Gilligan on Data by Tim Wilson

Marketing Measurement and the Mississippi River

Tim Wilson — Mon, 26 Jul 2010 15:00:25 +0000

At least once a week in my role at Resource Interactive, I get asked some flavor of this basic question: “How do I measure the impact of my digital/social media investment?” It’s a fair question, but the answer (or, in some cases, the impetus for the question) is complicated and, often, is related to the frustration gap — the logical leap that, since digital marketing is the most measurable marketing medium of all time, it enables a near-perfect linkage between marketing investments and financial results.

It’s no fun to be the bearer of Reality Tidings when asked the question, especially when it’s easy to sound like the reason we can’t make a clean linkage is because it’s really hard or we just aren’t smart enough to do so. There are countless sharp, well-funded people in the marketing industry trying to answer this exact question, and, to date, there is a pretty strong consensus when you get a group of these people together:

We all wish we had “the answer”
The evolution of consumers and the growth of social media adoption has made “the answer” more elusive rather than less
“The answer” is not something that is just around the corner — we’re chipping away at the challenge, but the increasing fragmentation of consumer experiences, and the explosion of channels available for marketers to engage with those consumers, is constantly increasing the complexity of “the question”

That’s not an easy message to convey.

So, How’s That Explanation Working Out for Ya’?

It’s a tough row to hoe — not just being a data guy who expends a disproportionate amount of energy, time, and brainpower trying to find a clean way to come at this measurement, but trying to concisely explain the complexity. Of late, I’ve landed on an analogy that seems to hold up pretty well: measuring marketing is like measuring the Mississippi River.

If you are tasked with measuring the Mississippi, you can head to New Orleans, don hip waders, load up a rucksack with instruments, and measure all sorts of things at the river’s mouth: flow volume, fish count, contaminants, etc. That’s analogous to measuring a brand’s overall marketing results: brand awareness, share of voice in the industry, customer satisfaction, revenue, profitability, etc. The explosion of digital and social media actually makes some of this measurement easier and cheaper than ever before through the emergency of various online listening and social media analytics platforms.

While these “mouth of the river” measures are useful information — they are measures of the final outcome that really matters (both in the case of the Mississippi and brand marketing) — how actionable are they, really? As soon as results are reported, the obvious questions come: “But, what’s causing those results?”

What causes the Mississippi River to flow at a certain rate, with a certain number of a fish, with a certain level of a certain contaminant where it empties into the Gulf of Mexico? It’s the combination of all that is happening upstream…and the Mississippi’s headwaters reach from Montana (and even western Canada) all the way to Pennsylvania! The myriad headwaters come together many times over — they interact with each other just as different marketing channels interact with and amplify each other — in thousands of ways over time.

If we’re looking to make the Mississippi cleaner, we could travel to western Kansas and check the cleanliness of the Smoky Hill River. If it’s dirtier than we think it should be, we can work to clean it up. But, will that actually make the Mississippi noticeably cleaner? Logic tells us that it certainly can’t hurt! But, rational thought also tells us that that is just one small piece in an almost incomprehensibly puzzle.

With marketing, we have a comparably complex ecosystem at work. We can measure the growth of our Facebook page’s fans, but how is that interacting with our Twitter feed and our web site and our TV advertising and blog posts that reference us and reviews of our products on retailer sites and our banner ads and our SEO efforts and our affiliate programs and our competitors’ presence in all of these areas and… ugh! At a high level, a marketer’s Mississippi River looks like this:

Not only does each of the “managed tactics” represent dozens or even hundreds of individual activities, but environmental factors can be a Mack truck that dwarfs all of the careful planning and investment:

Cultural trends — do you really think that the Silly Bandz explosion was carefully orchestrated and planned by Silly Bandz marketers (the CEO of Silly Bandz certainly thinks so — I’m skeptical that there wasn’t a healthy dose of luck involved)
Economic factors — during a global recession, most businesses suffer, and successful marketing is often marketing that manages to simply help keep the company afloat
Competition — if you are a major oil producer, and one of the top players in your market inadvertently starts dumping an unfathomable amount of crude into the Gulf of Mexico, your brand begins to look better by comparison (although your industry as a whole suffers on the public perception front)

“It’s complicated” is something of an understatement when trying to accurately measure either the Mississippi River or marketing!

So, We Just Throw Up Our Hands and Give Up?

Just because we cannot practically achieve the Holy Grail of measurement doesn’t mean that we can’t be data driven or that we can’t quantify the impact of our investments — it just means that we have to take a structured, disciplined approach to the effort and accept (and embrace) that marketing measurement is both art and science. In the Mississippi River example, there are really three fundamentally different measurement approaches:

Measure the river where it flows into the Gulf of Mexico
Measure all (or many) of the tributaries that feed into each other and, ultimately, into the main river
Model the whole river system by gathering and crunching a lot of data

The first two approaches are reasonably straightforward. The third gets complex, expensive, and time-consuming.

For marketers — and I’m just going to focus on digital marketing here, as that’s complex enough! — we’ve got an analogous set of options (as it should be…or I wouldn’t be calling this an analogy!):

Measuring the direct and cross-channel effect of each tactic on the overall brand outcomes is nirvana — that’s what we’d like to be able to do in some reasonably reliable and straightforward way. And, we’d like that to be able to factor in offline tactics and even environmental factors. For now, the most promising approach is to use panel-based measurement for this — take a sufficiently large panel of volunteers (we’re talking 10s or 100s of thousands of people here) who voluntarily have their exposure to different media tracked, and then map that exposure to brand results: unaided recall of the brand, purchase intent, and even actual purchases. But, even to do this in an incomplete and crude fashion is currently an expensive proposition. That doesn’t mean it’s not an investment worth making — it just means it’s not practical in many, many situations.

However, we can combine the other two approaches — measurement of tactics (tactics include both always-on channels such as a Facebook page or a web site, as well as campaigns that may or may not cut across multiple channels) and measurement of brand results. The key here is to have clearly defined objectives at the brand level and to align your tactic-level measurement with those same objectives. I’m not going to spend time here expanding on clear definition of objectives, but if you’re looking for some interesting thinking there, take a look at John Lovett and Jeremiah Owyang’s white paper on social marketing analytics. They list four basic objectives that social media can support. At the overall brand level, I think there are basically eight possible objectives that a consumer brand might be tackling (with room for any brand to have one or two niche objectives that aren’t included in that list) — and, realistically, focusing in on about half that many is smart business. But I said I wasn’t going to expand on objectives…

What is important is to apply the same objectives at the brand and the tactic level — each tactic isn’t necessarily intended to drive all of the brand’s objectives, so being clear as to which objectives are not expected to be supported by a given tactic can help set appropriate expectations.

Just because the objectives should align between the tactic and the brand-level measurement does NOT mean that the measures used to track progress against each objective should be the same. For instance, if one of your objectives is to increase engagement with consumers, at the brand level, this may be measured by the volume and sentiment of conversations occurring online about the brand (online listening platforms enable this measurement in near real-time). For the brand’s Facebook page (a tactic), which shares the objective, the measure may, instead, be the number of comments and likes for content posted on the page.

But…How Does That Really Help?

By using objectives to align the measurement of tactics and the measurement of the brand, you wind up with a powerful performance measurement tool:

As simplistic and extreme examples, consider the situation where all of your tactics are performing swimmingly, but the brand overall is suffering. This might be the result of a Mack truck environmental factor — which, hopefully, you are well aware of because you are a savvy marketer and are paying attention to the environment in which you are operating. If not, then you should consider revisiting your overall strategy — do you have the wrong tactics in place to support the brand outcomes you hope to achieve?

On the other hand, consider a situation where the brand overall is suffering and the tactics as a whole are suffering. In that case, you might have a perfectly fine strategy, but your tactical execution is weak. The first order of business is to get the tactics clicking along as designed and see if the brand results improve (in a sense, this is a preferable situation, as it is generally easier to adjust and improve tactics than it is to overhaul a strategy).

In practice, we’re seldom working in a world where things are as black and white (or as green and red) as this conceptual scenario. But, it can certainly be the case that macro-level measurement of an objective — say, increasing brand awareness — is suffering while the individual tactics are performing fine. Let’s say you heavily invested in your Facebook page as the primary tactic to drive brand awareness. The page has been growing total fans and unique page views at a rapid clip, but your overall brand awareness is not changing. You may realize that you’re starting from a very small number of fans on Facebook, and your expectation that that tactic will heavily drive overall brand awareness is not realistic — you need to introduce additional tactics to really move the brand-level awareness needle.

In the End, It’s Art AND Science

Among marketing measurement practitioners, the phrase “it’s art and science” is oft-invoked. It sounds downright cliché…yet it is true and it’s something that many marketers struggle to come to terms with. Look at marketing strategy development and execution this way:

“The data” is never going to generate a strategy — knowing your customers, your company, your competition, and a bevy of other qualitative factors should all be included in the development or refinement of your strategy. Certainly, data can inform and influence the strategy, but it cannot generate a strategy on its own. Performance measurement, though, is all about science — at its best, it is the quantitative and objective measurement of progress towards a set of objectives through the tracking of pre-defined direct and proxy measures. Dashboards can identify trouble spots and can trigger alerts, but their root causes and remediation may or may not be determined from the data — qualitative knowledge and hypothesizing (“arts”) are often just as valuable as drilling deeper into the data.

It’s a fun world we live in — lots of data that can be very valuable and can drive both the efficiency and effectiveness of marketing investments. It just can’t quite deliver nirvana in an inexpensive, easy-to-use, web-based, real-time dashboard! Similar Posts:

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Post tags: brand measurement, Facebook, Mississippi River

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Hubspot: 2010 Facebook Page Marketing Guide

Tim Wilson — Tue, 29 Jun 2010 16:30:28 +0000

Hubspot released a new ebook a couple of weeks ago, compiled and edited by the Who’s Blogging What folk, with yours truly contributing the Facebook measurement chapter.

It’s behind a registration page, but it’s a good 30-page read. Topics covered include:

Creating a Facebook Page
Examples of Effective Pages
Six Ways to Get Found on Facebook
Getting People to “Like” Your Facebook Page
Developing Content/Inbound Marketing for Facebook
Leveraging Facebook for Ecommerce
Facebook’s Potential to Make Sales Become Viral
Analyzing Facebook Traffic

It was a fun little project to contribute to! Check it out!Similar Posts:

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Integrated View of Visitors = Multiple Data Sources

Tim Wilson — Tue, 22 Jun 2010 18:30:25 +0000

I attended the Foresee Results user summit last month, and John Lovett of Web Analytics Demystified was the keynote speaker. It’s a credit to my general lack of organization that I wasn’t aware he was going to be speaking, much less keynoting!

John showed this diagram when discussing the importance of recognizing your capabilities:

The diagram starts to get at the never-ending quest to obtain a “360 degree customer view.” A persistent misperception among marketers when it comes to web analytics is that behavioral data alone can provide a comprehensive view of the customer. It really can’t — force your customers to behave in convoluted ways and then only focus on behavioral data, and you can draw some crazily erroneous conclusions (“Our customers appear to visit our web site and then call us multiple times to resolve a single issue. They must like to have a lot of interactions with us!”).

Combining multiple data sources — behavioral and attitudinal — is important. As it happened, Larry Freed, the Foresee Results CEO, had a diagram that came at the same idea:

This diagram was titled “Analytics Maturity.” It’s true — slapping Google Analytics on your web site (behavioral data) is cheap and easy. It takes more effort to actually capture voice-of-the-customer (attitudinal) data; even if it’s with a “free” tool like iPerceptions 4Q, there is still more effort required to ensure that the data being captured is valid and to analyze any of the powerful open-ended feedback that such surveys provide. Integrating behavioral and attitudinal data from two sources is tricky enough, not to mention integrating that data with your e-mail, CRM, marketing automation, and ERP systems and third-party data sources that provide demographic data!

It’s a fun and challenging world we live in as analysts, isn’t it?

(On the completely off-topic front: I did snag 45 minutes one afternoon to walk around the University of Michigan campus a bit, as the conference was hosted at the Ross School of Business; a handful of pictures from that moseying is posted over on Flickr.)Similar Posts:

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From Data to Action — The Many Flavors of Latency

Tim Wilson — Wed, 09 Jun 2010 16:30:14 +0000

I was flipping through the slides from a workshop that Teradata put on at The Ohio State University several months ago, and one of the diagrams jumped out and resonated with me. As I did some digging, it turns out this diagram has been floating around since at least 2004, if not for longer. It was created by Dr. Richard Hackathorn of Bolder Technology Inc. (BTI).

There are a slew of lousy recreations of the diagram (the original diagram wasn’t so hot, either). Rather than recreating it myself, I just snagged one of the cleaner ones, which came from a 4-year-old TDWI article:

The point of the diagram, as well as of most of the derivative works that reference it, is that the value of information has a direct relationship to the speed with which you can react to it. And, there are three distinct things that have to happen between the business event that triggers the information and ation actually being taken.

I don’t know if there is any real math or science behind the shape of the curve. As diagrammed, this says that you’ve already lost most of your value by the time you get to the “decision latency” point in the process. I don’t know that that is necessarily true in most cases. The diagram supports the assertions by all of the various BI/data tool vendors that data needs to be available in near real-time (and, of course, that’s something that all of the vendors claim they are better at than their competition).

But, is the data latency and analysis latency really the big value driver for marketers? In some cases, the data latency is a structural issue — conducting a campaign where the people exposed to it are likely to not convert for anywhere from 1 to 30 days…means you really need to wait for 30 days to see how the campaign played out. Analysis latency is real…but this really can be broken into two pieces: 1) the time to do the analysis and get it packaged for delivery, and 2) the time to schedule/coordinate the information delivery. And, then, certainly the decision latency is real.

In short, the “action time” components totally make sense, and it’s good to understand them. The shape of the curve, though, doesn’t necessarily stand up to scrutiny when looked at through a marketer’s lens.Similar Posts:

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Monish Datta Learns All about Facebook Measurement

Tim Wilson — Thu, 03 Jun 2010 15:00:46 +0000

Columbus Web Analytics Wednesday was last week — sponsored by Omniture, an Adobe company, and the topic wound up being “Facebook Measurement” (deck at the end of this post).

For some reason, Monish Datta cropped up — prominently — in half of the pictures I took while floating around the room. In my never-ending quest to dominate SEO for searches for Monish, this was well-timed, as I’m falling in the rankings on that front. You’d think I’d be able to get some sort of cross-link from http://www.monishdatta.com/, but maybe that’s not to be.

We had another great turnout at the event, AND we had a first for a Columbus WAW: a door prize. Omniture provided a Flip video camera and a copy of Adobe Premier Elements 8 to one lucky winner. WAW co-organizer Dave Culbertson presented the prize to the lucky winner, Matt King of Quest Software:

Due to an unavoidable last minute schedule change, I wound up pinch-hitting as the speaker and talked about Facebook measurement. It’s been something I’ve spent a good chunk of time exploring and thinking about over the past six months, and it was a topic I was slated to speak on the following night in Toronto at an Omniture user group, so it wound up being a nice dry run in front of a live, but friendly crowd.

I made some subsequent updates to the deck (improvements!), but below is substantially the material I presented:

Facebook Measurement

View more presentations from Resource Interactive.

In June, Columbus Web Analytics Wednesday is actually going to happen in Cincinnati — we’re planning a road trip down and back for the event. We’re hoping for a good showing!Similar Posts:

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Post tags: Cincinnati, Facebook, Monish Datta, Omniture, WAW, WAW Columbus

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Web Analytics Wednesday: Columbus Meets Cincinnati in June

Tim Wilson — Wed, 02 Jun 2010 02:56:55 +0000

We’ve been talking about trying to pull this off for a while, but it looks like it’s going to finally happen!

We’re excited to announce that for June’s event, we’ll be bringing together the Columbus and Cincinnati Web Analytics Wednesday groups! Join us on Wednesday, June 23, 2010 on the roof of 720 E. Pete Rose Way in Cincinnati for Web Analytics Wednesday. This month’s event is sponsored by Bridge Worldwide, CRM Metrix, and Resource Interactive. Our guest speaker is Scott Beck, VP of Communications & Media – Kroger at dunnhumby. He’s also an Adjunct Professor in the Graduate School of the Williams College of Business at Xavier University.

If you’re planning to attend, here’s what you need to do:

Cincinnati residents — click over to the Cincinnati WAW event site and RSVP (Note: parking will be $5)
Columbus residents — click over to the meetup posted on the Techlife Columbus meetup.com site and RSVP there. You’ll be prompted as to whether you are driving yourself or interested in carpooling when you register. Then, click over to the Columbus WAW event site and register there as well. (I know it’s a pain, but we really need both systems to effectively coordinate in this case.)

And now, a word about our sponsors:

Bridge Worldwide

Bridge Worldwide is a top 50 digital and relationship marketing agency. Bridge is a recent Gold Lion winner at Cannes, and the company follows a belief in Marketing With Meaning. Clients include Procter & Gamble, Abbott, ConAgra Foods, Kroger, Luxottica, Johnson & Johnson and Red Bull. Bridge Worldwide has locations in Cincinnati and New York City, and is part of WPP, the world’s largest agency holding company with over 100,000 employees.

CRM Metrix

CRM Metrix offers a full range of digital market research solutions to help clients make the best decisions at all stages of the digital marketing development process and to maximize the return on their digital marketing investment. Their market research solutions are designed for all aspects of digital marketing such as brand website, online ads, online campaigns, email CRM programs, social media, widgets, blogs, online sponsorships, and micro sites. A global one-stop shop.

Resource Interactive

Resource Interactive is one of the nation’s top-rated agencies with offices in Columbus, Cincinnati, and Palo Alto and more than 300 associates. Founded and headquartered in Columbus, Ohio, their Midwestern work ethic keeps them grounded without limiting their global reach. Now in their 29th year, Resource leads Fortune 500 companies around the world through an ever-evolving internet economy. They bring research-driven insights to our work, creating bold opportunities for consumer engagement and competitive advantage

We’re hoping for a good turnout for the event — strengthening the web analytics, SEO, SEM, and digital marketing community that already exists between Cincinnati and Columbus.

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Answering the “Why doesn’t the data match?” Question

Tim Wilson — Tue, 18 May 2010 17:05:51 +0000

Anyone who has been working with web analytics for more than a week or two has inevitably asked or been asked to explain why two different numbers that “should” match don’t:

Banner ad clickthroughs reported by the ad server don’t match the clickthroughs reported by the web analytics tool
Visits reported by one web analytics tool don’t match visits reported by another web analytics tool running in parallel
Site registrations reported by the web analytics tool don’t match the number or registrations reported in the CRM system
Ecommerce revenue reported by the web analytics tool doesn’t match that reported from the enterprise data warehouse

In most cases, the “don’t match” means +/- 10% (or maybe +/- 15%). And, seasoned analysts have been rattling off all the reasons the numbers don’t match for years. Industry guru Brian Clifton has written (and kept current) the most comprehensive of white papers on the subject. It’s 19 pages of goodness, and Clifton notes:

If you are an agency with clients asking the same accuracy questions, or an in-house marketer/analyst struggling to reconcile data sources, this accuracy whitepaper will help you move forward. Feel free to distribute to clients/stakeholders.

It can be frustrating and depressing, though, to watch the eyes of the person who insisted on the “match” explanation glaze over as we try to explain the various nuances of capturing data from the internet. After a lengthy and patient explanation, there is a pause, and then the question: “Uh-huh. But…which number is right?” I mentally flip a coin and then respond either, “Both of them” or “Neither of them” depending on how the coin lands in my head. Clifton’s paper should be required reading for any web analyst. It’s important to understand where the data is coming from and why it’s not simple and perfect. But, that level of detail is more than most marketers can (or want to) digest.

After trying to educate clients on the under-the-hood details…I almost wind up at a point where I’m asked the “Well, which number is right?” question. That leads to a two-point explanation:

The differences aren’t really material
What matters in many, many cases is more the trend and change over time of the measure — not its perfect accuracy (as Webtrends has said for years: “The trends are more important than the actual numbers. Heck, we put ‘trend’ in our company name!”

This discussion, too, can have frustrating results.

I’ve been trying a different tactic entirely of late in these situations. I can’t say it’s been a slam dunk, but it’s had some level of results. The approach is to list out a handful of familiar situations where we get discrepant measures and are not bothered by it at all, and then use those to map back to the data that is being focussed on.

Here’s my list of examples:

Compare your watch to your computer clock to the time on your cell phone. Do they match? The pertinent quote, most often attributed to Mark Twain, is as follows: “A man with one watch knows what time it is; a man with two watches is never quite sure.” Even going to the NIST Official U.S. Time Clock will yield results that differ from your satellite-synched cell phone. Two (or more) measures of the time that seldom match up, and with which we’re comfortable with a 5-10 minute discrepancy.

Photo courtesy of alexkerhead

Your bathroom scale. You know you can weigh yourself as you get out of the shower first thing in the morning, but, by the time you get dressed, get to the doctor’s office, and step on the scale there, you will have “gained” 5-10 lbs. Your clothes are now on, you’ve eaten breakfast, and it’s a totally different scale, so you accept the difference. You don’t worry about how much of the difference comes from each of the contributing factors you identify. As long as you haven’t had a 20-lb swing since your last visit to the doctor, it’s immaterial.

Photo courtesy of dno1967

For accountants…”revenue.” If the person with whom your speaking has a finance or accounting background, there’s a good chance they’ve been asked to provide a revenue number at some point and had to drill down into the details: bookings or billings? GAAP-recognized revenue? And, within revenue, there are scads of nuances that can alter the numbers slightly…but almost always in non-material ways.

Photo courtesy of alancleaver_2000

Voting (recounts). In close elections, it’s common to have a recount. If the recount re-affirms the winner from the original count, then the results is accepted and moved on from. There isn’t a grand hullabaloo about why the recount numbers differed slightly from the original account. In really close races, where several recounts occur, the numbers always come back differently. And, no one knows which one is “right.” But, once there is a convergence as to the results, that is what gets accepted.

Photo courtesy of joebeone

That’s my list. Do you have examples that you use to explain why there’s more value in picking either number and interpreting it rather than obsessing about reconciling disparate numbers. I’m always looking for other analogies, though. Do you have any?

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Brand Listening and Response Platform Capabilities Survey

Tim Wilson — Thu, 29 Apr 2010 17:15:17 +0000

At Resource Interactive, our clients frequently ask us, “What social media tools do you recommend?” It’s a tricky question for a couple of reasons:

Every time we’re asked, the request seems to come from a client with an entirely unique set of social media “tool” needs
There are somewhere between an oodle and a gazillion social media tools out there (most of them less than a couple of years old) that bill themselves as some form of social media listening/moderation/response/management tool

The truth is, even if we dive into the first issue deeply, there are so many tools out there, and their capabilities blur and blend into each other so much, that it’s a monumental task to rattle off a solid short list of tools with any confidence.

As such, we’re conducting a broad assessment of social media monitoring and publishing platforms to determine an appropriate classification of tool types, understand the capabilities of the platforms that are available in each area, and identify platforms with whom we would like to engage in deeper discussions so we can make appropriate recommendations to our clients.

Who We’re Evaluating

We’re casting as broad a net as we can, ranging from focused channel-specific “management” tools all the way to broad “pick up the pulse of the ‘net” listening platforms. Jeremiah Owyang compiled a list of the former, while Marshall Sponder published a list of the latter late last year. And, at least once a week, we hear of a new tool or two that fits somewhere in this world. Our current list is at the end of this post.

Broad or Deep?

We’re aiming for this survey to be biased towards broader rather than deeper. As such, we’ve put together an online survey that should take ~15 minutes for a company to complete that covers eight main areas. We do not expect any single tool to cover all areas, but that’s part of the point of this exercise – we want to group these tools according to their core capabilities:

Targeted Listening – the ability to monitor conversations occurring in specific places where a brand may have a presence online, such as a Facebook fan page, a specific Twitter account, or a specific web site
Broad Listening – the ability to comprehensively monitor conversations and content posted across the internet (with filter/query configuration narrowing down the content being monitored based on keywords or other criteria)
Listening Features – the specific capabilities and analysis that the tool performs in an automated fashion (sentiment, keyword-based tagging, etc.)
Publishing Targets – the ability to publish content from within the tool to various social media targets
Publishing Features – the specific capabilities available for publishing content (scheduling, preview, approval workflow, etc.)
Brand Response – the ability to react/respond to specific comments, tweets, or posts that are identified through the targeted listening described earlier
Analytics – the ability to provide dashboards and reports
Pricing Options – the different pricing models available for the tool (not specific costs – just how their pricing works)

Response Solicitation

As a first cut, we’re looking to spread the word of this effort via social media itself. Ideally, some of the tools (the “broad listening”-oriented ones) will pick up the mentions of this survey (for the smaller tools, I would expect even a Google Alert would pick this post up for them). So, please, help us get the word out, and leave a comment if you spot any tools missing from our list.

If you are a company that has a platform in this list (or one that isn’t in this list but that we should include), ping me on Twitter at @tgwilson (if you follow me, I’ll follow back within 24 hours and we can DM). Or, you can take the “g” out of my Twitter username and tack “@resource.com” on the end of it to go old-school and shoot me an e-mail. I’ll send you a link to the online survey (we’re not publishing the link so that we can make sure that only official company representatives respond for their products).

Tools List

Below is the list of tools we’re hoping to include:

Stay tuned!Similar Posts:

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Post tags: brand listening, moderation, SMMS, social media monitoring

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Digital Measurement and the Frustration Gap

Tim Wilson — Fri, 09 Apr 2010 15:10:48 +0000

Earlier this week, I attended the Digital Media Measurement and Pricing Summit put on by The Strategy Institute and walked away with some real clarity about some realities of online marketing measurement. The conference, which was relatively small (less than 100 attendees) had a top-notch line-up, with presenters and panelists representing senior leadership at first-rate agencies such as Crispin Porter + Bogusky, and Razorfish, major digital-based consumer services such as Facebook and TiVo, major audience measurement services such as comScore and Nielsen, and major brands such as Alberto Culver and Unilever. Of course, having a couple of vocal and engaged attendees from Resource Interactive really helped make the conference a success as well!

I’ll be writing a series of posts with my key takeaways from the conference, as there were a number of distinct themes and some very specific “ahas” that are interrelated but would make for an unduly long post for me to write up all at once, much less for you to read!

The Frustration Gap

One recurring theme both during the panel sessions and my discussions with other attendees is what I’m going to call The Digital Measurement Frustration Gap. Being at an agency, and especially being at an agency with a lot of consumer packaged goods (CPG) clients, I’m constantly being asked to demonstrate the “ROI of digital” or to “quantify the impact of social media.” We do a lot of measurement, and we do it well, and it drives both the efficient and effective use of our clients’ resources…but it’s seldom what is in the mind’s eye of our clients or our internal client services team when they ask us to “show the ROI.” It falls short.

This post is about what I think is going on (with some gross oversimplification) which was an observation that was actively confirmed by both panelists and attendees.

Online Marketing Is Highly Measurable

When the internet arrived, one of the highly touted benefits to marketers was that it was a medium that is so much more measurable than traditional media such as TV, print, and radio. That’s true. Even the earliest web analytics tools provided much more accurate information about visitors to web sites – how many people came, where they came from, what pages they visited, and so on – than television, print, or radio could offer. On a “measurability” spectrum ranging from “not measurable at all” to “perfectly measurable” (and lumping all offline channels together while also lumping all online channels together for the sake of simplicity), offline versus online marketing looks something like this:

Online marketing is wildly more measurable than offline marketing. With marketers viewing the world through their lens of experience – all grounded in the history of offline marketing – the promise of improved measurability is exciting. They know and understand the limitations of measuring the impact of offline marketing. There have been decades of research and methodology development to make measurement of offline marketing as good as it possibly can be, which has led to marketing mix modeling (MMM), the acceptance of GRPs and circulation as a good way to measure reach, and so on. These are still relatively blunt instruments, and they require accepting assumptions of scale: using massive investments in certain campaigns and media and then assessing the revenue lift allows the development of models that work on a much smaller scale.

The High Bar of Expectation

Online (correctly) promised more. Much more. The problem is that “much more” actually wound up setting an expectation of “close to perfect:”

This isn’t a realistic expectation. While online marketing is much more measurable, it’s still marketing – it’s the art and science of influencing the behavior of human beings, who are messy, messy machines. While the adage that it requires, on average, seven exposures to a brand or product before a consumer actually makes a purchase decision may or may not be accurate, it is certainly true that it is rare for a single exposure to a single message in a single marketing tactic to move a significant number of consumers from complete unawareness to purchase.

So, while online marketing is much more measurable than offline marketing, it really shines at measurement of the individual tactic (including tracking of a single consumer across multiple interactions with that tactic, such as a web site). Tracking all of the interactions a consumer has with a brand – both online and offline – that influence their decision to purchase remains very, very difficult. Technically, it’s not really all that complex to do this…if we just go to an Orwellian world where every person’s action is closely tracked and monitored across channels and where that data is provided directly to marketers.

We, as consumers, are not comfortable with that idea (with good reason!). We’re willing to let you remember our login information and even to drop cookies on our computers (in some cases) because we can see that that makes for a better experience the next time we come to your site. But, we shy away from being tracked – and tracked across channels – just so marketers are better equipped to know which of our buttons to push to most effectively influence our behavior. The internet is more measurable…but it’s also a medium where consumers expect a decent level of anonymity and control.

The Frustration Gap

So, compare the expectation of online measurement to the reality, and it’s clear why marketers are frustrated:

Marketers are used to offline measurement capabilities, and they understand the technical mechanics of how consumers take in offline content, so they expect what they get, for the most part.

Online, though, there is a lot more complexity as to what bits and bytes get pushed where and when, and how they can be linked together, as well as how they can be linked to offline activity, to truly measure the impact of digital marketing tactics. And, the emergence and evolution of social media has added a slew of new “interactions with or about the brand” that consumers can have in places that are significantly less measurable than traffic to their web sites.

Consumer packaged goods struggle mightily with this gap. Brad Smallwood, from Facebook, , showed two charts that every digital creative agency and digital media agency gnashes their teeth over on a daily basis:

A chart that shows the dramatic growth in the amount of time that consumers are spending online rather than offline
A chart that shows how digital marketing remains a relatively small part of marketing’s budget

Why, oh why, are brands willing to spend millions of dollars on TV advertising (in a world where a substantial and increasing number of consumers are watching TV through a time-shifting medium such as DVR or TiVo) without batting an eye, but they struggle to justify spending a couple hundred thousand dollars on an online campaign. “Prove to us that we’re going to get a higher return if we spend dollars online than if we spend them on this TV ad,” they say. There’s a comfort level with the status quo – TV advertising “works” both because it’s been in use for half a century and because it’s been “proven” to work through MMM and anecdotes.

So, the frustration gap cuts two ways: traditional marketers are frustrated that online marketing has not delivered the nirvana of perfect ROI calculation, while digital marketers are frustrated that traditional marketers are willing to pour millions of dollars into a medium that everyone agrees is less measureable, while holding online marketing to an impossible standard before loosening the purse strings.

My prediction: the measurement of online will get better at the same time that traditional marketers lower their expectations, which will slowly close the frustration gap. The gap won’t be closed in 2010, and it won’t even close much in 2011 – it’s going to be a multi-year evolution, and, during those years, the capabilities of online and the ways consumers interact with brands and each other will continue to evolve. That evolution will introduce whole new channels that are “more measurable” than what we have today, but that still are not perfectly measurable. We’ll have a whole new frustration gap!Similar Posts:

© Tim for Gilligan on Data by Tim Wilson, 2010. | Permalink | One comment | Add to del.icio.us
Post tags: Alberto Culver, comScore, Crispin Porter + Bogusky, Digital Media Measurement and Pricing, Facebook, frustration, Nielsen, Razorfish, Resource Interactive, The Strategy Institute, TiVo, Unilever

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Columbus Web Analytics Wednesday Recap: Don’t “Antisappoint” Visitors

Tim Wilson — Mon, 29 Mar 2010 14:20:48 +0000

We had a fantastic Web Analytics Wednesday last week in Columbus, sponsored by (Adobe) Omniture, with just under 50 attendees! Darren “DJ” Johnson was the presenter, and he spoke about web site optimization (kicking off with a riff of how “optimization” is an over-used word!). I, unfortunately, forgot my “good” camera, which means my photojournalism duties were poorly, poorly performed (DJ is neither 8′ tall, nor was he ignoring his entire audience):

One of the anecdotes that stuck with me was when DJ explained a personal experience he had clicking through on a banner ad (“I NEVER click on banner ads!” he exclaimed) and then having the landing page experience totally under-deliver on the promise of the ad. He used the term “antisappointment” (or “anticappointment?”) to describe the experience. It’s a handy word that works better orally than written down, but I’ll be shocked with myself if I don’t start using it!

I’ve been spending more and more time thinking about and working on optimization strategies of late, and DJ’s presentation really brought it all together. This post isn’t going to be a lengthy explanation of optimization and testing…because I’m really not qualified to expound on the subject (yet). But, I will drop down a few takeaways from DJ’s presentation that hit home the most with me:

Testing (and targeting) doesn’t typically deliver dramatic step function improvements, so don’t expect it to — it delivers incremental improvements over time that can add up to significant gains
(Because of the above) Testing isn’t a project; it’s a process — it’s not enough to plan out a test, run it, and evaluate the results; rather, it’s important to develop the organizational capabilities to always be testing
“Testing” without “targeting” is going to deliver limited results — while initial tests may be on “all visitors to the site,” it’s important to start segmenting traffic and testing different content at the segment level as quickly as possible

Good stuff.

In other news, I’ve got a few additional bullet points:

Our next Web Analytics Wednesday is tentatively slated to be a happy hour only (unsponsored or with a limited sponsor) on a Tuesday. If you don’t already get e-mail reminders and you’d like to, just drop me a note and I’ll add you to our list (tim at this domain)
The Ohio Interactive Awards are fast approaching! This event, started up by Teambuilder Search, huber+co. interactive, and 247Interactive, is shaping up to be a great event on April 29th at the Arena Grand Movie Theater (Resource Interactive is sponsoring the event happy hour)
The TechLife Columbus meetup.com group continues to grow and thrive, with over 1,500 members now — it’s free, and it’s a great way to find meetups and people who are involved in high tech and digital in central Ohio

It’s been a lot of fun to watch social media get put to use in central Ohio and make it so easy to find interesting people with shared interests. I’ve certainly gotten to know some great people over the past couple of years with a relatively low investment of my time and energy, and I’m a better person for it!Similar Posts:

© Tim for Gilligan on Data by Tim Wilson, 2010. | Permalink | No comment | Add to del.icio.us
Post tags: Adobe, Omniture, optimization, WAW, WAW Columbus

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