on.

• rule-selected content blocks and best offers: content is tailored to individuals not simply by inserting data elements (“Dear [First_Name]” but by executing rules that select different messages based on the situation. For example, a rule might send different messages based on the customer’s account balance.

• map drip-marketing message to buyer stage: best practice nurturing campaigns deliver messages that move the lead through a sequence of stages, typically starting with general information and becoming more product oriented. This is more effective than sending the same message to everyone or always sending product information.

• standard templates: messages are built using standard templates that share a desired look-and-feel and contain common elements such as headers and footers. This provides consistency, saves work, and ensures that policies are followed.

• share and reuse components (items, content blocks, images): like shared campaign components, shared marketing contents minimize the work needed to create many different, tailored campaigns. Sharing also makes it easy to deploy changes, such as a new price or new logo, without individually modifying every item in every campaign.

• unified content management system across channels: even though most marketing materials are channel-specific, many components such as images and text blocks can in fact be shared across different channels. Managing these through a single system further saves work, supports sharing, and ensures consistency.

Step 4: Execute Campaign. The campaign is deployed to actual customers. Best practice campaigns often run continuously, rather than being executed once and then replaced with something new. This lets marketers refine them over time, testing different treatments for different conditions and keeping the winners.

• separate treatments by segment: messages and campaign flows are tailored to the needs of each segment. This could be done by creating one campaign with variations for different segments or by creating separate campaigns for each segment. Which works best depends largely on your particular marketing automation system. Either way, shared components should keep the redundant work to a minimum.

• statistical modeling for segmentation: predictive model scores can often define segments more accurately than manual segmentations. Perhaps more important, they can be less labor-intensive to create, allowing marketers to build more segments and rebuild them more often. This matters because best practice marketing involves so many specialized campaigns and is constantly adjusting to new conditions.

• change campaign flow based on responses, events, activities: best practice campaigns change lead treatments in response to their behaviors. Thus, instead of a fixed sequence of treatments, they send leads down different branches and, in some cases, move them from one campaign to another. Changes may be triggered by activities within the campaign, such as response to a message or data provided within a form, or by information recorded elsewhere and reported to the marketing automation system.

• advanced scoring (complex rules, activity patterns, event depreciation, point caps): simple lead scoring formulas are often inaccurate predictors of future behavior. Best practice scoring may involve complex calculations based on relationships among several data elements, summarized activity detail, reduced value assigned to less recent events, and caps on the number of points assigned for any single type of activity. A related challenge for system designers is making complex formulas reasonably easy to set up and understand.

• company-level scores and activity tracking: the best practice campaign can use aggregated company or household data to calculate scores, guide individual treatments, and issue alerts. This allows more appropriate treatment than looking at each individual in isolation.

• multiple scores per lead: for companies with several products, the best practice to calculate a separate lead score for each. The scores may also have different thresholds for sending the lead to sales.

• define score formula jointly with sales: the salesperson is the ultimate judge of whether a lead is qualified. But many marketing departments still set up lead scoring formulas without sales input. Best practice is to work together on defining the criteria and then to periodically review the results to see if the formula can be improved.

• let sales return leads for more nurturing: traditional lead management is a one-way street, with leads sent from marketing to sales and then never heard from again. Best practice marketers allow salespeople to return leads to marketing for further nurturing. This improves the chances of a lead ultimately making a purchase, even if it doesn’t happen right away.

Step 5: Analyze Results. Learning from past campaigns may be the most important best practice of all. Having many targeted campaigns allows for continuous incremental improvement, achieved by quickly evaluating the return on each project and adjusting future programs based on the results.

• advanced response attribution: traditional methods often credit a lead to whichever campaign contacted them first, or whichever generated the first response. Best practice marketers look more deeply at the factors which may have influenced a lead’s behavior, often applying sophisticated analytics to estimate the incremental impact of different campaigns.

• standard metrics, within and across channels: resources can only be allocated to their optimal use if return on investment can be compared across campaigns. This requires standard metrics, which must be calculated consistently and clearly understood throughout the organization.

• formal test designs (a/b, multivariate): traditional marketers often do little testing, and the tests they do are often poorly designed. Best practice marketing involves continuous, formal testing designed to answer specific questions and lead to actionable results.

• capture immediate and long-term results: initial response rate or cost per lead fails to take into account the value of the leads generated, which can differ hugely from campaign to campaign. Best practice requires measuring the long-term value and building it into standard campaign metrics.

• evaluate on customer profitability, not revenue: customers with the same revenue can vary greatly in the actual profit they bring to the company, depending on the profit margins of their purchases and other costs such as customer support. Best practice metrics include accurate profitability measures, preferably drawn from an activity-based costing system.

• continually assess and reallocate spending: best practice marketers have a formal process to shift resources to the most productive marketing investments. These will change as campaigns are refined, business conditions evolve, and new opportunities emerge. A formal assessment process is essential because organizations otherwise tend to resist change.

Infrastructure. Individual campaigns are made possible by an underlying infrastructure that has best practices of its own.

• consolidated systems (multi-channel content management, campaign management and analytics): today’s marketing systems can usually handle multiple channels, so decommissioning older channel-based systems may save money as well as making multi-channel campaigns easier to execute. Consolidated multi-channel analytics, which may occur outside of the marketing automation system, are particularly important for gaining a complete view of each customer.

• advanced system training: marketing departments often provide workers with the minimum training needed to gain competency in their tools. Best practice departments recognize that additional training can make users more productive, particularly as the tools themselves add new capabilities that users would otherwise not be able to exploit.

• advanced analytics training: analytics play a central role in the continuous improvement process. Solid analytics training ensures that users can set up proper tests and interpret the results. Because data and tools are often already available, lack of training is frequently the main obstacle that prevents marketers from using analytics effectively.

• formal processes: best practice marketers develop, document and enforce formal, consistent business processes. This both ensures that work is done efficiently and makes it possible to execute changes when opportunities arise.

• cross-department cooperation: working with sales, service, finance and other departments is essential to sharing systems, data and metrics. A cross-department perspective ensures that each department considers the impact of its decisions on the rest of the company and on the customers themselves.

Summary

The best practice vision is many marketing campaigns, each precisely targeted, efficiently executed, and carefully designed to yield the greatest possible value. The campaigns are supported by detailed analysis to understand results and identify potential improvements. This information is quickly fed into new campaigns, ensuring that the company continually evolves its approaches and makes the best possible use of marketing resources. Continuous optimization is the ultimate best practice that all other practices should support.

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