0 BridgeTrack Integrates Some Online Channels

What do “Nude Pics of Pam Anderson” and “Real-Time Analytics, Reporting and Optimization Across All Media Channels” have in common?

1. Both headlines are sure to draw the interest of certain readers.
2. People who click on either are likely to be disappointed.

Truth be told, I’ve never clicked on a Pam Anderson headline, so I can only assume it would disappoint. But I found the second headline irresistible. It was attached to a press release about the 5.0 release of Sapient’s BridgeTrack marketing software.

Maybe next time I’ll try Pam instead. BridgeTrack seems pretty good at what it does, but is nowhere near what the headline suggests.

First the good news: BridgeTrack integrates email, ad serving, offer pages, and keyword bidding (via an OEM agreement with Omniture) through a single campaign interface. All channels draw on a common content store, prospect identifiers, and data warehouse to allow integrated cross-channel programs. Results from each channel are posted and available for analysis in real time.

That’s much more convenient than working with separate systems for each function, and is the real point of BridgeTrack. I haven’t taken a close look at the specific capabilities within each channel but they seem reasonably complete.

But it’s still far from “optimization across all media channels”.

Let’s start with “all media channels”. Ever hear of a little thing called “television”? Most people would include it in a list of all media channels. But the best that BridgeTrack can offer for TV or any other off-line channel is a media buying module that manages the purchasing workflow and stores basic planning information. Even in the digital world, BridgeTrack does little to address organic search optimization, Web analytics, mobile phones, or the exploding realm of social networks. In general, I prefer to evaluate software based on what it does rather than what it doesn’t do. But if BridgeTrack is going to promise me all channels, I think it’s legitimate to complain when they don’t deliver.

What about “optimization”? Same story, I’m afraid. BridgeTrack does automatically optimize ad delivery by comparing results for different advertisements (on user-defined measures such as conversion rates) and automatically selecting the most successful. The keyword bidding system is also automated, but that’s really Omniture.

Otherwise, all optimization is manual. For example, the press release says the BridgeTrack campaign manager “reallocates marketing dollars across channels that generate the most incremental return-on-spend.” But all it really does is present reports. Users have to interpret them and make appropriate changes in marketing programs. Similarly, email and offer page optimization means watching the results of user-defined rules and adjusting the rules manually. Rather than claiming that BridgeTrack “does” optimization, it might be accurate to say it “enables” it through integrated real time reports and unified campaign management. Given how hard it is to assemble information and coordinate campaigns without a tool like BridgeTrack, that’s actually quite enough.

Even within its chosen channels, BridgeTrack lacks automated predictive modeling and advanced analytics in general. (The ad server does offer some cool heat maps of placement performance.) This has direct consequences, since it means the system must rely heavily on user-defined rules to select appropriate customer treatments. Unfortunately, rule management is quite limited: users don’t even get statistics on how often different rules are fired or how they perform. The problem is compounded because rules can exist at many different levels, including within content, in content templates, and in campaign flows. Understanding interactions across different levels can be difficult, yet BridgeTrack provides little assistance. The central content store helps a bit, since rules embedded in a particular piece of content are shared automatically when the content is shared. BridgeTrack managers recognize this issue and hope to improve its rule management in the future.

In fact, despite the press release, BridgeTrack managers have a fairly realistic view of the product’s actual scope. This shows in recent agreements with Unica and Omniture to integrate with their respective marketing automation and Web analytics products. Users of the combined set of products would have many of the the planning, off-line marketing, project management and analytical tools that BridgeTrack itself does not provide.

(Actually, based on the July 2007 press release describing the BridgeTrack integration, Omniture positions itself as “online business optimization software” that provides “one standard view across all marketing initiatives”. That’s a bold set of claims. I’m skeptical but will wait to examine them some other day.)

BridgeTrack is a hosted solution. Pricing is designed to be comparable with the point solutions it replaces and therefore is calculated differently for specific activities: message volume for ad serving and email, cost per click for search bid management, and traffic levels for landing page hosting. The campaign manager and reporting systems support all the different channels. These are not usually sold independently but could be purchased for a monthly fee. Customer data integration, which combines BridgeTrack-generated data with information from external sources for reporting and customer treatments, is charged as a professional services project.

0 Datran Media Sells Email Like Web Ads

I wasn’t able to get to the ad:tech conference in New York City this week, but did spend a little time looking at the show sponsors’ Web sites. (Oddly, I was unable to find an online listing of all the exhibitors. This seems like such a basic mistake for this particular group that I wonder whether it was intentional. But I can’t see a reason.)

Most of the sponsors are offering services related to online ad networks. These are important but just marginally relevant my own concerns. I did however see some intriguing information from Datran Media, an email marketing vendor which seems to be emulating the model of the online ad networks. It’s hard to get a clear picture from its Web site, but my understanding is that Datran both provides conventional email distribution services via its Skylist subsidiary and helps companies purchase use of other firms’ email lists.

This latter capability is what’s intriguing. Datran is packaging email lists in the same way as advertising space on a Web site or conventional publication. That is, it treats each list as “inventory” that can be sold to the highest bidder in an online exchange. Datran not very creatively calls this “Exchange Online”, or EO. Presumably (this is one of the things I can’t tell from the Web site) the inventory is limited by the number of times a person can be contacted within a given period.

Datran also speaks of having an email universe of over100 million unique consumers. I can’t tell if this is its own compiled list or the sum of the lists it sells on behalf of its clients, although I’m guessing the former. The company offers event-based selections within this universe, such as people who have recently responded to an offer or made a purchase. This is more like traditional direct mail list marketing than Web ad sales, not that there’s anything wrong with that. Completing the circle, Datran also offers event-triggered programs to its conventional email clients, for retention, cross sales and loyalty building. This is not unique, but it’s still just emerging as a best practice.

From my own perspective, treating an email list as an inventory of contact opportunities exactly mirrors the way we see things at Client X Client. In our terminology, each piece of inventory is a “slot” waiting to be filled. Wasting slots is as bad as wasting any other perishable inventory, be it a Web page view, airline seat, or stale doughnut. One of the core tasks in the CXC methodology is identifying previously unrecognized slots and then attempting to wring the greatest value possible from them. It’s pleasing to see that Datran has done exactly that, even though they came up with the idea without our help.

The notion of slots also highlights another piece of ambiguity about Datran: are email customers purchasing an entire email, or an advertisement inserted into existing email? There is language on the company site that suggests both possibilities, although I suspect it’s the entire email. Actually, embedding ads in existing emails might be a more productive use of the “slots” that those emails represent, since it would allow delivery of more messages per customer. Whether it would also annoy recipients or diminish response is something that would have to be tested.

Datran offers other services related to online marketing, such as landing page optimization. This illustrates another trend: combining many different online channels and methods in a single package. This is an important development in the world of marketing software, and I plan to write more about it in the near future.

0 The Next Big Leap for Marketing Software

I’ve often written about the tendency of marketing automation vendors to endlessly expand the scope of their products. Over all this is probably a good thing for their customers. But at some point, the competitive advantage of adding yet another capability probably approaches nil. If so, then what will be the next really important change in marketing systems?

My guess is it will be a coordination mechanism to tie together all of those different components – resource management, execution, analysis, and so on. Think of each function as a horse: the more horses you rope to your chariot, the harder it is to keep control.

I’m not talking about data integration or marketing planning, which are already part of the existing architectures, or even the much desired (though rarely achieved) goal of centralized customer interaction management. Those are important but too rigid. Few companies will be technically able or politically willing to turn every customer treatment over to one great system in the sky. Rather, I have in mind something lighter-handed: not a rigid harness, but a carrot in front of those horses that gets them voluntarily pulling in the same direction. (Okay, enough with the horse metaphor.)

The initial version of this system will probably be a reporting process that gathers interactions from customer contact systems and relates them to future results. I’m stating that as simply as possible because I don’t think a really sophisticated approach – say, customer lifecycle simulation models – will be accepted. Managers at all levels need to see basic correlations between treatments and behaviors. They can then build their own mental models about how these are connected. I fully expect more sophisticated models to evolve over time, including what-if simulations to predict the results of different approaches and optimization to find the best choices. But today most managers would find such models too theoretical to act on the results. I’m avoiding mention of lifetime value measures for the same reason.

So what, concretely, is involved here and how does it differ from what’s already available? What’s involved is building a unified view of all contacts with individual customers and making these easy to analyze. Most marketing analysis today is still at the program level and rarely attempts to measure anything beyond immediate results. The new system would assemble information on revenues, product margins and service costs as well as promotions. This would give a complete picture of customer profitability at present and over time. Changes over time are really the key, since they alert managers as quickly as possible to problems and opportunities.

The system will store this information at the lowest level possible (preferably, down to individual interactions) and with the greatest detail (specifics about customer demographics, promotion contents, service issues, etc.), so all different kinds of analysis can be conducted on the same base. Although the initial deployments will contain only fragments of the complete data, these fragments will themselves be enough to be useful. The key to success will be making sure that the tools in the initial system are so attractive (that is, so powerful and so easy to use) that managers in all groups want to use them against their own data, even though this means exposing that data to others in the company. (If you’re lucky enough to work in a company where all data is shared voluntarily and enthusiastically – well, congratulations.)

You may feel what I’ve described is really no different from existing marketing databases and data warehouses. I don’t think so: transactions in most marketing databases are limited to promotions and responses, while most data warehouses lack the longitudinal customer view. But even if the technology is already in place, the approach is certainly distinct. It means asking managers to look not just at their own operational concerns, but at how their activities affect results across the company and the entire customer life cycle. More concretely, it allows managers to spot inconsistencies in customer treatments from one department to the next, and to compare the long-term results (and, therefore, return on investment) of treatments in different areas. Comparing return on investment is really a form of optimization, but that’s another term we’re avoiding for the moment.

Finally, and most important of all, assembling and exposing all this information makes it easy to see where customer treatments support over-all business strategies, and where they conflict with them. This is the most important benefit because business strategy is what CEOs and other top-level executives care about—so a system that helps them execute strategy can win their support. That support is what’s ultimately needed for marketing automation to make its next great leap, from one department to the enterprise as a whole.

0 Independent Teradata Makes New Friends

I had a product briefing from Teradata earlier this week after not talking for nearly two years. They are getting ready to release version 6 of their marketing automation software, Teradata Relationship Manager (formerly Teradata CRM). The new version has a revamped user interface and large number of minor refinements such as allowing multiple levels of control groups. But the real change is technical: the system has been entirely rebuilt on a J2EE platform. This was apparently a huge effort – when I checked my notes from two years ago, Teradata was talking about releasing the same version 6 with pretty much the same changes. My contact at Teradata told me the delay was due to difficulties with the migration. She promises the current schedule for releasing version 6 by December will definitely be met.

I’ll get back to v6 in a minute, but did want to mention the other big news out of Teradata recently: alliances Assetlink and Infor for marketing automation enhancements, and with SAS Institute for analytic integration. Each deal has its own justification, but it’s hard not to see them as showing a new interest in cooperation at Teradata, whose proprietary technology has long kept it isolated from the rest of the industry. The new attitude might be related to Teradata’s spin-off from NCR, completed October 1, which presumably frees (or forces) management to consider options it rejected while inside the NCR family. It might also reflect increasing competition from database appliances like Netezza, DATAllegro, and Greenplum. (The Greenplum Web site offers links to useful Gartner and Ventana Research papers if you want to look at the database appliance market in more detail.)

But I digress. Let’s talk first about the alliances and then v6.

The Assetlink deal is probably the more significant yet least surprising new arrangement. Assetlink is one of the most complete marketing resource management suites, so it gives Teradata a quick way to provide a set of features that are now standard in enterprise marketing systems. (Teradata had an earlier alliance in this area with Aprimo, but that never took hold. Teradata mentioned technical incompatibility with Aprimo’s .NET foundation as well as competitive overlap with Aprimo’s own marketing automation software.) In the all-important area of integration, Assetlink and Teradata will both run on the same data structures and coordinate their internal processes, so they should work reasonably seamlessly. Assetlink still has its own user interface and workflow engine, though, so some separation will still be apparent. Teradata stressed that it will be investing to create a version of Assetlink that runs on the Teradata database and will sell that under the Teradata brand.

The Infor arrangement is a little more surprising because Infor also has its own marketing automation products (the old Epiphany system) and because Infor is more oriented to mid-size businesses than the giant retailers, telcos, and others served by Teradata. Perhaps the separate customer bases make the competitive issue less important. In any event, the Infor alliance is limited to Infor’s real time decision engine, currently known as CRM Epiphany Inbound Marketing, which was always Epiphany’s crown jewel. Like Assetlink, Infor gives Teradata a quick way to offer a capability (real time interaction management, including self-adjusting predictive models) that is increasingly requested by clients and offered by competitors. Although Epiphany is also built on J2EE, the initial integration (available today) will still be limited: the software will run on a separate server using SQL Server as its data store. A later release, due in the first quarter of next year, will still have a separate server but connect directly with the Teradata database. Even then, though, real-time interaction flows will be defined outside of Teradata Relationship Manager. Integration will be at the data level: Teradata will provide lists of customers are eligible for different offers and will be notified of interaction results. Teradata will be selling its own branded version of the Infor product too.

The SAS alliance is described as a “strategic partnership” in the firms' joint press release, which sounds jarring from two previous competitors. Basically, it involves running SAS analytic functions inside of the Teradata. This turns out to be part of a larger SAS initiative called “in-database processing” which seeks similar arrangements with other database vendors. Teradata is simply the first partner to be announced, so maybe the relationship isn’t so special after all. On the other hand, the companies’ joint roadmap includes deeper integration of selected SAS “solutions” with Teradata, including mapping of industry-specific SAS logical data models to corresponding Teradata structures. The companies will also create a joint technical “center of excellence” where specialists from both firms will help clients improve performance of SAS and Teradata products. We’ll see whether other database vendors work this closely with SAS. In the specific area of marketing automation, the two vendors will continue to compete head-to-head, at least for the time being.

This brings us back to Teradata Relationship Manager itself. As I already mentioned, v6 makes major changes at the deep technical level and in the user interface, but the 100+ changes in functionality are relatively minor. In other words, the functional structure of the product is the same.

This structure has always been different from other marketing automation systems. What sets Teradata apart is a very systematic approach to the process of customer communications: it’s not simply about matching offers to customers, but about managing all the components that contribute to those offers. For example, communication plans are built up from messages, which contain collateral, channels and response definitions, and the collateral itself may contain personalized components. Campaigns are created by attaching communication plans to segment plans, which are constructed from individual segments. All these elements in turn are subject to cross-campaign constraints on channel capacity, contacts per customer, customer channel preferences, and message priorities. In other words, everything is related to everything else in a very logical, precise fashion – just like a database design. Did I mention that Teradata is a database company?

This approach takes some practice before you understand how the parts are connected – again, like a sophisticated database. It can also make simple tasks seem unnecessarily complicated. But it rewards patient users with a system that handles complex tasks accurately and supports high volumes without collapsing. For example, managing customers across channels is very straightforward because all channels are structurally equivalent.

The functional capabilities of Relationship Manager are not so different from Teradata’s main competitors (SAS Marketing Automation and Unica). But those products have evolved incrementally, often through acquisition, and parts are still sold as separate components. It’s probably fair to say that they not as tightly or logically integrated as Teradata.

This very tight integration also has drawbacks, since any changes to the data structure need careful consideration. Teradata definitely has a tendency to fit new functions into existing structures, such as setting up different types of campaigns (outbound, multi-step, inbound) through a single interface. Sometimes that’s good; sometimes it’s just easier to do different things in different ways.

Teradata has also been something of a laggard at integrating statistical modeling into its system. Even what it calls “optimization” is rule-based rather than the constrained statistical optimization offered by other vendors. I’m actually rather fond of Teradata’s optimization approaches: its ability to allocate leads across channels based on sophisticated capacity rules (e.g., minimum and maximum volumes from different campaigns; automatically sending overflow from one channel to another; automatically reallocating leads based on current work load) has always impressed me and I believe remains unrivaled. But allowing marketers to build and deploy true predictive models is increasingly important and, unless I’ve missed something, is still not offered by Teradata.

This is why the new alliances are so intriguing. Assetlink adds a huge swath of capabilities that Teradata otherwise would have very slowly and painstakingly created by expanding its core data model. Infor and SAS both address the analytical weaknesses of the existing system, while Infor in particular adds another highly desired feature without waiting to build new structures in-house. All these changes suggest a welcome sense of urgency in responding quickly to customer needs. If this new attitude holds true, it seems unlikely that Teradata will accept another two year delay in the release of Relationship Manager version 7.

0 Business Rules Forum Targets Enterprise Decisioning as the Next Big Thing

I’m headed back from the combined Business Rules Forum / Rules Technology Summit / Rules Expo conference in Orlando. Theme of the conference was ‘Enterprise Decisioning Comes of Age’. The general idea is that business rules have been applied extensively in a few areas, including fraud detection and insurance rating, and are now poised to play a larger role in coordinating decisions throughout the enterprise. This idea has been championed in particular by James Taylor, formerly of Fair Isaac and now running his own firm Smart (Enough) Systems, who seems to have near rock star status within this community.

This is all music to my own ears, since the Customer Experience Matrix is precisely designed as a tool to help enterprises understand how all their pieces fit together across channels and the customer life cycle. It therefore provides an essential framework for organizing, prioritizing and integrating enterprise decision projects. Whether the generic notion of ‘enterprise decision management’ really takes off as the Next Big Thing remains to be seen – it still sounds pretty geeky. One question is what it takes for CEOs to get really excited about the concept: because it is by definition enterprise wide, it takes CEO sponsorship to make it happen. Neither James nor other panelists at the discussions I heard really had an answer for that one.