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.
______________
* 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.)
Thursday, July 09, 2009
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.
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.
Wednesday, July 08, 2009
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 customer log-in page. 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.
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 customer log-in page. 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 | |
| SalesFusion360 | 846,961 | ||
| Lead Genesys | 557,199 | 1,015,851 | |
| blog | True Influence | 1,246,454 | |
| RightOnInteractive 5Buckets | 1,342,985 |
Tuesday, July 07, 2009
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.
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.
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.
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.
Wednesday, June 17, 2009
Marqui Combines Content Management and Demand Generation
Summary: Marqui started as a Web content management system and then added basic demand generation. It’s a good choice for organizations that need both and don’t have very sophisticated marketing requirements.
Marqui is one of the oldest demand generation vendors, founded in 2000. But that date is a bit misleading because the company’s original product was a Web content management system (CMS). It added demand generation features later in response to client requests. Today, content management and campaign management can be purchased separately although they are tightly integrated.
The entry of CMS vendors into the demand generation market is a bit of a mini-trend right now: others following the same path include Sitecore and Lyris-owned Hot Banana. Among conventional demand generation systems, Pardot is a spin-off from CMS vendor Hannon Hill and Marketbright includes extensive CMS features. Since the CMS marketplace is now almost totally commoditized, in particular by open source products like Joomla and Drupal, it makes sense for vendors to look for an adjacent field with greater profit potential.
Whether demand generation is the right refuge is another question. Marqui’s VP Marketing Richard Sharp defines “marketing automation” as the combination of Web content management and campaign management. In this view, content management is responsible for attracting, engaging and capturing leads, while campaign management captures, nutures, and sends leads to sales. That makes a nice diagram but it ignores the reality that content management systems are generally purchased and run by IT while demand generation systems belong to marketing.
This poses a serious sales challenge. Marketing and IT have different priorities, different cultures, and are likely to be buying systems at different times. In practice, Sharp said, most of Marqui’s new clients start with CMS and add campaign management later as the need becomes more evident. He said about one-third do purchase both modules at once.
Sharp also said he is finding that control of the company Web site is generally slipping away from IT departments, especially at smaller organizations. That sounds both true (as in “factually correct”) and right (as in “the way it should be”). As the Web site becomes a more prominent source of information for prospects, it’s increasingly important for marketers to watch and optimize its operations.
Still, the technical chores of managing the Web infrastructure will always remain with IT, so there’s an on-going question of who will be responsible for what. Ultimately, it’s hard to imagine that IT won’t have the dominant voice in selecting the CMS. This will leave marketing to either use the demand generation features embedded within the chosen CMS system or to integrate a separate demand generation product.
Encroachment by CMS systems poses another strategic threat to stand-alone demand generation vendors, who (at least in my opinion) are already in danger of being absorbed into CRM suites because of the need for closer integration between sales and marketing. I see demand generation as a tasty little fish swimming among some much larger sharks. This leads to an elaborate metaphor about hiding in coral reefs, but I'll restrain myself.
Marqui has the features you’d expect given its background: strong content management and basic demand generation. To accentuate the positive, the system provides hierarchical folders for marketing assets, version tracking, expiration dates, advanced templates, and fine-grained user rights management.
It also does a good job with Web forms, allowing users to specify whether responses update the main lead profile or are stored separately. The system can send notification messages to the person who completes the form and to someone else (e.g., a marketing or sales manager). It can also direct visitors who complete a form to another Web page.
One particularly nice feature is tight integration of Marqui-generated pages with Google Website Optimizer. This makes it much easier than usual to test alternative components within landing pages and elsewhere on the site. I can’t immediately recall any other demand generation vendor offering this integration, but haven’t checked carefully.
The outbound marketing features are not as advanced but should be adequate for simple programs. Users create subscriber groups (i.e., lists) by building rules; these can incorporate behaviors, such as email responses and Web page visits, as well as attributes and form responses. Behavior definitions can be include relative time (e.g., the past three days), which is important and not always the case with other products. However, the rules cannot reference membership in other groups, which makes some things harder. Groups can be dynamic (reselected each time they are used) or static (selected once and frozen) – a common but important capability.
Emails are defined as activities within a campaign and assigned an execution schedule, email template, and target group. Campaign activities can also be Web behaviors such as clicking on a banner ad. Each activity can be assigned several Web pages to track as goals, allowing reports to show leads moving through a conversion funnel. This feature is a somewhat unusual among demand generation systems but pretty common in Web analytics.
Users can also enter the cost of each activity and combine this with expected and actual revenues for Return on Investment reports. The revenues are based on opportunity records imported from the CRM system. This is probably adequate for most uses and more than some other demand generation products offer. But Marqui doesn’t capture cost details and can only link campaigns to opportunities when opportunity is "owned" by a lead from the demand generation system. Such links are often missing, and more advanced demand generation vendors offer alternative attribution methods to compensate.
Marqui’s features for lead scoring, multi-step campaigns and CRM synchronization are similarly basic. Lead scoring is associated with individual Web forms, a somewhat unusual approach. The scoring formulas can look at a broad range of data, including activities, attributes and form replies, but cannot cap the value from a single element or automatically reduce scores over time.
Multi-step campaigns are probably the weakest of all these features. Multiple activities can be assigned to the same campaign, but are not directly linked in a sequential flow. Nor is there any visualization of the entire campaign. A new interface is planned for later this summer.
The system can exchange data with Salesforce.com, NetSuite and Microsoft CRM Dynamics, but does not allow field-by-field update rules.
Pricing also leans toward the lower end, starting around $1,000 per month for campaign management and under $2,000 per month for campaign management and CMS combined. There are some additional charges based on email volume and for template creation.
Marqui's customers tend to be smaller organizations, and are not as concentrated in technology as clients of most demand generation vendors. This also reflects its base in content management software. Companies with basic demand generation needs that also want a tightly integrated CMS will find it worth a look.
Marqui is one of the oldest demand generation vendors, founded in 2000. But that date is a bit misleading because the company’s original product was a Web content management system (CMS). It added demand generation features later in response to client requests. Today, content management and campaign management can be purchased separately although they are tightly integrated.
The entry of CMS vendors into the demand generation market is a bit of a mini-trend right now: others following the same path include Sitecore and Lyris-owned Hot Banana. Among conventional demand generation systems, Pardot is a spin-off from CMS vendor Hannon Hill and Marketbright includes extensive CMS features. Since the CMS marketplace is now almost totally commoditized, in particular by open source products like Joomla and Drupal, it makes sense for vendors to look for an adjacent field with greater profit potential.
Whether demand generation is the right refuge is another question. Marqui’s VP Marketing Richard Sharp defines “marketing automation” as the combination of Web content management and campaign management. In this view, content management is responsible for attracting, engaging and capturing leads, while campaign management captures, nutures, and sends leads to sales. That makes a nice diagram but it ignores the reality that content management systems are generally purchased and run by IT while demand generation systems belong to marketing.
This poses a serious sales challenge. Marketing and IT have different priorities, different cultures, and are likely to be buying systems at different times. In practice, Sharp said, most of Marqui’s new clients start with CMS and add campaign management later as the need becomes more evident. He said about one-third do purchase both modules at once.
Sharp also said he is finding that control of the company Web site is generally slipping away from IT departments, especially at smaller organizations. That sounds both true (as in “factually correct”) and right (as in “the way it should be”). As the Web site becomes a more prominent source of information for prospects, it’s increasingly important for marketers to watch and optimize its operations.
Still, the technical chores of managing the Web infrastructure will always remain with IT, so there’s an on-going question of who will be responsible for what. Ultimately, it’s hard to imagine that IT won’t have the dominant voice in selecting the CMS. This will leave marketing to either use the demand generation features embedded within the chosen CMS system or to integrate a separate demand generation product.
Encroachment by CMS systems poses another strategic threat to stand-alone demand generation vendors, who (at least in my opinion) are already in danger of being absorbed into CRM suites because of the need for closer integration between sales and marketing. I see demand generation as a tasty little fish swimming among some much larger sharks. This leads to an elaborate metaphor about hiding in coral reefs, but I'll restrain myself.
Marqui has the features you’d expect given its background: strong content management and basic demand generation. To accentuate the positive, the system provides hierarchical folders for marketing assets, version tracking, expiration dates, advanced templates, and fine-grained user rights management.
It also does a good job with Web forms, allowing users to specify whether responses update the main lead profile or are stored separately. The system can send notification messages to the person who completes the form and to someone else (e.g., a marketing or sales manager). It can also direct visitors who complete a form to another Web page.
One particularly nice feature is tight integration of Marqui-generated pages with Google Website Optimizer. This makes it much easier than usual to test alternative components within landing pages and elsewhere on the site. I can’t immediately recall any other demand generation vendor offering this integration, but haven’t checked carefully.
The outbound marketing features are not as advanced but should be adequate for simple programs. Users create subscriber groups (i.e., lists) by building rules; these can incorporate behaviors, such as email responses and Web page visits, as well as attributes and form responses. Behavior definitions can be include relative time (e.g., the past three days), which is important and not always the case with other products. However, the rules cannot reference membership in other groups, which makes some things harder. Groups can be dynamic (reselected each time they are used) or static (selected once and frozen) – a common but important capability.
Emails are defined as activities within a campaign and assigned an execution schedule, email template, and target group. Campaign activities can also be Web behaviors such as clicking on a banner ad. Each activity can be assigned several Web pages to track as goals, allowing reports to show leads moving through a conversion funnel. This feature is a somewhat unusual among demand generation systems but pretty common in Web analytics.
Users can also enter the cost of each activity and combine this with expected and actual revenues for Return on Investment reports. The revenues are based on opportunity records imported from the CRM system. This is probably adequate for most uses and more than some other demand generation products offer. But Marqui doesn’t capture cost details and can only link campaigns to opportunities when opportunity is "owned" by a lead from the demand generation system. Such links are often missing, and more advanced demand generation vendors offer alternative attribution methods to compensate.
Marqui’s features for lead scoring, multi-step campaigns and CRM synchronization are similarly basic. Lead scoring is associated with individual Web forms, a somewhat unusual approach. The scoring formulas can look at a broad range of data, including activities, attributes and form replies, but cannot cap the value from a single element or automatically reduce scores over time.
Multi-step campaigns are probably the weakest of all these features. Multiple activities can be assigned to the same campaign, but are not directly linked in a sequential flow. Nor is there any visualization of the entire campaign. A new interface is planned for later this summer.
The system can exchange data with Salesforce.com, NetSuite and Microsoft CRM Dynamics, but does not allow field-by-field update rules.
Pricing also leans toward the lower end, starting around $1,000 per month for campaign management and under $2,000 per month for campaign management and CMS combined. There are some additional charges based on email volume and for template creation.
Marqui's customers tend to be smaller organizations, and are not as concentrated in technology as clients of most demand generation vendors. This also reflects its base in content management software. Companies with basic demand generation needs that also want a tightly integrated CMS will find it worth a look.
Monday, June 15, 2009
Cloud-Based QlikView Still Isn't Available as a Service
Summary: Pay-as-you-go pricing would make QlikView easier to buy, but the company doesn't offer this option. To make a stronger business case for the purchase, include the value of shifting work from IT to business users, and of producing results faster.
Last week’s post about QlikView 9.0 prompted an inquiry from a manager who has been trying for a year to convince his company to consider the product. Having run into this issue many times, I easily felt his pain and we speculated a bit on what might help things along.
One obvious tactic would be to purchase QlikView on a pay-as-you-go basis, presumably cloud-based. But a quick check with QlikView confirmed that they don’t allow this and have no plans to change.
The closest they come is to let their partners offer QlikView-based applications as a service. For example, they pointed me to SportsDataHub, which lets users analyze football statistics for $40 per year. But the key point about this and similar QlikView services is that you can only access data loaded by the partner. You can't define and load your own data sources directly. At best, you might be able to create your own reports based on the loaded data. (See QlikTech Marketing SVP Anthony Deighton's comment on this post for a little more on the subject.)
I don’t understand QliiView’s reluctance to adopt a Software-as-a-Service model. It has proven viable for many other software companies, including other business intelligence vendors. To me, it seems a natural extension of the company’s “seeing is believing” sales approach as well as a good way to sidestep the barriers raised by corporate IT.
In fact, QlikView’s tremendous ease-of-use makes it an excellent fit for the SaaS model, because business users can deploy it for themselves with minimal technical support. In our conversation last week, QlikTech's Deighton said the majority of clients already implement the system without purchasing any external services. If there was ever a piece of software suited to SaaS, this is it.
Be that as it may. The lack of a proper SaaS offering left my correspondent with several avenues to pursue:
- find a QlikView partner who would build an appropriate application and sell it to him on a services basis. This doesn’t seem very plausible because he probably won’t be able to commit enough funding to make the project worthwhile for the partner. I mean, if he had that much money, he could just buy the software outright in the first place.
- use an alternative system that costs less. Yes, QlikView is unique and wonderful, but products from ADVIZOR Solutions, Lyzasoft, Tableau Software and TIBCO Spotfire offer some of the same advantages at a much lower entry price. Again, this is far from ideal, and it might not work at all because I didn’t explore precisely which aspect of QlikView my correspondent found attractive. Still, it’s better than nothing.
(Vaguely related aside: today, people often cite author Jim Collins’ phrase “good is the enemy of great” as a reason to avoid compromise. Previously, I was more likely to see Voltaire’s “the best is the enemy of the good,” which means that compromise is better than nothing. I’m sure this reversal says something important about our society, although I can’t say what. You're welcome.)
- Find a way to sell QlikView internally. Of course, my correspondent had already been trying, so his question was whether I had any new ideas for how. This actually prompted some very deep thinking over the weekend, which will show up in my Information Management magazine column over the next several months. To summarize four pages in 100 words, there are two approaches to consider:
- do a cost of ownership analysis showing the savings from letting business users perform tasks currently done by IT. Traditional cost analysis compares the time it takes IT to do the work with one tool vs. another. This hides rather than highlights the advantages of QlikView and similar products.
- do a “time to result” analysis that measures the time spent waiting for IT to deliver solutions through multiple iterations. This applies to many analytical databases, not just QlikView, because their flexibility reduces the time spent building conventional BI structures like star schemas and data cubes.
Perhaps one of these will work. I hope so, because we could all benefit from finding ways to take advantage of what new technologies like QlikView have to offer.
Last week’s post about QlikView 9.0 prompted an inquiry from a manager who has been trying for a year to convince his company to consider the product. Having run into this issue many times, I easily felt his pain and we speculated a bit on what might help things along.
One obvious tactic would be to purchase QlikView on a pay-as-you-go basis, presumably cloud-based. But a quick check with QlikView confirmed that they don’t allow this and have no plans to change.
The closest they come is to let their partners offer QlikView-based applications as a service. For example, they pointed me to SportsDataHub, which lets users analyze football statistics for $40 per year. But the key point about this and similar QlikView services is that you can only access data loaded by the partner. You can't define and load your own data sources directly. At best, you might be able to create your own reports based on the loaded data. (See QlikTech Marketing SVP Anthony Deighton's comment on this post for a little more on the subject.)
I don’t understand QliiView’s reluctance to adopt a Software-as-a-Service model. It has proven viable for many other software companies, including other business intelligence vendors. To me, it seems a natural extension of the company’s “seeing is believing” sales approach as well as a good way to sidestep the barriers raised by corporate IT.
In fact, QlikView’s tremendous ease-of-use makes it an excellent fit for the SaaS model, because business users can deploy it for themselves with minimal technical support. In our conversation last week, QlikTech's Deighton said the majority of clients already implement the system without purchasing any external services. If there was ever a piece of software suited to SaaS, this is it.
Be that as it may. The lack of a proper SaaS offering left my correspondent with several avenues to pursue:
- find a QlikView partner who would build an appropriate application and sell it to him on a services basis. This doesn’t seem very plausible because he probably won’t be able to commit enough funding to make the project worthwhile for the partner. I mean, if he had that much money, he could just buy the software outright in the first place.
- use an alternative system that costs less. Yes, QlikView is unique and wonderful, but products from ADVIZOR Solutions, Lyzasoft, Tableau Software and TIBCO Spotfire offer some of the same advantages at a much lower entry price. Again, this is far from ideal, and it might not work at all because I didn’t explore precisely which aspect of QlikView my correspondent found attractive. Still, it’s better than nothing.
(Vaguely related aside: today, people often cite author Jim Collins’ phrase “good is the enemy of great” as a reason to avoid compromise. Previously, I was more likely to see Voltaire’s “the best is the enemy of the good,” which means that compromise is better than nothing. I’m sure this reversal says something important about our society, although I can’t say what. You're welcome.)
- Find a way to sell QlikView internally. Of course, my correspondent had already been trying, so his question was whether I had any new ideas for how. This actually prompted some very deep thinking over the weekend, which will show up in my Information Management magazine column over the next several months. To summarize four pages in 100 words, there are two approaches to consider:
- do a cost of ownership analysis showing the savings from letting business users perform tasks currently done by IT. Traditional cost analysis compares the time it takes IT to do the work with one tool vs. another. This hides rather than highlights the advantages of QlikView and similar products.
- do a “time to result” analysis that measures the time spent waiting for IT to deliver solutions through multiple iterations. This applies to many analytical databases, not just QlikView, because their flexibility reduces the time spent building conventional BI structures like star schemas and data cubes.
Perhaps one of these will work. I hope so, because we could all benefit from finding ways to take advantage of what new technologies like QlikView have to offer.
Wednesday, June 10, 2009
QlikView 9.0 Reaches for Broader Business Intelligence Market
QlikTech released version 9 of its QlikView business intelligence software today. The product has been in public beta for several months, so the general features are well known to people who care about such things.
Probably the item that attracted the most advance attention is an iPhone version that supports interactive analysis; this also works for other Java Mobile clients like Blackberry. It's cool (or ‘qool’, if you must) but not so important in the grand scheme of things. More significant changes include:
- availability through the Amazon Elastic Compute Cloud (EC2), which lets companies order up a QlikView-equipped server in minutes. (Of course, they still have to purchase a QlikView license.) Users can also expand or reduce the number of servers to match fluctuating needs. Advantages including avoiding the wait for new hardware, no need to physically install a server, and the ability to meet peak demands without making a fixed investment.
- API for real-time updates of in-memory data. This is an extension of previous changes that allowed incremental batch updates and manual data entry. But it still marks a major step towards letting QlikView run time-critical applications such as stock trade analysis, pricing and inventory management. No one will be processing orders on QlikView (hmm, never say never), but the line between analytical and transaction databases just got that much thinner.
- enhanced support for enterprise-level deployments. This includes centralized control panels for multiple servers; load balancing and fail-over; better thin-client support; multi-billion-row data sets; and more efficient calculations. These are critical as QlikView moves from being a departmental solution run primarily by business analysts to a mission-critical system backed by corporate IT.
- free Personal Edition with full development capabilities. The main limit vs. the licensed version is that Personal Edition cannot read QlikView files developed on any other copy of the software, and no one else can read files that Personal Editon generates. The goal is to make it easier for users to try the system on their own – a continuation of the company's long-standing "seeing is believing" strategy.
- functional enhancements including improved visualization, search and automation functions. These are nice but none seemed especially exciting. Changes in previous recent releases, such as set analysis (simultaneously comparing two sets of selected records) were more fundamental. Remember, we're talking about version 9: the system is already quite polished.
Of all these items, the one I found most thought-provoking was the free Personal Edition, which replaces a 15-day free trial. Removing the time limit let users build QlikView into their regular work. The strategy makes sense, but it doesn’t lower the $30,000 - $50,000 investment required for the smallest licensed QlikView installation. Few analysts, who are the most likely users for Personal Edition, have the clout to sponsor so large an investment. Competing analyst tools such as LyzaSoft, ADVIZOR Solutions and Tableau can generally provide a 5-10 user departmental deployment for under $10,000. Although QlikView is vastly more powerful than the others, the lower cost will give them an initial advantage. And once they’re in place, it’s hard to get a company to switch.
On the other hand, maybe QlikView is really moving to compete with traditional business intelligence tools like Cognos, Business Objects and MicroStrategy. QikView’s entry cost is vastly lower than those products, especially once you consider the savings in labor. But most enterprises have a BI tool already in place, so it’s not a matter of comparing entry costs. Rather, the choice is entry cost for QlikView vs. incremental deployment cost on the incumbent. The labor savings with QlikView are so great that it will still be cheaper for many projects. But QlikView will remain be a tough sell because IT departments are reluctant to invest in the staff training needed to support an additional tool.
QlikView will never fully replace the traditional data warehouse and BI tools because its in-memory approach limits the size of its databases. With 64 bit systems, the product can easily handle dozens of gigabytes of data. This is quite a lot, but even the smallest enterprise data warehouses now hold multiple terabytes. QlikView works with such systems by executing SQL queries against them, pulling down limited data sets, loading these into memory, and analyzing them. That’s an excellent and perfectly viable approach, but it does rely on the warehouse being there in the first place.
None of this is to suggest that QlikView has anything but a very bright future. When I first spoke with the company in 2005, it had just reached 2,000 clients; at last count, it had over 11,000. Revenue for 2008 was $120 million and had risen 50% from the previous year. The product has finally attracted attention from analyst firms like Gartner and Aberdeen and is very well rated in Nigel Pendse’s latest BI Survey. My brief fling as a VAR ended two years ago, but I still use it personally for any non-trivial data analysis work and remain absurdly pleased with the results. I won’t say QlikView is better than sex, but its pleasures are equally difficult to describe to the uninitiated. Anyone interested in BI software who hasn’t given it a try (QlikView, not sex) should download a copy and see what they’ve been missing.
Probably the item that attracted the most advance attention is an iPhone version that supports interactive analysis; this also works for other Java Mobile clients like Blackberry. It's cool (or ‘qool’, if you must) but not so important in the grand scheme of things. More significant changes include:
- availability through the Amazon Elastic Compute Cloud (EC2), which lets companies order up a QlikView-equipped server in minutes. (Of course, they still have to purchase a QlikView license.) Users can also expand or reduce the number of servers to match fluctuating needs. Advantages including avoiding the wait for new hardware, no need to physically install a server, and the ability to meet peak demands without making a fixed investment.
- API for real-time updates of in-memory data. This is an extension of previous changes that allowed incremental batch updates and manual data entry. But it still marks a major step towards letting QlikView run time-critical applications such as stock trade analysis, pricing and inventory management. No one will be processing orders on QlikView (hmm, never say never), but the line between analytical and transaction databases just got that much thinner.
- enhanced support for enterprise-level deployments. This includes centralized control panels for multiple servers; load balancing and fail-over; better thin-client support; multi-billion-row data sets; and more efficient calculations. These are critical as QlikView moves from being a departmental solution run primarily by business analysts to a mission-critical system backed by corporate IT.
- free Personal Edition with full development capabilities. The main limit vs. the licensed version is that Personal Edition cannot read QlikView files developed on any other copy of the software, and no one else can read files that Personal Editon generates. The goal is to make it easier for users to try the system on their own – a continuation of the company's long-standing "seeing is believing" strategy.
- functional enhancements including improved visualization, search and automation functions. These are nice but none seemed especially exciting. Changes in previous recent releases, such as set analysis (simultaneously comparing two sets of selected records) were more fundamental. Remember, we're talking about version 9: the system is already quite polished.
Of all these items, the one I found most thought-provoking was the free Personal Edition, which replaces a 15-day free trial. Removing the time limit let users build QlikView into their regular work. The strategy makes sense, but it doesn’t lower the $30,000 - $50,000 investment required for the smallest licensed QlikView installation. Few analysts, who are the most likely users for Personal Edition, have the clout to sponsor so large an investment. Competing analyst tools such as LyzaSoft, ADVIZOR Solutions and Tableau can generally provide a 5-10 user departmental deployment for under $10,000. Although QlikView is vastly more powerful than the others, the lower cost will give them an initial advantage. And once they’re in place, it’s hard to get a company to switch.
On the other hand, maybe QlikView is really moving to compete with traditional business intelligence tools like Cognos, Business Objects and MicroStrategy. QikView’s entry cost is vastly lower than those products, especially once you consider the savings in labor. But most enterprises have a BI tool already in place, so it’s not a matter of comparing entry costs. Rather, the choice is entry cost for QlikView vs. incremental deployment cost on the incumbent. The labor savings with QlikView are so great that it will still be cheaper for many projects. But QlikView will remain be a tough sell because IT departments are reluctant to invest in the staff training needed to support an additional tool.
QlikView will never fully replace the traditional data warehouse and BI tools because its in-memory approach limits the size of its databases. With 64 bit systems, the product can easily handle dozens of gigabytes of data. This is quite a lot, but even the smallest enterprise data warehouses now hold multiple terabytes. QlikView works with such systems by executing SQL queries against them, pulling down limited data sets, loading these into memory, and analyzing them. That’s an excellent and perfectly viable approach, but it does rely on the warehouse being there in the first place.
None of this is to suggest that QlikView has anything but a very bright future. When I first spoke with the company in 2005, it had just reached 2,000 clients; at last count, it had over 11,000. Revenue for 2008 was $120 million and had risen 50% from the previous year. The product has finally attracted attention from analyst firms like Gartner and Aberdeen and is very well rated in Nigel Pendse’s latest BI Survey. My brief fling as a VAR ended two years ago, but I still use it personally for any non-trivial data analysis work and remain absurdly pleased with the results. I won’t say QlikView is better than sex, but its pleasures are equally difficult to describe to the uninitiated. Anyone interested in BI software who hasn’t given it a try (QlikView, not sex) should download a copy and see what they’ve been missing.
Tuesday, June 09, 2009
Marketo Sales Insight Expands Salesforce Access to Marketing Data
Summary: Marketo's new Sales Insight ranks prospects for sales people, based on recent Web and email activities. It lets Marketo sell seats to sales departments, which could be more lucrative than selling its core demand generation system. But I expect the sales automation vendors to take the business for themselves.
Marketo today officially launched “Sales Insight”, an application that makes prospect activity history directly available to sales people from within Salesforce.com. I had a personal demonstration last week (are you impressed?), but there’s an online demo that seems to cover pretty much the whole product. Features include:
- a ranked prospect list, based on measures of interaction intensity (represented by one, two or three flames) and prospect value (up to three stars). The idea is to help the sales rep decide who to call first. Users can drill into the details of each account, including Web activities, emails and score history.
- a list of “interesting moments” for each prospect, showing activities that the company has deemed significant. The moments are set up as real time triggers within Marketo. They can be linked to a specific campaign or defined more generically (e.g., three Web site visits in two days). I found this the most interesting capability in the system, because it fills a middle ground between summarizing all activities and providing the item-by-item detail. It does depend on marketing setting up the definitions, rather than letting sales people create their own. But, then again, how many salespeople really want to do that?
- a “lead feed” feature that can send “interesting moment” alerts via RSS, SMS, email, iPhone and other mobile devices. Sales people can select the individuals and accounts to monitor and the types of activities that trigger alerts.
- an option to send emails and add prospects to Marketo campaigns.
- ability to track anonymous Web visits within the sales person’s territory, using IP lookup to identify the visiting company and location. This can be integrated with Demandbase and Jigsaw to download the names of contacts at those firms. The system can also open a window to LinkedIn to let the sales rep find network contacts of her own.
It’s irresistible to compare Sales Insight with Eloqua Prospect Profiler, launched two weeks ago (see my review), which also gives sales people access to prospect activities gathered by the marketing system. The products are designed around slightly different scenarios: while Marketo starts with a list to help the sales rep decide who to call, while Eloqua aims to help the rep understand a prospect she has already selected. Still, both systems provide views into the data and both let salespeople receive alerts about prospect activities.
There are some subtle differences. Marketo is a Force.com application that works only with Salesforce.com, while Eloqua works with several CRM products. Eloqua lets sales people define their own alerts rather than relying on marketing to predefine the “interesting moments”. Marketo lets sales reps send emails and add prospects to demand generation campaigns. Eloqua provides interesting graphs of activity trends. Marketo includes the anonymous visitor tracking.
It’s hard to say which product will be more appealing to sales people, but that probably won’t matter: any significantly attractive feature in one product will (and should) be quickly copied into the other. Competitors without any equivalent product are more at risk, but, you can bet they'll quickly add something similar if it becomes an issue.
What really matters is that these products provide an opportunity for the marketing system to integrate more deeply with sales. This is THE big industry trend right now, so much so that we’re probably due for some clever nay-saying. The attraction to vendors like Marketo and Eloqua is quite clear: they can expand the size of their installations by serving new customers within existing clients.
This could have a substantial impact on total revenues. At Marketo’s price of $49 per seat, a 20-user license would bring in another $1,000 per month. (Genius.com's Genius Pro, a somewhat similar tool that helps sales people track prospect activities, is also priced at $49 per seat.)Compare this with maybe $2,000 per client per month earned by most demand generation vendors. Figures like these radically change the economics of the demand generation business. They also explain why some vendors have been willing to sell to new clients at very low prices.
But these figures also raise the specter of sales automation vendors moving in the other direction. An average Salesforce.com seat is around $100 per month these days. From the Salesforce.com viewpoint, adding marketing automation for $1,000 to $2,000 per month per client isn't particularly exciting. But if that same application also justified another $49 for each seat, you're starting to talk real money.
Of course, this has always been the threat inherent in demand generation vendors’ symbiotic relationship with CRM in general and Salesforce.com in particular. I’m increasingly convinced that it’s just a matter of time before sales automation and demand generation / marketing automation do merge – and it will almost certainly be sales systems swallowing the marketing vendors, not the other way around.
That will put the business marketing world pretty much where consumer marketers have already landed: most companies will use the marketing features of their CRM vendors, except for a relatively small number of businesses with marketing needs so advanced that they can really need the special features of a “best of breed” system.
In support of this view, it’s worth noting that demand generation systems for small businesses already routinely include their own sales automation system. This integrated model will likely filter up into larger companies, even as CRM vendors add marketing automation features and move down from above. Vendors offering just marketing automation or just sales automation will be trapped in the middle – rarely a pleasant place for a vendor to be.
Marketo today officially launched “Sales Insight”, an application that makes prospect activity history directly available to sales people from within Salesforce.com. I had a personal demonstration last week (are you impressed?), but there’s an online demo that seems to cover pretty much the whole product. Features include:
- a ranked prospect list, based on measures of interaction intensity (represented by one, two or three flames) and prospect value (up to three stars). The idea is to help the sales rep decide who to call first. Users can drill into the details of each account, including Web activities, emails and score history.
- a list of “interesting moments” for each prospect, showing activities that the company has deemed significant. The moments are set up as real time triggers within Marketo. They can be linked to a specific campaign or defined more generically (e.g., three Web site visits in two days). I found this the most interesting capability in the system, because it fills a middle ground between summarizing all activities and providing the item-by-item detail. It does depend on marketing setting up the definitions, rather than letting sales people create their own. But, then again, how many salespeople really want to do that?
- a “lead feed” feature that can send “interesting moment” alerts via RSS, SMS, email, iPhone and other mobile devices. Sales people can select the individuals and accounts to monitor and the types of activities that trigger alerts.
- an option to send emails and add prospects to Marketo campaigns.
- ability to track anonymous Web visits within the sales person’s territory, using IP lookup to identify the visiting company and location. This can be integrated with Demandbase and Jigsaw to download the names of contacts at those firms. The system can also open a window to LinkedIn to let the sales rep find network contacts of her own.
It’s irresistible to compare Sales Insight with Eloqua Prospect Profiler, launched two weeks ago (see my review), which also gives sales people access to prospect activities gathered by the marketing system. The products are designed around slightly different scenarios: while Marketo starts with a list to help the sales rep decide who to call, while Eloqua aims to help the rep understand a prospect she has already selected. Still, both systems provide views into the data and both let salespeople receive alerts about prospect activities.
There are some subtle differences. Marketo is a Force.com application that works only with Salesforce.com, while Eloqua works with several CRM products. Eloqua lets sales people define their own alerts rather than relying on marketing to predefine the “interesting moments”. Marketo lets sales reps send emails and add prospects to demand generation campaigns. Eloqua provides interesting graphs of activity trends. Marketo includes the anonymous visitor tracking.
It’s hard to say which product will be more appealing to sales people, but that probably won’t matter: any significantly attractive feature in one product will (and should) be quickly copied into the other. Competitors without any equivalent product are more at risk, but, you can bet they'll quickly add something similar if it becomes an issue.
What really matters is that these products provide an opportunity for the marketing system to integrate more deeply with sales. This is THE big industry trend right now, so much so that we’re probably due for some clever nay-saying. The attraction to vendors like Marketo and Eloqua is quite clear: they can expand the size of their installations by serving new customers within existing clients.
This could have a substantial impact on total revenues. At Marketo’s price of $49 per seat, a 20-user license would bring in another $1,000 per month. (Genius.com's Genius Pro, a somewhat similar tool that helps sales people track prospect activities, is also priced at $49 per seat.)Compare this with maybe $2,000 per client per month earned by most demand generation vendors. Figures like these radically change the economics of the demand generation business. They also explain why some vendors have been willing to sell to new clients at very low prices.
But these figures also raise the specter of sales automation vendors moving in the other direction. An average Salesforce.com seat is around $100 per month these days. From the Salesforce.com viewpoint, adding marketing automation for $1,000 to $2,000 per month per client isn't particularly exciting. But if that same application also justified another $49 for each seat, you're starting to talk real money.
Of course, this has always been the threat inherent in demand generation vendors’ symbiotic relationship with CRM in general and Salesforce.com in particular. I’m increasingly convinced that it’s just a matter of time before sales automation and demand generation / marketing automation do merge – and it will almost certainly be sales systems swallowing the marketing vendors, not the other way around.
That will put the business marketing world pretty much where consumer marketers have already landed: most companies will use the marketing features of their CRM vendors, except for a relatively small number of businesses with marketing needs so advanced that they can really need the special features of a “best of breed” system.
In support of this view, it’s worth noting that demand generation systems for small businesses already routinely include their own sales automation system. This integrated model will likely filter up into larger companies, even as CRM vendors add marketing automation features and move down from above. Vendors offering just marketing automation or just sales automation will be trapped in the middle – rarely a pleasant place for a vendor to be.
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