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.

HiveFire Curata Cuts the Work in Content Aggregation

Summary: HiveFire Curata makes it easy to assemble and republish content on specialized topics, attracting visitors to your company’s Web site.

Here’s an irony for you: the world is awash with content, but marketers struggle to find enough of it. It’s like a sailor dying of thirst.

Of course, sailors really do die of thirst. It happens when they’re surrounded by salt water they can’t drink. Marketers have the same problem: they can’t use most of the content that’s available.

HiveFire Curata aims to solve this problem by making it easier for marketers to extract usable content from the surrounding ocean. In fact, Curata provides a complete system to not just locate the right content but also to organize and present it to the marketer’s target audience. The goal is to make finding and repurposing existing content easier than creating new content on your own.

More specifically, Curata lets marketers build Web sites that republish content on selected topics, such as news of a particular industry. This attracts the marketer’s target customers and positions the marketer’s firm as an authority in the field. Once the audience is assembled, the site can also deliver the company’s own content and advertisements.

The trick to making this work is efficiency. You don’t need a special tool to scan the Internet: a simple Google Alert or Twitter search will do that for free. But you’d still need to read each article, tag it with keywords, and post it to your site. The work adds up so quickly that most marketers can’t afford to do it.

Curata reduces this effort by using natural language processing to automatically identify, classify and tag potential articles. It then presents them for manual review before being posted to a Curata Web site, which automatically adds them to appropriate indexes for future reference. The result is an organized archive that offers real value to someone interested in a topic. Because the search and tagging are highly automated, Curata says a typical client processes 40 to 80 articles each day in about 20 minutes.

Setting up a Curata site requires little technical skill. Users choose a format and then use a page designer to place widgets for articles, blog posts, lists of articles by category, author or entity, news streams, site search, media galleries, subscriptions and user registration. They also define the sources and search terms and exclusions the system will use to find content. Sources can include social media, news feeds, patent registrations and RSS subscriptions. Content on the Web site can also be published through RSS subscriptions, email newsletters, Twitter, Facebook and LinkedIn.

Because the system is hosted by Curata, it can be set up and maintained without help from the corporate IT department or Web team. This is a critical advantage for many marketers who lack priority access to those resources.

This is all good, and many companies should find Curata well worth the $1,500 per month ($1,200 with an annual contract). But I did see a number of features I’d like added. These include:

- screening the selected articles. Currently the system presents the articles in the sequence they are found, without identifying redundancies or even removing exact duplicates. Intelligent screening could remove some articles and present similar ones together, saving considerable labor when large volumes are involved.

- ranking the selected articles. The system currently reports the traffic attracted by each article, but it doesn’t use this to predict the popularity of new articles. Such predictions should be well within the capabilities of the natural language engine. Nor does the system rank articles on other criteria such as the authority of the source. Ranking could let editors review the most important articles first and discard the others once they had reached their daily quota.

- more subscriber information. Visitors register with the system to post comments and subscribe the email newsletters. But the profile cannot be extended beyond name, password and email address. This is missing an obvious opportunity to capture more information about potential leads.

- subscriber behavior tracking. Curata doesn’t report on the behavior of individual visitors, such as which items they view or how often they visit. This is another bundle of information that marketers and salespeople could use to understand visitor interests and to identify hot prospects.

HiveFire was open to these ideas when we discussed them, so I’d expect to see some appear in the future. But it's worth noting that Curata already has about 40 clients, who are presumably satisfied enough the existing features to pay for them. So even in its current state, Curata is worth a look if you want to sail the seas of content aggregation.

LoopFuse Offers Free Marketing Automation System: Another Step Towards Industry Consolidation

Summary: LoopFuse has launched a free entry-level version of its marketing automation system. It's one example of how vendors are now competing to attract new users. Only the winners will survive industry consolidation, which may be here sooner than you think.

LoopFuse today promised to “transform” the marketing automation industry by offering a free version of its system. Although LoopFuse and others already provide free trials, this is indeed different: while most free trials expire after 30 days and often have limited functionality, LoopFuse’s FreeView can be used for as long as you like and provides pretty much the same features as the paid version of the system. The critical constraint is that volume is limited to 2,500 prospect names, 5,000 emails and 100,000 page views per month. In practice, this means that only very small companies will actually be able to use the free system as their primary long-term marketing system.

LoopFuse knows that, of course. When they briefed me last week, they said the main purpose of the new system is really to entice trial among companies just starting with marketing automation. They’ll make their money when users see the value they gain and pay for higher volumes and add-on features.

Personally, I’d argue that the really significant news out of LoopFuse is their newly tiered pricing structure. The entry point of $350 per month (for up to 10,000 prospects with unlimited emails and page views) is much lower than the $1,000 to $2,000 starting price of most full-function marketing automation systems. Prices at higher volumes are also much lower than competitors. This will put substantial pricing pressure on vendors who, in many cases, are already struggling to reach sustainable margins.

Here’s where the free system comes back into play. To make a free product viable, LoopFuse needed to engineer as much cost as possible out of the entire client life cycle. This means it had to be possible for clients to purchase and configure the system, learn how to use it and resolve support issues with next to no involvement by LoopFuse staff. Once this was accomplished, LoopFuse was in a position to charge lower fees to its paying clients as well. Other vendors – notably Pardot – have followed a similar cost-removal strategy. But LoopFuse may have been more focused than anyone else.

This doesn’t mean that LoopFuse’s success is guaranteed. Other vendors have similar price points for the small business market (see my list of demand generation vendors) although I suspect their internal costs are higher.

More important, price is just one factor in picking a system. Features, ease of use, and support from the vendor and business partners are usually (and rightly) the main considerations. The free product should increase the number of companies that try LoopFuse first, which will gain it paying customers down the road. But I think that most buyers will recognize that they are likely to stay with their first system and conduct a careful evaluation before they start.

For evidence that a free entry-level product does not automatically drive out higher priced systems, consider the hosted CRM market. Salesforce.com easily dominates despite the presence of surprisingly capable free products like ZohoCRM and FreeCRM .

Whatever the result for LoopFuse, the new offering is part of a larger pattern within the industry. Marketing automation (more precisely, B2B marketing automation) has now passed beyond the pioneer stage where fundamentally different approaches compete for acceptance. At this point, we all pretty much know what a marketing automation system does and, truth be told, the major systems are functionally quite similar.

Competition now shifts from building a technically better system to surviving the inevitable industry consolidation. This requires finding ways to attract masses of new customers as they enter the market.

LoopFuse’s price-driven approach is one such strategy. But many vendors have recently taken others:

- Eloqua, Silverpop, True Influence and at least one other vendor I can’t name are planning new interfaces that they believe will substantially improve ease of use, which they see as the critical barrier blocking many potential buyers. I’m skeptical that truly radical improvements are possible but am certainly eager to see what they come up with.

- LeadLife has embedded best practice hints throughout its system, another way to support adoption by users who lack marketing automation knowledge.

- Infusionsoft has repositioned itself as “email 2.0” rather than marketing automation. They believe this makes it easier for their target customers (under 25 employees) to see them as the next logical step beyond standard email.

- Genius.com added a new Demand Generation edition that falls between its basic Email Marketing and full-blown Marketing Automation products. This is another way of easing the transition from basic email marketing.

- LeadForce1 launched a solution that uses advanced text analysis to measure user intent, and thus provide much better guidance to salespeople than conventional behavioral analysis. Although their approach is based on superior technology, it's still a way to attract customers by offering radically greater value than competitors.

- Marketo now calls itself a “the revenue cycle management company”, giving equal public weight to lead management, sales insight and analytics. They still haven’t briefed me on this or their features to support large enterprises, but they seem to be seeking larger, more sophisticated clients who will presumably provide higher profit margins. Given how many other vendors are targeting small businesses, this certainly makes sense. But Marketo will also find itself competing with established marketing automation vendors like Aprimo, Neolane and Unica. who are entering this market from a different direction. It will also be competing with Eloqua, Silverpop and, perhaps most dangerously, the Market2Lead technology recently purchased by Oracle.

The Market2Lead-Oracle deal raises the other major question facing marketing automation vendors: what role CRM vendors will play? In addition to Oracle, CDC Software (owner of Pivotal CRM and MarketFirst) recently invested in Marketbright.

Of course, the really big question is whether Salesforce.com will make a similar move. There have been off-and-on rumors along those lines for months, followed by stout (if not necessarily credible) denial from Salesforce.com that it has any interest in that direction. I’ve tended to take them at their word, but Oracle and Salesforce.com are blood rivals, so Oracle’s move could easily prompt a Salesforce.com reaction.

Oddly enough, no seems to consider whether Microsoft will enter the game. That's surely a possibility, and would move towards a certainty if its two big on-demand CRM rivals both added marketing automation products. We might even see Google and Intuit participate: both already sell to small business marketers.

My fundamental conclusion is that the B2B marketing automation industry is about to enter the long-predicted stage of vendor consolidation, and that this will move quite quickly. The survivors will serve particular market segments: primarily small vs. large businesses, plus possibly some vertical industry specialization. The window for new entrants is rapidly closing, so any new player will need a major differentiator that creates a clear advantage and distinct identity.

Saffron Technology Organizes Data into Memories

Summary: Saffron Technology provides an analytical database that explores relationships among entities and their attributes. It can explore networks, find similarities and guide decisions. Saffron is considerably more flexible than standard semantic engines.

As I was preparing my June 3 review of link analysis vendor Centrifuge Systems, Centrifuge introduced me to their business partners at Saffron Technology. This is an interesting product in its own right.

Saffron describes itself as an “associative memory base product,” a phrase that definitely takes some explaining. In simplest terms, Saffron organizes information into sets of three or four related items.

More specifically, it stores pairs of items in the context of an entity. For example, “Jack-climb-hill”, “Jack-plant-beanstalk”, “Jack-jump-candlestick” and “Jack-build-house” are all part of what Saffron calls Jack’s “memory”.

Related sets can be grouped into "matrices" that share another item. Thus, one matrix could contain “Jack-Jill-up-hill”, “Jack-Jill-fetch-water”, “Jack-Jill-fall-down” and “Jack-Jill-break-crown”, while “Jack-beanstalk-plant-seed”, “Jack-beanstalk-climb-up”, “Jack-beanstalk-steal-harp” and “Jack-beanstalk-kill-giant” form a separate matrix.

Saffron physically prejoins the data in Jack’s memory so it can be accessed easily and shared elements can be stored only once. Jill’s memory is stored separately from Jack’s even though some sets contain the same data. Jill’s memory may also contain sets without Jack (but let’s not tell him). Depending on how the system is configured, the hill could have its own memory as well.

Saffon’s approach lets it handle the subject-verb-object triples used in semantic analysis. But unlike standard semantic triplestores, Saffron is not limited to this structure. Sets could contain all nouns (Jack-Jill-hill), which can be useful even if the precise relationship among the items isn’t known. Or one of the items could be a time dimension. The system also counts of how often each item pair occurs in the source data, supporting statistical as well as semantic analysis.

These features make Saffron substantially more flexible than a semantic system. They also let it work with many more data sources, since reliable subject-verb-object relationships are often unavailable.

This may sound pretty dry, but Saffron's actual applications have been cloak-and-dagger stuff like looking for terrorists and finding roadside bombs. Remember that I was introduced to Saffron by Centrifuge, whose link analysis system is used primarily for law enforcement and security investigations. Saffron’s approach works particularly well with the Centrifuge front-end.

The fundamental advantage of Saffron is that associations among different items are directly accessible for analysis. This lets the system support different types of queries including:

- connections (identifying relationships among items)
- networks (showing how entities connect with each other)
- analogies (finding entities with similar connections)
- classifications (placing similar entities into groups)
- trends (reporting how connections change over time)
- episodes (finding patterns that repeat over time)

Real-world applications extend beyond link analysis to classifications and decisions. For example, the system can select medical treatments for a particular patient or assign suspended loans to different collection processes. These are complex processes. The system must identify entities with similar characteristics, identify the treatments and outcomes for those entities and estimate the likely outcomes of applying different treatments to the current entity.

Saffron's advantage with such applications is that the characteristics, treatments and outcomes are all just items in the data store. There's no need to load them differently or build a causal model of how they interact. In other words, the system needs no inherent assumptions about how the world works. This lets it effortlessly incorporate new data, uncover hidden relationships and react to new situations.

Well, “effortlessly” is a bit of an exaggeration. Saffron does some pretty complicated calculations to decide which entities are most similar and which treatments have the highest expected value (i.e., outcome value x outcome probability). Users have to review results and make judgments to tune the system. But this is still much less work than conventional statistical modeling or rule-based systems.

Saffron’s technology lets users define the types of data to will store, load data into the system, and execute API calls for the different types of analysis (connections, networks, analogies, etc.) Saffron generally relies on external systems to identify entities within source data, classify them into the specified categories, and report their associations to Saffron. Saffron can load structured data as well.

Saffron runs on a 64 bit “soft appliance” that distributes its data over clusters of server drives. The company claims world-record performance at ingesting, storing and accessing triplestore data, as well as compression to about 20 bytes per triple compared with 50 to 150 bytes per triple in other triplestore systems.

But let’s not get too carried away: Saffron works with large but not gigantic databases. Customer systems have been in the one-terabyte range.

Pricing for Saffron is starts at $125,000 per server, where a standard server is an eight core machine with 16 gigabytes of RAM per core. A trial version of the system is also available on the Amazon EC2 cloud as SaffronSierra.

Privacy: Does Anybody Care?

To paraphrase HL Mencken, no one ever went broke underestimating the American public's commitment to privacy. "Quit Facebook Day" reportedly generated 31,000 account closings, compared with the roughly 500,000 new accounts that Facebook adds each day.

This lack of interest in privacy is a tremendous pity, because privacy violations can cause many types of real harm:

- identity theft
- physical violations including stalking and burglary when people are known to be out
- unjustified commercial treatment (e.g. denial of credit or employment) based on irrelevant or incorrect information
- unjustified government activity (e.g., placement on a No Fly list) based on irrelevant or incorrect information

Ironically, such problems seem to generate less public concern than techniques such as "behavioral targeting", even though the consequence of that is...um...receiving a relevant advertisement. I fully understand the real issue is people feel creepy to know that someone is sort-of watching them. But it's probably a good thing to remind them because the watching will continue whether behavioral targeting is regulated or not.

As the Facebook example shows, most people really don't care enough about privacy to protect it at the cost of other benefits, even minor ones like participating in Facebook. Similarly, many Americans seem downright eager to sacrifice their privacy from government surveillance in the name of national security.

The pity is that it's not an either/or choice. In many cases, technology can be designed to preserve privacy and still give the desired benefits. As a good example of what privacy-consciousness looks like when someone really cares, consider how the gun buyers are protected: gun dealers must check buyers' names against a database of felons, but the buyers' names are erased after a few days. (Of course, loopholes apply to "gun shows" but that's another discussion.) Another example -- never implemented so far as I know -- is that instead of reading drivers license information to prove patrons are old enough to drink, bars could have devices that simply scan the license and flash a green or red light depending on whether the person is old enough.

The point in both cases is that systems can be designed to access and retain the minimum amount of information necessary to fulfill their function. Many behavioral targeting systems already work this way -- capturing relevant data but not the actual identity of an individual. These principles could be applied more broadly and more systematically, but only if the people designing and regulating these systems made them a priority.

In practice it seems that other, less rational approaches are being adopted because they are more popular. To quote Mencken again, “For every problem there is a solution which is simple, clean and wrong.”

Without being excessively cynical, I think it's relevant to point out that privacy doesn't have much of a lobby, at least compared with, say, the National Rifle Association. Businesses want to collect data for marketing purposes. Consumer-friendly government officials are the natural opponents of this collection, but are constrained because many government agencies want the data for their own social and security purposes. The only organized opposition comes from a small set of privacy activists who themselves vary considerably in their priorities and capabilities. This means that, as a marketer, I don't spend much energy worrying about seriously restrictive privacy regulations -- even though I'd actually like to see some intelligent restrictions on data gathering by both business and government.

Checklists for Selecting a Marketing Automation System

Summary: here are some checklists to help select a marketing automation system. For more details, attend my Focus Webinar on June 29.

On June 29, I'll be giving a Webinar on “Matching a Marketing Automation System to Your Needs”, part of a day-long set of all-star lead management presentations organized by the Focus online business community. (Click here to register; it’s free.) Here's a bit of a preview.

My message boils down to two words: "use case". That is, prepare detailed use cases for the tasks you need and then have each potential vendor demonstrate how their system would execute them. The point is to focus on your actual requirements and not a generic list of capabilities or vendor rankings.

Another way to put it is: eat your vegetables. Don’t try to avoid the hard work of figuring out what you need the system to do. You’ll have to do that anyway, during implementation. But if you wait until then, you may find out too late that you selected the wrong system.

Even buyers who assess their needs may need some help figuring out what features those needs imply. Here are five tables extracted from the Webinar with some useful details.

The first table shows a sample use case for a Webinar program. (Click on the image to enlarge it.) It illustrates the need for the use case to be specific, both in terms of describing a specific marketing program and of describing the steps to execute the program. Most marketers could put together the first two columns, Tasks and Steps, from their own knowledge. The remaining column, Items to Test, lists system features that may be unfamiliar to marketers who have not previously worked with a marketing automation system. You may need some help (say, from consultants like Raab Associates Inc.) with adding this column to your own use cases.


The second table looks at functions for different types of marketing programs. The premise is that you need different marketing programs for each step in the customer life cycle, starting with awareness generation and ending with retention. Ideally you’ll have programs in each category, but in practice some categories are more important than others. To help focus your selection process on those high-priority categories, the table describes when each category is likely to be important. It then lists the key system function for each category and the specific features related to those functions.


The third table helps to assess the complexity of your needs. The first column describes the media you'll use and the second lists business characteristics contributing to program complexity. Required media can be directly compared with the media supported by potential vendors. Program complexity is a little trickier, but I’d consider your needs complex if more than three or four of the factors are present.


The fourth table is aimed at companies with complex programs. It lists specific requirements you may have and the features needed to meet them. Marketers who don’t need these features may be able to save some time and money by purchasing a system that doesn’t have them built in. On the other hand, some (but not all!) systems do a good job of hiding their advanced features when they’re not being used. So don't automatically rule out an advanced system without looking at it more closely. And bear in mind that you may need the more advanced features in the future.


The fifth table applies to all companies regardless of complexity. It lists features that are present in nearly all systems, but vary widely in their details. For each one, you’ll have to think carefully about your specific needs and see how well each vendor can handle them.


These tables don't list all the features you might need in a marketing automation system. Nor do they address other important considerations such as ease of use, support, partners and stability. I'll talk about all those in the Webinar, so be sure to tune in.

Using a Purchase Funnel to Measure Marketing Effectiveness: Better than Last-Click Attribution But Far From Perfect

Summary: Many vendors are now proposing to move beyond "last click" attribution to measure the impact of advertising on movement of customers through a sequence of buying stages. This is a definite improvement but not a complete solution.

Marketers have long struggled to measure the impact of individual promotions. Even online marketing, where every click can be captured, and often tracked back to a specific person, doesn’t automatically solve the problem. Merely tracking clicks doesn’t answer the deeper question of the causal relationships among different marketing contacts.

Current shorthand for the issue is “last click attribution” – as in, “why last click attribution isn’t enough”. Of course, vendors only start pointing out a problem when they’re ready to sell you a solution. So it won’t come as a surprise that a new consensus seems to be emerging on how to measure the value of multiple marketing contacts.

The solution boils down to this: classify different contacts as related to the different stages in the buying process and then measure their effectiveness at moving customers from one stage to the next. This is no different from the “sales funnel” that sales managers have long measured, nor from the AIDA model (awareness, interest, desire, action) that structures traditional brand marketing. All that’s new, if anything, is the claim to assign a precise value to individual messages.

Examples of vendors taking this approach include:

- Marketo recently announced new "Revenue Cycle Analytics" marketing measurement features with its customary hoopla. The conceptual foundation of Marketo’s approach is that it tracks the movement of customers through the buying stages. Although this itself isn’t particularly novel, Marketo has added some significant technology in the form of a reporting database that can reconstruct the status of a given customer at various points in the time. Although this is pretty standard among business intelligence systems, few if any of Marketo's competitors offer anything similar.

- Clear Saleing bills itself as an “advertising analytics platform”. Its secret sauce is defining a set of advertising goals (introducer, influencer, or closer) and then specifying which goal each promotion supports. Marketers can then calculate their spending against the different goals and estimate the impact of changes in the allocation. Credit within each goal can be distributed equally among promotions or allocated according to user-defined weights. While such allocation is a major advance for most marketers, it’s still far from perfect because the weights are not based on directly measuring each ad's actual impact.

- Leadforce1 offers a range of typical B2B marketing automation features, but its main distinction is to infer each buyer's position in a four-stage funnel (discovery, evaluation, use, and affinity) based on Web behaviors. The specific approach is to link keywords within Web content to the stages and then track which content each person views. The details are worth their own blog post, but the key point, again, is that the contents are assigned to sales stages and the system tracks each buyer’s progress through those stages. Although the primary focus of LeadForce1 is managing relationships with individuals, the vendor also describes using the data to assess campaign ROI.

Compared with last click attribution, use of sales stages is a major improvement. But it’s far from the ultimate solution. So far as I know, none of the current products does any statistical analysis, such as a regression model, to estimate the true impact of messages at either the individual or campaign level. They either rely on user-specified weights or simply treat all messages within each stage as a group. This lack of detail makes campaign optimization impossible: at best, it allows stage optimization.

Even more fundamentally, stage analysis assumes that each message applies to a single marketing stage. This is surely untrue. As brand marketers constantly remind us, a well-designed message can increase lifetime purchases among all recipients, whether or not they are current customers. It’s equally true that some messages affect certain stages more than others. But to ignore the impact on all stages except one is an oversimplification that can easily lead to false conclusions and poor marketing decisions.

Stage-based attribution has its merits. It gives marketers a rough sense of how spending is balanced across the purchase stages and lets them measure movement and attrition from one stage to the next. Combined with careful testing, it could give insight into the impact of individual marketing programs. But marketers should recognize its limits and keep pressing for solutions that measure the full impact of each program on all their customers.

Centrifuge Systems Offers Powerful, Flexible Link Analysis

Summary: Centrifuge Systems offers powerful, server-based link analysis and data visualization. It lets non-technical users load their own data, allowing them to work with minimal external support.

Centrifuge Systems offers data visualization software with a specialty in link analysis (that is, finding relationships among entities such as members of a social network). It isn’t the only vendor in the field – a quick search brought up this list of link analysis systems, which itself is not complete. Centrifuge tells me they are unique in offering link analysis that doesn’t require client software (only a browser with Adobe Flash) and works without a predefined data model. I can't personally confirm this, but was intrigued enough by Centrifuge that its uniqueness is not a prime concern.

Like other link analysis systems, Centrifuge has been used primarily for criminal and intelligence investigations. However, it is currently looking for additional applications such as marketing analysis to understand relationships between customers, locations and products. Since it does conventional data visualization in addition to the link analysis, Centrifugre is at least a potential replacement for visualization tools like Tableau and TIBCO Spotfire.

I had a briefing from Centrifuge a few months ago and recently downloaded their free trial system to play with it a bit. Not surprisingly, it was harder to use by myself than when a salesman was showing it to me. But the basic interface made sense and I can see that with a bit of practice, this would be a pretty effective system for a business analyst even if they lacked deep technical skills.

Setting up a project involves uploading data to the server, connecting to it, and then dragging data elements into position as dimensions and measures. Links between data elements are also defined by dragging fields into place. Users can refine their views by creating filters, derived values and bundles to combine selected items. Results can then be displayed from multiple perspectives including tables, link maps, charts (bar, line, pie, etc.), geographic and bubble maps, timeline, geospatial and drill-down charts.

The dragging itself wasn't as smooth as a typical desktop application, but it was perfectly serviceable and pretty impressive for working within a browser. Charts rendered almost instantly using the small sample data set. A larger volume might slow things down, but the heavy lifting is done on the server, so the system should scale well if the server is adequate. Centrifuge says its largest installations involve thousands of users and many millions of database rows.

The most important feature of Centrifuge is probably its ability to upload and link pretty much any type of data. External connections use JDBC drivers, which support sources including spreadsheets, XML and live feeds as well as conventional databases. The latest release lets analysts add new data sources by themselves, letting them work quickly with minimal technical support.

The system also lets users extract a subset of data and analyze it independently, reducing the load on the server. They can share their work by publishing it to a server as a PDF or live asset available to others. Newly published assets can be listed in an RSS feed.

Centrifuge was founded in 2007 and has multiple government clients, plus a few in private industry. Pricing starts at $4,000 for a single user perpetual license plus 18% annual maintenance.

Customer Worthy (The Book) Offers Methodology for Customer Experience Management

My friend and former business partner Michael Hoffman of ClientXClient recently sent a copy of his new book Customer Worthy, which explores use of his customer experience management tool, the CxC Matrix. I’ve long been a big fan of the Matrix*, which visualizes all the ways a customer can interact with a business. The new book provides a detailed explanation of Matrix concepts and applications.

The core concept is to “Think Like a Customer” (a favorite Hoffman catch phrase), meaning to understand each contact from the customer’s point of view. The book explains how to use the Matrix to document contacts throughout the customer life cycle, allowing companies to systematically visualize, analyze, monetize, prioritize and ultimately optimize each interaction. It shows how to extend the Matrix to the departmental and system view of each contact, giving companies a roadmap of the steps they must take to execute on Matrix concepts.

Other sections address privacy concerns and highlight the cost of poor service. A final section explains how each department throughout the company can use the Matrix to organize its internal work and coordinate with the rest of the organization.

Customer Worthy provides a good mix of inspiration, theory and practical examples. I’m pleased he’s taken the time to work through Matrix concepts at length, since it’s a rich topic that repays detailed examination. Even if you don’t deploy the Matrix in the forms that Hoffman describes, it’s worth reading to reinforce the broader points that (a) the customer comes first and (b) there are systematic ways to make that thought a reality.


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*This blog, which started when Hoffman and I were partners, was named for it.

Oracle Buys Market2Lead Intellectual Assets

Oracle tersely announced today that it had purchased the intellectual assets of demand generation vendor Market2Lead. This is an excellent fit for Oracle in that Market2Lead is a sophisticated product that is best suited to large, demanding marketing operations. Those are presumably the firms in Oracle's target market.

Market2Lead CEO Geoff Rego explained some of the mechanics of the deal to me in a private conversation, but the details were not for publication. However, a blog post by Eloqua's Joe Payne confirms that existing Market2Lead customers will remain clients of Market2Lead, while Oracle itself will be purchasing the technology itself. The effect is that those customers will have the option to stay with Market2Lead or migrate elsewhere over time. Payne's post says that Eloqua and Market2Lead have been discussing a path for Market2Lead clients who prefer Eloqua to an Oracle relationship.

The entry of Oracle into the demand generation space certainly reflects growing interest in the field. Note that Oracle's Seibel group already had a robust marketing automation solution for consumer marketers, so this does clarify that B2B marketing automation is different from B2C marketing automation. (This is why I prefer the term "demand generation" for B2B marketing automation, although it's been a losing battle.) If there's a single major distinction between the two types of systems, it's the heavy reliance of B2B marketing automation on sales automation data, which in practical terms means reliance on Salesforce.com. Part of the reason the deal was structured as a purchase of assets may be that Oracle is a major rival to Salesforce.com, and thus neither firm is all that interested in cooperating with the other.

I've been arguing for some time that we can expect an eventual merger of CRM and demand generation systems. The Oracle / Market2Lead deal seems a step in this direction: at the ownership level, those systems will now be integrated, even though they may remain fairly distinct technically. This would actually mirror the structure of Siebel's own merger of CRM and marketing automation components, which also used separate-though-synchronized databases the last time I looked.

A related question is whether this deal also heralds the start of consolidation among demand generation vendors. I do think the industry is overcrowded, but growth rates are still so high that I don't see that consolidation happening quite yet. Most of the activity has been among smaller businesses, who are not the primary clients for Oracle or Market2Lead. So I don't see other vendors as feeling much pressure as a result of this deal. Of course, this could change if Oracle pursues small business marketers directly, but I'd guess that it will take some time before they have a major impact.

Omniture Study Suggests Marketers Doubt Value of Analytics Investment

Not to beat a dead horse, but Wednesday’s eMarketer reported on yet another survey that touched on the question of why marketers don’t measure. Although the Omniture 2010 Online Analytics Survey is obviously limited to Web analytics, the answers probably apply to other types of measurement as well.

I wasn’t able to get a copy of the full survey results, despite two requests to Omniture and even filling it out myself, which was supposed to yield a copy that compared my answers with my peers'. Perhaps I’m peerless. But the snippets published in eMarketer are enough for now.


Specifically, eMarketer reported that the leading challenge in Web analytics was “talent”, cited by 58.4% of respondents. Assuming that “talent” is really a polite way of saying “skilled staff”, this suggests that lack of education, not lack of time, is the critical roadblock to better measurement. I’ve been betting the reason is time, but would reconsider in the face of new evidence.

But wait.

When I took the survey, the question about “talent” actually defined it as "lack of skill/time". So it’s perfectly possible that marketers picking "talent" really saw lack of time as the most important challenge.

My position is arguably strengthened by the relatively low ranking of "support/training" (37.6%) and "budget" (31.7%) in the answers. Those can certainly improve skills but they can’t expand the manager's available time. Even hiring more staff wouldn't do that.

On the other hand, the second- and third-ranked challenges were "actionability" (47.3%) and "finding insights" (41.5%) which both suggest doubts that Web analytics can deliver real value. This would show a need for education – but, as I wrote in my comment on the original Why Marketers Don't Measure post, it's a need for education in the fundamental utility of measurement, not education in specific techniques.

Bottom line: the Omniture survey confirms that marketers won’t invest in analytics until they’re convinced it’s the best use of their limited resources. Efforts to expand adoption of analytics should start with that.

DemandBase Adds Real-Time Access to Web Visitor Identities

Summary: DemandBase has added real-time access to its data identifying Web site visitors, enabling Web sites to deliver customized pages. It's another step in the company's systematic expansion.

It’s more than a year since my original post about DemandBase. At the time, they had just extended their product beyond basic IP-address-based Web visitor identification to provide company details and contact names. Last week they announced their next leap forward, an API to return detailed company information quickly enough to use it to tailor visitor treatments.
Specifically, ABR returns data within 10 milliseconds of the initial page request, in time to customize even the first page served. According to DemandBase, this compares with one to two seconds for conventional IP address look-ups.

ABR gains its speed by querying DemandBase’s own database rather than querying external directories. This is one of those things that is harder than it sounds. DemandBase built its database by monitoring which IP addresses most often visit its 2,000-plus clients, parsing multiple external IP directories for the owners and geo-locations of the servers at those addresses, and adding attributes from business directories including D&B, Hoovers and JigSaw. The company says it can associate three times as many visitors with U.S. business addresses as a conventional IP lookup.

Once it finds a match, ABR will return 15-20 client-selected company attributes including size, industry and corporate parent. The system can also apply and return a client’s own data, such as the salesperson assigned to a company and custom classifications for size or industry. These features were already available from DemandBase: what's new with ABR is exposing the data to other applications through a real time API.

One use for the data is to feed rules that send different messages to different sets of customers and prospects. DemandBase is also working to use the data to route chat requests to appropriate agents. Another benefit is sending shorter registration forms to system-identified visitors, improving completion rates while still capturing complete profile data. The system also improves Web analytics by flagging responses from specific companies and market segments, even when visitors fail to identify themselves, delete cookies, or reach the site without clicking on email links.

ABR is still a bit rough around the edges. In particular, there are no prebuilt connectors for specific application systems (Web site engines, CRM systems or analytics tools), so clients are on their own when it comes to integrating the information they receive. The first connectors are due shortly. Similarly, client data such as customers and sales people must currently be loaded by DemandBase staff. This will also change, first with a self-service file upload and eventually with a direct API connection.

Pricing for ABR is set at $2,500 per month for unlimited use. This is beyond the reach of many small businesses, but affordable for companies with the technical savvy and visitor volume to benefit from the system.

Beyond its intrinsic merits, ABR is an interesting illustration of DemandBase’s continuing effort to separate itself from the commodity businesses of IP lookup and compiled data. The company started by giving away its basic service, identification of company visitors to Web sites, to quickly build a large base of clients and partners. It then added value by enhancing the data with business directory information and making it easy to buy the names of individual contacts. ABR further expands the company’s footprint by using its data to enhance other systems, moving it beyond the business of selling stand-alone software. Clever folks.

CMO Survey: Measurement Isn't Our Top Priority

I’ve spent a lot of time looking at surveys to understand marketers’ priorities. Another one crossed my desk today, taken by Aprimo at Argyle Executive Forum’s 2010 CMO Spotlight Forum: Retail and Consumer Goods & Services on April 29, 2010 in New York.

The results are the most puzzling yet. The survey seems nice and simple: three questions with five answers each, and the answers contain similar categories. But the most common answer to each question suggests a different priority:

Q: What is driving the highest degree of change to your marketing strategies?
A: Creating more compelling customer/prospect experiences (37%)

Q: What is the CMO’s biggest challenge today?
A: Integrating and tracking multiple channels (37%)

Q: What is most broken in marketing?
A: Correlating marketing activities to revenues (39%)

So which is it, folks? Customer experience, channel integration or marketing measurement? It's nice to know that I could cite whichever I like if I have a particular point to support. But mostly this suggests that CMOs are just plain confused.

I suppose a more subtle interpretation would be that marketers know that correlation of activities with revenues is their "most broken" process, but consider fixing it less important than integrating multiple channels. You could argue this supports the case I made in my last two posts that marketers haven't invested in measurement because they have other priorities.

The table below gives a more complete view of the results, with color-coding of related answers across categories. You might see a bit of a pattern if you look hard enough: integration and measurement show up in four of top six cells. And I suppose the #3 rank of measurement in the "biggest challenge" category reinforces my argument about its low priority.

Goals Driving Most Change

Biggest CMO Challenge Today

Most Broken in Marketing

create compelling experiences 37%

integrate & track multiple channels 37%

correlate activity w/revenue 39%

ROI / accountability 27%

do more with less 28%

lack of channel integration 27%

digital marketing 18%	accountability / measurement 18%	too many silos 15%

integrate channels 17%

control messages in social media 11%

perceived lack of marketing value 10%

streamline operations 1%

keep up with social media 6%

channel-consistent messaging 10%

You can download the survey results and take a more detailed CMO survey if you're so inclined. Aprimo seems to be setting up some sort of community as well, although I couldn't find any actual discussion to date.

Why Marketers Don't Measure: A Test to Find Out

Last week's post Why Marketers Don't Measure generated some interesting debate on whether the problem is lack of time or lack of knowledge. It dawns on me that this should be a testable question -- something the assembled measurement gurus should find congenial.

My initial thought is an a/b test of email headlines, one offering "quick and easy ways to improve your marketing measurement" (i.e., time) and the other offering "learn how to do a better job measuring your marketing results" (i.e., knowledge). These could offer a book, Webinar, white paper or something else; what matters is which value proposition is more attractive, which would be measured simply through the open rate. Come to think of it, this could also be a split test in paid search or display ads.

I don't happen to have a suitable event upcoming to actually test this against, but perhaps someone out there could give it a try and share the results? Or can you think of a better test to answer the time vs. knowledge question?

Why Marketers Don't Measure

I had a small epiphany the other day when someone recommended that one of my clients needed a marketing measurement project. As author of The Marketing Performance Measurement Toolkit and a frequent speaker on the topic, I was surprised to find I didn’t like the idea. The problem was that this particular client had other marketing challenges that were more pressing. Even though their measurement could indeed be improved, a measurement project at this time would have been a distraction.

This got me to thinking. If I, a certified measurement guru, rejected a measurement project because we had other priorities, how much more likely are other marketers to make the same judgment? By coincidence – or was it? – I was speaking on the very topic a few days later, so I polled the audience. Sure enough, heads nodded vigorously: yes, they really understand the value of better measurement. But they just didn’t have time to set up a major effort.

It’s no news that marketers are busy. What makes this interesting (to me, at least) is that marketers have for years listed better measurement as a top priority but made little actual progress. When asked about obstacles, they generally come up with reasons like lack of data or measurement technology (For example, see the 2009 Marketing Performance Advantage study from CMG Partners and Chadwick Martin Bailey.) Since these are problems that can be solved with funding, they suggest that the root cause is that marketers doubt measurement is worth the investment or don’t know how to do it.

If ignorance is the problem, then education is the solution. This has long been my premise as a measurement evangelist: if only I could convince marketers that measurement is truly important and help them learn how to do it, they would take the plunge.

But if the real problem is lack of time, then education doesn't matter. My current thinking is that most marketers do sincerely want to improve their measurement programs and would even spend money to do it but just don’t have the time to set things up.

My analogy is a speedometer. We all recognize the benefits of a speedometer and use the speedometer built into our car, but few people would buy a speedometer by itself or attend seminars or buy books on speedometer design. We might glance at the speedometer when we buy a new car, but aren’t likely to give it much weight in our purchase decision. Similarly, I think marketers recognize that measurement is important and will use the measurement tools they have available, but few buy stand-alone measurement systems or make measurement a major factor in their product selection.

If I’m right about this, marketing system vendors are in an awkward position. They know that marketers are likely to use only the measurement tools their products provide, and thus that they should build in strong measurement capabilities to help their clients succeed. But they also know that marketers won’t buy their products because they have better measurement or pay extra for measurement features. So the software companies have no incentive to invest in better measurement capabilities.

Economists are familiar with this sort of market failure. It’s why seatbelts are required by law – because many buyers won’t pay extra for them despite their proven value. (Speedometers too, come to think of it.) Despite this, some marketing software includes extensive measurement features and some vendors have even attempted to differentiate their products with those features. I haven’t asked how that’s working out, but suspect it hasn’t been a major factor in many purchase decisions. (If any vendors care to comment on this point, I'd appreciate it.)

Consultants like myself have it easier. Although most marketers won’t spend either time or money on better measurement, there are enough others willing to pay consultants (basically trading time for money) for at least some of us to make a living.

The implications for me as a writer and speaker are a bit more pointed. Lectures aimed at inspiring or educating marketers about measurement are probably off target. Instead, marketers need concrete advice on how to do better measurement with their existing tools with a minimal investment in time. Such advice will lead to tactical and incremental projects rather than a grand unified measurement vision. But so long as it moves marketers in the right direction, it’s worthwhile.

Genoo Offers Web Marketing for Small Business

Summary: Genoo provides a simple Web site, demand generation and social marketing for $199 per month. It’s not the most sophisticated system or the prettiest, but some small businesses may find it's just what they need.

Genoo offers a small-business-oriented Web marketing system at a small-business-friendly price of $199 per month. I’m somewhat grandly labeling it a “Web marketing system” rather than “demand generation” because its microsite could replace a small company’s primary Web site. Demand generation features are adequate, if a bit rudimentary, and are supplemented by social marketing capabilities that do an above-average job of integrating social activities with traditional lead data. Over all, it’s an option worth considering for businesses with limited funding and limited needs. (For other small business systems, see my list of demand generation vendors from last November.)

Let’s start with the microsites. Each Genoo subscription includes a single site with unlimited pages using the client’s own domain name. Pages can be built with Genoo’s free standard design templates or clients can pay Genoo $500 for a custom template. Each page can incorporate CSS style sheets, tags for search engine optimization, social sharing widgets, data capture forms, and visitor comments. Commenters are automatically entered as leads into the Genoo database. The commenting system captures a URL, link text and Twitter name in addition to the usual first/last name and email address.

All pages are built and managed through a content library, which can also contain materials such as images, downloadable files and link lists. An RSS manager lets visitors subscribe to selected items, simplifying programs such as newsletters. RSS subscribers can also be automatically added as leads.

Data capture forms can be displayed within a Genoo page or linked to an externally-hosted page through Genoo-provided Javascript. Either configuration will post data directly to the Genoo database. One major limitation is that the system supports only a fixed set of data fields (29 if I counted correctly). Genoo plans to let users add custom fields but hasn’t set a date for this feature. User-defined surveys, which allow some expansion in data storage, are due this fall.

The current system lets users build forms with any of the existing fields, change formatting, labels and sequence, and designate fields as mandatory. Once a form is submitted, Genoo can add a lead type and lead source to the submitter’s record. Submission can also trigger a confirmation email, send the visitor to a confirmation Web page, and send an alert email to company staff.

Each lead can be tagged with multiple lead types. These can be set by page comments, content downloads and list criteria in addition to form submissions. List criteria can be based on combinations of existing lead types, other lead attributes (location, industry, company size, budget, etc.) and behaviors such as number of site visits, time since last visit, and number of emails.

The system can send emails through list selections or nurture programs. Leads enter nurture programs through triggers, which can be based on assignment of a new lead type or Web events such as email clicks, page views and downloads. Nurture programs contain one or more emails, each sent a specified number of days after the initial trigger event. Genoo’s nurture capabilities are barebones by today’s demand generation standards – email is the only type of message available, there’s no way to send different emails to different leads within the same step, and there's no way to skip a step. Genoo does plan to add direct mail and telemarketing options.

Let me modify that last statement just a bit: most of Genoo’s nurture capabilities are barebones. The scheme to coordinate movement of leads across sequences is quite elaborate – in fact, the term “Byzantine” comes to mind. For each sequence, users can a specify a trigger that will remove leads from the sequence and can decide whether entry to the sequence will remove a lead from all other sequences or a list of specific sequences. So far so good.

But if users really want to get fancy, they can also assign each sequence to a numeric level within track. They can then specify, separately for each sequence, whether entry to the sequence will suspend a lead from all other sequences within a track, from all sequences at lower levels within the same track, or all sequences at lower levels in all tracks. They can also block leads from entering a new sequence if the lead is already active at a sequence on a higher level. This is a very powerful and flexible approach, although users must be well organized to apploy it effectively. Of course, users can ignore these features if they wish.

Lead scoring in Genoo is more straightforward. Points can be assigned for attributes and activities, including the usual Web behaviors (page visits, form submissions, downloads) and social behaviors (sharing, commenting, RSS subscription). This is a closer integration of social into lead scoring than I recall seeing elsewhere. Users also specify how far back to look when assigning points and set a score threshold to submit a lead to CRM. Genoo maintains only one score per lead – a big problem for companies that want to score leads against different products, but a limit that Genoo shares with many other demand generation products.

Genoo offers bidirectional synchronization with Salesforce.com, although only a handful of the company's 32 current clients actually use it. Users have considerable control over which leads are shared, with options to create queues for leads to send to Salesforce and to specify which Salesforce.com campaigns will send leads back to Genoo.

Users can also create shared and personal follow-up queues within Genoo, complete with notes and scheduled activities for individual leads. This lets Genoo to provide basic contact management for clients without a separate CRM system.

Reporting in Genoo is reasonably complete, including source tracking, referrals, search keywords, email campaign results, links clicks, forms filled out, and forward-to-friend forms. The system doesn’t use IP addresses to report on the companies of anonymous Web site visitors, although the vendor is exploring an alliance with a third party to add this feature. As I mentioned in an earlier post on social marketing, Genoo is among the handful of systems that track social click-throughs to the original sharer, allowing marketers to see which leads are actively driving traffic through social media.

These features are all included in Genoo’s base price of $199 per month, regardless of file size or Web activity. Users pay another $8.50 per thousand for emails sent, which won't add much to most clients' bills. Clients wishing to use Genoo as a sales automation system pay another $9.95 per sales user per month. Set-up and support are free and there’s a 30 day free trial.

Genoo and Act-On Software Add Social Marketing Features

Summary: Two low-cost demand generation systems, Genoo and Act-On Software, have added unusually advanced social marketing features.

A few weeks back, I wrote about social marketing features from consumer marketing automation vendors. Naturally our friends in the business marketing space have been adding such features as well. I got details from two of them last week.

- Genoo, which offers a solid demand generation system for a rock-bottom $199/month, has placed a particular focus on capturing contact information from social interactions. People who comment on a Genoo-hosted Web page or subscribe to a Genoo-originated RSS feed can be loaded into the system as contacts and these activities can factor into their lead score. I don’t recall seeing either feature in any other demand generation system, although I haven't checked carefully.

Genoo also offers “share to social” badges for messages delivered by its system. These embed a unique ID to link any resulting Web visits back to the original sharer. This feature is not unique – Genius.com and smartFocus do something similar – but it’s still pretty unusual. However, the value is so obvious that I expect many other vendors will soon follow. Genoo can also assign lead score points for social media sharing.

I expect to post a more comprehensive review of Genoo in the next week or two.

- Act-On Software is another low-cost system, starting at $500 per month. It has made several important enhancements since my review in March 2009, notably multi-step campaign sequences and bi-directional integration with Salesforce.com.

To the current topic, it has also added a “Twitter Prospector” to reduce the labor required to mine Twitter for leads. This lets users define multiple search queries and see each result in separate columns. To screen out marketing pitches, the system can exclude tweets with embedded links. Users can reply to selected tweets through corporate accounts, drawing on a library of standard messages. This reduces the risk of inappropriate replies. Users can also forward a tweet to someone else for review or comment.

Act-On will also string together related tweets to give a sense of the on-going dialog. Web site visits driven from Twitter are flagged in the activity history of individual leads and in general Web analytics reports, although Act-On does not tie them to the originator like Genoo. It does add the Twitter ID of known visitors to their lead profile when possible.

Providing a library of standard replies to Twitter messages is not unique (see my December 2009 review of Spredfast for something similar). But it’s an unusual feature for a demand generation system, which typically defers to CRM for managing interactions with individuals. Act-On originally developed the feature for its own use, so perhaps there's no deep significance to its choice. It's also worth considering that the next logical step -- fully automated replies to social messages -- would almost surely fall within the normal scope of marketing and demand generation. (I'm not sure automated responses are such a great idea, but they will ultimately be the only way to manage the volume of messages presented in social media. So it's more a question of how to do them effectively than whether to do them at all.) What we see here is still more blurring of the boundaries between the demand generation and CRM systems, a trend I fully expect to continue.

Are Experts Obsolete? Not In My Informed Opinion

I recently tripped over an intriguing article on Extinction of the Expert by Denise Gershbein, a creative director at frog design. To be honest, I couldn’t quite follow her argument, but the gist seemed to be that true experts in the future will be people who can integrate information from multiple domains by leading teams of people who are themselves experts in different fields. I sense an infinite recursion here – are the “experts in different fields” themselves people who integrate other experts, or are they domain experts in the conventional sense? But as someone who makes a living based on my own claims of expertise, I’m less interested in Gershbein’s answer than her original question of whether experts will soon be obsolete.

My short answer, you won’t be surprised to learn, is no. Maybe I'm biased by self-interest, but it seems perfectly clear that there are many situations when the collective wisdom of the Internet won’t suffice. If I need a plumber or surgeon or marketing consultant, I need someone who can solve my individual problem, not provide generic advice or spend days researching the issue. In most cases, experts won't provide that kind of personal attention for free. (The exceptions, where experts will provide individual help as a hobby or public service or for glory or because someone else is funding them, are just that – exceptions.) Perhaps my personal expert will be able to call on a crowd of other experts for assistance. But each expert must start with a high level of personal knowledge to be effective. QED.

Even though I expect experts to survive in pretty much their current form, there are certainly changes in their surroundings. In particular, two major trends are well under way:

- information is much more accessible. I know you knew that, but have you considered the kind of information we’re talking about? What’s more accessible is basic information, such as “who are the major vendors in a given market”? Back in the day, just knowing the answer to that qualified you as an expert. Now, anyone can find it in an hour. But the critical point is that once you get beyond basic information, the important details – strengths and weaknesses, specific features, industry reputation – are not easily accessible, and you need to be an expert to even know which questions to ask. So even though experts need deeper knowledge than previously to add real value, people with specific questions still need experts to get the answers.

- experts are much more accessible. This is true in several senses: it’s easier to find an expert; there are more experts to find; and it’s easier to be recognized as an expert. The ease of publishing in blogs and other online venues has removed the bottleneck previously created by traditional media, allowing many more people to display their expertise and making them easier to find. That the number of true experts has expanded may seem debatable, but I believe the greater availability of information means that more people can learn what an expert needs to know. In practical terms, greater accessibility also means that more people can sell their expertise: thus, even if the total number of people with deep knowledge hasn’t expanded, the proportion of those people who are offering their services as experts has certainly grown. This means the net supply has definitely increased.

Of course, the loss of the filters provided by traditional media also means it’s easier for people to appear to be experts when they are not. This matters more in some fields than others: if a credentialing system is still in place, such as government-sanctioned licensing or industry certifications, then experts still must pass the traditional hurdles. But in fields like journalism and marketing, pretty much anybody can peddle their wares to whomever will buy them. This means that the success as a professional expert now requires a new set of self-promotion skills, although it would be naive to believe that success didn’t always require some type of self-promotion. I’d guess it’s easier today for a less-than-fully-competent expert to make a living, if only because it’s easier to attract potential clients. In fields where performance is highly subjective, it’s probably even possible for someone who gives objectively bad advice to build a base of happy reference clients. Although I’m not quite ready to concede that there is no ultimate objective measure of expertise, I do think it’s harder than ever for clients to assess the true competence of experts they are considering for hire.

Back to the original question: if there’s more competition from both competent and less-competent experts, are “true” experts are in danger of extinction? I still don’t think so, but do think they’ll find it harder to make a living, which may ultimately reduce the level of expertise available in the market. Advanced expertise involves considerable investment in training and research, which only well-established, profitable experts can afford. Those experts will continue to prosper by charging premium rates to discriminating clients, but there will be fewer of them and they'll be less likely to share what they know for free over the Internet.

Less knowledgeable clients will settle for less knowledgeable experts, who will be both cheaper and more accessible. Maybe that’s still a net gain compared to a world with a few experts whose rates are so high that many companies can’t afford them. A health care analogy would be a system where more patients get care, but they see a nurse-practitioner instead of a doctor. Since some care is better than none, the average level of care rises, despite the occasional catastrophic error because a more skilled expert was not consulted. (In actual health care, this doesn't happen because nurse-practitioners are trained to call a physician when appropriate. But in other fields, such safeguards don’t exist.)

The economics of being an expert are my problem, since that’s how I make my living. What you, Dear Reader, presumably must worry about is how to get the best value from the experts you employ while avoiding catastrophic results. At this point all I can advise is greater care than ever in selecting your experts – look beyond the persuasive blog posts for concrete experience and proven results. Perhaps community rating mechanisms will eventually make the selection easier, but at the moment you need to question whether the crowd truly knows best.

OneSource Survey: Salespeople Accept Value of Leads from Marketing

Summary: A survey of business-to-business salespeople finds they (still) consider themselves their best source of qualified leads. But marketing-generated leads are gaining increasing respect and salespeople are increasingly looking for help from outside data vendors. Marketers should work closely with salespeople to reinforce these trends, which promise to lower the overall cost per sale.

Most of my interactions are with marketers, so it was interesting to see the opinions of 136 salespeople reported in a recent survey from data vendor OneSource.

The most interesting information was what respondents saw as their largest source of qualified opportunities. By far the leader was “outbound prospecting”, which is a bit frightening given the high cost of such leads. For example, the State of Inbound Marketing 2010 survey from Hubspot found that outbound leads (from telemarketing, trade shows and direct mail) cost an average of $332, compared with $134 per inbound lead (from social media and Web sites).

I suspect that sales people have always felt they must rely on their own outbound prospecting to be successful. What’s probably more significant is that the three next-ranking sources in the OneSource survey come from marketing: Website, inbound calls and email campaigns. Events and trade shows actually rank below all of these. Bringing up the rear are social networking and direct mail, which are rated equal – a pretty impressive showing for social media if you think about it – and Webinars. All together, I see this as a perhaps-grudging recognition by sales people that marketing plays a critical and growing role in generating qualified leads.



Other survey answers were largely consistent with the theme of salesperson self-reliance. The most valuable types of information were targeted contact lists and new CRM contacts; the most useful external data was email address, direct phone numbers and segmented; and the most useful company information was the basics of location and size. These draw a picture of salespeople saying, “Hand me the leads and let me do the rest.” There’s no hint of a role for marketing in nurturing unqualified leads or building brand awareness, although those questions were not exactly asked.

One anomaly in this data is sharply increasing reliance on external business information services. Twelve percent of respondents said they had recently started using these services and a whopping 37% said they were relying on them more heavily. Just seven percent were relying on them less and only 24% are not using them at all. I see this as an acknowledgment by salespeople that outside resources can indeed make them more efficient, even if they still do the actual outbound prospecting themselves.


For what it’s worth, the survey (taken in December 2009) also found some optimism about future sales: 55% said their pipeline was significantly or somewhat better than last year, compared with 33% who said it was significantly or somewhat worse. But sales cycles are still growing: 59% said they were longer than last year vs. 16% saying they were shorter. Although I wouldn’t read too much into such a small survey, this is at least consistent with the hypothesis that there’s a long-term trend towards lengthier, more complicated sales cycles that will continue even once the economy recovers.

Altogether, the results reinforce the conventional wisdom that marketers need to work closely with sales departments to ensure they are delivering qualified leads and that sales people recognize this. Longer-term projects such as lead nurturing and branding are harder to tie to specific sales revenues, but marketers must trace this connection to justify their funding.

SAS, Unica and smartFocus Add Social Media Features

Summary: major consumer-oriented marketing automation vendors have all added some type of social media capabilities. But some focus on monitoring conversations while others help marketers send more messages. Be sure you know which you're getting.

On Monday, marketing automation vendors SAS and Unica both announced new social media capabilities. SAS provided quite a bit of detail while Unica did not, so I can’t compare the two announcements in depth. [Unica provided additional detail after this post was written.] But combined with a social network marketing announcement in February from smartFocus and Alterian's acquisition of social media monitoring system Techrigy last July, all major consumer-oriented marketing automation vendors have now added some flavor of social media marketing to their systems.

What’s really interesting is how widely those flavors vary.

- Techrigy lets marketers and service departments monitor, analyze and respond to comments in social media. See my discussion last July for details.

- SAS's new solution has analytical functions similar to Techrigy, including conversation monitoring and capture, content classification by topic and sentiment, drill-down to individual documents, influence measurement, and dashboards. But it doesn’t seem to include the case management features that a publicity or service department would use to interact with individuals.

- smartFocus aims not to monitor general social media activity but to measure the influence of individuals. Although the press release is short on details, the company told me that what it's really providing is a “share to social” option for system-generated emails. This lets smartFocus track how each recipient shares the item, identify Web visitors who clicked on the shared item, and collect the behaviors of those visitors. This data is linked back to the original recipient, so smartFocus can measure the activity each recipient has generated and profile that recipient's responders. Although the approach is far from comprehensive – it only tracks items that the smartFocus sent and the recipient shared – it does tie those activities to hard metrics such as purchases. It is quite different from calculating influence by counting followers or content reuse, which are the more conventional approaches to social media measurement.

- Unica announced several enhancements to its flagship Enterprise system, of which three had no particular social media focus: adding data capture forms to emails; adding personalization to Web sites via page tags; and a new graphical interface for its event-detection system. A fourth item, incorporating data from social media Web sites in the Web analytics solution, is useful but not ground-breaking. The only substantial new social media addition is Unica’s own “share to social” option, which the company confirms does not link shared items back to the original sharer as does smartFocus.

If there’s a lesson in all this, it’s that “social media solution” is far from a simple check box on your requirements list. Vendor solutions differ widely and will continue to vary for quite some time. SAS and Alterian chose to start with monitoring and measurement, while Unica and smartFocus jumped right into messaging. This nicely illustrates a similar split among marketers in choosing which to do first. Many recognize the need for measurement but can't resist the lure of sending messages that will generate immediate response. But even if you start with a messaging solution, be sure to add monitoring as quickly as possible. I suspect that most firms will find that the information they gather from social media is ultimately more valuable than the relatively small amount of business they gain from social media directly.

VisualIQ Measures Marketing Impacts Across All Channels

Summary: VisualIQ combines customer-level transactions and contact history with traditional aggregate data to produce better marketing performance measurement. It hasn't solved the problem of identifying the same customer across channels, but it's trying.

I was going to start this post by writing that last-click attribution has recently come under fire, but the first Google hit on the topic brings up a study from 2007. So maybe the criticism isn’t particularly new. But the fact remains that, now more than ever, marketers are trying to measure the impact of all contacts on customer behavior.

Broadly speaking, the problem is attacked in two ways. One, most common among consumer goods manufacturers and others who do not sell directly to their customers, uses aggregated data in marketing mix models to find correlations between marketing efforts and total sales. The other, favored by banks, retailers, communications providers and others who do sell directly to known buyers, assesses the impact of each contact with specific individuals. Last-click attribution is a particular challenge for online marketers because they fall between these two situations: they can often identify their buyers but not trace their full contact history.

VisualIQ, founded in 2005 as Connexion.a, proposes to straddle these worlds by combining aggregate-level models with customer-specific contact history. They haven’t found a magic bullet: like everyone else, VisualIQ tracks online customers through cookies, with all the limits that implies. But VisualIQ strives to make the best use of what’s available by unifying data from as many online campaigns as possible, linking cookies with online transactions, and then linking online transactions to offline identities.

This approach offers some general advantages and two specific capabilities. The general advantages come from assembling all advertising and customer transaction information in one database. This allows VisualIQ to analyze campaign results, do whatever identity matching is possible, and to isolate the impact of source, contact frequency, demographics, location and other variables. VisualIQ, a hosted service, has invested heavily in technology to analyze massive data sets along such dimensions.

The first specific capability is relating pre-purchase contacts to actual purchases for individual customers, thus moving beyond last-click attribution. Although this is subject to the limits of cookie-based tracking, VisualIQ does what it can to build a unified identity by sharing the same cookie IDs across as many online channels as possible. The second capability is building mix models with data from actual customer contacts instead of market-level estimates or surveys. VisualIQ says it has found this yields more accurate results than traditional information.

This is all good stuff and VisualIQ has packaged it nicely in a tiered set of offerings. These range from campaign-level reporting to customer-based insights to predictive modeling and simulation, with prices for the simplest system starting as low as $5,000 to $10,000 per month. The company has had considerable success, counting major banks, retailers, and communications firms as clients. Note that these are all industries that sell to their customers directly.

But VisualIQ’s specific offerings are just part of the story. What’s really important is setting explicit goals of linking identities across channels and measuring cross-channel marketing impacts. These are arguably the core challenges in marketing measurement today. This focus has led VisualIQ to look for alternatives to cookies and to use existing methods to combine online and offline information for the same person.

The company is also seeking to make it easier to apply its results. Today, it basically generates reports that suggest better media allocations and advertising contents. But it is working to automatically feed those findings as rules into execution systems such as ad servers and ad exchanges. This brings marketers closer to the ultimate goal of self-optimizing programs. Other vendors are also pursuing self-optimization, but VisualIQ promises the advantage of decisions based on data from all channels rather than a single channel or, heaven forbid, just the last click.