The Internet promises marketers an exquisite measurability: you can tell precisely where each Web site visitor came from, and what people from each source do after they arrive. But non-advertising media such as blogs, online news articles, YouTube, Facebook and Twitter are a blind spot because many references to a company don’t contain a clickable link. (Tealium, whose solution I’ll discuss shortly, put the figure at 80% in one study.) Without a link, users either must type the destination URL into their browser or find the site through a search engine. Either way, the visit is not associated with the original source. Therefore, marketers who want to know, say, how many site visits were prompted by a particular YouTube video have no direct way to find out.
Tealium, a developer of specialized Web analytics tools founded last year by veterans of WebSideStory/Visual Sciences, offers Tealium Social Media as a solution. It first builds a list of Internet references to a product, based on automated searches of sources such as Google News and Blogsearch, YouTube, Bloglines, Twitter, etc., plus any other RSS source you might have available. The system then checks whether visitors to a company Web site have previously visited one of these references by checking the cache of the visitor’s browser. If a match is found, the visit is attributed to that source.
I’m going to stop right here and say that this struck me as raising a significant privacy issue. I hadn’t really given the matter any thought but had assumed my browser history was private. But a Google search on "read browser history" shows that a method to check whether someone has visited a specified URL is widely known. This is what Tealium does and it isn’t as invasive as simply reading everything. More important, Tealium doesn't track individuals: rather, it reports how many people come from a given source. This is little different from conventional Web analytics, so I guess there is no particular privacy objection to the product. And, yes, you can always clear your browser cache or shorten the retention period. Quick show of hands: how many of you have actually done that? I thought so. End of sermon.
Tealium’s approach won’t be 100% accurate, since some people really do clean out their browser caches,. A few people will also access a site from a different computer or browser than the one where they saw the reference. Nor will Tealium capture referrals, such as an email I sent you with a product’s name after reading an article about it. But most of these problems apply to other Web analytics techniques, and on the whole the data should be accurate enough to be useful. It will certainly give a good measure of the relative power of different sources.
The system must also choose how to assign credit if the visitor’s cache contains more than one of the reference items. Tealium handles this by ranking the items on popularity and recency, and assigning the match to the highest ranked item. This seems reasonable.
Of course, Tealium can only measure Web-based activities. This almost goes without saying, but it's worth reminding ourselves every so often that there are still plenty of non-Web interactions taking place.
Tealium originally intended to present its social media results in a stand-alone interface. But the vendor decided a couple of months ago to instead feed them into existing Web analytics products, and Google Analytics in particular. This reduced the work Tealium had to perform (no reporting or data storage), hence lowering development and operating costs. From the client viewpoint, it integrates the social media results with other Web analytics, allowing direct comparisons between paid and unpaid media. In addition, downstream measures such as conversions or purchases automatically become available for the Tealium-derived sources. This was a very wise move.
What Tealium won’t provide is measures of sentiment, such as whether a particular social media reference was praise or criticism, of comments on particular subjects, or of changes in customer attitudes. Nor does it claim to. There are of course many other systems in this field; see last week’s post on reputation monitoring systems for a pointer to a detailed list.
Pricing of Social Media starts at $2,000 for implementation plus $250 per month with a one year contract. Price grows slightly as users add keywords and data feeds but is not related to actual traffic volume. The system has been in beta test with six clients until recently, and is being formally launched today.
Social Media is Tealium’s third product. The other two are WebToCRM, which captures Web visitor data and posts it to a CRM system, and Universal Tag, which lets a single page tag feed visitor data to multiple Web analytics systems.
Wednesday, January 21, 2009
Thursday, January 15, 2009
Interesting Conference on Real Time Communications; Great List of Tools for Reputation Monitoring
I spent yesterday morning at a conference on “Real-Time Communications” presented by the Business Development Institute and sponsored by PR Newswire. Not surprisingly, given the sponsor, this turned out to be mostly by and for public relations professionals. This group’s main concern seemed to be reacting to public criticism, and “real time media” meant primarily blogging and Twitter. There was heavy representation from the pharmaceutical industry in particular, which, as several speakers mentioned with obvious frustration, is highly constrained by regulatory rules from making proactive comments. Beyond reacting to immediate crises, it seems the main media relations strategy of this group is to reach out to better educate the press about industry issues, so any reporting will be based on a reasonably accurate understanding of the situation. Apparently even this basic approach is somewhat revolutionary in the industry: keynote Ray Kerins of Pfizer said that until he took over as VP Worldwide Communications two years ago, the company policy was to simply ignore the first phone call from any reporter. Interesting attitude, that.
Kerins also provided perhaps the most intriguing factoid of the day, which was that 15,000 journalists lost their jobs in 2008. (I traced this figure to the Web site Paper Cuts , which tracks reports of newspaper layoffs and buyouts. Apparently the total includes all newspaper employees, not just newsroom staff. But either way, it’s a big number.) Kerins’ comment was that many of the people being let go are well-trained and experienced reporters, who provide “context and analysis”. They are being replaced in many cases by bloggers and other non-professional observers who offer “speed” but are often not as knowledgeable, thorough or objective. This is a big issue, particularly for someone in a complicated industry such as pharmaceuticals.
Another, related point came from Morgan Johnston, Corporate Communications Manager of JetBlue, who described a situation where a customer complained while at the airport to 10,000 online readers about not being compensated properly when her baggage didn’t show up—only to have it appear 15 minutes later. (I’m not clear whether this was on Twitter or a conventional blog.) His point was that the damage was done, even if she posted a follow-up message saying that all was well. The original complaint will live on more or less forever, and people may not notice the final resolution. The particular moral here was the need to respond very quickly to such complaints so the company’s reaction becomes part of the permanent record.
From my own perspective, I was struck by the focus on reacting to other people’s comments in real-time media, as opposed to using those media for a company’s own marketing programs. I suppose the outbound programs are run by marketing rather than public relations.
On the specific issue of marketing measurement, no one at the conference seemed to feel they could meaningfully measure the return on investment of blogging and other projects. From the reactive PR perspective, it’s largely about being defensive and preventing damage to reputation, so it’s probably something you can’t afford not to do. The very little discussion I heard about proactive programs mentioned that it’s occasionally possible to count the direct leads or revenue, but there isn’t much of a way to measure the long-term financial value. This matches my own observations, mostly because the impact of these programs is usually too small to isolate from other factors that also affect performance. There might however be non-financial measures that are more sensitive, like Web site traffic by source.
One very specific and highly valuable product of the conference was a casual remark by one panelist to look at a Web post by Dan Schawbel at Mashable.com for tools to measure brand reputation online. I tracked this down and found two extremely valuable posts, one describing free brand monitoring tools and another describing paid reputation monitoring tools (many of which are very inexpensive). There’s no point to my listing the products here, since you can just read the posts themselves. But this is very useful information – indeed, it made the whole morning worthwhile.
Kerins also provided perhaps the most intriguing factoid of the day, which was that 15,000 journalists lost their jobs in 2008. (I traced this figure to the Web site Paper Cuts , which tracks reports of newspaper layoffs and buyouts. Apparently the total includes all newspaper employees, not just newsroom staff. But either way, it’s a big number.) Kerins’ comment was that many of the people being let go are well-trained and experienced reporters, who provide “context and analysis”. They are being replaced in many cases by bloggers and other non-professional observers who offer “speed” but are often not as knowledgeable, thorough or objective. This is a big issue, particularly for someone in a complicated industry such as pharmaceuticals.
Another, related point came from Morgan Johnston, Corporate Communications Manager of JetBlue, who described a situation where a customer complained while at the airport to 10,000 online readers about not being compensated properly when her baggage didn’t show up—only to have it appear 15 minutes later. (I’m not clear whether this was on Twitter or a conventional blog.) His point was that the damage was done, even if she posted a follow-up message saying that all was well. The original complaint will live on more or less forever, and people may not notice the final resolution. The particular moral here was the need to respond very quickly to such complaints so the company’s reaction becomes part of the permanent record.
From my own perspective, I was struck by the focus on reacting to other people’s comments in real-time media, as opposed to using those media for a company’s own marketing programs. I suppose the outbound programs are run by marketing rather than public relations.
On the specific issue of marketing measurement, no one at the conference seemed to feel they could meaningfully measure the return on investment of blogging and other projects. From the reactive PR perspective, it’s largely about being defensive and preventing damage to reputation, so it’s probably something you can’t afford not to do. The very little discussion I heard about proactive programs mentioned that it’s occasionally possible to count the direct leads or revenue, but there isn’t much of a way to measure the long-term financial value. This matches my own observations, mostly because the impact of these programs is usually too small to isolate from other factors that also affect performance. There might however be non-financial measures that are more sensitive, like Web site traffic by source.
One very specific and highly valuable product of the conference was a casual remark by one panelist to look at a Web post by Dan Schawbel at Mashable.com for tools to measure brand reputation online. I tracked this down and found two extremely valuable posts, one describing free brand monitoring tools and another describing paid reputation monitoring tools (many of which are very inexpensive). There’s no point to my listing the products here, since you can just read the posts themselves. But this is very useful information – indeed, it made the whole morning worthwhile.
Thursday, December 18, 2008
Aberdeen Reports Show Varied Roles for Performance Measurement
Our friends at Aberdeen Group apply a highly standardized research process to technology issues. They take a survey that asks companies about their business performance and the business processes, organization, knowledge management, technologies and performance measures related to a technology. They then divide the companies into leaders (“best-in-class”), laggards and industry average based on their business performance, and compare replies for the different groups. The not-quite-stated implication is that the differences in performance are caused by differences in the other factors. This is not necessarily correct (the ever-popular post hoc ergo propter hoc fallacy) and you could also wonder about the sample size (usually around 200) and how accurately people can answer such detailed questions. But so long as you don’t take the studies too seriously, they always give an interesting look at how firms at different maturity levels manage the technologies at hand.
It so happens that three of the Aberdeen studies have been sitting on my desk for some time, so I had a chance to look at them together. The topics were Lead Nurturing, Trigger Marketing and Cross-Channel Campaign Management. All are currently available for free although the sponsors may contact you in exchange.
Since the Aberdeen reports all follow a similar format, it’s easy to compare their contents. From the perspective of marketing performance measurement, they contain two elements of interest. These are the performance measures highlighted as distinguishing best-in-class companies, and the role of measurement among recommended strategic actions. Here’s a brief look at each of these in the three reports:
Lead Nurturing. The report highlighted number of qualified leads and lead-to-close ratio as critical performance measures, and found that 77% of best-in-class companies were tracking them. It also recommended tracking revenue associated with leads, although it found only 35% of best-in-class companies could do this. But otherwise, it didn’t see performance measurement as a central issue: the primary focus was on matching marketing messages to the prospect’s current stage in the buying cycle. Other important strategies were leveraging multiple channels, identifying prospect buying cycle and needs, and using automated lead scoring to move customers through the cycle.
Trigger Marketing. This report did not identify particular marketing measures as critical, although it did say that having defined performance goals for trigger marketing programs is important. It reported the most common measure is change in response rates, used by 69% of all respondents. (The next most common measure, change in retention rates, was used by just 54%.) I take this as a sign of immaturity (among the respondents, not Aberdeen), since response rate is a primitive measure compared with profitability and return on marketing investment, which were used by 43% and 42% respectively. This is consistent with another finding: the most common strategic action is to “link trigger marketing activities to increased revenues and other business results” (32%). I interpret that as meaning people are just learning to do make that linkage and are simply using response rate until they figure it out. It might be worth noting that the Aberdeen analyst highlighted digital dashboards as next step for best-in-class companies wishing to do still better, although I didn’t see a particularly compelling case for selecting that over other possible activities. But I’m all in favor of dashboards, so I’m glad to see it.
Cross-Channel Campaign Management. Again, the report doesn’t specify particular performance measures. It does say that it’s important to optimize future campaigns based on past performance (pretty obvious) and highlight real-time tracking of results across channels (less obvious, although I’m not so sure I agree. Immediate results may not in fact correlate with long-term profitability). This report did include segmentation and analytics as a strategic actions. (I consider these as part of performance measurement.) In particular, it stressed that best-in-class companies were focused on identifying their high value customers and treating them uniquely. Most of the recommendations, however, were about building the infrastructure needed to coordinate marketing messages across channels, and then executing those coordinated campaigns.
So where does this leave us? I don’t draw any grand lessons from these three reports, except to note that financial measures (i.e., customer profitability and return on investment) don’t play much of a role in any of them. Even that probably just confirms that such measures not widely available, which we already knew. But it’s good to know that people are working on performance measurement and that Aberdeen is baking it into its research.
It so happens that three of the Aberdeen studies have been sitting on my desk for some time, so I had a chance to look at them together. The topics were Lead Nurturing, Trigger Marketing and Cross-Channel Campaign Management. All are currently available for free although the sponsors may contact you in exchange.
Since the Aberdeen reports all follow a similar format, it’s easy to compare their contents. From the perspective of marketing performance measurement, they contain two elements of interest. These are the performance measures highlighted as distinguishing best-in-class companies, and the role of measurement among recommended strategic actions. Here’s a brief look at each of these in the three reports:
Lead Nurturing. The report highlighted number of qualified leads and lead-to-close ratio as critical performance measures, and found that 77% of best-in-class companies were tracking them. It also recommended tracking revenue associated with leads, although it found only 35% of best-in-class companies could do this. But otherwise, it didn’t see performance measurement as a central issue: the primary focus was on matching marketing messages to the prospect’s current stage in the buying cycle. Other important strategies were leveraging multiple channels, identifying prospect buying cycle and needs, and using automated lead scoring to move customers through the cycle.
Trigger Marketing. This report did not identify particular marketing measures as critical, although it did say that having defined performance goals for trigger marketing programs is important. It reported the most common measure is change in response rates, used by 69% of all respondents. (The next most common measure, change in retention rates, was used by just 54%.) I take this as a sign of immaturity (among the respondents, not Aberdeen), since response rate is a primitive measure compared with profitability and return on marketing investment, which were used by 43% and 42% respectively. This is consistent with another finding: the most common strategic action is to “link trigger marketing activities to increased revenues and other business results” (32%). I interpret that as meaning people are just learning to do make that linkage and are simply using response rate until they figure it out. It might be worth noting that the Aberdeen analyst highlighted digital dashboards as next step for best-in-class companies wishing to do still better, although I didn’t see a particularly compelling case for selecting that over other possible activities. But I’m all in favor of dashboards, so I’m glad to see it.
Cross-Channel Campaign Management. Again, the report doesn’t specify particular performance measures. It does say that it’s important to optimize future campaigns based on past performance (pretty obvious) and highlight real-time tracking of results across channels (less obvious, although I’m not so sure I agree. Immediate results may not in fact correlate with long-term profitability). This report did include segmentation and analytics as a strategic actions. (I consider these as part of performance measurement.) In particular, it stressed that best-in-class companies were focused on identifying their high value customers and treating them uniquely. Most of the recommendations, however, were about building the infrastructure needed to coordinate marketing messages across channels, and then executing those coordinated campaigns.
So where does this leave us? I don’t draw any grand lessons from these three reports, except to note that financial measures (i.e., customer profitability and return on investment) don’t play much of a role in any of them. Even that probably just confirms that such measures not widely available, which we already knew. But it’s good to know that people are working on performance measurement and that Aberdeen is baking it into its research.
Thursday, December 11, 2008
Survey: Marketing Accountability Measures Remain Weak
Every year since 2005, the Association of National Advertisers and vendor MMA (Marketing Management Analytics) have joined forces to produce a survey on marketing accountability. Although the details change each year, the general results have been sadly consistent: marketers, finance executives and senior management are very unhappy with their marketing measurement capabilities.
In the 2008 study, released in July and just recapitulated in a new MMA white paper, only 23% of the marketers were satisfied with their metrics for marketing’s impact on sales, and just 19% were satisfied with metrics showing marketing impact on ROI and brand equity.
Furthermore, only 14% of the marketers felt their senior management had confidence in marketing’s forecasts of sales impact. And even this is probably optimistic: a separate MMA-funded study, also cited in the new white paper, found that only 10% of financial executives use marketing forecasts to help set the marketing budget.
The obvious question is why so little progress has been made. Marketers consistently rank performance measurement as their top priority (for example, see the CMO Council’s Marketing Outlook 2008 survey). Nor are marketers doing this out of the goodness of their hearts: they know that being able to show the impact of their expenditures is the best way to protect and grow their budgets. So marketers have every reason to work hard at developing performance measures that finance and senior management will accept.
And yet...when the ANA survey asked marketers to rank their accountability challenges, the top score (45%) went to “understanding the impact of changes in consumer attitudes and perceptions on sales”. This strikes me as odd, if the marketers’ ultimate goal is to understand the impact of marketing programs on sales. Measuring the impact of marketing programs and measuring the impact of customer attitudes are not the same thing.
Nor is this a simple fluke of the wording. A separate question showed the most common accountability investment was in “brand and customer equity models” (53%). These also measure the link between attitudes and sales.
One explanation for the disconnect would be that marketers can already measure the relationship between marketing programs and consumer attitudes, so they can complete the analysis by adding the link between attitudes and sales. This seems a bit optimistic, especially since it also assumes that marketers also understand the impact on sales of marketing programs that are not aimed at consumer attitudes, such as price and trade promotions.
A more plausible explanation would be that the link between attitudes and sales is the hardest thing to measure, so that’s where marketers put their effort. Or, maybe that relationship is the question that marketers find most intriguing because, well, that’s the sort of thing they care about. A cynic might suggest that marketers don’t want to measure the link between marketing programs and sales because they don’t want to know the answer. But even the cynic would acknowledge that marketers need a way to justify their budgets, so that can’t be it.
None of these answers really satisfies me, but let’s put this question aside. I think we can safely assume that marketers really do want to measure their performance. This leaves the question of why they haven’t made much progress in doing it.
One reason could be that they simply don’t know how. Marketing measurement is truly difficult, so that’s surely part of it.
Another possibility is that they know how, but lack the resources. Since good marketing measurement can be quite expensive, this is probably part of the problem as well. Remember that the resources involved will ultimately come from the corporate budget, so finance departments and senior management must also agree that marketing measurement is the best thing to spend them on. And, indeed, this doesn’t seem to be their priority. The white paper states that “the number of CEOs and CFOs championing marketing accountability programs within their firms remained negligible and unchanged from 2007.”
This is a pretty depressing conclusion, although to me it has the ring of truth. Fuss though they may, CEOs and CFOs are not willing to invest money to solve the problem. Indeed our friend the cynic might argue that they are the ones with a motivation to avoid measurement, since it gives them more flexibility to allocate funds as they prefer.
The white paper doesn’t dwell on this. It just lists lack of senior management involvement as one of many obstacles. The paper authors then go on to propose a four step process for developing an accountability program:
- assess and benchmark existing capabilities and resources
- define an achievable future state, in terms of the business questions to answer and the resources required to answer them
- work with stakeholders to align metrics with corporate goals and key business questions
- establish a roadmap with a multi-year phased approach
There’s not much to argue with here. The paper also provides a reasonable list of success factors, including:
- realistic stakeholders expectations
- agreement on scope at the start of the project
- cross-functional team with clearly defined roles, responsibilities and communication points
- simple math and analytics
- integration of analytics for pricing, ROI, and brand analysis
Again, it’s all sound advice. Let’s hope you can get the resources to follow it.
In the 2008 study, released in July and just recapitulated in a new MMA white paper, only 23% of the marketers were satisfied with their metrics for marketing’s impact on sales, and just 19% were satisfied with metrics showing marketing impact on ROI and brand equity.
Furthermore, only 14% of the marketers felt their senior management had confidence in marketing’s forecasts of sales impact. And even this is probably optimistic: a separate MMA-funded study, also cited in the new white paper, found that only 10% of financial executives use marketing forecasts to help set the marketing budget.
The obvious question is why so little progress has been made. Marketers consistently rank performance measurement as their top priority (for example, see the CMO Council’s Marketing Outlook 2008 survey). Nor are marketers doing this out of the goodness of their hearts: they know that being able to show the impact of their expenditures is the best way to protect and grow their budgets. So marketers have every reason to work hard at developing performance measures that finance and senior management will accept.
And yet...when the ANA survey asked marketers to rank their accountability challenges, the top score (45%) went to “understanding the impact of changes in consumer attitudes and perceptions on sales”. This strikes me as odd, if the marketers’ ultimate goal is to understand the impact of marketing programs on sales. Measuring the impact of marketing programs and measuring the impact of customer attitudes are not the same thing.
Nor is this a simple fluke of the wording. A separate question showed the most common accountability investment was in “brand and customer equity models” (53%). These also measure the link between attitudes and sales.
One explanation for the disconnect would be that marketers can already measure the relationship between marketing programs and consumer attitudes, so they can complete the analysis by adding the link between attitudes and sales. This seems a bit optimistic, especially since it also assumes that marketers also understand the impact on sales of marketing programs that are not aimed at consumer attitudes, such as price and trade promotions.
A more plausible explanation would be that the link between attitudes and sales is the hardest thing to measure, so that’s where marketers put their effort. Or, maybe that relationship is the question that marketers find most intriguing because, well, that’s the sort of thing they care about. A cynic might suggest that marketers don’t want to measure the link between marketing programs and sales because they don’t want to know the answer. But even the cynic would acknowledge that marketers need a way to justify their budgets, so that can’t be it.
None of these answers really satisfies me, but let’s put this question aside. I think we can safely assume that marketers really do want to measure their performance. This leaves the question of why they haven’t made much progress in doing it.
One reason could be that they simply don’t know how. Marketing measurement is truly difficult, so that’s surely part of it.
Another possibility is that they know how, but lack the resources. Since good marketing measurement can be quite expensive, this is probably part of the problem as well. Remember that the resources involved will ultimately come from the corporate budget, so finance departments and senior management must also agree that marketing measurement is the best thing to spend them on. And, indeed, this doesn’t seem to be their priority. The white paper states that “the number of CEOs and CFOs championing marketing accountability programs within their firms remained negligible and unchanged from 2007.”
This is a pretty depressing conclusion, although to me it has the ring of truth. Fuss though they may, CEOs and CFOs are not willing to invest money to solve the problem. Indeed our friend the cynic might argue that they are the ones with a motivation to avoid measurement, since it gives them more flexibility to allocate funds as they prefer.
The white paper doesn’t dwell on this. It just lists lack of senior management involvement as one of many obstacles. The paper authors then go on to propose a four step process for developing an accountability program:
- assess and benchmark existing capabilities and resources
- define an achievable future state, in terms of the business questions to answer and the resources required to answer them
- work with stakeholders to align metrics with corporate goals and key business questions
- establish a roadmap with a multi-year phased approach
There’s not much to argue with here. The paper also provides a reasonable list of success factors, including:
- realistic stakeholders expectations
- agreement on scope at the start of the project
- cross-functional team with clearly defined roles, responsibilities and communication points
- simple math and analytics
- integration of analytics for pricing, ROI, and brand analysis
Again, it’s all sound advice. Let’s hope you can get the resources to follow it.
Friday, December 5, 2008
TraceWorks' Headlight Integrates Online Measurement and Execution
I’ve been looking at an interesting product called Headlight from a Danish firm TraceWorks. Headlight is an online advertising management system, which means that it helps marketers to plan, execute and measure paid and unpaid Web advertising.
According to TraceWorks CEO Christian Dam, Headlight traces its origins to an earlier product, Statlynx, which measured the return on investment of search marketing campaigns. (This is why Headlight belongs on this blog.) The core technology of Headlight is still the ability to capture data sent by tags inserted in Web pages. These are used to track initial responses to a promotion and eventual conversion events. The conversion tracking is especially critical because it can capture revenue, which provides the basis for detailed return on investment calculations. (Setting this up does require help from your company's technology group; it is not something marketers can do for themselves.)
These functions are now supplemented by functions that let the system actually deliver banner ads, including both an ad serving capability and digital asset management of the ad contents. The system can also integrate with Google AdWords paid search campaigns, automatically sending tracking URLs to AdWords and using those URLs in its reports. It can also capture tracking URLs from email campaigns.
All Web activity tracking may make Headlight sound like a Web analytics tool, but it’s quite different. The main distinction is that Headlight lets users set up and deliver ad campaigns, which is well outside the scope of Web analytics. Nor, on the other hand, does Headlight offer the detailed visitor behavior analysis of a Web analytics system.
The campaign management functions extend both to the planning that precedes execution and to the evaluation that follows it. The planning functions are not especially fancy but should be adequate: users can define activities (a term that Headlight uses more or less interchangeably with campaigns), give them start and end dates, and assign costs. The system can also distinguish between firm plans and drafts. TraceWorks expects to significantly expand workflow capabilities, including sub-tasks with assigned users, due dates and alerts of overdue items, in early 2009.
Evaluation functions are more extensive. Users can define both corporate goals (e.g., total number of conversions) and individual goals (related to specific metrics and activities) for specific users, and have the system generate reports that will compare these to actual results. Separate Key Performance Indicator (KPI) reports show selected actual results over time. In addition, something the vendor calls a “WhyChart” adds marketing activity dates to the KPI charts, so users can see the correlation between different marketing efforts and results. Summary reports can also show the volume of traffic generated by different sources.
The value of Headlight comes not only from the power of the individual features but the fact that they are tightly integrated. For example, the asset management portion of the system can show users the actual results for each asset in previous campaigns. This makes it much easier for marketers to pick the elements that work best and to make changes during campaigns when some items work better than others. The system can also be integrated with other products through a Web Service API that lets external systems call its functions for AdWords campaign management, conversion definition, activity setup, and reporting.
Technology aside, I was quite impressed with the openness of TraceWorks as a company. The Web site provides substantial detail about the product, and includes a Wiki with what looks like fairly complete documentation. The vendor also offers a 14 day free trial of the system.
Pricing also seems quite reasonable. Headlight is offered as a hosted service, with fees ranging from $1,000 to $5,000 per month depending on Web traffic. According to Dam, the average fee is about $1,300 per month. Larger clients include ad agencies who use Headlight for their own clients.
Incidentally, the company Web site also includes an interesting benchmarking offer, which lets you enter information about your own company's online marketing and get back a report comparing you to industry peers. (Yes, I know a marketing information gathering tool when I see one.) At the moment, unfortunately, the company doesn't seem to have enough data gathered to report back results. Or maybe it just didn't like my answers.
TraceWorks released its original Statlynx product in 2003 and launched Headlight in early 2007. The system currently serves about 500 companies directly and through agencies.
According to TraceWorks CEO Christian Dam, Headlight traces its origins to an earlier product, Statlynx, which measured the return on investment of search marketing campaigns. (This is why Headlight belongs on this blog.) The core technology of Headlight is still the ability to capture data sent by tags inserted in Web pages. These are used to track initial responses to a promotion and eventual conversion events. The conversion tracking is especially critical because it can capture revenue, which provides the basis for detailed return on investment calculations. (Setting this up does require help from your company's technology group; it is not something marketers can do for themselves.)
These functions are now supplemented by functions that let the system actually deliver banner ads, including both an ad serving capability and digital asset management of the ad contents. The system can also integrate with Google AdWords paid search campaigns, automatically sending tracking URLs to AdWords and using those URLs in its reports. It can also capture tracking URLs from email campaigns.
All Web activity tracking may make Headlight sound like a Web analytics tool, but it’s quite different. The main distinction is that Headlight lets users set up and deliver ad campaigns, which is well outside the scope of Web analytics. Nor, on the other hand, does Headlight offer the detailed visitor behavior analysis of a Web analytics system.
The campaign management functions extend both to the planning that precedes execution and to the evaluation that follows it. The planning functions are not especially fancy but should be adequate: users can define activities (a term that Headlight uses more or less interchangeably with campaigns), give them start and end dates, and assign costs. The system can also distinguish between firm plans and drafts. TraceWorks expects to significantly expand workflow capabilities, including sub-tasks with assigned users, due dates and alerts of overdue items, in early 2009.
Evaluation functions are more extensive. Users can define both corporate goals (e.g., total number of conversions) and individual goals (related to specific metrics and activities) for specific users, and have the system generate reports that will compare these to actual results. Separate Key Performance Indicator (KPI) reports show selected actual results over time. In addition, something the vendor calls a “WhyChart” adds marketing activity dates to the KPI charts, so users can see the correlation between different marketing efforts and results. Summary reports can also show the volume of traffic generated by different sources.
The value of Headlight comes not only from the power of the individual features but the fact that they are tightly integrated. For example, the asset management portion of the system can show users the actual results for each asset in previous campaigns. This makes it much easier for marketers to pick the elements that work best and to make changes during campaigns when some items work better than others. The system can also be integrated with other products through a Web Service API that lets external systems call its functions for AdWords campaign management, conversion definition, activity setup, and reporting.
Technology aside, I was quite impressed with the openness of TraceWorks as a company. The Web site provides substantial detail about the product, and includes a Wiki with what looks like fairly complete documentation. The vendor also offers a 14 day free trial of the system.
Pricing also seems quite reasonable. Headlight is offered as a hosted service, with fees ranging from $1,000 to $5,000 per month depending on Web traffic. According to Dam, the average fee is about $1,300 per month. Larger clients include ad agencies who use Headlight for their own clients.
Incidentally, the company Web site also includes an interesting benchmarking offer, which lets you enter information about your own company's online marketing and get back a report comparing you to industry peers. (Yes, I know a marketing information gathering tool when I see one.) At the moment, unfortunately, the company doesn't seem to have enough data gathered to report back results. Or maybe it just didn't like my answers.
TraceWorks released its original Statlynx product in 2003 and launched Headlight in early 2007. The system currently serves about 500 companies directly and through agencies.
Friday, November 28, 2008
Judging the Value of Marketing Data
Last week’s post on ranking demand generation vendors highlighted a fundamental challenge in marketing measurement: the data you want often isn’t available. So a great deal of marketing measurement comes down to deciding which of the available data best suits your needs, and ultimately whether that data is better than nothing.
It’s probably obvious why using bad data can be worse than doing nothing, but in case this is read by, say, a creature from Mars: we humans tend to assume others are telling the truth unless we have a specific reason to question them. This innate optimism is probably a good thing for society as a whole. But it also means we’ll use bad data to make decisions which we would approach more cautiously if we had no data at all.
But how do you judge a piece of data? Here is a list of criteria presented in my book The MPM Toolkit, due in late January.
· Existence. Ok, this is pretty basic, but the information does have to exist. Let’s avoid the deeper philosophical issues and just say that data exists if it is recorded somewhere, or can be derived from something that’s recorded. So the color of your customers’ eyes only exists as data if you’ve stored it on their records or can look it up somewhere else. If the data doesn’t exist, you may be able to capture it. Then you have to compare the cost of capturing it with its value. But that’s a topic for another day.
· Accessibility. Can you actually access the data? To get back to last week’s post, we’d love to know the revenue of each demand generation vendor. This data certainly exists in their accounting systems, but they haven’t shared it with us so we can’t use it. Again, it’s often possible to gain access to information if you’re willing to pay the price, and you must once more compare the price with the value. In fact, the price / value tradeoff will apply to every factor in this list, so I won’t bother to mention it from here on out.
· Coverage. What portion of the universe is covered by the data? In the case of demand generation vendors, the number of blog posts was a poor measure of market attention because the available sources clearly didn’t capture all the posts. In itself, this isn’t necessarily fatal flaw, since a fair sample could still give a useful relative ranking. But we can’t judge whether the coverage was a fair sample because we don’t know why it was incomplete. This is a critical issue when assessing whether, or more precisely how, to use incomplete data. (In the demand generation case, the very small numbers of blog posts added another issue, which is that the statistical noise of a few random posts could distort the results. This is also something to consider, although hopefully most of your marketing data deals with larger quantities.)
· Accuracy. Data may not have been accurate to begin with or it may be outdated. Data can be inaccurate because someone purposely provided false information or because the mechanism is inherently flawed. Survey replies can have both problems: people lie for various reasons and they may not actually know the correct answers. Even seemingly objective data can be incorrect: a simple temperature reading may inaccurate because the thermometer was miscalibrated, someone read it wrong, or the scale was Celsius rather than Fahrenheit. Errors can also be introduced after the data is captured, such as incorrect conversions (e.g., inflation adjustments used to create “constant dollar” values) or incorrect aggregation (e.g., customer value statistics that do not associate transactions with the correct customers). In our demand generation example, statistics on search volume were highly inaccurate because the counts for some terms included results that were clearly irrelevant. As with other factors listed here, you need to determine the level of accuracy that’s required for your specific purpose and assess whether the particular source is adequate.
· Consistency. Individually accurate items can be collectively incorrect. To continue with the thermometer example, readings from some stations may be in Celsius and others in Fahrenheit, or readings from a single station may have changed from Fahrenheit to Celsius over time. This particular difference would be obvious to anyone examining the data, although it could easily be overlooked in a large data set that combined information from many sources. Other inconsistencies are much more subtle, such as changes in wording of survey questions or the collection mechanism (e.g., media consumption diaries vs. automated “people meters”). As with coverage, it’s important to understand any bias introduced by these factors. In our demand generation analysis, Compete.com used several different techniques to measure Web traffic, and it appeared that these yielded inconsistent results for sites with different traffic levels.
· Timeliness. The primary issue with timeliness is how quickly data becomes available. In the past, it often took weeks or months to gather marketing information. Today, data in general moves much more quickly, although some information still take months to assemble. There is a danger that quickly available data will overwhelm higher-quality data that appears later. For example, initial response rate to a promotion is immediately available, but the value of those responses can only be measured over time. Decisions based only on gross response often turn out to be incorrect once the later performance is included in the analysis. Still, timely data can be extremely important when it can lead to adjustments that improve results, such as moving funds from one promotion to another. Online marketing in particular often allows for such reactions because changes can be made in hours or minutes, rather than the weeks and months needed for traditional marketing programs.
I haven’t listed cost as a separates consideration only because there are often incremental investments that can made to change a data element’s existence, accessibility, coverage, etc. Those investments would change its value as well. But you will ultimately still need to assess the total cost and value of a particular element, and then compare it with the cost and value of other elements that could serve a similar purpose. This assessment will often be fairly informal, as it was in last week’s blog post. But you still need to do it: while an unexamined life may or not be worth living, unexamined marketing data will get you in trouble for sure.
Friday, November 21, 2008
Twitter Volume for Demand Generation Vendors
A comment on my previous post suggested Twitter mentions as a possible measure of vendor market presence. That had in fact occurred to me, but I hadn't bothered to check because I assumed the volume would be too low. But since the topic had been raised, I figured I'd take a peek.
The first two Twitter monitoring sites I looked at, Twitscoop and Twitterment, seemed to confirm my suspicion: of the three most popular vendors, Eloqua had 6 Twitscoop hits and 3 Twitterment hits; Silverpop had 2 on each; and Marketo had 3 on Twitscoop and none on the other. No point in looking further here.
But then I checked Twitstat. In addition to having a slightly less childish name, it seems to either do a more thorough search or look back further in time: for whatever reason, it found 152 hits for Eloqua, 65 for Silverpop, and 133 for Marketo. Much more interesting.
Alas, the numbers dropped down considerably after that, as you can see in the table below. Everything else is in single digits except for two anomalies LoopFuse with 22 mentions and Bulldog Solutions with a whopping 217. Interestingly, both those sites also had exceptionally high blog hit numbers on IceRocket. The root cause is probably the same: one or two active bloggers or Twitter users (which seems to be the accepted term; I guess we can't call them Twits) are enough to skew the figures when volumes are so low. More particularly, LoopFuse gets a lot of attention because some of its founders are closely tied to the open source community. Bulldog Solutions just seems to have a group of employees who are serious into Twitter. In fact, I now know more about their lives than I really care to (although there was nothing indiscreet in the posts, I'm pleased to report).
A couple of side notes:
- the very short length of the messages does make them easy to read, which paradoxically means you can actually gather more information from Twitter than by scanning blog posts, because reading the blog posts takes too much time. Of course, when we're dealing with such tiny volumes, there is no way to generalize from what you read: Twitter is strictly anecdotal evidence, and perhaps even dangerous for that reason.
- there seemed to be several Tweets that were purposely sent for marketing purposes. Nothing wrong with that, and they were quite open about it. Just interesting how quickly some firms have picked up on this. (OK, not so quickly: Twitter has been around since 2006 and very popular for about a year now.)
Still, the bottom line for the purposes of measuring demand generation vendors is still the same as for blogs: too little volume to be a reliable measure of relative market interest.
Twitterment | Ice Rocket | Alexa | Alexa | |
twitter mentions | blog posts | rank | share x 10^7 | |
| Already in Guide: | ||||
| Eloqua | 152 | 286 | 20,234 | 70,700 |
| Silverpop | 65 | 188 | 29,080 | 30,500 |
Marketo | 122 | 229 | 68,088 | 17,000 |
Manticore Technology | 0 | 56 | 213,546 | 6,100 |
Market2Lead | 5 | 5 | 235,244 | 4,800 |
Vtrenz | 8 | 53 | 295,636 | 3,600 |
Marketing Automation: | - | |||
Unica Affinium | 6 | 43 | 126,215 | 8,500 |
Alterian | 5 | 145 | 345,543 | 2,500 |
Aprimo | 6 | 139 | 416,446 | 2,200 |
Neolane | 5 | 64 | 566,977 | 1,690 |
Other Demand Generation: | - | |||
Marketbright | 9 | 167,306 | 5,400 | |
Pardot | 4 | 33 | 211,309 | 3,600 |
Marqui Software | 2 | 19 | 211,767 | 4,400 |
ActiveConversion | 2 | 12 | 257,058 | 3,400 |
Bulldog Solutions | 219 | 43 | 338,337 | 3,200 |
OfficeAutoPilot | 2 | 5 | 509,868 | 2,000 |
Lead Genesys | 1 | 5 | 557,199 | 1,450 |
LoopFuse | 22 | 43 | 734,098 | 1,090 |
eTrigue | 1 | 1,510,207 | 430 | |
PredictiveResponse | 1 | 0 | 2,313,880 | 330 |
FirstWave Technologies | 0 | 11 | 2,872,765 | 170 |
NurtureMyLeads | 0 | 5 | 4,157,304 | 140 |
Customer Portfolios | 0 | 3 | 5,097,525 | 90 |
Conversen | 1 | 0 | 6,062,462 | 70 |
FirstReef | 0 | 0 | 11,688,817 | 10 |
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