It’s not that I’m obsessive, but just to gnaw a bit more on last week’s bone about the coming unification of Web and other marketing data...
- a recent survey sponsored by enterprise marketing automation vendor Unica found that “integration with other marketing solutions” was the most commonly cited web analytics challenge (46%).
This was followed by “verifying accuracy of data (inflation/deflation)” (41%) and “not comprehensive/missing types of data” (32%). It’s interesting that the question was about Web analytics in particular – even analyzing Web results by itself requires non-Web data.
- another survey by another marketing automation vendor, Alterian, found the most-commonly cited top obstacle in online marketing (25% of respondents) was “integration of online with database marketing and offline channels”.
Now, this isn’t exactly the same answer as the Unica survey, since the question isn’t limited to data integration. But Alterian also reported that “lack of ability to assess or manage internal infrastructure and culture challenges (25%) and the integration of all the technology to power the cycle (20%) were identified as the biggest factors in implementing the customer engagement cycle.” So clearly data and system integration are indeed primary concerns for multi-channel marketing.
For still more on this topic, see today’s post on the MPM Toolkit blog, describing a very detailed report in eMarketer about Online Brand Measurement. This provides still more evidence for the need for integration of Web and non-Web data, in addition to other issues.
Case closed.
This is the blog of David M. Raab, marketing technology consultant and analyst. Mr. Raab is founder and CEO of the Customer Data Platform Institute and Principal at Raab Associates Inc. All opinions here are his own. The blog is named for the Customer Experience Matrix, a tool to visualize marketing and operational interactions between a company and its customers.
Tuesday, September 29, 2009
Wednesday, September 23, 2009
Web Analytics Is Dead. So Is Customer Centricity. I Need a Drink.
Summary: Web analytics is merging into the broad world of marketing measurement across all media, which itself is shifting focus from tracking individuals to understanding group behavior. Although Web analytics and marketing automation vendors are currently wrestling over who will house customer data, both are likely to lose custody to enterprises who want to control their data for themselves.
Even as analysts are still sorting through the implications of last week’s acquisition of Omniture by Adobe, the industry saw two additional important announcements this week: Omniture combining its data with comScore to help measure Web advertising audiences, and Nielsen working with Facebook to poll consumers on advertising impact.
Both announcements share several interesting features: they don't rely on traditional Web analytics (tracking page views); they involve vendors who report data from consumer panels; and they relate to measuring advertising measurement. Maybe they coincided simply because the big Advertising Week conference is now under way. But I think they, along with the Omniture/Adobe deal itself, hint at something more profound: the end of Web analytics as we know it.
Ok, that may not be as earth-shattering as the end of several other things you might imagine. But many marketers are just getting their arms around traditional Web analytics. So it’s worth warning them that things are about to change again.
Smarter Content on the Way
Let’s start with Omniture/Adobe. After thinking about it for a week (and hearing what the participants said), I think the main purpose of the deal was to let Adobe build content that was more intelligent in two ways:
- First, the content will be inherently “instrumented” to report how, when, where and which people are consuming it, using techniques go beyond traditional Web analytics methods (server logs, Javascript tags and cookies). This is needed because content increasingly exists outside of plain vanilla Web pages that can be tracked with conventional techniques. Problems include Flash, video, audio and other non-HTML Web content; venues like mobile, digital video recorders and interactive TV; widgets that migrate through social networks; and plain old cookie deletion. Web analytics vendors are striving to extend their technologies to capture these, but at some point you have to look for a different basic model. Content that can itself “phone home” rather than relying on the carrier medium could be the long-term answer.
- Second, content will be self-optimizing. This involves built-in tests and, perhaps, a sort of swarm intelligence where subsequent views are actually modified based on previous results reported by the content itself. Imagine a widget with a built-in A/B headline test: every time someone accesses it, the widget offers one headline or the other, and reports the result to a central server. (This could be done without transmitting personally identifiable information, so privacy issues are minimal.) Once a pattern emerges, the server could instruct the distributed widgets to only display the winning headline, or, better still, to start a new test. Even without a central server, each copy of the widget could still run its own test and, assuming it’s accessed enough times, adjust all by itself.
Who Owns The Data?
So far so good, and I think that’s plenty of reason to justify spending $1.8 billion for Omniture. But I also think Adobe was interested in the fact that Omniture controls so much of its clients’ data.
There is a battle brewing over that issue: like most Web analytics vendors, Omniture stores Web traffic data on its own servers and sells clients the ability to access that data. That didn’t raise any particular business issues when Web data was viewed largely in isolation. But as the Web takes an increasingly central role in customer contacts, marketers need to merge that Web data with their other customer information. Indeed, if you want to use that data to help guide customer interactions across channels, the data must be not just centralized but also updated in real-time. That means marketers either give all their non-Web data to their Web analytics vendor, or directly capture Web analytics data on their own servers.
The Web analytics vendors see this future and recognize that they’ll be more important to their clients, and thus able to charge higher fees, if they hold everything. Marketing automation vendors and in-house IT groups see the same future and recognize the threat to their own positions. Thus, the business-oriented marketing automation vendors (i.e., demand generation vendors: Eloqua, Silverpop, Marketo, etc.) already capture Web behavior in their own systems and integrate it directly with customer management. The big consumer-oriented marketing automation vendors (SAS, Teradata, Unica) also offer Web analytics, although perhaps less tightly integrated.
The problem here is that the Web analytics vendors and demand generation vendors are largely SaaS systems, so both hold the integrated customer data outside of the client’s own data center. It’s not clear that clients – especially big enterprise clients – will continue to accept this. The consumer-oriented marketing automation vendors already largely support on-premise configurations, so they may be the real winners in this battle. Yet bear in mind that looming behind the marketing automation vendors are the enterprise CRM vendors, who also offer largely on-premise installations. They may eventually gobble up the marketing automation business and the Web analytics data along with it. In that case, Web analytics vendors who hope to become rich stewards of centralized customer databases will be very disappointed.
Customer-Centricity Is Obsolete
I also think there may be one still deeper trend at play here, although this is more speculative. Let’s call it a shift from customer-centric to community-centric marketing. Since customer centricity has been the ultimate goal of marketers, or at least marketing gurus, for several decades, I expect some skepticism.
But think of it this way: marketing has always been about deploying and propagating messages to consumers. In recent years, we’ve striven and become technically more able to target those messages directly at individuals. Yet messages were never really limited to one person. Even if they were delivered privately, they could be shared directly through conversation, physical and electronic pass-along, and indirectly as consumers discussed their experiences with the company in general. Thus, there has always been a community component to marketing campaigns. In cases such as word of mouth programs, this was even the primary objective.
Today, of course, that sort of sharing has become increasingly important for every marketing project. Thus marketers have more need to track the secondary impact of their messages on the larger community. Happily, they also have more technology to do the tracking.
Here’s what’s interesting, though. Marketers will never be able to trace the exact path of each message from one person to another. And even if the data were available, there were no privacy constraints and they could handle the volume, marketers would still face the insurmountable challenge of that multiple messages influence final behavior. That is, they could never meaningfully say that one particular message was the single reason a customer did something. All they can ever do is to look at the many different messages a customer probably received and compare these with actual behavior. If the customer did what you wanted, the messages somehow worked.
If this sounds familiar, it should: it’s the classic problem faced by brand marketers in measuring the value of their investments. Their solution has always been to measure intermediate variables such as consumer attitudes, and to measure these through samples rather than by polling everyone in the market.
This brings us full circle to the panel-based attitudinal research at the core of the Omniture/comScore and Nielsen/Facebook deals. Once you recognize that what’s most important is the broad community impact of your marketing efforts, you fall back on those types of measures rather than attempting the impossible, and impossibly expensive, task of tracing the exact path followed by each individual. In other words, what we’re seeing here is not some Mad Men-style reversion to obsolete brand marketing behaviors, but a recognition that modern marketing is community-driven, so its measurements must be as well.
Now, if I can just find a reason to bring back the three-martini lunch….
Even as analysts are still sorting through the implications of last week’s acquisition of Omniture by Adobe, the industry saw two additional important announcements this week: Omniture combining its data with comScore to help measure Web advertising audiences, and Nielsen working with Facebook to poll consumers on advertising impact.
Both announcements share several interesting features: they don't rely on traditional Web analytics (tracking page views); they involve vendors who report data from consumer panels; and they relate to measuring advertising measurement. Maybe they coincided simply because the big Advertising Week conference is now under way. But I think they, along with the Omniture/Adobe deal itself, hint at something more profound: the end of Web analytics as we know it.
Ok, that may not be as earth-shattering as the end of several other things you might imagine. But many marketers are just getting their arms around traditional Web analytics. So it’s worth warning them that things are about to change again.
Smarter Content on the Way
Let’s start with Omniture/Adobe. After thinking about it for a week (and hearing what the participants said), I think the main purpose of the deal was to let Adobe build content that was more intelligent in two ways:
- First, the content will be inherently “instrumented” to report how, when, where and which people are consuming it, using techniques go beyond traditional Web analytics methods (server logs, Javascript tags and cookies). This is needed because content increasingly exists outside of plain vanilla Web pages that can be tracked with conventional techniques. Problems include Flash, video, audio and other non-HTML Web content; venues like mobile, digital video recorders and interactive TV; widgets that migrate through social networks; and plain old cookie deletion. Web analytics vendors are striving to extend their technologies to capture these, but at some point you have to look for a different basic model. Content that can itself “phone home” rather than relying on the carrier medium could be the long-term answer.
- Second, content will be self-optimizing. This involves built-in tests and, perhaps, a sort of swarm intelligence where subsequent views are actually modified based on previous results reported by the content itself. Imagine a widget with a built-in A/B headline test: every time someone accesses it, the widget offers one headline or the other, and reports the result to a central server. (This could be done without transmitting personally identifiable information, so privacy issues are minimal.) Once a pattern emerges, the server could instruct the distributed widgets to only display the winning headline, or, better still, to start a new test. Even without a central server, each copy of the widget could still run its own test and, assuming it’s accessed enough times, adjust all by itself.
Who Owns The Data?
So far so good, and I think that’s plenty of reason to justify spending $1.8 billion for Omniture. But I also think Adobe was interested in the fact that Omniture controls so much of its clients’ data.
There is a battle brewing over that issue: like most Web analytics vendors, Omniture stores Web traffic data on its own servers and sells clients the ability to access that data. That didn’t raise any particular business issues when Web data was viewed largely in isolation. But as the Web takes an increasingly central role in customer contacts, marketers need to merge that Web data with their other customer information. Indeed, if you want to use that data to help guide customer interactions across channels, the data must be not just centralized but also updated in real-time. That means marketers either give all their non-Web data to their Web analytics vendor, or directly capture Web analytics data on their own servers.
The Web analytics vendors see this future and recognize that they’ll be more important to their clients, and thus able to charge higher fees, if they hold everything. Marketing automation vendors and in-house IT groups see the same future and recognize the threat to their own positions. Thus, the business-oriented marketing automation vendors (i.e., demand generation vendors: Eloqua, Silverpop, Marketo, etc.) already capture Web behavior in their own systems and integrate it directly with customer management. The big consumer-oriented marketing automation vendors (SAS, Teradata, Unica) also offer Web analytics, although perhaps less tightly integrated.
The problem here is that the Web analytics vendors and demand generation vendors are largely SaaS systems, so both hold the integrated customer data outside of the client’s own data center. It’s not clear that clients – especially big enterprise clients – will continue to accept this. The consumer-oriented marketing automation vendors already largely support on-premise configurations, so they may be the real winners in this battle. Yet bear in mind that looming behind the marketing automation vendors are the enterprise CRM vendors, who also offer largely on-premise installations. They may eventually gobble up the marketing automation business and the Web analytics data along with it. In that case, Web analytics vendors who hope to become rich stewards of centralized customer databases will be very disappointed.
Customer-Centricity Is Obsolete
I also think there may be one still deeper trend at play here, although this is more speculative. Let’s call it a shift from customer-centric to community-centric marketing. Since customer centricity has been the ultimate goal of marketers, or at least marketing gurus, for several decades, I expect some skepticism.
But think of it this way: marketing has always been about deploying and propagating messages to consumers. In recent years, we’ve striven and become technically more able to target those messages directly at individuals. Yet messages were never really limited to one person. Even if they were delivered privately, they could be shared directly through conversation, physical and electronic pass-along, and indirectly as consumers discussed their experiences with the company in general. Thus, there has always been a community component to marketing campaigns. In cases such as word of mouth programs, this was even the primary objective.
Today, of course, that sort of sharing has become increasingly important for every marketing project. Thus marketers have more need to track the secondary impact of their messages on the larger community. Happily, they also have more technology to do the tracking.
Here’s what’s interesting, though. Marketers will never be able to trace the exact path of each message from one person to another. And even if the data were available, there were no privacy constraints and they could handle the volume, marketers would still face the insurmountable challenge of that multiple messages influence final behavior. That is, they could never meaningfully say that one particular message was the single reason a customer did something. All they can ever do is to look at the many different messages a customer probably received and compare these with actual behavior. If the customer did what you wanted, the messages somehow worked.
If this sounds familiar, it should: it’s the classic problem faced by brand marketers in measuring the value of their investments. Their solution has always been to measure intermediate variables such as consumer attitudes, and to measure these through samples rather than by polling everyone in the market.
This brings us full circle to the panel-based attitudinal research at the core of the Omniture/comScore and Nielsen/Facebook deals. Once you recognize that what’s most important is the broad community impact of your marketing efforts, you fall back on those types of measures rather than attempting the impossible, and impossibly expensive, task of tracing the exact path followed by each individual. In other words, what we’re seeing here is not some Mad Men-style reversion to obsolete brand marketing behaviors, but a recognition that modern marketing is community-driven, so its measurements must be as well.
Now, if I can just find a reason to bring back the three-martini lunch….
Thursday, September 17, 2009
RightNow Adds Social Community Capabilities (But Don't Expect Support Costs to Fall as a Result)
Summary: RightNow has extended its social media footprint by purchasing HiveLive, which lets companies build public and private communities. It also released a benchmark survey showing that online channels (email, chat, Web self-service) don't do much to reduce customer service telephone calls.
In keeping with my recent posts about broader utilization of social media, I had a chat earlier this week with on-demand CRM vendor RightNow , who updated me on their recent purchase of HiveLive. HiveLive provides a social community platform, which means it lets companies build their own discussion groups, forums and such. HiveLive has many features to support business communities, both in terms of engaging with customers over issues such as product features and bugs, and in terms of building internal communities such as project teams.
HiveLive fits with RightNow’s vision of giving customers a seamless flow between community applications and a company’s traditional service systems. For example, if a question posted to a forum goes unanswered for a specified time, it can be escalated into a service system as a case to be handled by the company’s support group. If I understood correctly, RightNow and HiveLive can do this already.
We discussed deeper sharing, such as having answers developed in a public forum become part of a company’s internal customer service knowledgebase. That’s something RightNow may add in the future.
Our discussion veered onto other topics, and in particular how seriously companies really take the goal of improving the customer experience. RightNow shared a copy of its recent RightNow Multi-Channel Contact Center Benchmark Report, which was interesting in its own right.
One tidbit I found particularly intriguing was how few telephone service calls are “deflected” into email, chat and Web self-service channels. In the survey, most companies reported that fewer than 10% of customers in those channels would otherwise have made a phone call.
You could see this as bad news for the theory that having alternate channels available will reduce the need for call center agents. Or you could consider it good news that customers have more choices to pick the interaction method they find most congenial.
Another interesting item was that 55% of companies have some mechanism to gather feedback from customers, but just 10% of those use an IVR survey, which I personally consider the most effective way to gain broad participation. Again, you can treat this as good news (at least half the companies are trying) or bad news (just 5% of the total are doing it effectively). Either way, it’s food for thought.
Acxiom Uses Social Media Data to Segment Email Lists
Summary: Acxiom's new social media marketing tool gathers public data about social media links and uses it to segment email lists. It's a different, and arguably more practical, approach to helping marketers take advantage of social media.
Acxiom last week released a new “social media marketing” solution called Relevance-X Social.
The press release is frustratingly vague (“With the ability to engage socially active customers and prospects in their preferred networks, marketers can link that knowledge to relevant communications that ignite conversations on behalf of the brand.”) But, on talking to the company, it turns out there is a pretty interesting product here. (Disclosure: I am a consultant to Acxiom, although I had nothing to do with this product).
What Acxiom has done – and this is so Acxiom – is to ignore the content posted in people’s social media comments or profiles, and just capture the “hard” information about links between people and membership in groups. Apparently (and I’m taking Acxiom’s word on this), this data is publicly available from most social networks (Twitter, Facebook, MySpace, LinkedIn, Plaxo and some more specialized ones) once you know someone’s email address. So Acxiom has taken its own database of more than 500 million email addresses and found the connections for each.
Relevance-X then accepts a marketer’s own email list – presumably its customers or prospects – and returns information from its own database about the matching names. This avoids at least some privacy and spam issues, since marketers are only given information about people they already have some type of relationship with.
The main application of this information is sending targeted emails. Thus, a bank might send one message to customers who belonged to a financial planning group, and a different message to customers who don’t. Other segmentation might be based on the total number of connections, membership in the company's own fan group, or information the company already knows from other sources.
The key point here is that Acxiom is using social media to execute traditional database marketing. This is quite different from most social media marketing products, which boil down to monitoring for posts on specified topics, responding to individuals, or to publishing messages to groups through the network itself. In a way, it seems rather old-fashioned to use social media data as a basis for outbound marketing. But for marketers struggling to find a practical use for social media, it's better than many alternatives.
(As Ed Park points out in a comment below, other vendors including RapLeaf and Unbound Technology also build similar databases by capturing social media links.)
Relevance-X includes two other components. One is the ability to tag the content it publishes – such as links within emails or messages posted to group pages – so marketers can track response. This is done with standard page tags and browser cookies, so what’s important here is not the technology but the ability to measure results. Again, this is something that traditional database marketers consider essential – and that other social media products sometimes struggle to accomplish.
The other component is a separate social media monitoring service that tracks keyword mentions, sentiments and trends, but on an aggregate basis rather than by tracking individuals. Acxiom is using a third party product for this. The goal is to supplement the direct response tracking with a more general measure of marketing program impacts.
Pricing for Relevance-x Social is based on the number of relationships (typically email addresses) researched and on the number, size and complexity of the campaigns being managed. It can be purchased on a campaign-by-campaign basis or annual subscription. Pricing for a basic campaign could start at around $25,000.
Acxiom last week released a new “social media marketing” solution called Relevance-X Social.
The press release is frustratingly vague (“With the ability to engage socially active customers and prospects in their preferred networks, marketers can link that knowledge to relevant communications that ignite conversations on behalf of the brand.”) But, on talking to the company, it turns out there is a pretty interesting product here. (Disclosure: I am a consultant to Acxiom, although I had nothing to do with this product).
What Acxiom has done – and this is so Acxiom – is to ignore the content posted in people’s social media comments or profiles, and just capture the “hard” information about links between people and membership in groups. Apparently (and I’m taking Acxiom’s word on this), this data is publicly available from most social networks (Twitter, Facebook, MySpace, LinkedIn, Plaxo and some more specialized ones) once you know someone’s email address. So Acxiom has taken its own database of more than 500 million email addresses and found the connections for each.
Relevance-X then accepts a marketer’s own email list – presumably its customers or prospects – and returns information from its own database about the matching names. This avoids at least some privacy and spam issues, since marketers are only given information about people they already have some type of relationship with.
The main application of this information is sending targeted emails. Thus, a bank might send one message to customers who belonged to a financial planning group, and a different message to customers who don’t. Other segmentation might be based on the total number of connections, membership in the company's own fan group, or information the company already knows from other sources.
The key point here is that Acxiom is using social media to execute traditional database marketing. This is quite different from most social media marketing products, which boil down to monitoring for posts on specified topics, responding to individuals, or to publishing messages to groups through the network itself. In a way, it seems rather old-fashioned to use social media data as a basis for outbound marketing. But for marketers struggling to find a practical use for social media, it's better than many alternatives.
(As Ed Park points out in a comment below, other vendors including RapLeaf and Unbound Technology also build similar databases by capturing social media links.)
Relevance-X includes two other components. One is the ability to tag the content it publishes – such as links within emails or messages posted to group pages – so marketers can track response. This is done with standard page tags and browser cookies, so what’s important here is not the technology but the ability to measure results. Again, this is something that traditional database marketers consider essential – and that other social media products sometimes struggle to accomplish.
The other component is a separate social media monitoring service that tracks keyword mentions, sentiments and trends, but on an aggregate basis rather than by tracking individuals. Acxiom is using a third party product for this. The goal is to supplement the direct response tracking with a more general measure of marketing program impacts.
Pricing for Relevance-x Social is based on the number of relationships (typically email addresses) researched and on the number, size and complexity of the campaigns being managed. It can be purchased on a campaign-by-campaign basis or annual subscription. Pricing for a basic campaign could start at around $25,000.
Tuesday, September 15, 2009
Adobe Buys Omniture: Good for Marketers, Bad for Marketing Automation Vendors
Summary: Adobe's agreement to purchase Omniture illustrates the on-going convergence of Web content management and Web analytics systems. This puts pressure on marketing automation vendors, who also want to provide Web analytics and content management, and who are already being pressed by customer relationship management (CRM) vendors. That's a pretty unpleasant position.
Adobe's announcement that it will purchase Omniture for $1.8 billion makes perfect sense. As I discussed in July, marketers have a lot to gain from tight integration between a Web content management system (CMS) like Adobe's Dreamweaver and Web analytics and optimization like Omniture.
Let's take it as a given, then, that major Web content management systems will soon include integrated analytics. This sets up a new clash between marketing automation vendors and Web CMS vendors. One of Omniture's major selling points before the merger was its ability to combine information across all online marketing channels, and I think they were working towards adding offline channels as well. Although short-term priorities will probably shift now towards Adobe integration, I doubt their long-term ambitions in that direction will evaporate.
And even if the CMS vendors do restrict their focus to online, they will still be competing with Web CMS and analytics solutions from marketing automation vendors who realize that online is too big a sector for them to ignore. Even though both sets of vendors will need to provide some degree of openness so their clients can move data from one platform to another, both will really want to sell their clients the entire execution and analysis stack, and will tightly integrate them to encourage this.
I think I've made this point before, but I'll repeat it again: the marketing automation vendors are really being squeezed between the Web vendors on one side, and the CRM vendors on the other. This is a very unpleasant position, since both CMS and CRM vendors are much larger than the marketing automation specialists. It's hard to see how they can survive as anything but niche products in the not-too-distance future.
This position probably puts me at odds with industry analysts who see great opportunities for growth in the marketing automation space. (I'd point to specific examples but can't find any just this minute.) The general argument seems to be that low adoption rates mean there's plenty of unmet need that will eventually lead to sales. I agree that adoption is low -- but there's no guarantee that the marketing automation specialists will be the ones who fill the gap. Improved CRM or CMS offerings might actually meet marketers needs. And if since nearly everyone has or needs a CRM and CMS system, it will actually be easier for companies to use the expanded features in their existing systems than to buy a separate marketing automation product.
If anybody has a good counter argument, I'd be happy to hear it.
Two further thoughts:
- When I asked one of the marketing automation vendors recently whether he considered CMS vendors as competitors, he said he didn't because CMS vendors still sell primarily to IT, while marketing automation is purchased by marketing. Assuming this is true, then Omniture also helps Adobe by giving access to marketing departments.
- The acquisition may make marketing automation vendors more attractive acquisition candidates for CMS vendors wishing to beef up their marketing capabilities. Autonomy (Interwoven), Open Text, and EMC (Documentum) could all swallow a Unica, Aprimo or Alterian without stopping to chew.
Adobe's announcement that it will purchase Omniture for $1.8 billion makes perfect sense. As I discussed in July, marketers have a lot to gain from tight integration between a Web content management system (CMS) like Adobe's Dreamweaver and Web analytics and optimization like Omniture.
Let's take it as a given, then, that major Web content management systems will soon include integrated analytics. This sets up a new clash between marketing automation vendors and Web CMS vendors. One of Omniture's major selling points before the merger was its ability to combine information across all online marketing channels, and I think they were working towards adding offline channels as well. Although short-term priorities will probably shift now towards Adobe integration, I doubt their long-term ambitions in that direction will evaporate.
And even if the CMS vendors do restrict their focus to online, they will still be competing with Web CMS and analytics solutions from marketing automation vendors who realize that online is too big a sector for them to ignore. Even though both sets of vendors will need to provide some degree of openness so their clients can move data from one platform to another, both will really want to sell their clients the entire execution and analysis stack, and will tightly integrate them to encourage this.
I think I've made this point before, but I'll repeat it again: the marketing automation vendors are really being squeezed between the Web vendors on one side, and the CRM vendors on the other. This is a very unpleasant position, since both CMS and CRM vendors are much larger than the marketing automation specialists. It's hard to see how they can survive as anything but niche products in the not-too-distance future.
This position probably puts me at odds with industry analysts who see great opportunities for growth in the marketing automation space. (I'd point to specific examples but can't find any just this minute.) The general argument seems to be that low adoption rates mean there's plenty of unmet need that will eventually lead to sales. I agree that adoption is low -- but there's no guarantee that the marketing automation specialists will be the ones who fill the gap. Improved CRM or CMS offerings might actually meet marketers needs. And if since nearly everyone has or needs a CRM and CMS system, it will actually be easier for companies to use the expanded features in their existing systems than to buy a separate marketing automation product.
If anybody has a good counter argument, I'd be happy to hear it.
Two further thoughts:
- When I asked one of the marketing automation vendors recently whether he considered CMS vendors as competitors, he said he didn't because CMS vendors still sell primarily to IT, while marketing automation is purchased by marketing. Assuming this is true, then Omniture also helps Adobe by giving access to marketing departments.
- The acquisition may make marketing automation vendors more attractive acquisition candidates for CMS vendors wishing to beef up their marketing capabilities. Autonomy (Interwoven), Open Text, and EMC (Documentum) could all swallow a Unica, Aprimo or Alterian without stopping to chew.
Friday, September 11, 2009
A Heartwarming Story of Social Media, Family and QlikView
My son works as a sports researcher at a cable television network. His job seems mainly to be looking things up in online databases and, on broadcast days, watching several games simultaneously. It's nice work if you can get it.
In terms of technology, Microsoft Word and Excel meet most of his needs. But I did introduce him to QlikView several years back, and he learned enough to analyze statistics for his college basketball team. When QlikView introduced its free Personal Edition, he decided to use it at work to track a database of college recruiting prospects. Despite (or because of) his lack of technical background, and without any formal QlikView training, he created a very nice system to find prospects based on different characteristics and create ad hoc statistical summaries.
The centerpiece is a map that displays the number of recruits by state. Because this is QlikView, the map is automatically redrawn each time he makes a selection: so he can see recruits for a certain position, or going to a particular school, or whatever. This is the sort of thing that gets sports people excited. In fact, his colleagues were so pleased that there’s talk of using a version of the map on-air.
The only fly in this ointment was that neither he nor I could find a way to get the map to show the numbers for all the states simultaneously. We could get different sized bubbles reflecting the state counts, and we could see the actual figure for each state by hovering over it. Recognizing my own limits as a QlikView developer, I asked for help on the QlikView user forum and from friend on the QlikView consulting staff. The consultant didn't think it was possible, so we let the matter drop.
Fast-forward one month, to yesterday, when I received a notification that someone had responded to my forum query with a solution. It took a couple of tries, and some additional help from forum members, to get it to work on my son’s map. But you can imagine how pleased we were when we finally saw the map as originally envisioned.
This story illustrates quite a bit about QlikView. Building the original map was easy – my son was able to do it with little help, even though QlikView was doing some very sophisticated processing under the hood. (Specifically, on-the-fly data aggregation along user-defined calculated dimensions, without touching the underlying database). But getting the system to do exactly what he needed did take some special knowledge. (He had to use the number of students by state as his primary dimension, not the X/Y map coordinates.) The adjustment took just a few minutes, but only a QlikView expert would realize that’s how you do it.
To generalize a bit more broadly, then, QlikView really does enable non-technical users to do amazing things, and it really is as powerful as its advocates (myself included) like to claim. But users do need some training to be effective – something that advocates are sometimes reluctant to admit.
The story also illustrates the value of social media. QlikView’s forum is an amazing source of help for users of all skill levels. It works because QlikView has a community of highly engaged advocates who are both expert in the product and willing to help each other.
The forum provides several strategic benefits for QlikView: it helps users become successful (thus driving wider adoption); it lets users succeed even if they don’t receive proper training (which many will not, particularly among users of the free Personal Edition); it reduces the need for paid support staff; and it provides a window into common problems and requirements. It also reinforces the commitment of the engaged users themselves, by publicly rewarding their contributions. Although I’ve never discussed the forum with QlikView management, they obviously understand these benefits well enough to justify their continued investments in it.
This isn’t to say that social media would provide the same value to everyone. QlikView fits several specific conditions – enthusiastic expert users, problems that can be solved fairly easily, etc. – that won’t always apply. But as an example what social media can sometimes accomplish, QlikView is a great case study waiting to be written.
In terms of technology, Microsoft Word and Excel meet most of his needs. But I did introduce him to QlikView several years back, and he learned enough to analyze statistics for his college basketball team. When QlikView introduced its free Personal Edition, he decided to use it at work to track a database of college recruiting prospects. Despite (or because of) his lack of technical background, and without any formal QlikView training, he created a very nice system to find prospects based on different characteristics and create ad hoc statistical summaries.
The centerpiece is a map that displays the number of recruits by state. Because this is QlikView, the map is automatically redrawn each time he makes a selection: so he can see recruits for a certain position, or going to a particular school, or whatever. This is the sort of thing that gets sports people excited. In fact, his colleagues were so pleased that there’s talk of using a version of the map on-air.
The only fly in this ointment was that neither he nor I could find a way to get the map to show the numbers for all the states simultaneously. We could get different sized bubbles reflecting the state counts, and we could see the actual figure for each state by hovering over it. Recognizing my own limits as a QlikView developer, I asked for help on the QlikView user forum and from friend on the QlikView consulting staff. The consultant didn't think it was possible, so we let the matter drop.
Fast-forward one month, to yesterday, when I received a notification that someone had responded to my forum query with a solution. It took a couple of tries, and some additional help from forum members, to get it to work on my son’s map. But you can imagine how pleased we were when we finally saw the map as originally envisioned.
This story illustrates quite a bit about QlikView. Building the original map was easy – my son was able to do it with little help, even though QlikView was doing some very sophisticated processing under the hood. (Specifically, on-the-fly data aggregation along user-defined calculated dimensions, without touching the underlying database). But getting the system to do exactly what he needed did take some special knowledge. (He had to use the number of students by state as his primary dimension, not the X/Y map coordinates.) The adjustment took just a few minutes, but only a QlikView expert would realize that’s how you do it.
To generalize a bit more broadly, then, QlikView really does enable non-technical users to do amazing things, and it really is as powerful as its advocates (myself included) like to claim. But users do need some training to be effective – something that advocates are sometimes reluctant to admit.
The story also illustrates the value of social media. QlikView’s forum is an amazing source of help for users of all skill levels. It works because QlikView has a community of highly engaged advocates who are both expert in the product and willing to help each other.
The forum provides several strategic benefits for QlikView: it helps users become successful (thus driving wider adoption); it lets users succeed even if they don’t receive proper training (which many will not, particularly among users of the free Personal Edition); it reduces the need for paid support staff; and it provides a window into common problems and requirements. It also reinforces the commitment of the engaged users themselves, by publicly rewarding their contributions. Although I’ve never discussed the forum with QlikView management, they obviously understand these benefits well enough to justify their continued investments in it.
This isn’t to say that social media would provide the same value to everyone. QlikView fits several specific conditions – enthusiastic expert users, problems that can be solved fairly easily, etc. – that won’t always apply. But as an example what social media can sometimes accomplish, QlikView is a great case study waiting to be written.
Wednesday, September 09, 2009
Why Social Media Really Matters
Summary: marketing has shifted steadily over time from passive to active consumer engagement. Social media is the latest stage in this evolution. Marketers need to master new skills at each stage; as they do, advertising budgets will shift to take advantage of the new medium's increased effectiveness.
Of all that research I mentioned last week, two pairs of facts stood out. One was the disparity between the time people spend on online activities (20% to 30% of total media time) and the share of advertising expenditures spent online (10% to 15%). Although some difference may be justified by the differences in media effectiveness, this still suggests to me that ad spending will continue to shift into online media until the spending is roughly proportional.
The other disparity was that search accounts for 5% of online time but 60% of online ad spending. Some of this may be due to the fact that it’s much easier to buy search advertising (think Google AdWords) than other types of online ads. But I think the primary reason is that search serves as a gateway to other Internet activity—so marketers wishing to drive traffic to their own Web sites need search advertising to make this happen.
The final, related factoid is that social media have grown from virtually nothing to nearly 20% of online time over the past few years. This matters because social media are an alternative gateway to finding Web content: instead of doing a search, I can ask my online community for information or recommendations. Thus, social media present a major threat to search advertising revenues. Although social media currently gather under 3% of online advertising, this will surely change as marketers work to find ways to exploit its potential. If you’ve been wondering why Google should be concerned about Twitter and Facebook, that’s your answer.
These shifts from offline to online advertising and from search to social media suggest a progression through four stages:
1. mass media, or broadcasting: this began in the late 19th century with the emergence of national brands and national print media. Today it is represented primarily by television. You can date TV-dominated era from, say, 1950 to 1985.
2. database marketing, or, more poetically, narrowcasting. This is about direct contact with segmented groups of customers. Date it from 1985 to 1997.
3. search marketing. This is characterized by use of search engines to drive traffic to Web sites. I’m being arbitrary but let's date it from 1998 to 2007.
4. social marketing. This is use of social media to connect with consumers. I’ll date it from 2008, although effective marketing uses of social media are just starting to emerge.
As each new medium has emerged over years, some portion of advertising dollars has shifted from the preexisting media. Of course, the old media don’t go away completely. Indeed, traditional mass media (including radio and print as well as TV) still account for the largest share of advertising spend.
The four media differ along several dimensions. These include:
- consumer engagement. Broadcast is the most passive medium; essentially, it’s yelling at people who may or may not be interested in the message. The audience in database marketing is still passive, but it's targeted at segments that marketers have some reason to believe are interested. With search marketing, the consumer takes a somewhat active role in deciding what to look for, even though the ads themselves are still placed by marketers. With social marketing, control is directly in the hands of consumers, who decide which messages they will receive.
- authority. I find this an intriguing concept. Basically it has to do with how consumers decide which messages they should believe. In the mass media, authority is essentially conferred – people believe things because they are "seen on TV" or have the "Good Housekeeping Seal of Approval". With database marketing, the medium (typically direct mail, more recently email or telephone) doesn’t itself confer much authority, so the message itself must command attention because it’s relevant to the consumer’s needs of the moment. This relevance motivates the recipient to actively explore the marketing offer and assess whether its source is credible.
In search marketing, the source of authority is implicitly based on the group itself: Google PageRank is largely determined by the number of links to a Web site – a version of “wisdom of the crowd”. With social marketing, group-based authority is explicit: consumers can see the number of followers, recommendations, reviews and other ratings provided by group members and decide whether to trust them.
- post-sale relationship. This defines the relationship between the marketer and consumer after the initial purchase. In the mass media world, the relationship barely exists: customers use the product and, hopefully, like it enough to buy it again. At most they ask for service if there’s a problem. With database marketing, post-sales contacts become important for cross-sell, upsell and retention. Indeed, this is where database marketing truly shines because it’s where rich data is available for targeting and relationship building.
Search marketing reaches a new level of engagement because customers can interact directly with the company Web site. This lets them initiate transactions, send messages, and in some cases actually change product configurations such as setting telephone features. With social marketing, consumers take direct control, initiating engagement themselves and, even more important, publicly sharing their engagements with other community members.
- marketing focus. This shows the critical task that marketers must master. With mass media, the primary marketing goal is selecting a message that builds a successful brand. For database marketers, the key skill is effective segmentation. Search marketing is primarily focused on developing content, both to attract traffic via organic search and to meet consumer needs once they appear at the site. For social marketing, the ultimate goal is convincing consumers to become brand advocates. Content is still important, of course, but its nature shifts from information that visitors consume to tools like widgets that empower them to share their enthusiasm with others.
The following table summarizes these dimensions.
At the risk of stating the obvious, the table shows a steady increase in consumer empowerment from the passive receipt of mass marketing message to active control in social media. Because this is a fundamental change from traditional mass media marketing, it has several important implications:
- for each new medium, marketers must learn new skills.
- as marketers learn new skills, they will use the new medium more effectively.
- as marketers use the new medium more effectively, it will receive increasing portions of their ad budgets.
- since social media is very new, its share of advertising budgets will continue to grow for some time.
In short, social media matters not because it's cool, but because it offers marketers a new and more effective way to reach their consumers. Marketers who fail to master the required skills will fall behind marketers who do.
Of all that research I mentioned last week, two pairs of facts stood out. One was the disparity between the time people spend on online activities (20% to 30% of total media time) and the share of advertising expenditures spent online (10% to 15%). Although some difference may be justified by the differences in media effectiveness, this still suggests to me that ad spending will continue to shift into online media until the spending is roughly proportional.
The other disparity was that search accounts for 5% of online time but 60% of online ad spending. Some of this may be due to the fact that it’s much easier to buy search advertising (think Google AdWords) than other types of online ads. But I think the primary reason is that search serves as a gateway to other Internet activity—so marketers wishing to drive traffic to their own Web sites need search advertising to make this happen.
The final, related factoid is that social media have grown from virtually nothing to nearly 20% of online time over the past few years. This matters because social media are an alternative gateway to finding Web content: instead of doing a search, I can ask my online community for information or recommendations. Thus, social media present a major threat to search advertising revenues. Although social media currently gather under 3% of online advertising, this will surely change as marketers work to find ways to exploit its potential. If you’ve been wondering why Google should be concerned about Twitter and Facebook, that’s your answer.
These shifts from offline to online advertising and from search to social media suggest a progression through four stages:
1. mass media, or broadcasting: this began in the late 19th century with the emergence of national brands and national print media. Today it is represented primarily by television. You can date TV-dominated era from, say, 1950 to 1985.
2. database marketing, or, more poetically, narrowcasting. This is about direct contact with segmented groups of customers. Date it from 1985 to 1997.
3. search marketing. This is characterized by use of search engines to drive traffic to Web sites. I’m being arbitrary but let's date it from 1998 to 2007.
4. social marketing. This is use of social media to connect with consumers. I’ll date it from 2008, although effective marketing uses of social media are just starting to emerge.
As each new medium has emerged over years, some portion of advertising dollars has shifted from the preexisting media. Of course, the old media don’t go away completely. Indeed, traditional mass media (including radio and print as well as TV) still account for the largest share of advertising spend.
The four media differ along several dimensions. These include:
- consumer engagement. Broadcast is the most passive medium; essentially, it’s yelling at people who may or may not be interested in the message. The audience in database marketing is still passive, but it's targeted at segments that marketers have some reason to believe are interested. With search marketing, the consumer takes a somewhat active role in deciding what to look for, even though the ads themselves are still placed by marketers. With social marketing, control is directly in the hands of consumers, who decide which messages they will receive.
- authority. I find this an intriguing concept. Basically it has to do with how consumers decide which messages they should believe. In the mass media, authority is essentially conferred – people believe things because they are "seen on TV" or have the "Good Housekeeping Seal of Approval". With database marketing, the medium (typically direct mail, more recently email or telephone) doesn’t itself confer much authority, so the message itself must command attention because it’s relevant to the consumer’s needs of the moment. This relevance motivates the recipient to actively explore the marketing offer and assess whether its source is credible.
In search marketing, the source of authority is implicitly based on the group itself: Google PageRank is largely determined by the number of links to a Web site – a version of “wisdom of the crowd”. With social marketing, group-based authority is explicit: consumers can see the number of followers, recommendations, reviews and other ratings provided by group members and decide whether to trust them.
- post-sale relationship. This defines the relationship between the marketer and consumer after the initial purchase. In the mass media world, the relationship barely exists: customers use the product and, hopefully, like it enough to buy it again. At most they ask for service if there’s a problem. With database marketing, post-sales contacts become important for cross-sell, upsell and retention. Indeed, this is where database marketing truly shines because it’s where rich data is available for targeting and relationship building.
Search marketing reaches a new level of engagement because customers can interact directly with the company Web site. This lets them initiate transactions, send messages, and in some cases actually change product configurations such as setting telephone features. With social marketing, consumers take direct control, initiating engagement themselves and, even more important, publicly sharing their engagements with other community members.
- marketing focus. This shows the critical task that marketers must master. With mass media, the primary marketing goal is selecting a message that builds a successful brand. For database marketers, the key skill is effective segmentation. Search marketing is primarily focused on developing content, both to attract traffic via organic search and to meet consumer needs once they appear at the site. For social marketing, the ultimate goal is convincing consumers to become brand advocates. Content is still important, of course, but its nature shifts from information that visitors consume to tools like widgets that empower them to share their enthusiasm with others.
The following table summarizes these dimensions.
| medium | consumer engagement | authority | post-sale relationship | marketing focus |
| mass media (broadcasting) | passively exposed | conferred | service / support | brand message |
| database marketing (narrowcasting) | targeted | relevance-based | cross sell / upsell / retention | segmentation |
| search marketing | activity-triggered | implicit group | Web self-service | content |
| social marketing | consumer-controlled | explicit group | public engagement | empowerment |
At the risk of stating the obvious, the table shows a steady increase in consumer empowerment from the passive receipt of mass marketing message to active control in social media. Because this is a fundamental change from traditional mass media marketing, it has several important implications:
- for each new medium, marketers must learn new skills.
- as marketers learn new skills, they will use the new medium more effectively.
- as marketers use the new medium more effectively, it will receive increasing portions of their ad budgets.
- since social media is very new, its share of advertising budgets will continue to grow for some time.
In short, social media matters not because it's cool, but because it offers marketers a new and more effective way to reach their consumers. Marketers who fail to master the required skills will fall behind marketers who do.
Thursday, September 03, 2009
Show Me the Numbers: Hard Data on Internet Use and Media Spend
Summary: Here are links to about twenty studies with statistics on online media consumption and advertising spend. Many are contradictory, but it's clear that marketers need to invest in social media, which might eventually replace search as the primary way that customers find them.
I’m sitting on a panel next week that will discuss long-term marketing trends. Naturally I have plenty of opinions on the topic, but just for fun I decided to scare up a few facts to reinforce them. This led to a highly entertaining, though uncompensated, scavenger hunt through the Web.
You won’t be surprised that there’s plenty of data out there. But I thought I’d share some of sources I found for answers to my basic questions, and perhaps a couple of insights I hadn’t quite considered before.
1. How are people actually spending their time online? And, in particular, are social media as important as industry gurus claim they are?
Probably the most comprehensive study along these lines was Global Faces and Networked Places, released by Neilsen in March 2009. This showed that as of December 2008, search was still the most common Internet activity (used by 85.9% of the online population), compared with just 65.1% for email. Social networks and blogs are the fastest growing application, now exceeding email with a participation rate of 66.8%.
Digging a little deeper within the social media category, the women’s blogger community BlogHer reported in its 2009 Women and Social Media Study that as of March 2009, 75% of women participated in social networks, compared with 55% who read blogs, 40% read message boards or forums, and 16% update status on platforms like Twitter. (The Twitter figures are surely much higher by now.) Nineteen percent actually publish their own blog while 29% comment on blogs. This reinforces (at least for women) the sense that social networks are rapidly emerging as the dominant Web activity.
Netpop Research reinforces this point in Media Shifts to Social, which found that as of September and October 2008, communications (including email, instant messaging, blogs and photo sharing) had risen to 32% of online time from 27% in 2006. Entertainment (games, videos, and “accessing Web sites for fun”) dropped from 49% to 20% in the same period. Sadly, the public materials don’t tell us where the rest of the time went. Netpop agreed with BlogHer’s general participation figures, reporting that 76% of American broadband users participate in social media (105 million of 133 million total).
By contrast, the Pew Internet & American Life Project Survey in December 2008 found only 35% of adult online Americans had a social media profile. Based on the other studies, this seems low – although a social media profile is a more restrictive requirement than the other definitions apply. Pew did find that 65% of American teens had profiles.
One drawback with these studies is that they only look whether people participate in different activities, not how much time they spend. The Online Publishers Association has tracked time since 2003 in conjunction with Nielsen. Its most recent report shows that in the past year, time spent on “community” applications like Facebook and Myspace has more than doubled from 8.8% to 18.5% of the total. (Blogs are also apparently part of “community”, although this isn't stated explicitly.) Since total time online has also expanded, time per visitor has grown even more.
Despite the growth of community, the OPA still shows content (40.6%) and communications (25.2) asl the dominant uses. Commerce (11.0%) and search (4.7%) account for the rest.
Looking at older OPA figures, which are available on MarketingCharts, the biggest change is the reduction in communications, which had a 46% share back in 2003. At that time, social networks were lumped into content, which had a 34% share. Today, the combination of content and community accounts for 59% of users’ time.
The position of blogs is ambiguous because most reports lump them in with other social media. Forrester’s just-published The Broad Reach Of Social Technologies contains a table, available in Josh Bernoff’s Groundswell blog, shows that social media “joiners” rose from 25% to 51% of the online population in the past two years, while content “spectators” (which includes blog readers) grow from 48% to 73%. But that’s pretty much the opposite of the BlogHer ratios mentioned earlier (55% blog readers vs. 75% social media participation). So the jury is still out.
Summary: What does it all mean? Here are my main observations:
- social media are indeed booming, but still account for a minority of online time. So even though marketers need to find ways to use social media for business purposes, they still have time to figure it out.
- everybody uses search, but they don’t spend much time on it. Search still earns the bulk of online advertising fees because it's a gateway to other content, and perhaps because it's the easiest Web advertising to buy and optimize. But its share may erode as social media provide alternative paths to desired content.
- blogs are probably growing more slowly than other social media, but they still account for a substantial portion of online activity. Marketers might be investing in blogs than they are really worth.
2. How does consumption of online media compare with consumption of other media?
Council for Research Excellence’s Video Consumer Mapping Study found more than five hours of TV watching per day (43% of total media time), vs. 80 minutes of Internet usage (10.7%). The Internet figure seems low, but this was a very careful and sophisticated study. These figures may only include the time when a medium had the consumer's primary attention -- so just having an instant message window open on your desktop wouldn't count.
Magazine Publishers Association reported the share of time with different media, although you have to read the table carefully because it reports minutes spent by of “users” of each medium rather than the average across all consumers. But the MPA also points to a study from MRI MediaDay (again published on Marketing Charts) showing the percentage of consumers using each medium. The combined figures show an average consumer spends about four and a half hours of TV per day (47.5% of total time) but only one and half hours of Internet (15.2% of total).
Incidentally, the MPA also argues that time alone isn’t the best measure of advertising value, since some media are more influential with their consumers than others. This is a point worth considering. The MPA bases this on Deloitte's State of the Media Democracy Survey, which unfortunately I couldn't find posted. The MPA provides other, related data in its 92-page guide Magazines: The Medium of Action.
A Forrester chart, posted on CNET shows five years of data on time spent per week with major media. The chart shows that Internet has more than doubled since 2004 and nearly caught up with TV. It reports about two hours per day with TV, accounting for about 34% of total time vs. 33% for Internet.
The Media Audit gives yet another set of statistics on time by medium. It also finds that TV is just slightly ahead of online, at 33% vs. 29% of time respectively. But it pegs TV viewing around three and a half hours per day.
Summary: These are serious conflicts, which I see no way to reconcile. Two studies show TV and Internet each accounting for about one-third of media time, while the other two show TV accounting for about 45% and Internet for 10-15%. The wide variations in estimated total time are also, um, noteworthy.
3. What is the share of ad spending for different media?
PriceWaterhouseCoopers and Wilkofsky Gruen Associates report in their Global Entertainment and Media Outlook: 2009-2013 (via eMarketer) that ad spending will total $170 billion this year, including $62 billion (36%) for TV and $25 billion (15%) for Internet and mobile.
Zenith Optimedia pretty much agrees: its October 2008 report shows U.S. spending at $179 billion for 2008, with a worldwide share of 37.5% for TV and 10.2% for the Internet.
On the other hand, the Direct Marketing Association shows spending at $339 billion total in 2008 including $75.9 billion (22.4%) for TV and $39.4 billion (11.6)%) for “new media and other”, which presumably includes Internet. The DMA also breaks out the portion of each medium used for direct response. It must have a pretty generous definition, since it puts 52.1% of the total in that category.
WPP’s groupm estimates in its Interaction: Addressable, Searchable, Social and Mobile study (via MarketingCharts) that interactive media’s share of total advertising is 14% in North America and 13% worldwide for 2008.
Summary: it’s hard to compare these figures, but everyone agrees that online spending is somewhere between 10-15% of the total, while TV gets 30% or more. Assuming that consumers spend about the same amount of time with both, and that advertising on both is equally effective, online media should get a larger share of ad budgets.
4. Where are marketers moving their budgets?
Forrester and Marketing Profs report B-to-B Marketing in 2009 shows that business marketers most commonly use their company Web site, email, public relations and trade shows. Another table from the same study, referenced by The Event Marketing Insider, shows marketers plan their greatest increases for the company Web site, search marketing, online video and Webinars.
A Forrester chart posted on Mashable shows interactive marketing spend by category, projected from 2009 to 2014. Search marketing accounts for about $15 billion of $25 billion total today and will grow 15% per year vs. 17% for the total. Mobile marketing and social media will grow faster, but will only expand from 4.4% in 2009 to 8% in 2014. Email marketing and display advertising account for the balance.
Online Marketing Blog surveyed marketers about their planned digital marketing channels in 2009. The top three were: blogging (34%), microblogging (Twitter) (29%) and Search engine optimization (28%).
Summary: marketers are moving their budgets online, primarily into the traditional channels (blogging, Web site, search).
4. Which media most affect purchase decisions?
Marketing Sherpa found buyers making complex purchases were relying more heavily on virtual events (Webinars, trade shows), search engines and Web sites, and less heavily on email, face-to-face trade shows, video programming and advertising.
Forrester (via ReadWriteWeb) found emails from friends, consumer reviews and search engines were the most trusted information sources, while personal blogs, company social networking profiles, and company blogs are least trusted.
TNS Media Intelligence in Digital World, Digital Life (via eMarketer) found that recommendations by friends, online news, newspapers and TV news were the most trusted information sources, while user forums, company brochures, free newspapers and private blogs were least trusted. Product comparison sites, industry Web sites and company Web sites were in the middle.
Summary: Marketers may be overspending on blogs and search. Social media could be a better investment -- if we could find a way to use them effectively.
I’m sitting on a panel next week that will discuss long-term marketing trends. Naturally I have plenty of opinions on the topic, but just for fun I decided to scare up a few facts to reinforce them. This led to a highly entertaining, though uncompensated, scavenger hunt through the Web.
You won’t be surprised that there’s plenty of data out there. But I thought I’d share some of sources I found for answers to my basic questions, and perhaps a couple of insights I hadn’t quite considered before.
1. How are people actually spending their time online? And, in particular, are social media as important as industry gurus claim they are?
Probably the most comprehensive study along these lines was Global Faces and Networked Places, released by Neilsen in March 2009. This showed that as of December 2008, search was still the most common Internet activity (used by 85.9% of the online population), compared with just 65.1% for email. Social networks and blogs are the fastest growing application, now exceeding email with a participation rate of 66.8%.
Digging a little deeper within the social media category, the women’s blogger community BlogHer reported in its 2009 Women and Social Media Study that as of March 2009, 75% of women participated in social networks, compared with 55% who read blogs, 40% read message boards or forums, and 16% update status on platforms like Twitter. (The Twitter figures are surely much higher by now.) Nineteen percent actually publish their own blog while 29% comment on blogs. This reinforces (at least for women) the sense that social networks are rapidly emerging as the dominant Web activity.
Netpop Research reinforces this point in Media Shifts to Social, which found that as of September and October 2008, communications (including email, instant messaging, blogs and photo sharing) had risen to 32% of online time from 27% in 2006. Entertainment (games, videos, and “accessing Web sites for fun”) dropped from 49% to 20% in the same period. Sadly, the public materials don’t tell us where the rest of the time went. Netpop agreed with BlogHer’s general participation figures, reporting that 76% of American broadband users participate in social media (105 million of 133 million total).
By contrast, the Pew Internet & American Life Project Survey in December 2008 found only 35% of adult online Americans had a social media profile. Based on the other studies, this seems low – although a social media profile is a more restrictive requirement than the other definitions apply. Pew did find that 65% of American teens had profiles.
One drawback with these studies is that they only look whether people participate in different activities, not how much time they spend. The Online Publishers Association has tracked time since 2003 in conjunction with Nielsen. Its most recent report shows that in the past year, time spent on “community” applications like Facebook and Myspace has more than doubled from 8.8% to 18.5% of the total. (Blogs are also apparently part of “community”, although this isn't stated explicitly.) Since total time online has also expanded, time per visitor has grown even more.
Despite the growth of community, the OPA still shows content (40.6%) and communications (25.2) asl the dominant uses. Commerce (11.0%) and search (4.7%) account for the rest.
Looking at older OPA figures, which are available on MarketingCharts, the biggest change is the reduction in communications, which had a 46% share back in 2003. At that time, social networks were lumped into content, which had a 34% share. Today, the combination of content and community accounts for 59% of users’ time.
The position of blogs is ambiguous because most reports lump them in with other social media. Forrester’s just-published The Broad Reach Of Social Technologies contains a table, available in Josh Bernoff’s Groundswell blog, shows that social media “joiners” rose from 25% to 51% of the online population in the past two years, while content “spectators” (which includes blog readers) grow from 48% to 73%. But that’s pretty much the opposite of the BlogHer ratios mentioned earlier (55% blog readers vs. 75% social media participation). So the jury is still out.
Summary: What does it all mean? Here are my main observations:
- social media are indeed booming, but still account for a minority of online time. So even though marketers need to find ways to use social media for business purposes, they still have time to figure it out.
- everybody uses search, but they don’t spend much time on it. Search still earns the bulk of online advertising fees because it's a gateway to other content, and perhaps because it's the easiest Web advertising to buy and optimize. But its share may erode as social media provide alternative paths to desired content.
- blogs are probably growing more slowly than other social media, but they still account for a substantial portion of online activity. Marketers might be investing in blogs than they are really worth.
2. How does consumption of online media compare with consumption of other media?
Council for Research Excellence’s Video Consumer Mapping Study found more than five hours of TV watching per day (43% of total media time), vs. 80 minutes of Internet usage (10.7%). The Internet figure seems low, but this was a very careful and sophisticated study. These figures may only include the time when a medium had the consumer's primary attention -- so just having an instant message window open on your desktop wouldn't count.
Magazine Publishers Association reported the share of time with different media, although you have to read the table carefully because it reports minutes spent by of “users” of each medium rather than the average across all consumers. But the MPA also points to a study from MRI MediaDay (again published on Marketing Charts) showing the percentage of consumers using each medium. The combined figures show an average consumer spends about four and a half hours of TV per day (47.5% of total time) but only one and half hours of Internet (15.2% of total).
Incidentally, the MPA also argues that time alone isn’t the best measure of advertising value, since some media are more influential with their consumers than others. This is a point worth considering. The MPA bases this on Deloitte's State of the Media Democracy Survey, which unfortunately I couldn't find posted. The MPA provides other, related data in its 92-page guide Magazines: The Medium of Action.
A Forrester chart, posted on CNET shows five years of data on time spent per week with major media. The chart shows that Internet has more than doubled since 2004 and nearly caught up with TV. It reports about two hours per day with TV, accounting for about 34% of total time vs. 33% for Internet.
The Media Audit gives yet another set of statistics on time by medium. It also finds that TV is just slightly ahead of online, at 33% vs. 29% of time respectively. But it pegs TV viewing around three and a half hours per day.
Summary: These are serious conflicts, which I see no way to reconcile. Two studies show TV and Internet each accounting for about one-third of media time, while the other two show TV accounting for about 45% and Internet for 10-15%. The wide variations in estimated total time are also, um, noteworthy.
3. What is the share of ad spending for different media?
PriceWaterhouseCoopers and Wilkofsky Gruen Associates report in their Global Entertainment and Media Outlook: 2009-2013 (via eMarketer) that ad spending will total $170 billion this year, including $62 billion (36%) for TV and $25 billion (15%) for Internet and mobile.
Zenith Optimedia pretty much agrees: its October 2008 report shows U.S. spending at $179 billion for 2008, with a worldwide share of 37.5% for TV and 10.2% for the Internet.
On the other hand, the Direct Marketing Association shows spending at $339 billion total in 2008 including $75.9 billion (22.4%) for TV and $39.4 billion (11.6)%) for “new media and other”, which presumably includes Internet. The DMA also breaks out the portion of each medium used for direct response. It must have a pretty generous definition, since it puts 52.1% of the total in that category.
WPP’s groupm estimates in its Interaction: Addressable, Searchable, Social and Mobile study (via MarketingCharts) that interactive media’s share of total advertising is 14% in North America and 13% worldwide for 2008.
Summary: it’s hard to compare these figures, but everyone agrees that online spending is somewhere between 10-15% of the total, while TV gets 30% or more. Assuming that consumers spend about the same amount of time with both, and that advertising on both is equally effective, online media should get a larger share of ad budgets.
4. Where are marketers moving their budgets?
Forrester and Marketing Profs report B-to-B Marketing in 2009 shows that business marketers most commonly use their company Web site, email, public relations and trade shows. Another table from the same study, referenced by The Event Marketing Insider, shows marketers plan their greatest increases for the company Web site, search marketing, online video and Webinars.
A Forrester chart posted on Mashable shows interactive marketing spend by category, projected from 2009 to 2014. Search marketing accounts for about $15 billion of $25 billion total today and will grow 15% per year vs. 17% for the total. Mobile marketing and social media will grow faster, but will only expand from 4.4% in 2009 to 8% in 2014. Email marketing and display advertising account for the balance.
Online Marketing Blog surveyed marketers about their planned digital marketing channels in 2009. The top three were: blogging (34%), microblogging (Twitter) (29%) and Search engine optimization (28%).
Summary: marketers are moving their budgets online, primarily into the traditional channels (blogging, Web site, search).
4. Which media most affect purchase decisions?
Marketing Sherpa found buyers making complex purchases were relying more heavily on virtual events (Webinars, trade shows), search engines and Web sites, and less heavily on email, face-to-face trade shows, video programming and advertising.
Forrester (via ReadWriteWeb) found emails from friends, consumer reviews and search engines were the most trusted information sources, while personal blogs, company social networking profiles, and company blogs are least trusted.
TNS Media Intelligence in Digital World, Digital Life (via eMarketer) found that recommendations by friends, online news, newspapers and TV news were the most trusted information sources, while user forums, company brochures, free newspapers and private blogs were least trusted. Product comparison sites, industry Web sites and company Web sites were in the middle.
Summary: Marketers may be overspending on blogs and search. Social media could be a better investment -- if we could find a way to use them effectively.
Tuesday, September 01, 2009
Net-Results Simplifies Demand Generation for Small Business
Summary: Net-Results is simpler to use than comparable demand generation systems because it applies the same features to many tasks. The system is aimed at small business but offers an interesting design lesson for everyone.
When Net-Results’ showed me their marketing automation system, the demonstration ended so quickly that I wondered what was missing. But on reflection I realized that Net-Results offers a full set of demand generation functions. The demonstration was short because the system uses only a few features to deliver them. In an industry where every competitor is striving for grater ease of use, stand-out simplicity is an impressive achievement.
The key to Net-Results’ approach is to build everything around segments. Email campaigns are targeted at segments; Web visitors are classified into segments; behavior alerts are triggered by segments; lead scores are assigned to segments; leads are sent to the sales system based on segments; reports are run against segments. This simplifies the system in two ways: marketers have fewer features to learn, and they can reuse their work across many functions.
Let’s run through the standard demand generation process to see how this works in practice. This process has five functions: send emails to prospects; capture responses on landing pages; score leads; send qualified leads to sales; and nurture non-qualified leads with multi-step campaigns.
Prospects enter Net-Results from external Web forms (more about that later), file imports, manual data entry, or Salesforce.com synchronization. They’re assigned to campaigns by defining entry conditions for campaign steps, which the system calls “actions”. These conditions are not themselves segments but can be copied from existing segment definitions or built with the standard segment-creation interface.
Campaigns can have multiple actions, each with its own entry conditions. Actions can be arranged hierarchically with several "children" attached to the same "parent". Each lead is assigned to the first "child" action whose entry conditions it meets. This allows leads to follow different paths within the same campaign.
The approach imposes some limits, since different branches cannot be reunited. But it will meet the needs for most marketers. Net-Results plans to remove the limits by allowing actions to send leads directly to other actions, within or across campaigns.
Users can also specify a waiting period between actions, and whether to send alerts when a lead qualifies for an action. The actions themselves can send an email, adjust a lead score, or send the lead to Salesforce.com. Since entry conditions can also accept leads into nurture campaigns, the Net-Results actions by themselves account for four of the five core demand generation functions.
The fifth core function, capturing Web response, is Net-Results’ main deviation from standard demand generation techniques. Nearly all demand generation systems let marketers create and deploy landing pages outside of the company Web site. Net-Results does not. Rather, it copies data captured on existing Web forms and posts it to the Net-Results database. This requires users to add a bit of Javascript to company Web pages.
Loading data from existing Web forms requires mapping the original form fields into the Net-Results databases. Net-Results makes this as simple as possible by reading field names on the existing form and suggesting Net-Results fields that are likely to match. Such mapping may sound a scary to serious technophobes, but it’s less work than building a form from scratch.
Net-Results argues that its approach avoids the “vendor lock-in” that comes from using forms hosted by the demand generation vendor. I guess that’s true, but doubt it’s important to most marketers. On the other hand, the Net-Results approach means marketers cannot create new forms without help from whoever runs the company Web site. This strikes me as a significant drawback, which other demand generation systems are expressly designed to avoid.
I wouldn’t be surprised to see Net-Results add a form builder fairly soon, although they didn’t say they were planning to. The system already has an email authoring tool, which includes a graphical editor and works from user-defined templates. Extending this to build Web forms should be pretty simple.
The Javascript tracking code also allows Net-Results to capture the behavior of Web visitors. This is another standard feature for demand generation systems. Here’s where segments reappear, since Web behavior can be used in segment definitions and system reports are run against segments.
Running reports against segments may not sound too exciting, but it greatly simplifies marketing analysis. Practical applications include reports to salespeople about their own accounts and reports on campaign results. Each report can run and emailed to specified users on a user-specified schedule. Reports include graphs as well as tabular data. The system's main reports all relate to Web behavior: visitors, traffic source, search terms, and pages viewed.
The Web visitor report is particularly impressive: it's almost a separate application, similar to the tools that other demand generation vendors use to give salespeople a view of Web activity. Users start with a list of visitors (within a segment, of course) showing key information including source, name, email address, telephone, company, most recent visit date, pages viewed, and visit duration. They can then select a lead and drill into the details of current and previous visits. They can also take actions including sending the lead to Salesforce.com and issuing an alert. Marketers could easily extend direct access to salespeople, since system security could restrict the salesperson to her own leads. An incremental user costs just $25 per month.
Net-Results can also issue automatic alerts, again based on entrance into a segment. Alerts can be directed to one or more email addresses and are summarized in a periodic report.
So what about building the segments themselves? There’s no truly easy way to define complex selections, but Net-Results does a reasonable job of balancing simplicity with power. Segments can have general attributes including security (specifying which user groups can access the segment), automatic exclusion of known Internet Service Providers (so reports can only show visitors from identifiable companies), automatic inclusion of only known contacts (to report only on previously-identified individuals), and parsing of “get” variables from the incoming Web address (to capture information passed within the URL). Treating these selections as attributes reduces the complexity of the segmentation statement itself.
Users build the segmentation statements by selecting data categories (visit activities, contact attributes, campaigns, lists, Web forms, traffic source) and then choosing attributes relevant to each category. For example, attributes for Web visits include pages visited and duration, while attributes for contacts include name, company and job title. Many vendors use a similar approach, which I consider the best method for helping non-technical users to create complex segmentations.
Users can group multiple criteria into blocks. All conditions within a block must be met for a lead to qualify; a lead must qualify for at least one block to qualify for the segment. (In more technical terms: the system uses "and" conditions within each block, and "or" conditions between blocks.) Although some subtle queries can’t be created with this approach, it should meet the vast majority of marketers’ needs. Few demand generation systems offer more power, and many offer less.
Once a segment is defined, users can view the records it selects to check that it works as intended. They can then save the segment and assign it to alerts or reports.
Is Net-Results really simpler than other demand generation systems? To some extent it depends on your definition. Net-Results supports many marketing functions with relatively few features. This is one type of simplicity. But different features tailored to different functions could, at least in theory, make other systems more efficient at each task. This is another kind of simplicity. In practice, I felt that Net-Results’ shared features were just as efficient as specialized features used in other systems. So, yes, I ultimately think Net-Results will be simpler for most users.
Net-Results’ drive for simplicity is based on its target market of small businesses. Many of its clients have just one marketer on staff. These people don’t have the time or resources to use a complicated system, and may not need the refinements, such as rule-driven dynamic content within emails, that Net-Results doesn't provide.
Pricing is also aimed at small businesses. [Note: the following is revised price information provided by the vendor as of December 2009.] Fees are based on a combination of page views, email volume, support hours and length of commitment. A client with 60,000 page views, 20,000 emails, and 5 hours of support would pay about $700 per month on a month-to-month basis and just over $600 for an annual agreement. Half of those numbers (30,000, 10,000, 2 hours) would run $400/$350 based on agreement length. The company reports its average billing per client is around $500 per month. No contract is required and Net-Results offers a 14 day free trial.
The Net-Results system was launched in April 2009 and the vendor says it now has “hundreds” of clients. Some have converted from a simpler predecessor product that was launched in 2006.
When Net-Results’ showed me their marketing automation system, the demonstration ended so quickly that I wondered what was missing. But on reflection I realized that Net-Results offers a full set of demand generation functions. The demonstration was short because the system uses only a few features to deliver them. In an industry where every competitor is striving for grater ease of use, stand-out simplicity is an impressive achievement.
The key to Net-Results’ approach is to build everything around segments. Email campaigns are targeted at segments; Web visitors are classified into segments; behavior alerts are triggered by segments; lead scores are assigned to segments; leads are sent to the sales system based on segments; reports are run against segments. This simplifies the system in two ways: marketers have fewer features to learn, and they can reuse their work across many functions.
Let’s run through the standard demand generation process to see how this works in practice. This process has five functions: send emails to prospects; capture responses on landing pages; score leads; send qualified leads to sales; and nurture non-qualified leads with multi-step campaigns.
Prospects enter Net-Results from external Web forms (more about that later), file imports, manual data entry, or Salesforce.com synchronization. They’re assigned to campaigns by defining entry conditions for campaign steps, which the system calls “actions”. These conditions are not themselves segments but can be copied from existing segment definitions or built with the standard segment-creation interface.
Campaigns can have multiple actions, each with its own entry conditions. Actions can be arranged hierarchically with several "children" attached to the same "parent". Each lead is assigned to the first "child" action whose entry conditions it meets. This allows leads to follow different paths within the same campaign.
The approach imposes some limits, since different branches cannot be reunited. But it will meet the needs for most marketers. Net-Results plans to remove the limits by allowing actions to send leads directly to other actions, within or across campaigns.
Users can also specify a waiting period between actions, and whether to send alerts when a lead qualifies for an action. The actions themselves can send an email, adjust a lead score, or send the lead to Salesforce.com. Since entry conditions can also accept leads into nurture campaigns, the Net-Results actions by themselves account for four of the five core demand generation functions.
The fifth core function, capturing Web response, is Net-Results’ main deviation from standard demand generation techniques. Nearly all demand generation systems let marketers create and deploy landing pages outside of the company Web site. Net-Results does not. Rather, it copies data captured on existing Web forms and posts it to the Net-Results database. This requires users to add a bit of Javascript to company Web pages.
Loading data from existing Web forms requires mapping the original form fields into the Net-Results databases. Net-Results makes this as simple as possible by reading field names on the existing form and suggesting Net-Results fields that are likely to match. Such mapping may sound a scary to serious technophobes, but it’s less work than building a form from scratch.
Net-Results argues that its approach avoids the “vendor lock-in” that comes from using forms hosted by the demand generation vendor. I guess that’s true, but doubt it’s important to most marketers. On the other hand, the Net-Results approach means marketers cannot create new forms without help from whoever runs the company Web site. This strikes me as a significant drawback, which other demand generation systems are expressly designed to avoid.
I wouldn’t be surprised to see Net-Results add a form builder fairly soon, although they didn’t say they were planning to. The system already has an email authoring tool, which includes a graphical editor and works from user-defined templates. Extending this to build Web forms should be pretty simple.
The Javascript tracking code also allows Net-Results to capture the behavior of Web visitors. This is another standard feature for demand generation systems. Here’s where segments reappear, since Web behavior can be used in segment definitions and system reports are run against segments.
Running reports against segments may not sound too exciting, but it greatly simplifies marketing analysis. Practical applications include reports to salespeople about their own accounts and reports on campaign results. Each report can run and emailed to specified users on a user-specified schedule. Reports include graphs as well as tabular data. The system's main reports all relate to Web behavior: visitors, traffic source, search terms, and pages viewed.
The Web visitor report is particularly impressive: it's almost a separate application, similar to the tools that other demand generation vendors use to give salespeople a view of Web activity. Users start with a list of visitors (within a segment, of course) showing key information including source, name, email address, telephone, company, most recent visit date, pages viewed, and visit duration. They can then select a lead and drill into the details of current and previous visits. They can also take actions including sending the lead to Salesforce.com and issuing an alert. Marketers could easily extend direct access to salespeople, since system security could restrict the salesperson to her own leads. An incremental user costs just $25 per month.
Net-Results can also issue automatic alerts, again based on entrance into a segment. Alerts can be directed to one or more email addresses and are summarized in a periodic report.
So what about building the segments themselves? There’s no truly easy way to define complex selections, but Net-Results does a reasonable job of balancing simplicity with power. Segments can have general attributes including security (specifying which user groups can access the segment), automatic exclusion of known Internet Service Providers (so reports can only show visitors from identifiable companies), automatic inclusion of only known contacts (to report only on previously-identified individuals), and parsing of “get” variables from the incoming Web address (to capture information passed within the URL). Treating these selections as attributes reduces the complexity of the segmentation statement itself.
Users build the segmentation statements by selecting data categories (visit activities, contact attributes, campaigns, lists, Web forms, traffic source) and then choosing attributes relevant to each category. For example, attributes for Web visits include pages visited and duration, while attributes for contacts include name, company and job title. Many vendors use a similar approach, which I consider the best method for helping non-technical users to create complex segmentations.
Users can group multiple criteria into blocks. All conditions within a block must be met for a lead to qualify; a lead must qualify for at least one block to qualify for the segment. (In more technical terms: the system uses "and" conditions within each block, and "or" conditions between blocks.) Although some subtle queries can’t be created with this approach, it should meet the vast majority of marketers’ needs. Few demand generation systems offer more power, and many offer less.
Once a segment is defined, users can view the records it selects to check that it works as intended. They can then save the segment and assign it to alerts or reports.
Is Net-Results really simpler than other demand generation systems? To some extent it depends on your definition. Net-Results supports many marketing functions with relatively few features. This is one type of simplicity. But different features tailored to different functions could, at least in theory, make other systems more efficient at each task. This is another kind of simplicity. In practice, I felt that Net-Results’ shared features were just as efficient as specialized features used in other systems. So, yes, I ultimately think Net-Results will be simpler for most users.
Net-Results’ drive for simplicity is based on its target market of small businesses. Many of its clients have just one marketer on staff. These people don’t have the time or resources to use a complicated system, and may not need the refinements, such as rule-driven dynamic content within emails, that Net-Results doesn't provide.
Pricing is also aimed at small businesses. [Note: the following is revised price information provided by the vendor as of December 2009.] Fees are based on a combination of page views, email volume, support hours and length of commitment. A client with 60,000 page views, 20,000 emails, and 5 hours of support would pay about $700 per month on a month-to-month basis and just over $600 for an annual agreement. Half of those numbers (30,000, 10,000, 2 hours) would run $400/$350 based on agreement length. The company reports its average billing per client is around $500 per month. No contract is required and Net-Results offers a 14 day free trial.
The Net-Results system was launched in April 2009 and the vendor says it now has “hundreds” of clients. Some have converted from a simpler predecessor product that was launched in 2006.