Alterian Pushes Into Social Media Management with Techrigy Acquisition

Summary: Alterian's purchase of Techrigy marks the first integration of serious social media management with marketing automation. Others are sure to follow.

Marketing automation vendor Alterian yesterday announced its acquisition of social media monitoring company Techrigy. Even though the Techgrity deal is the first direct acquisition I recall of a social media monitoring system by a marketing automation vendor, it strikes me as an obvious step. Marketers have been scratching their collective heads for years over how to integrate social media, and marketing automation vendors are very aware of their needs.

I’m not even totally surprised that Alterian was the first to jump into this pool. Although other marketing automation vendors like Unica and SAS are generally more expansive, Alterian has been particularly aggressive about integrated customer management. Previous acquisitions include Web content management (MediaSurface, 2008), contact optimisation (Campaign Calculus 2.0, 2007), email (Dynamics Direct, 2006), marketing resource management (Nvigorate, 2006), and hosted analytics services (MarkIT, 2005).

In fact, according to Alterian’s very interesting FAQ about the Techrigy acquisition, “Engagement marketing” is the core of their current corporate vision. Although I’m generally allergic to sweeping vision statements, I think Alterian has earned the right to use that one. Sparingly.

What really impresses me is that Techrigy is a serious social media monitoring solution. This isn’t about making it easy to react to comments on Twitter, add friends on Facebook, or research prospects on LinkedIn, which is how most marketing automation vendors are approaching social media. Instead (or in addition) Techrigy supports sophisticated searches, categorization, sentiment analysis, influence measurement, author tracking, and case management.

This set of features means that Techrigy is really built more for corporate PR departments and marketing agencies than one-on-one customer management. But that makes the acquisition still more intriguing. I expect Alterian to extend the product to monitor and manage individual relationships, thereby integrating social media with other aspects of customer management.

This would be a major step beyond using aggregate social media data as a way to measure marketing performance – although even such measurement would be itself a great leap forward for most companies today.

It’s by no means certain that Techrigy can actually scale up to manage this many individual relationships. Current users probably track just a small number of individuals and cases, such as key bloggers and specific complaints that must be resolved. Ramping from that to tracking millions of individuals is likely to uncover serious bottlenecks. But even if the system can’t do this today, Alterian should eventually be able to rework it to overcome any obstacles. This sort of processing is a good fit for Alterian’s columnar database engine, which is the core of its business.

I spent some time playing with Techrigy yesterday, using the free version available on their Web site. This allows only 1,000 search results, which is far too few for any real business purpose. But it did give a good flavor for the system.

On the whole, I liked Techrigy very much. Per my previous comment, I was particularly impressed with the scope of the functions.

These start with searching for articles to analyze. The search interface allows advanced logic, complete with Boolean statements, local and global exclusions, and rules to assign the articles to categories for later analysis.

The searches run against articles assembled by Techrigy in a database that stretches back for two years and includes 1.5 billion entries. Sources include blogs, social networks (publicly-accessible sections of Facebook, MySpace, etc.), microblogs (Twitter, Friendfeed, etc.), message boards/forums (such as LinkedIn discussions), wikis (such as Wikipedia), video and photo sharing sites (Flickr, YouTube), and some mainstream media blogs (The New York Times, Wall Street Journal). Querying this database is where the Alterian database engine should shine – yesterday, running even my simple searches took longer than I’d like.

Users can also add their own feeds to search. This could not only capture specialized sources that are too small for Techrigy to monitor, but might include private sources such as a company’s user forums. This opens up a range of important applications beyond public social media tracking.

Searches can run on command, continuously, or on a regular schedule. Results can be streamed to an external viewer as an RSS feed or presented in standard reports. The most basic report shows daily volumes with trends over time. Results can be categorized and filtered based on author popularity (a 0-10 score based on audience), author demographics (age and gender, where known), domains, sources, and keywords. Additional reports show word clouds with themes, which can be derived from keywords or more advanced semantic analysis. There's even a Google Maps mash-up to show author locations. The semantic engine can also tag posts with positive or negative brand sentiment, content tone and emotions.

Users can dig into these reports to view the underlying articles. The system starts with a list of article summaries, similar to a set of Google search results. Users can then select an article and drill into its details, including extracted Web site information and traffic rank, content analysis showing sources of the system-applied tags, the full article itself, and links to Alexa, Technorati, Compete and Quantcast information about the article source.

Users can also delete the entry, mark it as spam, adjust the system-assigned tags, and edit information about the author. This author tracking is what could ultimately be expanded into tracking of individual customers.

Finally, users can assign the article to a user for review or action. This engages the workflow system, which can notify the assigned user and keep track of the article’s status, notes and priority. Here the system moves from social media monitoring into actual relationshipship management.

Techrigy’s user interface is generally okay, although I sometimes had a hard time finding functions such as how to rerun a report. This would presumably go away after a bit of experience. Response time was a little slower than I’d like for tasks such as a applying a filter or presenting an article list. However, this might not be typical: the Alterian acquisition has attracted a lot of attention and generated more than 400 new trial users (per a Twitter post). In any case, this is where the Alterian engine should help.

As for the semantic engine itself – I was underwhelmed by the accuracy of the results. I especially enjoyed the Twitter post “Twitter for B2B Marketing - Marketo: Sin Descripción http://tinyurl.com/mfuh3n” being tagged as negative, religious, and – wait for it -- written in Danish.

A more serious problem is articles like “Ten Mistakes Marketers Make” being tagged as a strongly negative brand reference. But this is probably an issue with most semantic engines (I had a similar problem with ScoutLabs). Presumably Techrigy’s accuracy will improve over time. But even if it doesn’t, users will adjust to what it can do. In practice, you’d expect a company to review all entries tagged as negative, which would then be reclassified or dealt with as appropriate.

Current pricing for Techrigy starts at $600 per month for 20,000 stored search results. Of course, pricing could change under the new ownership.

In sum, Techrigy is an interesting product on its own, but the real story here is the potential for merging social media with other marketing systems. Although this was clearly inevitable, it’s exciting to see Alterian start to make it happen. We can expect other marketing automation vendors to follow quite quickly.

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More on Web Traffic Rankings for Demand Generation Vendors

Last week’s post on Web traffic rankings of demand generation vendors generated a couple of private responses from vendors, pointing out that the Alexa statistics include traffic to operational subdomains for client landing pages and user log-in. In itself, this doesn’t bother me, since it provides data on actual use of the systems. But different products work differently*, so figures for some vendors include landing page traffic while figures for other vendors do not. This makes the rankings even less accurate than they seemed before (which wasn’t very accurate to begin with).

Despite these concerns, I still think the Alexa figures are a useful measure of vendors’ relative market position. My ultimate justification is that the rankings roughly correspond to the vendors self-reported client counts and growth rates. There's value in having an objective, non-self-reported measure, even a crude one, to put the different competitors in perspective.

Some of the vendors offered alternative measures, such as search counts from Google AdWords. Those are interesting too, although they are probably more driven by the scope of the vendor’s marketing program than anything else. My admittedly vague notion of “market presence” includes more than the number of inquiries a vendor is attracting. Basically the goal is to help people identify the “major players” in the industry, since most buyers want to focus on those products.

An interesting by-product of the post was to learn that some marketers were apparently questioned by their management about why they ranked where they did, with the implicit suggestion that a low rank suggested they were doing a poor job. Given that the Alexa figures are heavily influenced by existing client activities, this is not at all a fair inference.

That the question came up at all suggests these companies have not already established standard measures of marketing performance. If such measures were in place and reported regularly, then a random and irrelevant factiod like the Alexa rankings would not have raised any concerns or at least would have made it easy to respond. I guess it’s no news that many companies don't have proper marketing performance measures, but this is still more evidence of why they need them.

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* Most vendors host landing pages for their clients, but sometimes the addresses are a subdomain of the client site rather than of the vendor. Client subdomains would presumably not be captured in the Alexa statistics. Many vendors offer both options, so their statistics would capture traffic for some client landing pages but not others.

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SiteCore Adds Analytics and Marketing To Web Content Management

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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ParAccel Toots Its Horn and Revs Its Database Engine

Summary: Over the past year, columnar analytical database vendor ParAccel has methodically proven its claims about speed, scalability and easy deployment. Now it's looking to grow fast.

When I first wrote about analytical database vendor ParAccel in a February 2008 post, it was one of several barely distinguishable vendors offering massively parallel, SQL-compatible columnar databases. Their main claim to fame was a record-setting performance on the TPC-H benchmark, but even the significance of that was unclear since few vendors bother with the TPC process.

Since then, ParAccel has delivered an impressive string of accomplishments, including deals with demanding customers (Merkle, PriceChopper, Autometrics, TRX) and an important alliance with EMC to create a “scalable analytic appliance”. To top it off, they recently announced their 2.0 release, a new TPC-H record, and $22 million Series C funding. (Full disclosure: they also hired me to write a white paper.)

Of all these, perhaps the most significant news is that the new TPC-H benchmark comes at the 30 terabyte level.* ParAccel’s previous TPC-H championships were at the 100 GB to 1 TB levels.

The change reflects a general growth in the scale of systems supported by MPP columnar databases. ParAccel reports its largest production installation holds 18 TB of compressed data, which probably translates to something more than 50 TB of input. Segment-leader Vertica reports several production installations larger than 100 TB. Neither had more than 10 TB in production a year ago.

These figures still don’t put the columnar systems in the same ballpark as the petabyte-scale database appliances like Netezza, Greenplum and Aster Data, but they do open up some major new possibilities. In case you’re wondering, ParAccel’s TPC-H results were seven times faster and had 16 times better price / performance than the previous record, held by Oracle.

But pure scalability isn’t the key selling point for ParAccel. More than anything, the company stresses its ability to handle complex queries without specialized data schemas or indexes. This means that existing data structures can be loaded as is and queried immediately. The net result is a much faster “time to answer” than competitive systems, which do tailor schemas and/or indexes to specific questions. It also means that new queries can be answered immediately, without waiting for schema modifications or new indexes.

The 2.0 release extends these advantages with a new query optimizer that handles very complex joins and correlated subqueries; parallel data loading (nearly 9 TB per hour in the TPC-H benchmark) and User Defined Functions; enhanced compression; and “blended scans” that avoid Storage Area Network (SAN) controller bottlenecks by loading SAN data onto compute nodes and querying them directly. It also adds some special features such as Oracle SQL support and column encryption for financial data. Another set of enhancements are designed to provide enterprise-class reliability, availability and manageability, such as back-up and failover. Several of these features are already in production, although the official 2.0 release date is August.

The new release and added funding mark a transition of ParAccel from quiet introduction to full-throated selling. Over the past year, the company has carefully limited its participation in Proof of Concept (POC) competitions, the key selection tool in this segment. This gave it time to refine its POC processes, add system features, and build initial client references. It says it can now complete a typical POC in three days, often leaving while other vendors are still getting started. The company is now ramping up its lead generation and inside sales operations, aiming to grow quickly beyond its dozen-plus existing installations. (To provide some context: Vertica reports more than 100 clients.) We'll see what comes next.


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* For some serious doubt-sowing about the new benchmarks, see Daniel Abadi's post (be sure to read the comments) and ParAccel's response. What really matters, as ParAccel points out, is performance in customer POCs. The company says its performance has never been beaten, although there was one tie. (For sheer entertainment, check out the related string on Curt Monash's blog.)

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Lyzasoft White Paper Looks at Coordinating Business Analysts and IT

Summary: a new white paper says business analysts gather data with little help from IT. I'm not so sure, but agree that collaboration tools like Lyza Commons can help both groups cooperate.

Analytical software vendor Lyzasoft has just published a white paper by data warehouse guru Dr. Barry Devlin on how business analysts and IT can work together. (Click to download Collaborative Analytics: Sharing and Harvesting Analytic Insights across the Business.) Since I’ve spent much time pondering this very issue, I was quite curious to see his perspective.

The paper describes a fundamental contrast between a “center out” model of data usage favored by IT (carefully and centrally controlled) and an “edge based” model favored by business analysts, who act as independent data “hunter-gatherers” to combine and use data in ways that the central resources are not designed to support. Devlin's term for this is “emergent prototyping”, a trial-and-error process of reworking an analysis until it produces something useful.

He also suggests that analysts work first by themselves, and then, if they find something interesting, share it with other analysts. Only later, when something seems really important and reusable, will they try to get corporate IT to add it to the central systems.

My own mental model is slightly different. I see analysts as spending very little time gathering data. In practice, most of what they need resides in corporate systems, so analysts are largely at the mercy of IT to provide extracts of required sources. Although waiting for those extracts is probably the biggest constraint on what analysts can accomplish, they don't spend that time twiddling their thumbs. Most of their work day (apart from meetings, etc.) is spent manipulating and interpreting data, and, as Devlin suggests, discussing results with other analysts.

This difference in perspective has some impact on judging what matters in a business analysis tool. If data gathering is really important, then features for extraction and consolidation are critical. If manipulation and interpretation matter most, then features for processing and visualization are at the top of the list.

As I recall, Lyza doesn’t offer particularly advanced extraction or consolidation features (e.g. fuzzy matching), so this isn’t necessarily a topic they should stress. Lyzasoft might disagree – and I’ll gladly concede that the system allows basic joins and filters that are well beyond what you can do in Excel. Still, to my mind, the real strength of Lyza is the ability to create data process flows, which save analysts from trying to do similar work by manually modifying Excel spreadsheets. (Click to read my Lyza review.)

Either way, though, features to document and share analytical processes still matter. Those are really the focus of this white paper, which is written to support the "Lyza Commons” product. Commons lets analysts share their work, trace the origins of each shared item, and use one analysis as input to another. As the paper points out, this both fosters cooperation among analysts and makes it easier for IT to add their activities to the company’s core business intelligence systems. Both benefits should free up analysts’ time for new projects, letting them foxus on what they do best.

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Demand Generation Vendor Traffic Rankings

Summary: Based on Web traffic rankings, new demand generation vendors with low prices are gaining market presence. Pardot and (perhaps) Genius.com look particularly strong. But Eloqua, Silverpop and Marketo remain industry leaders.

Last November, after much consideration of alternatives, I settled on Alexa three-month Web traffic rankings as a reasonable way to measure the relative market presence of demand generation vendors. You can see that post here. I revisited that data today, adding a few new vendors and dropping some of the very minor ones. Results are in the following table.

(Note: after I posted this, it was pointed out to me that the bulk of traffic on several sites relates to customer log-ins rather than marketing prospects. For example, Alexa says that 89.4% of visitors to eloqua.com next go to now.eloqua.com, which is the domain for client landing pages and user log-in. I don't know whether this particular nuance makes the Alexa rankings a less useful indicator of market presence, but it probably means the figures relate more to existing customers than prospects. Alexa is a crude measure for many reasons -- although I do think the rankings correlate roughly with a vendor's volume of business and marketing actvitiy, I wouldn't go much further. - David)

There are no huge surprises. The leaders among demand generation systems are still Eloqua, Silverpop and Marketo. Infusionsoft and Genius.com also rank very highly, but they serve broader markets (small business and salespeople, respectively) so a direct comparison with pure-play demand generation vendors may not be appropriate. Silverpop's figures may also be inflated by its consumer email production business.

Vendors showing significant growth (highlighted in green) are mostly new entrants with below-average prices: Pardot, OfficeAutoPilot and LoopFuse. ActiveConversion is not new but also has a low price point. The outlier here is eTrigue, a long-established player that I've never looked at in depth. Their ranking is still very low, but has increased substantially. Judging from the press releases on their Web site, this may be due to a new release last October that added Salesforce.com integration. I'll explore further when time permits.

The only vendor with a really major drop in ranking was Lead Genesys, another long-time industry participant.

As the entries in the first column indicate, I've reviewed nearly all these vendors in either this blog or the Raab Guide to Demand Generation Systems. (The links all point to blog entries.) The only important exception is LoopFuse, which I have deferred at the company's request. (How about it guys? Ready yet?) NurtureHQ doesn't quite seem to be a full-scale demand generation system, insofar as it seems to lack landing pages. But its relatively high rank still surprised me, so I'll make it a priority to learn more.

My general interpretation of these numbers is that demand generation remains a dynamic market -- new participants can still enter successfully if their product and pricing are attractive enough. This is good news for marketers, since continued competition will result in continued product improvements. Major advances are still needed in usability, particularly for complex marketing programs, and in coordination with sales systems. Vendors who can deliver on these key requirements at reasonable price points should earn their place as tomorrow's industry leaders.

reviewed in:	vendor:	Alexa rank: November 2008	Alexa rank: July 2009
blog	Infusionsoft		4,993
guide	Eloqua	20,234	10,036
guide	Silverpop / Vtrenz	29,080	28,640
guide	Marketo	68,088	51,463
blog	Genius.com		70,007
blog	Pardot	211,309	92,530
blog	OfficeAutoPilot	509,868	153,232
guide	Marketbright	167,306	180,141
blog	ActiveConversion	257,058	192,634
guide	Manticore Technology	213,546	203,501
blog	Marqui Software	211,767	265,780
guide	Market2Lead	235,244	296,914
blog	Act-On Software		344,806
	LoopFuse	734,098	353,994
	NurtureHQ		367,152
blog	Treehouse Interactive		419,315
guide	Neolane	566,977	537,863
blog	LeadLife		677,156
	eTrigue	1,510,207	728,720
blog	SalesFusion360		846,961
	Lead Genesys	557,199	1,015,851
blog	True Influence		1,246,454
blog	RightOnInteractive 5Buckets		1,342,985

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LucidEra's Failure: More Evidence that Marketers Won't Pay for Measurement

I’m just catching up with what happened while I was on vacation these past two weeks. One piece of news is the demise of LucidEra, which this blog profiled almost exactly one year ago. According to SearchDataManagement.com, the company said it shut down because it couldn’t raise new funds or find a buyer.

There has been some learned discussion of the causes of LucidEra’s collapse on Timo Elliot’s BI Questions Blog. Much seems to focus on the apparent operating costs. These must have been substantial, since the company raised $15.6 million in 2007 and, presumably, has since spent it all.

Still, I think the fundamental problem was a lack of customers. When I spoke with LucidEra in June 2008 they said they had about 40 paying clients. When I spoke with them again in October 2008, the number was 50 and it was still at 50 when we spoke in April 2009. In other words, LucidEra was making very few sales or, even worse, was able to make new sales but couldn’t retain its customers. [For more insight based on comments by LucidEra managers, see this post on the Datadoodle blog.]

With the benefit of 20/20 hindsight, LucidEra’s strategic decision to focus on building sales analysis applications primarily for Salesforce.com was a mistake. Bear in mind that there are about 60,000 Salesforce.com customers – selling to 50 of them is less than 0.1% penetration.

I suspect LucidEra’s price point, around $3,000 per month depending on the details, was too rich for many of its prospective clients. Not that they couldn’t actually afford it – but they didn’t want to spend that much money on sales analysis.

This is not surprising. I reluctantly concluded some time ago that marketers (and presumably sales managers) are not willing to spend money on measurement systems even though they consistently say in surveys that better measurement is a high priority. For recent evidence along these lines, see the 2009 Marketing ROI and Measurements Study published by Lenskold Group and sponsored by MarketSphere, which found that “6 in 10 firms (59%) indicate having an increased demand for marketing measurements, analysis and reporting in 2009 without the budget necessary for those measurement efforts.”

Many analysts and other on-demand business intelligence vendors have been quick to assert that LucidEra’s failure does not reflect a problem with the notion of on-demand BI in general. I agree, since I see the key to LucidEra's demise as its uniquely narrow focus on sales analysis. Indeed, competitors including Birst and GoodData have leapt to offer a new home to orphaned LucidEra clients.

Still, the apparently high costs to sustain a small client base suggests the economics of this business are not as attractive as they seem. LucidEra's Darren Cunningham did tell me that their costs were particularly high because they were not a multi-tenant solution and had to manage the entire BI stack to support a single application. Presumably other on-demand BI vendors can run more cheaply. Still there does seem to be a little more reason for caution in approaching on-demand BI vendors, even though there is not (yet) any cause for alarm.

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