HubSpot Spreads Its Wings

The folks at HubSpot have been busy this summer, announcing their acquisition of Performable in June and their HubSpot App Marketplace last week. Both events mark a continued expansion of their product.

The company gave me a brief preview of the App Marketplace back in May, when the public beta had just launched. App markets are quite the fashion right now, and HubSpot’s joins the Eloqua AppCloud announced in June. In both cases, what’s really happening is the vendor has published APIs that make it easier for other vendors to build products that integrate with their systems. Such APIs are available to varying degrees for other marketing automation products too, so an app marketplace isn’t quite as huge a leap as it may seem. But marketplaces do make it easier to find compatible applications and, done right, ensure that deployment is very simple.

I couldn’t find a public list of the available HubSpot apps, but their press release cites a connector for Microsoft Dynamics CRM and my notes from May mention custom analytics and shopping cart integration.

Unlike smartphone app stores or Salesforce.com AppExchange, the marketing automation vendor app markets won’t establish their products as “platforms” for a broad range of tasks (although the vendors can dream). They instead extend the functionality of the core product and, mostly, simplify integration with other products that already exist independently. In other words, the app markets are useful but not huge strategic differentiators.

Acquisitions, on the other hand, can be strategically decisive. HubSpot didn’t make that claim for its Performable deal, which shows an admirable sense of reality. Performable offers some interesting capabilities but nothing that radically alters HubSpot’s market position.

The main feature of Performable is an ability to define “events”, which can be page visits, form submissions, or other Web behaviors. This is a useful extension of standard Web behavior tracking techniques. Like other Web tracking, it requires users to install a small Javascript tag on their Web pages. Performable also has existing connectors with a variety of social media, help desk, email, billing, chat and CRM systems. Events and connectors make it easy to build a central database of customer behavior.

Performable leverages this central database with some impressive reporting, showing the first, last, and intervening sources (i.e., the Web site they came from) for visitors who reach each event. Although HubSpot already had reasonable Web analytics, Performable's ability to incorporate additional external activity is a substantial improvement.

Events can also trigger multi-step campaigns that send an email or call an external URL. The URL calls can including parameters with customer information or other data, providing lightweight integration with nearly any external system. Performable also has an impressive landing page builder that supports a/b testing and can ensure that visitors assigned to a particular test group are treated consistently in later visits.

However, the multi-step campaign engine is quite basic. It allows wait periods and conditional steps, but does not allow grouping to automatically exclude customers who meet one condition from subsequent steps. That's a pretty basic feature, typically used to send different messages to different segments at the same stage of a campaign. Users who wanted to do this would need to write conditions for each step that exclude conditions for previous steps. This can be a pain-staking and error-prone chore.

Multi-step campaigns are a weakness in the existing HubSpot system, so it's disappointing that Performable doesn't provide much help. Somewhat similarly, Performable relies on third-party email systems, so it doesn't directly improve HubSpot’s existing email engine, which also lags competitors.

But HubSpot made clear that the Performable acquisition was as much about getting first-rate development talent as about the product itself. In fact, the entire Performable staff joined HubSpot after the acquisition and Performable CEO David Cancel is now HubSpot’s Chief Product Officer. So in that sense, at least, the acquisition is indeed strategic.

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B2B Marketing Automation Industry Size and Segments

As I mentioned yesterday, our new B2B Marketing Automation Vendor Selection Tool (VEST) asks vendors to estimate the number of clients in each of four size categories.

This provides an interesting overview of the industry. The segments are defined based on revenue. Installation counts are:

Looking at the raw percentages doesn’t make much sense since businesses in each group are quite different. There’s a strong case to be made that micro-businesses in particular have such different needs that their vendors are not really part of the same industry as the rest of B2B marketing automation. I’ve described those differences in this post and go into them in our Vendor Selection Workbook (different from the VEST, and free on the Raab Guide site.)

But if you do want to consider all these vendors as one industry, the minimum adjustment to make is to account for differences in price. The table below calculates revenues using reasonable assumptions about revenue per client in each segment:

Combined with the previous chart, this shows the micro-business segment represents 61% of clients but just 17% of industry revenues. At the other extreme, large business represents just 6% of clients but 28% of revenue. The small- and mid-size companies are the heart of the industry , with 55% of the revenue from 33% of the clients.

The $257.5 million revenue estimate is reasonable but it excludes revenues from B2B marketing automation vendors not in the VEST report and the B2B revenues of B2C marketing automation firms. So I’d estimate total industry revenue at $325* million for 2011. This represents a 50% growth over my estimate for 2010. That is consistent with the growth rate I reported yesterday.

The figures also shed light on the ever-popular question of penetration rates. The table below shows company counts by revenue range from business list compiler Manta. But not all of these are B2B marketers. Looking at the industry categories, I'd put the estimated market at half the total.


The 26.7% figure for the large company category is clearly too high, but that's easy to explain: big companies have lots of divisions, so many vendors have sold to a little piece of those firms. There’s certainly still plenty of opportunity left. It’s possible the 3% figure for mid-size firms reflects some of this effect as well.

Figures for the first three categories are more intriguing. They're much lower than the usual estimates that 5% to 10% of companies have marketing automation. Either the surveys behind those estimates are incorrect or my market definition is too broad.

It’s probably a bit of each: surveys tend to reach people who have above-average interest in the topic, and my 50% figure is based on categories that could potentially use marketing automation, not the categories that have deployed it so far. A count of the pioneer companies, basically tech and manufacturing industries, would reduce the estimated market to anything from one quarter to one tenth the numbers shown. This would translate to penetration rates of 10% to 30%, which is more in line with current estimates.

But I’d argue that the market is already growing beyond this core group, so the long-term potential is considerably larger. That’s great news – so long as vendors don’t get stuck in the current niche and so long as competitors from the CRM, email, Web software, Web advertising or other industries don’t swoop in and snatch it all away.

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*The original version of this post estimated $300 million. On consideration, I raised the estimate to $325 million because
- my revised estimate for 2010 was $225
- the 52% growth rate in the previous post was in number of clients, but growth is faster in the higher-priced segments, so the revenue growth would be higher
- average prices are probably rising a bit in the mid-sized segment and big segments, so revenue would rise faster than client counts
- the client counts were gathered in May and June, so they are not quite mid-year figures

I would have gone higher, but the large-company figures are probably overstated in my estimates because many of the 1,200 installations are small, departmental systems that wouldn't generate anything near $60,000 per year.

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B2B Marketing Automation Growth Slowed In First Half of 2011

You know that red-hot B2B marketing automation industry? Don’t look now, but growth is already slowing.

Our just-released update to the B2B Marketing Automation Vendor Selection Toolkit (VEST) shows that client counts grew just over 50% over the year ending in June, compared with nearly 100% growth for the year ending last December. That’s a marked decline, and the pattern is consistent across individual vendors: although some grew faster than others, each grew slower than during the previous period.*

You might think the slower rate is expected because each period starts from a larger base. But it turns out that even the absolute number of new clients fell: about 6,100 were added during the recent period, compared 7,000 during the earlier year. I’ll say that again: fewer new B2B marketing automation systems were sold during the past year than the year ending six months earlier. Ouch.

Here’s the actual data:

As of:	Client Count	Year-Earlier Client Count	Change in Client Count	Growth Rate
June 2011	17,215	11,098	6,117	55%
December 2011	14,177	7,212	6,965	97%

These figures come from eight vendors including all the industry heavyweights: Infusionsoft, OfficeAutoPilot, HubSpot, Pardot, Marketo, Eloqua, Manticore Technology, and Genius. The report actually covers 17 vendors, but the others either were not in the January edition or didn’t provide accurate year-earlier information. The eight companies account for more than 90% of the total installations, so the exclusions are statistically insignificant.**

One obvious question is whether different segments of the industry are growing at different rates. The new report sheds light on this as well. We now ask vendors to estimate their client counts based on four segments:

- micro-businesses, under $5 million in revenue;
- small businesses, $5 to $20 million revenue;
- mid-size business, $20 to $500 million revenue, and
- large business, $500 million or more revenue.

The micro-business segment is concentrated among three vendors: Infusionsoft and OfficeAutoPilot, which serve micro-businesses almost exclusively, and HubSpot, which estimates 50% of its clients are micro-businesses. The remaining five vendors in my data (Pardot, Marketo, Eloqua, Manticore Technology, and Genius) have 69% of their clients in the small and mid-size segments.

The slowdown in growth rates applies to the both sets of vendors, although the small and mid-size group is slightly stronger. Client counts show the same pattern: the absolute increase in the most recent period was lower for the micro-business vendors (4,777 vs. 5,650), while it was essentially flat for the small and mid-size business vendors (1,315 vs. 1,340).

Year-on-Year Growth Rate (Client Count)
Year Ending:	Infusionsoft, OfficeAutoPilot, HubSpot	Pardot, Marketo, Eloqua, Manticore Technology, Genius	All Vendors Combined
June 2011	52%	68%	55%
December 2011	97%	93%	97%

So, what does this mean? Is the marketing automation bubble about to burst?

Not necessarily. Year-on-year growth of 50% is nothing to sneeze at, and, as I mentioned earlier, some vendors are growing much faster. Also bear in mind that several vendors have recently received large infusions of funding, which they'll spend on sales and marketing to further accelerate growth.

But it’s still worth sounding a note of caution. Business plans predicated on the industry continuing to grow exponentially now look more dubious than ever. B2B marketing automation could still stall – as B2C marketing automation did – as a niche product for an elite group of sophisticated marketers. It's fine for vendors to expand their product scope, as several are. But they shouldn’t let this distract them from the more fundamental task of growing the base market through promotion, education, and training.

I like irony as much as anyone, but if the demand generation industry failed to generate demand for its own product, no one would be laughing.

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*As best we can tell. Some vendors provided partial information, so we had to do some interpolation. And the data flowed in over a two month period, so it doesn’t all align precisely with the January and December time-frames. But the pattern is so strong and so consistent that the general conclusions seem reliable.

**There a few mid-sized vendors who didn’t make the report at all, including Act-On Software and ActiveConversion, which have about 300 clients each. I’d guess these and other vendors add 1,000 to 2,000 to the total client count.

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ExactTarget and Eloqua Stake Their Claim To Centralized Customer Management

You probably saw ExactTarget’s June 13 announcement of its strategic partnership with Marketo and Eloqua’s June 21 announcement of its new AppCloud marketplace for connectors with other systems. So did I. But it took a little while to connect with the vendors to get the details, so I’m only now ready to write about them.

Both announcements shared a theme of integration between core marketing platforms and other marketing systems. That Eloqua sees itself as the center of a marketing infrastructure isn’t surprising, although it does show how far we've traveled from the once-common view of marketing automation as an auxiliary to the sales automation “system of record”. ExactTarget’s aspiration to a central role was less expected, since its original and still primary business is email delivery. But ExactTarget has added mobile, Web pages, and social in recent years. They've been pulling these together with an “Interactive Marketing Hub” in beta since last September, which is now used by 500 of their 4,000 clients. The IMH, as we cognoscenti call it, combines ExactTarget's email, mobile, Web pages, Web visitor tracking, and social media with external touchpoints as well as Salesforce.com and Microsoft CRM.

The IMH sports a slick user interface with a very nice dashboard showing real-time updates of summary statistics for each channel. It also provides a central marketing calendar of campaigns across the channels. The underlying database can be simple lists, as in traditional email system, or a proper multi-table structure acting as the primary marketing database. As Captain Planet used to say, The Power Is Yours.

It’s perfectly sensible for ExactTarget to move in this direction, since it otherwise risks being pushed to the unprofitable edges of the marketing world as a commodity email engine. In fact, the real head-scratcher was why ExactTarget would deal with Marketo if it had ambitions to occupy the same central turf. (Marketo’s motivation is obvious: to gain broader distribution.)

ExactTarget’s answer was refreshingly honest: IMH lacks key B2B marketing automation features including lead scoring, advanced segmentation, and multi-step campaigns. The campaign engine will be improved before IMH's official launch this September, but other specialized B2B features probably won’t be added. ExactTarget also sees Marketo as the first of many partner applications for IMH, further clarifying that they see it in the central position.

Eloqua’s AppCloud is obviously modeled on Salesforce.com’s AppExchange and other application stores. The goal is for third parties to extend the value of a core platform by building tools that enhance it. In Eloqua’s case, most of the initial applications are connectors with other systems for Webinars, social communities, messaging and data acquisition. These will be joined over time by apps that add functionality within Eloqua itself. The AppCloud is an extension of Eloqua’s earlier Cloud Connector initiative, which provides APIs for external systems to access Eloqua data and functions. Basically, AppCloud makes it easier to find and deploy those connectors.

I did ask Eloqua how AppCloud relates to its Revenue Performance Management positioning. This felt like a pretty clever question until I later saw it was addressed in the AppCloud press release. Oh well. The answer came smoothly enough: AppCloud makes it easier to gather the activity data needed for Revenue Performance Management analysis. That makes sense, although AppCloud implies a more active integration with external systems than simply reporting against them.

Both the ExactTarget and Eloqua announcements reflect a strategy of positioning their products as a company’s primary customer management system. If you recall my post last week on Adobe and Oracle announcements, those firms also wanted to place themselves at the center of the customer management universe. So does pretty much everyone else.

Obviously they all can’t win this game. At the end of the day, I’d still put my money on the big CRM systems as the logical central repository for customer data. But I do believe that many auxiliary systems will continue to feed data to the central system and somehow coordinate treatment decisions with it. Connectors created to service ExactTarget, Eloqua, and others will make it easier to integrate the peripheral systems with whichever product ends up in the middle. So it’s all good.

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Dueling Strategies: Adobe and Oracle Take Opposite Paths to Customer Experience Management

Adobe on Monday announced a new “Digital Enterprise Platform for Customer Experience Management”. The platform fills the center of Adobe’s three-part corporate mission to “make, manage, and measure” digital content and experiences. The other two pieces were already in place: “make” is Adobe’s original content creation business, while “measure” is Omniture Web analytics.

The strategic significance of the announcement seems more important than the actual product enhancements. These include improved integration of the company’s Web content management system (formerly Day C5) with Scene 7 dynamic content and Omniture Survey and Test & Target; features for salespeople and customer service agents to customize standard documents in a controlled fashion; integrated content reviews and workflows; and a platform to build and share content in multiple formats. The announcement also included beta versions of tools for social engagement, online enrollment, and agent workspaces. Good stuff but nothing earth-shaking.

Adobe's strategy itself is a curious mixture of broad ambition and narrow execution. Adobe describes its scope as nothing less than optimizing customer experience and marketing spend across the entire customer journey, from first learning about a company through validation, purchase decision, product use, and commitment. But Adobe also explicitly limits its scope to digital channels, and implicitly limits its concern to content creation, delivery, and evaluation. In fact, the only customer-facing technology Adobe offers is Web site management. Otherwise, Adobe expects even digital content such as emails to be delivered by third party products. Offline interactions, such as telephone and retail, are definitely out of the picture. Nor does Adobe manage the underlying customer database, marketing campaigns, or deep analytics. The only exceptions are customer profiles, segmentation, and content to support Web personalization.

The company argues the tools it does provide, combined with the cross-channel content sharing, are enough to build a unified digital customer experience. I’m not so sure that’s correct, and even if it is, I question whether customers will be happy to have only their digital experiences be unified. Either way, marketers will certainly need other vendors' products to manage their full customer relationships.

On the other hand, I do agree with Adobe’s argument that its approach lets clients create a unified digital experience without replacing their entire enterprise infrastructure. This is certainly an advantage.

Adobe’s announcement was released on Monday, but I didn’t get around to writing about it until today. The delay is unfortunate, since the attention of the enterprise marketing automation world has already shifted to yesterday’s announcement that Oracle is acquiring Web “experience” management vendor FatWire Software. I’m not sure I accept “Web experience management” as a legitimate software category, but FatWire does combine conventional Web content management with unusually strong targeting, personalization, content analytics, digital asset management, mobile, and social features. Perhaps that justifies calling it more than plain old Web content management.

The strategic purpose of the FatWire acquisition is self-evident: to fill a gap in Oracle’s customer-facing technologies, which already had ATG ecommerce and general Enterprise Content Management for Web sites, as well as Oracle CRM and Oracle Loyalty. (Oracle isn’t very creative with product names.) FatWire will allow much richer, more personalized and targeted Web site interactions. It also provides some Web analytics, although I still think Oracle has a gap to fill there.

The Oracle and Adobe announcements do highlight a clear strategic contrast. Adobe has largely limited itself to digital interactions, and has largely avoided customer-facing systems except for Web sites. Oracle has embraced the full range of online and offline interactions, including customer-facing systems in every channel. Oracle has also hedged its bets a bit with Real Time Decisions, which can coordinate customer treatments delivered by non-Oracle systems and powered by non-Oracle data sources. Of the other enterprise-level marketing automation vendors, IBM, SAS and Teradata share Adobe's focus on digital channels and its avoidance of customer-facing systems, although they resemble Oracle in offering deep analytics and customer database management.

Based on my fundamental rule that “suites win”, I think Oracle’s strategy is more likely to succeed. But only time will tell.

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How Do You Measure the Influence of Marketing Messages?

My review of Coremetrics Lifestyle raised the issue of measuring the impact of marketing materials on customer behavior. Of course, this is just one piece of the marketing attribution puzzle. But it’s worth a separate discussion because it’s such a common question – and, unlike so many measurement problems, this one actually has an answer.

Let’s start with the original impetus. This was an “influence” report that showed the percentage of people reaching a marketing stage who had received specific marketing treatments (or had other attributes such as source, product history, demographic, etc.). The idea was that treatments received by a higher percentage of customers were more influential. In other words, if 100% of new buyers saw a white paper offer and just 50% saw a Webinar invitation, then the white paper has more influence than the Webinar.

Plausible, yes. But wrong.

Let’s think through the example. What if the white paper is offered to everyone? Yes, 100% of new buyers saw it, but so did 100% of non-buyers. We know exactly nothing about whether it made its recipients more or less likely to purchase.

Now, let’s say just 10% of prospects see the Webinar invitation, compared with 50% of buyers. Can we say it has a positive influence? Still no: maybe the Webinar attracts hot prospects who would have purchased anyway. It’s even possible that the Webinar offer annoys people and actually reduces purchase rates. You can’t tell from these figures.

In other words, it’s not enough to know what was seen by customers who became buyers (or, more generally, by people who took any particular action). You also need to know what was seen by non-buyers and, ideally, to compare results for groups that are similar except for that particular treatment.

So, what measures do make sense for assessing influence?

- the simplest measure compares the result rate of treated customers with results for non-treated customers. You might find that 20% of people who receive a white paper became buyers, compared with 10% of people who don’t receive the white paper. These two figures can be combined in a single ratio: 20% of treated / 10% of non-treated = 2.0. The higher the ratio, the more it seems that receiving the white paper increased the likelihood that someone would purchase. But it’s no more than a suggestion: maybe the white paper was sent to people who were stronger prospects to begin with.

- a more advanced measure adjusts for the audience by attempting to limit the non-treated group (e.g., non-buyers) to customers similar to the target group. This could be done by building a statistical model that uses all other attributes to predict behavior. Or, you could apply lead scores or funnel stage definitions. Whatever the technique, the result is to divide the audience into groups that are expected to behave similarly. The calculation would then compare results of treated vs. non-treated customers in each same group. So, a report might find that 40% of “stage 3 leads” (whatever they are) made a purchase after attending a Webinar, while just 15% of “stage 3 leads” made a purchase if they didn't attend a Webinar. Again, the treated and non-treated figures could be combined in a ratio (40% / 15% = 2.7)

- of course, the only true measure is a structured test. This ensures that the only difference between the treated and non-treated groups is the treatment itself. Without such tests, there's a good chance that the customers selected for treatment would have performed differently in any event.

A proper reporting system would present the ratios along with actual result rates, trends over time, the number of customers receiving each treatment, and comparisons with ratios for other treatments. These figures help marketers focus their energies on the most valuable opportunities. Still, the starting point is always a comparison of treated vs. non-treated performance: without that, the numbers could mean anything.

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Swyft Offers Low-Cost Interaction Management Software as a Service

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

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

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

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

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



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

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


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



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

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

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

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

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

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

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

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