New Study, Same Results: Minority of Companies Do Effective Marketing Performance Measurement

The latest addition to my collection of surveys about marketing measurement is The Marketing Performance Advantage, a joint effort from strategic marketing consultants CMG Partners and market researcher Chadwick Martin Bailey. Based on 400 online interviews among CFOs, CEOs and marketing employees of companies with 100+ employees, this is one of the larger and more sophisticated studies on the topic.

One-Quarter of Companies Measure Marketing Performance Effectively

The main finding is that about one-quarter of marketers feel they do an adequate job of measurement. This matches other studies on the topic. The survey asked several questions along those lines:

- 20% say their company "excels" at measurement
- 22% "excel" at using measurement-based insights to drive improvement
- 24% see a positive impact from measurement, and
- 27% have fully integrated measurement into marketing planning

The study also resembled other research in showing that many more marketers list measurement as a top priority (44%) than actually do it.

Marketing VP's Are More Satisfied with Measurement Than Anyone Else

One intriguing detail was that senior marketers seem eerily "overconfident" (the authors' word) compared with those above and below them in the organization.

- 13% of marketing vice presidents consider marketing performance measurement a "huge challenge", compared with 34% to 38% of CEOs, marketing directors and marketing managers, and 61% of CFOs.

- 38% of marketing vice presidents felt that measurement has a "huge impact" on their business, compared with 15% to 29% of CEOs, marketing directors and marketing managers, and 7% of CFOs.

How well is your organization performing with respect to measuring the performance of marketing initiatives? How well are you using insights to improve the performance of marketing initiatives?

This is a huge challenge...	CEO	CFO	VP Marketing	Director Marketing	Manager Marketing
Measuring MP	36%	61%	13%	38%	34%
Improving MP	28%	61%	9%	38%	38%

To what extent, if at all, has measuring the performance of your marketing initiatives improved your business?

Impact of MP on your business	CEO	CFO	VP Marketing	Director Marketing	Manager Marketing
No impact	29%	52%	0%	21%	21%
Neutral	42%	41%	62%	64%	50%
Huge Impact	29%	7%	38%	15%	29%

Although the authors don't make the connection, these results help to explain why more money isn't invested in marketing measurement: the marketing vice presidents who control the purse strings are the least convinced they have a major problem.

Barriers to Measurement: Data, Technology and Process

The survey also asked about major barriers to marketing measurement. These include all the usual suspects. If anything, what was intriguing was that executive support is such a small issue compared with the others:

Barriers to improvement (% answers 1-4 on scale of 1-10):

- 40% collecting the right data
- 40% technology/systems
- 39% clear & effective processes
- 36% use of customer analytics
- 36% organizational alignment
- 26% skills sets
- 20% senior level buy-in

Effective Companies Have Clear Process to Apply Measurements, Invest in Measurement Capabilities and Hold Marketing Accountable for Results

Another set of questions covered adoption of best practices, and compared answers from companies reporting positive impact from marketing measurement with answers from the others. The biggest differences were in having clear processes to ensure that measurement-based insights are applied to decisions; the next tier included marketing targeted investments and holding marketing accountable for measured results. Senior level buy-in, strategic alignment and usage outside of marketing were less prominent.

Best practice adoption (index of use by companies reporting positive impact, where 100=average of all companies)

- 251 clear process to ensure measurements are applied to decisions
- 215 targeted investments in measurement technology/systems, skills and data
- 206 marketing held accountable on performance metrics
- 161 alignment of marketing activities to strategic business objectives
- 159 senior level buy-in
- 145 usage beyond marketing

eMarketer Report Details Next Steps for Online Brand Measurement

eMarketer recently released a deeply researched report on Online Brand Measurement. Since it touched on several topics I’ve been pondering recently (see Web Analytics Is Dead… on my Customer Experience Matrix blog) , I read it with particular care.

This is a long report (58 pages), so I won’t review it in detail. But here are what struck me as the critical points:

- Web measurement has largely focused on counting views and clicks, not measuring long-term brand impact. Counting is much easier but it doesn’t capture the full value of any Web advertisement. One result has been that marketers overspend on search ads, which are great at generating immediate response, and underspend on Web display ads which influence long term behavior even if they don’t generate as many click-throughs.

- Media buyers want Web publishers to provide the equivalent of Gross Rating Points (GRPs), so they can effectively compare Web ad buys with purchases in other media. That’s okay as far as it goes, but it’s still just about counting, not about measuring the quality or impact of the impressions. As the paper points out, even engagement measures such as time on site or mentions in social media, don’t necessarily equate to positive brand impact.

- Just about everyone agrees that the right way to measure brand impact is to tailor measurements to the goal of a particular marketing program. This may sound like a conflict with the desire for a standard GRP-like measure, but it really reflects the distinction between counting the audience and measuring impact. GRPs work fine for buying media but not for assessing results. Traditional media face precisely the same dichotomy, which is why marketing measurement is still a puzzle for them as well. And just as most offline brand measures are ultimately based on surveys and panels, I'd expect most online brand measures will be too.

- Meaningful impact measurement will integrate several data types, including online behaviors, visitor demographics, offline marketing activities and actual purchase behavior. These will come from a combination of direct online sources (i.e., traditional Web analytics), panel-based research and surveys (for audience and attitudinal information), and offline databases (for demographics and purchases). Ideally these would be meshed within marketing mix models and response attribution models that would estimate the incremental impact of each marketing program and allow optimization. But such sophisticated models won’t appear tomorrow.

To me, this final point is the most important because it points to a “grand unification theory” of marketing measurement that combines the existing distinct disciplines and sources. The paper cites numerous current efforts, including:

- multimedia databases being created (separately) by panel-based measurement firms including comScore, Nielsen, Quantcast and TNS Media Compete;

- Datatran Media’s Aperture, which combines email and postal addresses with Acxiom household data, IXI financial data, MindSet Marketing healthcare data and NextAction retail data;

- a joint effort between Omniture and WPP’s Kantar Group that combines data from email, search, display ads and traditional media;

- another Nielsen project combining TV ad effectiveness information from Nielsen IAG with panel purchase data from Nielsen Homescan.

These all reinforce the claim I made in last week’s blog post that individual data will increasingly be combined with panel- and survey-based information to provide community-level insights that are actually more valuable than individual data alone.

ANA Agency/Client Forum: Agency Performance Isn't Based on Results

I spent most of yesterday at the Association of National Advertisers (ANA)’s Agency/Client Forum. The agenda covered a range of timely topics including digital advertising and social media. But I think it’s fair to say that most of energy was focused on the pocketbook issue of agency compensation.

In particular, the question du jour was value-based compensation or its cousin, pay-for-performance. I would have thought those were pretty much the same thing, but as Coca Cola’s Director of Worldwide Media & Communication Operations Sarah Armstrong set out in a detailed description of Coke’s own process, value-based compensation works largely by estimating a reasonable cost in advance, while pay-for-performance is based on after-the-fact assessments. (Coke’s process incorporates both – a base fee that is intended cover agency costs, plus up to 30% bonus based on performance.)

However, as several speakers made clear during the day, most pay-for-performance measures are based on agency behaviors such as innovation, strategic thought and execution, rather than business results such as sales, market share or even communications activities such as media cost savings. Specifically, an ANA survey that will be formally released in mid-October found that 56% of agency performance measures were based on qualitative metrics, vs just 19% on business results and 25% on communications metrics.

My initial reaction to this survey was pretty dismissive – either you pay for results or you don’t. But the fundamental rationale, mentioned by several speakers through the day, is that business results are affected by many factors beyond the agency’s control, so it really wouldn’t be fair to penalized or reward them purely on that basis. The analyst in me says it’s still worth trying to isolate the agency's contribution to results, but this is definitely a valid point. So including the subjective measures does make more sense than I initially thought.

A related question that ran through several presentations was whether agencies are commodities. One presenter flashed a survey that showed 80% of respondents thought they are (I didn’t capture the details of that survey, but think it was an informal online poll, so it’s probably not very meaningful). But both the clients and agencies among conference speakers felt strongly that they are not.

What was interesting, though, was the sorts of distinguishing features that speakers cited – strategic insights, brand stewardship, creative genius, etc. Those are based largely on the skills and chemistry of the individuals working on an account. As the cliche says, those assets “go down the elevators every night” – that is, they are individuals rather than property of the agency itself. So it’s possible that the agencies themselves are pretty much commodities (i.e., have about the same processes and technology) even if their people are different.

And even when it comes to people, I find it hard to believe that any one agency can really have people who are on average much better than any other agency. There are, in fact, plenty of smart and creative people in the world. Yes, there are occasional true geniuses, and clients lucky enough to find them working on their accounts may indeed gain a strategic advantage. Perhaps some of those geniuses are even so clever that they can build an entire culture around themselves to leverage their skills. But I'd say that level of genius is very much the exception.

In general, then, I suspect that once a quality agency comes up to speed, it would produce roughly similar results to another quality agency. This doesn't mean that you could immediately switch from one to another. But over the long term, agencies probably are something close to a commodity.

This relates back to the performance measurement questions. The value of an agency really does lie in its strategic, creative, and execution contributions, plus its ability to work closely with the client. In theory, most agencies should be able to do these equally well. But in fact, there will be variations based on the individual team members as well as (to a lesser degree, I think) differences in agency processes and culture. So it makes sense for performance evaluations to focus on those factors, even though they’re subjective. Marketers must measure those factors to identify areas needing improvement, either by changing performance of their current agency partners or switching to new ones.

Mzinga Survey Shows Most Companies Don't Measure Social Media ROI

Toute le blogosphere is in love with social media, which of course means that some contrarians have to argue that it’s over-hyped. So it was interesting to see a survey (available here; registration required) show that social technologies are indeed widely adopted: 86% of 555 respondents said they are currently using them for business purposes, and 61% said it was an ongoing component of their business.

Caveat: the survey was sponsored by social technology vendor Mzinga in conjunction with the Babson Executive Education program, so they had a stake in the outcome. But I didn't see any obvious problems with it, and even allowing for some bias, the results still suggest wide social technology usage among a broad spectrum of businesses.

Probably the most interesting result from a marketing measurement perspective was that just 16% of respondents reported measuring ROI on their social media programs. No surprise, alas, but worrisome because programs that can’t prove ROI are subject to cancellation when money is tight.

Somewhat supporting this line of reasoning, the survey showed that just 40% of respondents had budget dedicated to social media and 57% had employees assigned to it. Perhaps many of those employees work for free, but a more likely explanation is that their costs are not part of project budgets because they're part of a vaguely fixed "overhead". This makes it easier to sustain a social media effort without formal economic justification. But it can’t be a permanent situation – managers will eventually realize that time spent on social media has a real cost. So justification of some sort will ultimately be needed.

Of course, that justification won’t necessarily be ROI. We all know that many traditional marketing investments are not justified on the basis of ROI, and marketing is by far the most common social media application (57%, vs 39% for internal collaboration, 31% other, 29% customer service & support, 25% sales, 21% human resources, 16% strategy and 14% product development). Marketing in social media could easily go unmeasured as well.

Indeed, just 8% of respondents said their social technology system could showcase ROI, vs. 41% who said it couldn’t. An impressively large 44% didn’t know, which I interpret to mean that they didn't care enough to find out. So I think it’s safe to say that ROI measurement hasn’t been a major priority.

The other intriguing figure in this survey was that 55% of respondents said there was no feature/function that they'd like added to their social media platform. REALLY? They can't be trying very hard: I mean, I can think of features I’d like added to a light bulb.*

If people are satisfied with their tools in such a rapidly evolving space, they probably aren’t using them for much. Or, to put it more charitably, maybe they recognize that they’re not taking advantage of what’s already available and feel they should master that before looking for anything more. Either way, this suggests that most deployments are quite immature.

One final factoid: 61% are integrating social media within their Web site or other sites, vs. 40% running standalone community sites and 39% deploying as social widgets in third party sites such as Facebook. I’m surprised that community sites and widgets are so popular. Maybe these are signs of experimentation. Anyway, it’s food for thought.

My general take, then: the survey shows wide testing of social technologies, but little deep engagement. Without a firm economic or other justification, there’s a good chance that the efforts won’t be sustained. So it’s up to social technology gurus, and vendors like Mzinga, to start demonstrating not just what social technology can do, but what makes it worth an investment.

__________________________________________
* How about an indicator that shows how long until it burns out? Preferably with a wireless Internet connection that alerts me when failure is imminent.

CMO Council Study: Customer Loyalty Is Fleeting

The CMO Council and Catalina Marketing’s Pointer Media Network recently released a major study on consumer loyalty in packaged goods brands. The study, Losing Loyalty: The Consumer Defection Dilemma™, draws on Catalina’s vast loyalty card transaction database to analyze the individual buying patterns of more than 32 million consumers in 2007 and 2008 across 685 leading CPG brands.

The bottom line is that “loyal” consumers are not as reliable as most of us might have guessed. “For the average brand in this study, 52% of highly loyal consumers in 2007 either reduced loyalty or completely defected from the brand in 2008.” You can download the 12 page report for details.

Not surprisingly, the report proposes to use individualized targeting services like Pointer Media Network to reduce churn by making carefully selected offers to at-risk consumers. Although the recommendation is obviously self-serving, I do think it’s correct.

But it seems to me that the implications are more fundamental. In the eternal debate about brand value, finding that loyalty evaporates more quickly than expected makes it even harder to justify marketing programs that don’t bring about an immediate, measurable return.

I’ve seen arguments (sorry, I can’t recall where) that the traditional buying model of awareness – interest – trial – purchase doesn’t correspond to reality. The survey results seem consistent with that position, in that they present consumer behavior as much less predictable than expected. This further reinforces the idea that investments with short-term results are more reliable than the long-term investments traditionally associated with brand building.

Pardon the cliche, but what we’re talking about here is a paradigm shift. If consumers don’t follow a predictable buying pattern, then brand value models based on such a pattern are not justifiable. Marketers need a fundamentally new framework to predict how their activities will affect consumer behavior. This framework may owe more to chaos theory than a linear process flow. I don’t know what they new model will look like, but recognizing that one is necessary is the first step towards creating it. If anybody out there has some candidates to offer, I’d love to hear about them.

Two More Surveys Confirm that Most Marketers Don't Track ROI

The Sales Lead Management Association and Velos Group published their annual lead management practices survey last week. (Read it here; free registration required.) The survy had a relatively small sample (just over 140 responses) and was weighted towards smaller companies (80% had fewer than 25 sales reps). But it still provides some insight into how many companies actually do business.

The key finding from a marketing measurement viewpoint was that 62.5% of respondents do not track ROI on marketing programs. This is not especially surprising; in fact, it’s better than the 76% reporting they do not use ROI another, larger study released last week by Lenskold Group. (Click here for the Lenskold study.) But it’s still bad news.

Perhaps even more distressing is that just 19.3% of the respondents listed their inability to track ROI as a major sales lead management concern. Subtracting those from the 62.5%, this means that more than 40% were not particularly concerned about their failure to track ROI. It MIGHT also mean that many of those 40% actually could track ROI if they wanted to, although it’s more likely that most don’t have the capability but don’t consider that a problem.

The other findings from the survey also generally confirm that dismal state of the art, at least among smaller firms.

- More than half the respondents (55.5%) said they do not qualify their marketing inquiries before sending them to sales. This implies a huge waste of time by salespeople who then do the qualifications themselves, or, more likely, cherry pick the leads that look superficially promising and ignore the rest. Unless a company has managed to staff its sales team with clairvoyants, this is a guarantee that it will discard some good leads and spend more than it should on some bad ones.

- One-third (33.8%) don’t use sales automation or customer relationship management systems. Again, this is fundamental efficiency-killer. The survey also found that companies using these systems were not terribly satisfied with the results: 54% rated their satisfaction at 5 or less on a scale of 1 to 10. Maybe the problem is with the software itself, but I suspect the issue is lack of training and other supporting investments.

- Half had no formal sales forecasting process (27.2%) or used Excel only (23.8%). Again, this shows very immature sales management at these companies.

I must say I find these results quite sad, given how long these tools have been available and how well their benefits are established.

But perhaps it’s best to adopt the more positive attitude of the survey authors and see this as an opportunity. As they put it, respondents “have a lot of room for improvement in their sales and marketing best practices. By spending time and resources in this critical business area, companies will be able to increase sales, allocate marketing resources more efficiently and will be able to forecast their sales more accurately. All of which will help them survive these difficult economic times.”

Whopper Freak-Out Wins Ad Effectiveness Award

I received a mailing with the agenda for the Association of National Advertisers' Marketing Accountability and Effectiveness Conference in New York on June 2. This looks like a good event, covering all the usual-but-useful bases: proving the value of marketing (Enterprise Rent-a-Car), earning a place at the "C-suite" table (panel led by Ernst & Young), advanced analytics (VG Corporation) and media optimization (Citizens Bank).

But my favorite is an "EFFIE" Award for Burger King, for its "Whopper Freak-out" campaign, which "explored deprivation to see what would happen if America's most beloved burger was removed from the menu forever without any announcement." Since I avoid both television and Burger King, this was news to me, but I gather a bunch of TV commercials were involved. Interesting.

Synonyms for "To Make Use Of"

This isn't really a blog post but I couldn't find another easy way to put the image below on the Web. It's from www.visualthesaurus.com, which is certainly something I'm happy to publicize a bit because it is indeed useful. This specific map addresses a problem I've had for years, which is finding a word to convey "making use of something". Typically I want to use "exploit" but that sounds rather harsh. This map has a number of alternatives.

Marketing Measurement Book Includes Free Online Forms

I'm not usually quite so self-promotional but suppose it's reasonable to announce final publication of my long-promised book The Marketing Measurement Toolkit. It's a step-by-step tutorial on the process of building a marketing measurement system, from initial project definition through deployment. The idea was to move beyond the theories (important as they are) to help people with the practical details. You can order from the publisher at www.racombooks.com.

My favorite feature of the book (especially since they didn't put my picture on the cover) is a collection of forms and scorecards that help people to organize their project and assess risk factors. I've put these online here where anyone can download them. Obviously they make more sense in the context of the book, but even without that I think they'll provide useful checklists at different project stages.

Here, for example, is an extract from the Analytics Readiness Scorecard in chapter 8. The extract covers only Response Measurement, while the full scorecard includes similar sections on Segmentation Models, Predictive Models, Marketing Mix Models, Simulation Models and Optimization Models. The idea is to figure out which types of analytics your company can build with its current resources, or, looking at it slightly differently, which resources it must add to do the analytics you want. Users enter a 1-5 score for the existing and needed columns, and the system then calculates a gap. This isn't intended to provide much more than conventional wisdom, but a big, well-organized pile of conventional wisdom can be very useful.

Analytics Readiness Scorecard
Response Measurement	existing	needed	gap	comment
source captured directly			0
contact history available			0
response survey available			0
pre/post analysis possible			0
test/control possible			0
multi-variate test possible			0
total	0	0	0

So, by all means, check out the forms and, if you're so inclined, purchase the book. Any comments are more than welcome.

Rate This Neutral: Scout Labs Social Media Monitoring is Definitely Cool, Possibly Accurate

Sure I like flashing lights and buzzers: what technologist doesn’t? And if a product has all that plus a low price, it’s darn near irresistible. So I was quite excited when I saw Scout Labs, a very nicely packaged social media monitoring tool that combines automated search, sentiment identification, importance ranking, trend reporting, alerts, bookmarking, and collaboration for under $300 per month. What’s not to like?

A couple things, it turns out. But let’s look at the good stuff first. Scout Labs’ combines three of the five social media measures I proposed last week (tracking mentions, identifying mentioners, measuring influence, understanding sentiment and measuring impact). Specifically, it searches blogs, news feeds, video and photo sites, Twitter and some social network sites (although not yet the big ones); provides influence measures; and classifies blog posts by sentiment. It doesn’t attempt to identify mentioners (i.e., track multiple posts by the same individual), or to measure the impact of an item on its audience. But three out of five is pretty good.

More important, the things that Scout Labs does, it does well. The search feature lets users specify multiple terms and whether each term is required, relevant or excluded. Once a search is defined, the system will automatically scan the top 12 million blogs for qualified entries, rate their sentiments as positive, negative or neutral, and show them in a list. Each item on the list shows the blog headline and phrases with the search terms highlighted. A side box shows common words in all the entries, ranked by frequency. This by itself gives a quick view of what’s being said about the search target.

Users can drill into the listed items to see the full entry, details about where it came from, how many external links attach to the item and its source, and the sentiment rating. They can manually revise the rating, bookmark the item with keywords, attach a note for discussion, and email a link with a system-generated summary and the user’s own comments to anyone the user chooses. The system currently uses the link counts as an influence measure, and can rank the items by influence or date. Scout Labs is working to upgrade its influence metric by integrating Web traffic data and a measure of the source’s relevance to the search topic.

But there’s more. The system can prepare graphs showing trends in volume, sentiment, and share of total blog mentions. Graphs can compare statistics for up to four different searches. Users can specify the date ranges to report on, currently going back up to three months and soon extending to six months.

Things are a little less exciting once you move beyond the blogosphere. The system will list search results for photo sites, video sites and Twitter, but doesn’t offer sentiment tracking or graphs. Scout Labs is working on adding sentiment tracking to Twitter comments. I guess it's not fair to ask them to measure sentiment for photos or videos.

As to pricing, the smallest Scout Labs plan allows five saved searches for $99 per month, although the company thinks expects most businesses will take plans for 25 or more searches, which start at $249 per month. There are no limits on the number of users or search hits in any plan and the system continuously updates the results of the saved searches.

So far so good. There's a free 30 day trial, so I set up two test searches in Scout Labs, each for a demand generation software vendor I track closely. The system found many of the posts I expected, and it was definitely fun and convenient to dig into them. If I worked at one of those firms, I would gladly pay $249 per month for this.

But then I ran the same searchs in IceRocket, a free tool that also does searches of blogs and other sources. IceRocket found nearly twice as many hits during the same time period, and they looked legitimate. Ouch. But Scout Labs acknowledges that its 12 million blogs don’t cover the entire blogsphere (over 100 million blogs, last I heard), and it does let you add feeds if one you want is missing. Plus IceRocket doesn’t support saved searches or do any of the other cool stuff. So I’m a little worried about coverage but still willing to pay Scout Labs’ fee.

Next I took a closer look at the sentiment ratings in the Scout Labs results. I didn’t expect them to be perfect, but was seriously disappointed. On one search, 32 of 39 items were labeled as neutral. Some of those were actually pretty positive, but, as Scout Labs explains in a recent blog post, they try to be conservative by labeling items as neutral unless the tone is clear. Fair enough. But the seven positive items were all pretty much neutral too. For example, several were help wanted postings that simply specified experience with the products in question. There were no items classified as negative, although one or two of the posts arguably could have been.

In the blog post I just mentioned, Scout Labs offers a detailed discussion of its sentiment rating technique. The gist is that they don’t just count “happy” and “sad” words, but semantically analyze each entry to understand which words relate to the search topic. Sounds good in theory. They also say their automated ratings agree with college-educated humans about 75% of the time. In comparison, they say, college-educated humans agree with each other about 85% of the time. (Clearly they are not talking about married couples.)

But if the vast majority of items are neutral, that’s less useful than it sounds. Remember the basic statistics: if 80% of the items are neutral, then a system that blindly ranks everything as neutral will be correct 80% of the time. The ratings that really count are the positives and negatives, and I wonder how often a human would agree with those ratings in Scout Labs. I’d want to look at that much more closely before deciding whether to rely on Scout Labs' results.

I'd still pay for Scout Labs for the convenience of the searches, statistics and collaboration tools. As I say, it's a very nice interface. I might even find on closer examination that the sentiment ratings are useful even if they’re only somewhat accurate: after all, they might still get a trend right and call up useful samples. But much as I like the bells and whistles, I’m not as enthusiastic about Scout Labs as when I started.

Vizu Measures the Brand Impact of Online Ads with Just One Question

I wrote last week about a general framework for measuring the marketing impact of social media. This proposed a general hierarchy of:

1. tracking mentions
2. identifying mentioners
3. measuring influence
4. understanding sentiment
5. measuring impact

As with all marketing measurement, the hardest task is the last one: measuring impact. This requires connecting the messages that people receive with their actual subsequent behavior, and hopefully establishing a causal relationship between the two. The fundamental problem is the separation between those two events: unless the message and purchase are part of the same interaction, you need some way to link the two events to the same person. A second problem is the difficulty of isolating the impact of a single event from all the other events that could influence someone’s behavior.

These problems are especially acute for brand advertising, which pretty much by definition is not connected with an immediate purchase. Brand advertisers have long dealt with this by imagining buyers moving through a sequence of stages before they make the actual purchase. A typical set of stages is awareness, interest, knowledge, trial (the first actual purchase) and regular use (repeat purchases).

Even though these stages exist only inside the customer’s head, they can be measured through surveys. So can more detailed attitudes towards a product such as feelings about value or specific attributes. For both types of measurement, marketers can define at least a loose connection between the survey results and eventual product purchases. Although the resulting predictions are far from precise, they offer a way to measure subtle factors, such as the impact of different advertising messages, that techniques based on actual purchases cannot.

The Internet is uniquely well suited for this type of survey-based analysis, since people can be asked the questions immediately after seeing an advertisement. One vendor that does this is Factor TG, which I wrote about last year (click here for the post.) Another, which I mentioned last week, is Vizu .

What makes Vizu different from other online brand advertising surveys is that each Vizu survey asks just one question. The question itself changes with each survey, and is based on the specific goal for the particular campaign. Thus, one survey might ask about awareness, while another might ask about purchase intentions. Vizu asks its question to a small sample of people who saw an advertisement and also to a control group of people who were shown something else. It assumes that the difference in answers between the two groups is the result of seeing the advertisement itself.

Although asking a single question may seem like a fairly trivial approach, it actually has some profound implications. The most important one is that it greatly increases response rate: Vizu founder Dan Beltramo told me participation can be upwards of 3 percent, compared with tenths or hundredths of a percent for longer traditional surveys.

This in turn means statistically significant survey results become available much sooner, giving marketers quick answers and letting them watch trends over relatively short time periods. It also provides significant results for much smaller ad campaigns or for panels within larger campaigns. This lets marketers compare results from different Web sites and for different versions of an ad, allowing them to fine tune their media selections and messages ways that traditional surveys cannot.

Another benefit of simplicity is lower costs. Vizu can charge just $5,000 to $10,000 per campaign, allowing marketers to use it on a regular basis rather than only for special projects. Vizu also has little impact on the performance of the Web sites running the surveys, reducing cost from the site owner's perspective.

The disadvantage of asking just one question is that you get just one answer. This prevents detailed analysis of results by audience segments, or exploration of how an ad affects multiple brand attributes. Vizu actually does provide a little information about the impact of frequency, drawn from cookies that track how often a given person has been exposed to a particular advertisement. Vizu also tracks where the person saw the ad, allowing some inferences about respondents based on the demographics of the host sites. Mostly, however, Vizu argues that a single answer is a good thing in itself because it keeps everyone involved focused on the ad campaign’s primary objective.

According to Beltramo, Vizu’s main customers are online ad networks and site publishers, who use the Vizu results as a way to show their accountability to ad agencies and brand advertisers. Some agencies and advertisers also contract with the firm directly.

What, you may be asking, has all this to do with social media measurement? Vizu’s approach applies not just to display advertising but also to social media projects such as downloadable widgets and micro sites.

Even though Vizu can’t fully bridge the measurement gap between exposure and actual purchases, it does offer more insights than simply counting downloads, clickthroughs or traffic. In a world where so little measurement is available, every improvement is welcome.

Tools for Social Media Measurement

I was whining last week on my other blog about the lack of integrated solutions for social media analytics. No sooner had I written that, of course, than up popped several interesting solutions to prove me wrong. I plan to write soon about a couple of specific products, but will use this post to set a framework for evaluation.

I suppose I should start with a definition of “social media”. By this I simply mean any communication method that allow users to interact directly with each other, as opposed to a broadcast medium where only a few people can send messages. I’m not intending to be especially restrictive here – I’d include blogs, public forums, Facebook , Myspace, YouTube , Flickr , Twitter, LinkedIn, Plaxo and many others. These all provide a huge stream of public chatter that marketers can tap into both to monitor what is being said about their products and to proactively spread their preferred messages.

From a measurement perspective, I see several distinct functions. Today, these are largely served by separate point solutions. Integrated systems are beginning to emerge that combine at least a few. The ultimate integrated system would service them all. The functions are:

- tracking mentions. This is the simplest goal; it simply means uncovering and reporting on social media events that relate to your product, brand or company. The fundamental tool here is the keyword search. Many systems do these, and some even combine different social network sources to provide a consolidated report. Google Alerts is probably the best known, although it doesn’t do much with social media aside from blogs. BoardTracker and Linqia are more focused on social communities.

- identifying mentioners. Most social media comments are signed with a user ID of some sort, but the identity of the person behind that ID is often not clear. I haven’t actually seen tools that address this, but they probably exist. What’s needed is to look at whatever public profile is available, use that to find out other information about the person, and then in turn see if you can find that person in other social media. As a not-too-scary example, I recently saw a Twitter post that mentioned a vendor I follow. Checking out the poster's profile to see if she was worth “following”, I saw that she was from a small town where I used to live. Curious, I then found her in Linked In and discovered the company she worked for. Yes, this sounds uncomfortably like stalking, but it’s old news that the Internet is really good for that. What’s interesting here is the potential to help understand background of an individual and her social media profile. The steps that I took could easily be automated; indeed, products like ZoomInfo do something similar, although so far as I can tell they don't include social media other than blogs.

- measuring influence. Influence has two overlapping dimensions: the influence of an individual mentioner, and the influence of a particular event. The mentioner’s influence is related to the profile I just mentioned, but also to blog readership, “friends” and network members in various social platforms, authority as measured by links and recommendations, etc. Again, these statistics are available in a scattered fashion for individual social media, and it wouldn’t be hard to build a system to pull them together once you had linked the user IDs. Surely someone is out there doing this but I haven’t tripped over them. Maybe if I spent more time at the gym?

Measuring the influence of a particular event is actually easier. It is a matter of links, views, downloads, recommendations, ratings, etc. The statistics are often published along with the item itself. One possible tool is TrackUr, a low-cost product (from $18 to $197 per month) that scores Web sites based on “the number of backlinks pointing to a web site, the number of blog discussions, an estimate of traffic, and even the number of times the web site has discussed the phrase in the past.” Another that I suspect costs much more is Radian6, which “tracks comments, viewership, user engagement and other metrics, 24/7, so that you can clearly see the reach and affect[sic] each post has on the community.” It also can “uncover the influencers online by topic, based on user-determined formula weightings.”

- understanding sentiment. This is the domain of semantic analysis (that’s a pun, kind of), which is a long-established field with many players. One specialist applying its technology to real-time Web content is Hapax. Solutions integrated more closely with social media search include Crimson Hexagon and newly-launched Scout Labs Scout Labs is also a low-cost option, with plans starting at $99 per month and currently offering 30-day free trial.

- measuring impact. Ah, the bottom line: what did people exposed to the social media event actually do? Even the Web hasn’t yet reached the stage of universal behavior tracking that would really let you answer this, and I personally hope it never does. But one product that gets close is Tealium Social Media, which builds a list of Web URLs (both social media and regular online media) related to your product, checks which of those your Web site visitors had seen previously, and pops the results into Google Analytics so you can treat the Web events like any other visitor source. (See my earlier blog post on Tealium for details.) At the other end of the process, Vizu lets marketers embed a question in Web ads that asks about the brand attitudes, and compares this against answers of people who didn’t see the ad, thereby measuring the net impact of the ad itself. The vendor has embedded its questions in social media applications from vendors including Lotame (ads in social networks), AdNectar (social ‘gifting’) and Buddy Media (custom social applications). See their press release for details.

When All Marketing is Internet Marketing, All Agencies are Internet Agencies

A little press notice this week reported a January 20 announcement from Ogilvy North America of “strategic alliances” with marketing automation software vendor Unica and marketing database integrator Pluris. On its face, this seemed to suggest a change in strategy for all three firms, moving towards a database marketing agency approach that combines technology, marketing strategy, data and analytics. But close reading of the press release shows this is just an agreement to make referrals. When I asked one of the players involved, they confirmed that’s all there is.

Nevertheless, the announcement prompted a little flurry of speculation in the Twittersphere / blogosphere (we need a new term -- blabosphere?) about changes in the role of traditional advertising agencies. Even though the database marketing agency model has been held a relatively small niche for decades (pioneers like Epsilon were founded in the late 1960’s), the thought seems to be that it will soon become the dominant model.

I’m skeptical. In some ways, the basic technologies for customer management have actually become more accessible to non-specialist companies. In particular, the hardest part, building a customer database, has largely been taken over by customer relationship management systems. Once that’s in place, it’s not much more work to add a serious marketing automation system. In fact, all you do is buy software like Unica’s—which is why a firm like Ogilvy doesn’t need to build its own, or to have a particularly intimate relationship with Unica itself. Yes, Ogilvy and other agencies need database marketing competencies. But all they really need to do is manage a firm like Acxiom doing the actual work. This takes expertise but much less capital and human investment than doing it yourself.

So, if database marketing has become easier, there is even less need than in the past for an integrated database marketing agency. Database marketing has remained a small part of the industry because its scope is too limited, particularly in dealing with non-customers (who mostly are not in your database). (Yes, the credit card industry is an exception.)

But the Internet is changing the equation substantially. Advertising agencies marginalized database marketing because customer management is not their core business. But advertising agencies exist to buy ads, and Internet advertising is now too important for them ignore. Plus, Internet advertising is much closer to agencies’ traditional core business of regular advertising, so it’s much easier for them to conceive it as a logical extension of their offerings. Even though many specialist agencies sprung up to handle early Internet advertising, the traditional agencies are now reasserting their control.

Now here’s the key point: managing Internet ads is not the same as managing traditional advertising. Ad agencies will develop new skills and methods for the Internet, and those skills and methods will eventually spread throughout the agency as a whole. Doing a good job at creating, buying and evaluating Internet advertising requires vastly more data and analysis than doing a good job at traditional mass media. It will take a while for the agencies to develop these skills and procedures, but these are smart people with ample resources who know their survival is at stake. They will keep working at it until they get it right.

Once that happens, those skills and methods won’t stop at the door of the Internet department. Agencies will recognize that the same skills and methods can be applied to other parts of their business, and frankly I expect that they’ll find themselves frustrated to be reminded how poorly traditional marketing has been measured. Equipped with new tools and enlightened by a vision of how truly modern marketing management, agency leaders will bring the rest of their business up to Internet marketing standards of measurement and accountability. It’s like any technology: once you’ve seen color TV, you won’t go back to black and white.

We’re already seeing hints of this in public relations, where the traditional near-total lack of performance measurement is rapidly being replaced by detailed analyses of the impact of individual placements. In fact, the public relations people are even pioneering quantification of social network impact, perhaps the trickiest of all Internet marketing measurement challenges.

So, yes, I do see a great change in the role of advertising agencies. I even expect they will resemble the integrated strategy, technology, analytics and data of today’s database marketing agencies. But it won’t happen because the ad agencies adopt a database marketing mindset. It will happen because they want to keep on making ads.

Razorfish Study Measures Direct Response to Social Media

I’ve been spending more time than I should recently on Twitter (follow me at @draab). It provides a fascinating peek into the communal stream-of-consciousness, which would be pretty horrifying (“Britney…Brad…Jen…Obama…groceries…Britney…Britney…Britney”) if you couldn’t choose the people and search terms you follow. This filtering (which I do via a great product called Tweetdeck) turns Twitter into a very efficient source of information I wouldn’t see otherwise.

Naturally, my interest in Twitter also extends to how you measure its business value, and by extension the value of social media in general. Since the people I follow on Twitter are both marketers and Twitter users, they discuss this fairly often. One recent post (technically a “tweet” but the term seems so childish) pointed to a study Social Media Measurement: Widgets and Applications by interactive marketing agency Razorfish.

The study turns out to be a very brief and straightforward presentation of two projects, both involving creation of downloadable widgets. One was promoted largely through conventional media and the other through widget distribution service Gigya. For each project, we’re told the costs, number of visitors and/or downloads, how much time and money they spent, and the return on investment. The not-very-surprising findings were that people who spent more time also spent more money and, more broadly, that “social media may be used effectively as a way of engaging users and potential customers.” A less predictable and potentially more significant finding from the first project was that people who were referred by a friend downloaded more often and spent much more money than people who were attracted by the media. The numbers were: downloads, 23% vs. 8%; spend any money, 9% vs. 1%; and amount spent, $23.00 vs $3.14. But the study points out that the numbers were very small—only 216 individuals arrived at the landing page as a result of a friend’s email, vs. 41,599 from media sources. These figures are drawn only from the first project because the second project couldn’t be measured this way.

From a marketing measurement standpoint, none of this seems break any new ground. Visitors are tracked by their source URLs and subsequent behavior is tracked through cookies. The ROI is calculated on straight revenue (it really should be profit) and seems to include only immediate purchases. This is particularly problematic for the second project, which promoted a $399 product with very limited supply that sold out in one minute. (The study doesn’t say, but based on this award citation it seems to be a special edition Nike Air Jordan shoe.) Clearly the point of such Air Jordan promotions isn’t immediate revenue, but brand building at its hard-to-measure best. The real challenge of evaluating social media is measuring this type of indirect impact. This study makes no claim to do that, but I’ll keep my eyes out for others that do.

Tealium Measures Response to Social Media

The Internet promises marketers an exquisite measurability: you can tell precisely where each Web site visitor came from, and what people from each source do after they arrive. But non-advertising media such as blogs, online news articles, YouTube, Facebook and Twitter are a blind spot because many references to a company don’t contain a clickable link. (Tealium, whose solution I’ll discuss shortly, put the figure at 80% in one study.) Without a link, users either must type the destination URL into their browser or find the site through a search engine. Either way, the visit is not associated with the original source. Therefore, marketers who want to know, say, how many site visits were prompted by a particular YouTube video have no direct way to find out.

Tealium, a developer of specialized Web analytics tools founded last year by veterans of WebSideStory/Visual Sciences, offers Tealium Social Media as a solution. It first builds a list of Internet references to a product, based on automated searches of sources such as Google News and Blogsearch, YouTube, Bloglines, Twitter, etc., plus any other RSS source you might have available. The system then checks whether visitors to a company Web site have previously visited one of these references by checking the cache of the visitor’s browser. If a match is found, the visit is attributed to that source.

I’m going to stop right here and say that this struck me as raising a significant privacy issue. I hadn’t really given the matter any thought but had assumed my browser history was private. But a Google search on "read browser history" shows that a method to check whether someone has visited a specified URL is widely known. This is what Tealium does and it isn’t as invasive as simply reading everything. More important, Tealium doesn't track individuals: rather, it reports how many people come from a given source. This is little different from conventional Web analytics, so I guess there is no particular privacy objection to the product. And, yes, you can always clear your browser cache or shorten the retention period. Quick show of hands: how many of you have actually done that? I thought so. End of sermon.

Tealium’s approach won’t be 100% accurate, since some people really do clean out their browser caches,. A few people will also access a site from a different computer or browser than the one where they saw the reference. Nor will Tealium capture referrals, such as an email I sent you with a product’s name after reading an article about it. But most of these problems apply to other Web analytics techniques, and on the whole the data should be accurate enough to be useful. It will certainly give a good measure of the relative power of different sources.

The system must also choose how to assign credit if the visitor’s cache contains more than one of the reference items. Tealium handles this by ranking the items on popularity and recency, and assigning the match to the highest ranked item. This seems reasonable.

Of course, Tealium can only measure Web-based activities. This almost goes without saying, but it's worth reminding ourselves every so often that there are still plenty of non-Web interactions taking place.

Tealium originally intended to present its social media results in a stand-alone interface. But the vendor decided a couple of months ago to instead feed them into existing Web analytics products, and Google Analytics in particular. This reduced the work Tealium had to perform (no reporting or data storage), hence lowering development and operating costs. From the client viewpoint, it integrates the social media results with other Web analytics, allowing direct comparisons between paid and unpaid media. In addition, downstream measures such as conversions or purchases automatically become available for the Tealium-derived sources. This was a very wise move.

What Tealium won’t provide is measures of sentiment, such as whether a particular social media reference was praise or criticism, of comments on particular subjects, or of changes in customer attitudes. Nor does it claim to. There are of course many other systems in this field; see last week’s post on reputation monitoring systems for a pointer to a detailed list.

Pricing of Social Media starts at $2,000 for implementation plus $250 per month with a one year contract. Price grows slightly as users add keywords and data feeds but is not related to actual traffic volume. The system has been in beta test with six clients until recently, and is being formally launched today.

Social Media is Tealium’s third product. The other two are WebToCRM, which captures Web visitor data and posts it to a CRM system, and Universal Tag, which lets a single page tag feed visitor data to multiple Web analytics systems.

Interesting Conference on Real Time Communications; Great List of Tools for Reputation Monitoring

I spent yesterday morning at a conference on “Real-Time Communications” presented by the Business Development Institute and sponsored by PR Newswire. Not surprisingly, given the sponsor, this turned out to be mostly by and for public relations professionals. This group’s main concern seemed to be reacting to public criticism, and “real time media” meant primarily blogging and Twitter. There was heavy representation from the pharmaceutical industry in particular, which, as several speakers mentioned with obvious frustration, is highly constrained by regulatory rules from making proactive comments. Beyond reacting to immediate crises, it seems the main media relations strategy of this group is to reach out to better educate the press about industry issues, so any reporting will be based on a reasonably accurate understanding of the situation. Apparently even this basic approach is somewhat revolutionary in the industry: keynote Ray Kerins of Pfizer said that until he took over as VP Worldwide Communications two years ago, the company policy was to simply ignore the first phone call from any reporter. Interesting attitude, that.

Kerins also provided perhaps the most intriguing factoid of the day, which was that 15,000 journalists lost their jobs in 2008. (I traced this figure to the Web site Paper Cuts , which tracks reports of newspaper layoffs and buyouts. Apparently the total includes all newspaper employees, not just newsroom staff. But either way, it’s a big number.) Kerins’ comment was that many of the people being let go are well-trained and experienced reporters, who provide “context and analysis”. They are being replaced in many cases by bloggers and other non-professional observers who offer “speed” but are often not as knowledgeable, thorough or objective. This is a big issue, particularly for someone in a complicated industry such as pharmaceuticals.

Another, related point came from Morgan Johnston, Corporate Communications Manager of JetBlue, who described a situation where a customer complained while at the airport to 10,000 online readers about not being compensated properly when her baggage didn’t show up—only to have it appear 15 minutes later. (I’m not clear whether this was on Twitter or a conventional blog.) His point was that the damage was done, even if she posted a follow-up message saying that all was well. The original complaint will live on more or less forever, and people may not notice the final resolution. The particular moral here was the need to respond very quickly to such complaints so the company’s reaction becomes part of the permanent record.

From my own perspective, I was struck by the focus on reacting to other people’s comments in real-time media, as opposed to using those media for a company’s own marketing programs. I suppose the outbound programs are run by marketing rather than public relations.

On the specific issue of marketing measurement, no one at the conference seemed to feel they could meaningfully measure the return on investment of blogging and other projects. From the reactive PR perspective, it’s largely about being defensive and preventing damage to reputation, so it’s probably something you can’t afford not to do. The very little discussion I heard about proactive programs mentioned that it’s occasionally possible to count the direct leads or revenue, but there isn’t much of a way to measure the long-term financial value. This matches my own observations, mostly because the impact of these programs is usually too small to isolate from other factors that also affect performance. There might however be non-financial measures that are more sensitive, like Web site traffic by source.

One very specific and highly valuable product of the conference was a casual remark by one panelist to look at a Web post by Dan Schawbel at Mashable.com for tools to measure brand reputation online. I tracked this down and found two extremely valuable posts, one describing free brand monitoring tools and another describing paid reputation monitoring tools (many of which are very inexpensive). There’s no point to my listing the products here, since you can just read the posts themselves. But this is very useful information – indeed, it made the whole morning worthwhile.