Dynamic Logic Announces New Partnership with IRI and Introduces New Solution To Integrate the Branding and Sales Effects of Digital Ad Campaigns Findings from Pilot “AdIndex Connects with IRI” Study Demonstrate the Power of Bringing Together Attitudinal Insights and Purchase Data January 7, 2010
Posted by Mark Blei in : Dynamic Logic Press Release, General announcments, industry news , add a commentDynamic Logic Launches Optimization Tool, Delivering Real-Time View of Online Ad Campaign Performance
“Adometer” Gauges Initial Breakthrough, Enabling Creative and Media Changes to Be Made While Campaigns Are Still Live
New York, November 19, 2009 — Millward Brown’s Dynamic Logic, the leader in measuring digital advertising effectiveness, announced today the launch of Adometer™, an optimization tool that gives advertisers an early indication of a campaign’s performance. The tool is based on real-time measures of “breakthrough” including how memorable an ad is and whether the target audience is being reached. Adometer’s attitudinal measures offer an alternative or enhancement to traditional online tools that optimize based on click-through or lead generation alone, which can often provide a misleading picture of a branding campaign’s true impact.
“With Adometer, clients now have a reliable decision-support tool for making creative or media changes while a campaign is still live,” says Michelle Eule, Managing Director, AdIndex Solutions for Dynamic Logic. “While many factors play a role in campaign effectiveness, breakthrough is critical, especially when brand-building is an objective. By providing a real-time indication of whether or not a campaign is breaking through, advertisers can make necessary changes early on, before impressions are wasted.”
Adometer works by launching a short survey that appears directly within the frame of an advertisement. Results, which are delivered in an easy-to-use online interface, can be filtered by target audience or other audience segments, providing more granular insights over other solutions that offer single-question surveys. Below are examples of the types of actionable insights Adometer provides:
- Dynamic Logic Adometer Sample Output (click for larger view)
“In many ways, clients have their hand on the optimization trigger, so to speak, and they are looking for a reliable tool that can either confirm their advertising is working, or give them the insight to know what to change,” commented Jean Robinson, President of Dynamic Logic. “We believe Adometer will be a welcome addition to the market.”
Adometer can be used as a complement to Dynamic Logic’s more thorough, in-market measurement solutions. For more information, email sales@dynamiclogic.com.
Read a great article today on pharma and digital advertising . July 20, 2009
Posted by markblei in : industry news , add a commentDigital Media Buzz Had this great piece written by Rebecca Jacoby on how and why pharma companies are being moved into adapting to digital .
Quotes Brian Bass president of Bass Advertising and Marketing.
Characteristically, intranet access occurs via password and activity is monitored to keep tentacles from tangling, rules in place and operations fluid. Intrinsically, a pharmaceutical company’s intranet potentially tracks digital projects great and small while rendering a consistent hum of daily inter-office employee communications, schedules, announcementsetc..
Bass also goes onto say
Right now,, a tremendous amount of digital activity concerns sales training, with a thrust toward engaging learning as a positive process. “It is groundbreaking for Pharma because it ties together many operations of sales training under a single banner, including development of traditional printed materials such as detail aids and brochures with interactive programs into a nonlinear approach with text, audio and flash.
The sales and training materials will assure pharmaceutical representatives will be knowledgeable and well-informed, but how is digital media used to educate other audiences about health care products and medications?
It is critical to receive all parts of the content of a CME program, and the process is not as nonlinear as I’d like it to be,” comments Bass. He stresses that a nonlinear approach to CME should still allow a participant to track progress, finish each component and complete an assessment. For instance, a participant could choose to do part “C” then part “A” and “D” then “B.” The components would be completed, the order of completion the participant’s choice.”
I recommend you take a gander if you have any interest in the Pharma sector you can access it by clicking here
Dynamic Logic's Ken Mallon comments on recent OPA/comScore research June 30, 2009
Posted by Mark Blei in : Ken Mallon, Staff posts, industry news , comments closed Ken Mallon Dynamic Logic’s SVP Custom Solutions & Ad Effectiveness Consulting speaks out about recent research released by the Online Publishers Association in conjunction with comScore.
Ken is a 25-year research veteran having applied research methods, statistics and data mining expertise to a variety of fields including health, pharmaceuticals, marketing, and internet behavior. At Dynamic Logic, Ken heads the Custom Solutions team, providing specialized research and consulting services to top clients. Before joining Dynamic Logic, Ken was Director of Product Development, Director of Marketing Solutions, and Director of Data Mining at Yahoo!, where he helped to create Yahoo!’s data-mining group, as well as their behavioral targeting system, unique consumer insights, and passively collecting data and advertising products.
Ken holds a Master of Health Science in biostatistics from Johns Hopkins University, a Master of Science in statistics from Stanford University and a Bachelor of Science in secondary math education from University of Connecticut. Kens comments appear below.
Last week, OPA and comScore released some research titled “The Silent Click: Building Brands Online”. Dynamic Logic is a long-time friend of the OPA (we love you, Stu!), but I just had to comment on this. While we agree with one of the key messages of the research – to stop putting emphasis on CTR – we disagree with the overarching framework and believe some of the research methods are misleading.
FRAMEWORK
I won’t start with a methodological discussion (methods geeks, skip to the bottom of the article where we can have a nice statistical dialogue). Instead, let’s start higher with the overall framework. In the key findings (slide 52) this research states:
Search + Site Visitation + e-Commerce spending = a smart formula for measuring display ad effectiveness.
We fundamentally disagree with this concept. On page 5 of the deck, Carrie Frolich, Managing Director Digital, Mediaedge: cia, is quoted as saying:
“Remember why you’re advertising … You are not advertising for clicks … What you’re advertising for is to sell me stuff or change perception, and that’s what we need to be measuring against.”
Frolich is right-on. This is very similar to what I say on just about every panel and conference speaking engagement in which I participate:
“At the end of the day, you care about two things – did my advertising help sell something or did it change someone’s opinion. Everything else is a surrogate or noise.”
We believe that the right formula is:
Perception changes + sales (both online and offline) = the best formula for measuring display ad effectiveness.
We believe that post-view behaviors play a key role diagnostically and add color to the above.
The brand perceptions part can be handled via surveys (passively collected comments via blogs and otherwise can play a role as well) and the sales impact part must utilize one of several methods for capturing both online and offline sales which I’ll go into later.
I want to digress for a moment into a pharmaceutical industry parallel. During my years as a statistical scientist at UCSF, Genentech and Amgen, I was taught that at the end of the day, when talking about drug interventions, a medicine must do one of two things. It must either save lives or improve quality of life. All other things are surrogates or noise. Sound familiar? If a drug improved your cholesterol, but didn’t improve your quality of life or reduce the risk of death, would you take it? Probably not. If an ad format increased interaction but didn’t make people like your brand better and didn’t increase sales, was it effective?
I know a lot of this sounds like I’m discrediting post-view behavior. I don’t mean to do that. Post-view behaviors such as driving search, visits to the advertiser site, brochure downloads and trailer views can be important diagnostic tools for understanding lifts or lack thereof in brand perception and sales. But, by themselves, they are not ultimate measures of ad effectiveness. There is one post-view behavior worth clarifying – e-commerce. In the Dynamic Logic framework – it’s all about perceptions and sales – e-commerce is included in the latter. It’s part of the sales impact measurement. Online sales, although they are technically a post-view behavior, are not a surrogate. They are part of the real deal.
Now, let’s get back to Carrie Frolich. If she’s right and I believe she is, then why doesn’t the research presented include any brand perception results? And, why is the sales impact information only limited to online and not offline sales?
Dynamic Logic is known for measuring the branding impact of digital advertising and we do this via live web-intercept survey. But, what some of our clients are increasingly discovering is that we can do much more. We are currently advocating a broad-based way of measuring the impact of display ads – brand impact + offline sales estimation + e-commerce (where appropriate) + other post-view behaviors to add color and for diagnostic use.
Some nine months ago, we discussed internally the impact of the economy and wondered what we might be able to do for our clients who were feeling increasing pressure. What we heard again and again from our clients is “ROI, ROI – we want more ROI and … it can’t be expensive to measure”. Publishers, agencies, advertisers and technology providers are under increased pressure from management and clients to deliver results. This type of pressure has always existed in digital but now it’s heavier than ever.
As a result of this need, we have begun thinking very creatively about what we can do. We worked out a simple, straight-forward and relatively inexpensive way of estimating the offline and online sales impact of display advertising (and website exposure) applicable to just about any advertised product. This, combined with our patented approach to measuring changes in brand perception, completed the sales + perception = display ad impact formula we advocate and has been reinforced by Carrie Frolich. Also, since our tracking technology could be used to capture post-view behaviors such as e-commerce, we had that element as well.
What was missing were other post-view behaviors such as impact on search and impact on website visitation other than the advertiser site. An example of this would be measuring the traffic to kbb.com following display ad exposure to an automotive campaign.
Meanwhile, TNS became one of our cousin companies, opening the door to closer collaboration and data integration with Cymfony and Compete. Sometimes, when you ask for something, you get it! By collaborating with Compete, we can now estimate the impact of display ads on search volume and website traffic to any prominent site. And, what of Cymfony? What role can they play? Longer-term, we hope to use their technology to enhance the measure of perceptions (among other things). This is currently assessed largely via surveys, but could be enhanced with passively-collected data across the Web.
So, to sum up regarding the framework,
INCOMPLETE: Search + Site Visitation + e-Commerce spending = a smart formula for measuring display ad effectiveness.
CORRECT: Perception changes + sales (both online and offline) = the best formula for measuring display ad effectiveness.
And, by the way, although some of our capabilities are not fully productized in this regard, we can deliver today on this way of measuring digital advertising effectiveness and can do so in a relatively cost-effective way.
Thank-you, Carrie!
MISLEADING METHODS
And, now on the more tedious discussion of the methods used in this research. First, I give OPA and comScore credit for being responsible researchers and using the term correlation. Also, they didn’t do statistical testing to compare the control and exposed group. Since the groups were not scientifically equivalent, not testing is the right thing to do since statistical significance would have no meaning anyway.
That being said, I think more could have been done to make the comparison groups more comparable. This is important because, although they are careful to use the term correlation so that people should not conclude causality, we all know that the untrained reader will immediately conclude causality.
As an example, let’s look at slide 16. It shows that visitors to a brand’s site who had been exposed to that brand’s advertising ended up spending more time on the site and consumed more pages. Firstly, let me say this. I believe in display advertising. I believe online ad exposure is likely to cause someone to end up spending more time on a website. I’ve just seen too much controlled data to support it. So, I have to believe it. However,
1) This research doesn’t prove that ad exposure leads to greater site consumption
2) The authors don’t directly claim it to be true (they use the careful and correct term, correlation), but
3) Most people will arrive at the conclusion that online ad exposure drives increased brand consumption in terms of website time spent and pages visited (I’ve read dozens of tweets with that interpretation)
Although, again, I believe (3) is likely to be true, I’m just saying that it doesn’t follow from the data presented. Although the authors cover themselves statistically by not testing and by using the term correlation, I feel it’s a bit irresponsible given that much of the audience isn’t well-trained in statistical interpretation.
I have the same complaint for nearly all the comparisons that are made in this presentation. It’s a bit worse in cases where there is an unexposed versus exposed comparison. Let’s look at slide 17 for example. It shows that those who were exposed to advertising had 7% more e-commerce than unexposed (similar results on slide 18).
First, look at the x-axis. The range of x-axis is from 200 to 250. When I was a statistics student I learned that shortening the axis to make the difference seem larger, is a reporting no-no. But, that’s largely a pet-peeve – I can see why you’d want to do that. My main criticism is the selection of the unexposed as the control group. To avoid misleading results, one must select the comparison group very carefully and since it wasn’t done scientifically, great care should be taken to make the groups as comparable as possible either by weighting, multivariate regression, stratification or other techniques.
Let me explain just one possible reason for having a 7% difference that has nothing to do with ad exposure. Take the example of re-targeting. That’s when you show an ad to someone because they previously visited your site (and you smartly cookied them) or they previously performed a search in your category or for your brand. If you do a retargeting campaign, you are selecting a subset of the population who has a far greater chance of being interested in and therefore greater chance of purchasing your product. Same goes for good behavioral targeting (there’s good and there’s bad – but, I’ll save that topic for another blog). So, it very well could be that the exposure itself played no role in later e-commerce. It could just be a function of good targeting. And, if the unexposed group possibly came from other websites than the exposed, then in-context targeting could have been the reason for increased e-commerce.
Thus, again, although I believe in online ads and believe they increase e-commerce, the research presented doesn’t show it. The same methodological criticism applies to the rest of the results.
Again, we are supporters of the OPA. But, we think comScore did them somewhat of a disservice with this research. I believe that online advertising drives e-commerce, increases search and has many other positive brand benefits, I don’t think this research proves it.
If you want to measure the complete impact of display advertising – brand impact and sales, talk to us at Dynamic Logic. We can provide valuable and robust scientific data within our framework for measuring display ad effectiveness:
Perception changes + sales (both online and offline) = the best formula for measuring display ad effectiveness.
Best,
Ken Mallon
Senior Vice President
Custom Solutions & Ad Effectiveness Consulting
Follow us on twitter: Dynamiclogic Join our Facebook Page Join our group on LinkedIn
